| 1. |
- Khoshahval, Samira, et al.
(författare)
-
A Personalized location-based and serendipity-oriented point of interest recommender assistant based on behavioral patterns
- 2018
-
Ingår i: Geospatial Technologies for All : Selected Papers of the 21st AGILE Conference on Geographic Information Science - Selected Papers of the 21st AGILE Conference on Geographic Information Science. - Cham : Springer International Publishing. - 1863-2351 .- 1863-2246. - 9783319782072 - 9783319782089 ; part F3, s. 271-289
-
Konferensbidrag (refereegranskat)abstract
- The technological evolutions have promoted mobile devices from rudimentary communication facilities to advanced personal assistants. According to the huge amount of accessible data, developing a time-saving and cost-effective method for location-based recommendations in mobile devices has been considered a challenging issue. This paper contributes a state-of-the-art solution for a personalized recommender assistant which suggests both accurate and unexpected point of interests (POIs) to users in each part of the day of the week based on their previously monitored, daily behavioral patterns. The presented approach consists of two steps of extracting the behavioral patterns from users’ trajectories and location-based recommendation based on the discovered patterns and user’s ratings. The behavioral pattern of the user includes their activity types in different parts of the day of the week, which is monitored via a combination of a stay point detection algorithm and an association rule mining (ARM) method. Having the behavioral patterns, the system exploits two recommendation procedures based on conventional collaborative filtering and K-furthest neighborhood model to recommend typical and serendipitous POIs to the users. The suggested POI list contains not only relevant and precise POIs but also unpredictable and surprising items to the users. To evaluate the system, the values of RMSE of each procedure were computed and compared. Conducted experiments proved the feasibility of the proposed solution.
|
|
| 2. |
- Mansourian, Ali, et al.
(författare)
-
Geospatial Technologies for All: Preface
- 2018
-
Ingår i: Geospatial technologies for all : Selected Papers of the 21st AGILE Conference on Geographic Information Science - Selected Papers of the 21st AGILE Conference on Geographic Information Science. - Cham : Springer International Publishing. - 1863-2246 .- 1863-2351. - 9783319782072 - 9783319782089 ; part F3
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
|
|
| 3. |
- Pilesjö, Petter, et al.
(författare)
-
Harmonizing GIS Education: South - North Perspectives : Lessons learnt from Mozambique, Rwanda, Sweden, and Uganda
- 2018
-
Ingår i: Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden.
-
Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to critically examine, discuss, draw conclusions, and come up with ideas how to harmonize GIS education in order to realize the envisaged clientele benefits globally. The paper draws experiences and lessons learnt, with examples from ongoing joint GIS MSc programs/courses being implemented in Mozambique, Rwanda, and Uganda. All the five courses (3 in Uganda, 1 in Mozambique, and 1 in Rwanda) are currently financially supported by the Swedish International Development Cooperation Agency (Sida) capacity development and institutional development grants. The GIS programmes and course units in the southern institutions have a high demand from clients, especially at graduate level. However, their implementation and uptake is impeded by challenges like credit systems, pedagogic approach, field work, student interaction, and software, which are discussed. It is concluded that there is still a long way to go before harmonization, allowing GIS students to freely move between different countries during their education, is possible. Low/no cost exchange of teachers and “best practice” are identified as important initial steps to reach harmonization, focusing on younger teachers, as well as exchange of material and use of open source GIS software.
|
|
| 4. |
|
|
| 5. |
- Sbarra, AN, et al.
(författare)
-
Mapping routine measles vaccination in low- and middle-income countries
- 2021
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 589:7842, s. 415-
-
Tidskriftsartikel (refereegranskat)abstract
- The safe, highly effective measles vaccine has been recommended globally since 1974, yet in 2017 there were more than 17 million cases of measles and 83,400 deaths in children under 5 years old, and more than 99% of both occurred in low- and middle-income countries (LMICs)1–4. Globally comparable, annual, local estimates of routine first-dose measles-containing vaccine (MCV1) coverage are critical for understanding geographically precise immunity patterns, progress towards the targets of the Global Vaccine Action Plan (GVAP), and high-risk areas amid disruptions to vaccination programmes caused by coronavirus disease 2019 (COVID-19)5–8. Here we generated annual estimates of routine childhood MCV1 coverage at 5 × 5-km2pixel and second administrative levels from 2000 to 2019 in 101 LMICs, quantified geographical inequality and assessed vaccination status by geographical remoteness. After widespread MCV1 gains from 2000 to 2010, coverage regressed in more than half of the districts between 2010 and 2019, leaving many LMICs far from the GVAP goal of 80% coverage in all districts by 2019. MCV1 coverage was lower in rural than in urban locations, although a larger proportion of unvaccinated children overall lived in urban locations; strategies to provide essential vaccination services should address both geographical contexts. These results provide a tool for decision-makers to strengthen routine MCV1 immunization programmes and provide equitable disease protection for all children.
|
|
| 6. |
- Abdolmajidi, Ehsan, et al.
(författare)
-
Matching authority and VGI road networks using an extended node-based matching algorithm
- 2015
-
Ingår i: Geo-Spatial Information Science. - : Informa UK Limited. - 1009-5020 .- 1993-5153. ; 18:2-3, s. 65-80
-
Tidskriftsartikel (refereegranskat)abstract
- The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on an accurate and efficient network-matching algorithm. The study begins with a comparison of the two main strategies for network matching: segment-based and node-based matching. The comparison shows that the result quality is comparable for the two strategies, but the node-based result is considerably more computationally efficient. Therefore, we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components. Finally, we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database (NVDB) in Scania, Sweden. The case study reveals that OSM has a completeness of 87% in the urban areas and 69% in the rural areas of Scania. The accuracy of the matching process is approximately 95%. The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions.
|
|
| 7. |
- Abdolmajidi, Ehsan, et al.
(författare)
-
The stock-flow model of spatial data infrastructure development refined by fuzzy logic
- 2016
-
Ingår i: SpringerPlus. - : Springer Science and Business Media LLC. - 2193-1801. ; 5:1
-
Tidskriftsartikel (refereegranskat)abstract
- The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average–Average inference and Center of Area defuzzification can better model the dynamics of SDI development.
|
|
| 8. |
- Aturinde, Augustus, et al.
(författare)
-
Analysis of spatial co-occurrence between cancer and cardiovascular disease mortality and its spatial variation among the Swedish elderly (2010–2015)
- 2020
-
Ingår i: Applied Geography. - : Elsevier BV. - 0143-6228. ; 125
-
Tidskriftsartikel (refereegranskat)abstract
- CVD and cancer are the two leading causes of death worldwide. Improvement in cancer early detection and treatment has resulted in an increased number of cancer survivors. However, many of the survivors tend to develop CVD often leading to their demise. Conversely, people with pre-existing CVD conditions, especially the elderly, have increased chances of developing cancer and dying from the same. The World Health Organization, consequently, recommends joint management of both diseases. However, in Sweden, as with many other countries, few studies have explored the nature of the associations between the two disease mortalities and their spatial variation at a population level. This study uses correlation, global Moran's index and global bivariate Moran's index to investigate national trends of cancer and CVD crude mortality rates in the Swedish elderly. Spatial scan statistics, spatial overlay and local entropy maps were used to analyse for spatial co-occurrence, local joint spatial clustering and associations in the 2010–2015 cancer and CVD crude mortality rates for the Swedish elderly (65+ years). Mortality data were obtained from the Swedish Healthcare Registry. Our results showed that throughout the years of study, the correlation between cancer and CVD crude mortality rates was averagely positive. Spatial correlation analysis (univariate and bivariate) showed that the contribution of the neighbourhood mortality rates to the observed mortality rates was weak, though significant. From cluster analysis, the cancer and CVD crude mortality rates showed differences in clustering spatial scales with CVD clustering at a smaller scale. Finally, local entropy maps showed that cancer and CVD crude mortality rates were not always related across Sweden, but whenever they were, the relationship was mainly positive and linear. This study contributes to cancer and CVD public health efforts in Sweden by identifying areas where the two causes of death spatially co-occur, and where the two exhibit no spatial overlap. This provides a valuable starting ground for more focused studies to identify local drivers and/or informs coordinated targeted intervention in both causes of death.
|
|
| 9. |
- Aturinde, Augustus, et al.
(författare)
-
Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda
- 2019
-
Ingår i: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 19:1, s. 215-215
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.
|
|
| 10. |
- Aturinde, Augustus, et al.
(författare)
-
Space–Time Surveillance of COVID-19 Seasonal Clusters : A Case of Sweden
- 2022
-
Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 11:5
-
Tidskriftsartikel (refereegranskat)abstract
- While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space–time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space–time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space–time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked.
|
|
| 11. |
|
|
| 12. |
- Aturinde, Augustus, et al.
(författare)
-
Spatial analysis of HIV-TB co-clustering in Uganda
- 2019
-
Ingår i: BMC Infectious Diseases. - : Springer Science and Business Media LLC. - 1471-2334. ; 19:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Tuberculosis (TB) is the leading cause of death for individuals infected with Human immunodeficiency virus (HIV). Conversely, HIV is the most important risk factor in the progression of TB from the latent to the active status. In order to manage this double epidemic situation, an integrated approach that includes HIV management in TB patients was proposed by the World Health Organization and was implemented in Uganda (one of the countries endemic with both diseases). To enable targeted intervention using the integrated approach, areas with high disease prevalence rates for TB and HIV need to be identified first. However, there is no such study in Uganda, addressing the joint spatial patterns of these two diseases.METHODS: This study uses global Moran's index, spatial scan statistics and bivariate global and local Moran's indices to investigate the geographical clustering patterns of both diseases, as individuals and as combined. The data used are TB and HIV case data for 2015, 2016 and 2017 obtained from the District Health Information Software 2 system, housed and maintained by the Ministry of Health, Uganda.RESULTS: Results from this analysis show that while TB and HIV diseases are highly correlated (55-76%), they exhibit relatively different spatial clustering patterns across Uganda. The joint TB/HIV prevalence shows consistent hotspot clusters around districts surrounding Lake Victoria as well as northern Uganda. These two clusters could be linked to the presence of high HIV prevalence among the fishing communities of Lake Victoria and the presence of refugees and internally displaced people camps, respectively. The consistent cold spot observed in eastern Uganda and around Kasese could be explained by low HIV prevalence in communities with circumcision tradition.CONCLUSIONS: This study makes a significant contribution to TB/HIV public health bodies around Uganda by identifying areas with high joint disease burden, in the light of TB/HIV co-infection. It, thus, provides a valuable starting point for an informed and targeted intervention, as a positive step towards a TB and HIV-AIDS free community.
|
|
| 13. |
- Dinc, Pinar, et al.
(författare)
-
Fighting Insurgency, Ruining the Environment : the Case of Forest Fires in the Dersim Province of Turkey
- 2021
-
Ingår i: Human Ecology. - : Springer Science and Business Media LLC. - 1572-9915 .- 0300-7839. ; 49:4, s. 481-493
-
Tidskriftsartikel (refereegranskat)abstract
- Environmental destruction has long been used as a military strategy in times of conflict. A long-term example of environmental destruction in a conflict zone can be found in Dersim/Tunceli province, located in Eastern Turkey. In the last century, at least two military operations negatively impacted Dersim’s population and environment: 1937–38 and 1993–94. Both conflict and environmental destruction in the region continued after the 1990s. Particularly after July 2015, when the brief peace process that began in 2013 ended, conflict between the Turkish state and the Kurdistan Workers’ Party (PKK) resumed and questions arose about the cause of forest fires in Dersim. In this research we investigate whether there is a relationship between conflict and forest fires in Dersim. This is denied by the Turkish state but asserted by many Dersim residents, civil society groups, and political parties. We use a multi-disciplinary approach, combining methods of qualitative analysis of print media (newspapers), social media (Twitter), and local accounts, together with quantitative methods: remote sensing and spatial analysis. Interdisciplinary analysis combining quantitative datasets with in-depth, qualitative data allows a better understanding of the role of conflict in potentially exacerbating the frequency and severity of forest fires. Although we cannot determine the cause of the fires, the results of our statistical analysis suggest a significant relationship between fires and conflict in Dersim, indicating that the incidence of conflicts is generally correlated with the number of fires.
|
|
| 14. |
- Farnaghi, Mahdi, et al.
(författare)
-
Blockchain, an enabling technology for transparent and accountable decentralized public participatory GIS
- 2020
-
Ingår i: Cities. - : Elsevier BV. - 0264-2751. ; 105
-
Tidskriftsartikel (refereegranskat)abstract
- Web-based public participatory GIS (PPGIS) has been used by governmental organizations to facilitate people's contribution to decision-making processes. However, these applications do not provide an open and transparent environment for public participation. This study suggests that PPGISs should be developed as decentralized applications (DApp) based on Ethereum blockchain technology to have a fully open, transparent, and accountable environment for public participation. In a blockchain-based PPGIS, the collected data are securely saved on the blockchain. The validity of the data, replicated on the nodes of the peer-to-peer blockchain network, is ensured through a consensus process without any central control. The data is tamper-free and immutable. Additionally, the data is openly accessible to institutions and citizens. A prototype PPGIS was developed as a DApp through which users can participate in the site selection of urban facilities. Using the application, they compare and rank different criteria. The system solves an analytic hierarchy process to calculate the weights of the criteria. A suitability map is generated afterward and published to be used by both citizens and decision-makers. The feasibility of the application, along with the issues that need to be considered while using blockchain technology for urban planning and development, are thoroughly discussed.
|
|
| 15. |
- Farnaghi, Mahdi, et al.
(författare)
-
Disaster planning using automated composition of semantic OGC web services: A case study in sheltering
- 2013
-
Ingår i: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715. ; 41, s. 204-218
-
Tidskriftsartikel (refereegranskat)abstract
- Spatial data are crucial in disaster planning. However, because of the dynamic, urgent and uncertain nature of disasters, certain data and functionalities may be inaccessible to decision makers when they are required. Web service composition offers a possible solution whereby disaster planners can integrate spatial web services to generate new spatial data and functionalities, quickly, from existing ones. This paper proposes an automatic solution for composing OWSs (Open Geospatial Consortium Web Services) for disaster planning. A semantic annotation approach based on the Resource Description Framework (RDF) and SPARQL languages is used to describe OWSs semantically. A conceptual model for AI (Artificial Intelligence) planning is also proposed that works based on RDF and SPARQL. An AI planning algorithm was implemented based on the proposed conceptual model to compose semantic OWSs. The applicability of the proposed solution is investigated through a case study in evacuation sheltering. The case study demonstrates that the proposed automatic composition approach can enhance the efficiency of OWS integration and thereby improve the disaster management process. (c) 2013 Elsevier Ltd. All rights reserved.
|
|
| 16. |
- Farnaghi, Mahdi, et al.
(författare)
-
Dynamic Spatio-Temporal Tweet Mining for Event Detection : A Case Study of Hurricane Florence
- 2020
-
Ingår i: International Journal of Disaster Risk Science. - : Springer Science and Business Media LLC. - 2095-0055 .- 2192-6395. ; 11:3, s. 378-393
-
Tidskriftsartikel (refereegranskat)abstract
- Extracting information about emerging events in large study areas through spatiotemporal and textual analysis of geotagged tweets provides the possibility of monitoring the current state of a disaster. This study proposes dynamic spatio-temporal tweet mining as a method for dynamic event extraction from geotagged tweets in large study areas. It introduces the use of a modified version of ordering points to identify the clustering structure to address the intrinsic heterogeneity of Twitter data. To precisely calculate the textual similarity, three state-of-the-art text embedding methods of Word2vec, GloVe, and FastText were used to capture both syntactic and semantic similarities. The impact of selected embedding algorithms on the quality of the outputs was studied. Different combinations of spatial and temporal distances with the textual similarity measure were investigated to improve the event detection outcomes. The proposed method was applied to a case study related to 2018 Hurricane Florence. The method was able to precisely identify events of varied sizes and densities before, during, and after the hurricane. The feasibility of the proposed method was qualitatively evaluated using the Silhouette coefficient and qualitatively discussed. The proposed method was also compared to an implementation based on the standard density-based spatial clustering of applications with noise algorithm, where it showed more promising results.
|
|
| 17. |
- Farnaghi, Mahdi, et al.
(författare)
-
Multi-Agent Planning for Automatic Geospatial Web Service Composition in Geoportals
- 2018
-
Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 7:10
-
Tidskriftsartikel (refereegranskat)abstract
- Automatic composition of geospatial web services increases the possibility of taking full advantage of spatial data and processing capabilities that have been published over the internet. In this paper, a multi-agent artificial intelligence (AI) planning solution was proposed, which works within the geoportal architecture and enables the geoportal to compose semantically annotated Open Geospatial Consortium (OGC) Web Services based on users’ requirements. In this solution, the registered Catalogue Service for Web (CSW) services in the geoportal along with a composition coordinator component interact together to synthesize Open Geospatial Consortium Web Services (OWSs) and generate the composition workflow. A prototype geoportal was developed, a case study of evacuation sheltering was implemented to illustrate the functionality of the algorithm, and a simulation environment, including one hundred simulated OWSs and five CSW services, was used to test the performance of the solution in a more complex circumstance. The prototype geoportal was able to generate the composite web service, based on the requested goals of the user. Additionally, in the simulation environment, while the execution time of the composition with two CSW service nodes was 20 s, the addition of new CSW nodes reduced the composition time exponentially, so that with five CSW nodes the execution time reduced to 0.3 s. Results showed that due to the utilization of the computational power of CSW services, the solution was fast, horizontally scalable, and less vulnerable to the exponential growth in the search space of the AI planning problem.
|
|
| 18. |
- Guo, Zijian, et al.
(författare)
-
Exploring the structural characteristics of intra-urban shared freight network and their associations with socioeconomic status
- 2023
-
Ingår i: Travel Behaviour and Society. - : Elsevier BV. - 2214-367X. ; 32
-
Tidskriftsartikel (refereegranskat)abstract
- In recent years, shared freight systems have emerged in many cities as a new modality of freight transportation. However, little attention has been paid to the impact of a city's socioeconomic status on the characteristics of a shared freight network. To fill this gap, in this study, the structural characteristics of an intra-urban shared freight network are measured from the perspective of complex networks, and the correlations between network structure and socioeconomic status are examined. A case study is conducted in Hong Kong using large amounts of GPS trajectory data for freight vehicles and socioeconomic data. The results show that socioeconomic variables such as population size, percentage of elderly residents, percentage of residents with a marital status classified as “other” (i.e., separated, widowed, or divorced), and percentage of residents employed in the tertiary sector have distinct correlations with the structural characteristics. These correlations display spatial non-stationarity. This research can potentially assist decision-makers in improving the operating efficiency of shared freight systems and the governance of digital freight transport.
|
|
| 19. |
- Hansson, Erik, et al.
(författare)
-
An ecological study of chronic kidney disease in five Mesoamerican countries : associations with crop and heat
- 2021
-
Ingår i: BMC Public Health. - : Springer Science and Business Media LLC. - 1471-2458. ; 21:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Mesoamerica is severely affected by an epidemic of Chronic Kidney Disease of non-traditional origin (CKDnt), an epidemic with a marked variation within countries. We sought to describe the spatial distribution of CKDnt in Mesoamerica and examine area-level crop and climate risk factors.METHODS: CKD mortality or hospital admissions data was available for five countries: Mexico, Guatemala, El Salvador, Nicaragua and Costa Rica and linked to demographic, crop and climate data. Maps were developed using Bayesian spatial regression models. Regression models were used to analyze the association between area-level CKD burden and heat and cultivation of four crops: sugarcane, banana, rice and coffee.RESULTS: There are regions within each of the five countries with elevated CKD burden. Municipalities in hot areas and much sugarcane cultivation had higher CKD burden, both compared to equally hot municipalities with lower intensity of sugarcane cultivation and to less hot areas with equally intense sugarcane cultivation, but associations with other crops at different intensity and heat levels were not consistent across countries.CONCLUSION: Mapping routinely collected, already available data could be a first step to identify areas with high CKD burden. The finding of higher CKD burden in hot regions with intense sugarcane cultivation which was repeated in all five countries agree with individual-level studies identifying heavy physical labor in heat as a key CKDnt risk factor. In contrast, no associations between CKD burden and other crops were observed.
|
|
| 20. |
- Harrie, Lars, et al.
(författare)
-
The need for country masks for future national greenhouse gas flux estimations
- 2018
-
Ingår i: Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden. - 9783319782089
-
Konferensbidrag (refereegranskat)abstract
- The Paris Agreement requests a substantial reduction of greenhouse gas (GHG) emissions. These emissions are currently mainly estimated from bottom-up inventories and process-based models of land and ocean fluxes. Another, complementary approach is based on measurements of the atmospheric GHG concentration in combination with atmospheric inverse modelling to provide the GHG fluxes. For the latter approach the GIScience community should contribute with providing an appropriate country mask to enable estimations of national budgets. This paper aims at describing the requirement of such a country mask as well as report on technical solutions for preliminary tests we made on national GHG flux estimations.
|
|
| 21. |
- Huang, Weiming, et al.
(författare)
-
Geospatial data integration and visualisation using Linked Data
- 2017
-
Ingår i: Proceedings of the 4th AGILE PhD School. - 1613-0073. ; 2088
-
Konferensbidrag (refereegranskat)abstract
- Geospatial data are increasingly available nowadays, and this leads to more analyses and visualisation of geospatial data from several sources. To enable this, we need homogenous data as well as proper integration methods. Geospatial data integration has been a longstanding research topic for decades, and this paper discusses the utilisation of Linked Data technology stack to alleviate the geospatial data integration, particularly in the multi-scale context. Furthermore, this paper also discusses the possibilities of incorporating symbolisation information in Linked Data along with the integrated linked geospatial data for visualisation.
|
|
| 22. |
- Huang, Weiming, et al.
(författare)
-
Multiple Representation for Geospatial Linked Data
- 2018
-
Ingår i: Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden. - 9783319782089
-
Konferensbidrag (refereegranskat)abstract
- Current techniques for visualising geospatial Linked Data are limited in terms of multiple representation, which has been studied for decades by cartographers and considered as a prerequisite for deriving appropriate geovisualisation applications. In order to alleviate this issue, this paper presents a work in progress, in which the multiple representation geospatial data are released as Linked Data, and linked to the Linked Data gazetteer GeoNames. In the study, we use extended INSPIRE draft RDF vocabularies to explicitly link multiple representations and their visualisation scales. The results show that the released multiple representation geospatial Linked Data can effectively enrich the geometric information for the test data in GeoNames, and provide better visualisation performance.
|
|
| 23. |
- Huang, Weiming, et al.
(författare)
-
Synchronising geometric representations for map mashups using relative positioning and Linked Data
- 2018
-
Ingår i: International Journal of Geographical Information Science. - : Informa UK Limited. - 1365-8816 .- 1362-3087. ; 32:6, s. 1117-1137
-
Tidskriftsartikel (refereegranskat)abstract
- Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.
|
|
| 24. |
- Huang, Weiming, et al.
(författare)
-
Towards Knowledge-Based Geospatial Data Integration and Visualization : A Case of Visualizing Urban Bicycling Suitability
- 2020
-
Ingår i: IEEE Access. - 2169-3536. ; 8, s. 85473-85489
-
Tidskriftsartikel (refereegranskat)abstract
- Geospatial information plays an indispensable role in various interdisciplinary and spatially informed analyses. However, the use of geospatial information often entails many semantic intricacies relating to, among other issues, data integration and visualization. For the integration of data from different domains, merely using ontologies is inadequate for handling subtle and complex semantic relations raised by the multiple representations of geospatial data, as the domains have different conceptual views for modelling the geographic space. In addition, for geospatial data visualization - one of the most predominant ways of utilizing geospatial information - semantic intricacies arise as the visualization knowledge is difficult to interpret and utilize by non-geospatial experts. In this paper, we propose a knowledge-based approach using semantic technologies (coupling ontologies, semantic constraints, and semantic rules) to facilitate geospatial data integration and visualization. A traffic spatially informed study is developed as a case study: visualizing urban bicycling suitability. In the case study, we complement ontologies with semantic constraints for cross-domain data integration. In addition, we utilize ontologies and semantic rules to formalize geospatial data analysis and visualization knowledge at different abstraction levels, which enables machines to infer visualization means for geospatial data. The results demonstrate that the proposed framework can effectively handle subtle cross-domain semantic relations for data integration, and empower machines to derive satisfactory visualization results. The approach can facilitate the sharing and outreach of geospatial data and knowledge for various spatially informed studies.
|
|
| 25. |
- Ismail, Kamukama, et al.
(författare)
-
Spatio-temporal trends and distribution patterns of typhoid disease in Uganda from 2012 to 2017
- 2021
-
Ingår i: Geospatial health. - : PAGEPress Publications. - 1970-7096 .- 1827-1987. ; 15:2
-
Tidskriftsartikel (refereegranskat)abstract
- Typhoid disease continues to be a global public health burden. Uganda is one of the African countries characterized by high incidences of typhoid disease. Over 80% of the Ugandan districts are endemic for typhoid, largely attributable to lack of reliable knowledge to support disease surveillance. Spatial-temporal studies exploring major characteristics of the disease within the local population have remained limited in Uganda. The main goal of the study was to reveal spatial-temporal trends and distribution patterns of typhoid disease in Uganda for the period 2012 to 2017. Spatial-temporal statistics revealed monthly and annual trends of the disease at both regional and national levels. Results show that outbreaks occurred during 2015 and 2017 in central and eastern regions, respectively. Spatial scan statistic using the discrete Poisson model revealed spatial clusters of the disease for each of the years from 2012 to 2017, together with populations at risk. Most of the disease clustering was in the central region, followed by western and eastern regions (P <0.01). The northern region was the safest throughout the study period. This knowledge helps surveillance teams to i) plan and enforce preventive measures; ii) effectively prepare for outbreaks; iii) make targeted interventions for resource optimization; and iv) evaluate effectiveness of the intervention methods in the study period. This exploratory research forms a foundation of using Geographical Information Systems (GIS) in other related subsequent research studies to discover hidden spatial patterns that are difficult to discover with conventional methods.
|
|
| 26. |
- Jeihouni, Mehrdad, et al.
(författare)
-
Decision Tree-Based Data Mining and Rule Induction for Identifying High Quality Groundwater Zones to Water Supply Management : a Novel Hybrid Use of Data Mining and GIS
- 2020
-
Ingår i: Water Resources Management. - : Springer Science and Business Media LLC. - 0920-4741 .- 1573-1650. ; 34:1, s. 139-154
-
Tidskriftsartikel (refereegranskat)abstract
- Groundwater is an important source to supply drinking water demands in both arid and semi-arid regions. Nevertheless, locating high quality drinking water is a major challenge in such areas. Against this background, this study proceeds to utilize and compare five decision tree-based data mining algorithms including Ordinary Decision Tree (ODT), Random Forest (RF), Random Tree (RT), Chi-square Automatic Interaction Detector (CHAID), and Iterative Dichotomiser 3 (ID3) for rule induction in order to identify high quality groundwater zones for drinking purposes. The proposed methodology works by initially extracting key relevant variables affecting water quality (electrical conductivity, pH, hardness and chloride) out of a total of eight existing parameters, and using them as inputs for the rule induction process. The algorithms were evaluated with reference to both continuous and discrete datasets. The findings were speculative of the superiority, performance-wise, of rule induction using the continuous dataset as opposed to the discrete dataset. Based on validation results, in continuous dataset, RF and ODT showed higher and RT showed acceptable performance. The groundwater quality maps were generated by combining the effective parameters distribution maps using inducted rules from RF, ODT, and RT, in GIS environment. A quick glance at the generated maps reveals a drop in the quality of groundwater from south to north as well as from east to west in the study area. The RF showed the highest performance (accuracy of 97.10%) among its counterparts; and so the generated map based on rules inducted from RF is more reliable. The RF and ODT methods are more suitable in the case of continuous dataset and can be applied for rule induction to determine water quality with higher accuracy compared to other tested algorithms.
|
|
| 27. |
|
|
| 28. |
- Li, Aoyong, 1993, et al.
(författare)
-
Comprehensive comparison of e-scooter sharing mobility: Evidence from 30 European cities
- 2022
-
Ingår i: Transportation Research Part D: Transport and Environment. - : Elsevier BV. - 1361-9209. ; 105
-
Tidskriftsartikel (refereegranskat)abstract
- Although e-scooter sharing has become increasingly attractive, little attention has been paid to a comprehensive comparison of e-scooter sharing mobility in multiple cities. To fill this gap, we conduct a comparative study to reveal the similarity and difference of e-scooter sharing mobility by collecting and analyzing vehicle availability data from 30 European cities during post COVID-19 pandemic. The comparisons are implemented from four perspectives, including temporal trip patterns, statistical characteristics (i.e., trip distance and duration), utilization efficiency, and wasted electricity during idle time. Results suggest that the similarity and difference co-exist between e-scooter sharing services in the cities, and utilization efficiency is significantly related with the number of e-scooters per person and per unit area. Surprisingly, on average nearly 33% of electricity are wasted during idle time in these cities. These research findings can be beneficial to further optimizing e-scooter sharing mobility services for transportation planners and micro-mobility operators.
|
|
| 29. |
- Li, Aoyong, et al.
(författare)
-
How did micro-mobility change in response to COVID-19 pandemic? : A case study based on spatial-temporal-semantic analytics
- 2021
-
Ingår i: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715. ; 90
-
Tidskriftsartikel (refereegranskat)abstract
- Cities worldwide adopted lockdown policies in response to the outbreak of coronavirus disease 2019 (COVID-19), significantly influencing people's travel behavior. In particular, micro-mobility, an emerging mode of urban transport, is profoundly shaped by this crisis. However, there is limited research devoted to understanding the rapidly evolving trip patterns of micro-mobility in response to COVID-19. To fill this gap, we analyze the changes in micro-mobility usage before and during the lockdown period exploiting high-resolution micro-mobility trip data collected in Zurich, Switzerland. Specifically, docked bike, docked e-bike, and dockless e-bike are evaluated and compared from the perspective of space, time and semantics. First, the spatial and temporal analysis results uncover that the number of trips decreased remarkably during the lockdown period. The striking difference between the normal and lockdown period is the decline in the peak hours of workdays. Second, the origin-destination flows are used to construct spatially embedded networks. The results suggest that the origin-destination pairs remain similar during the lockdown period, while the numbers of trips between each origin-destination pair is reduced due to COVID-19 pandemic. Finally, the semantic analysis is conducted to uncover the changes in trip purpose. It is revealed that the proportions of Home, Park, and Grocery activities increase, while the proportions of Leisure and Shopping activities decrease during the lockdown period. The above results can help planners and policymakers better make evidence-based policies regarding micro-mobility in the post-pandemic society.
|
|
| 30. |
- Lubida, Alex, et al.
(författare)
-
Land-use planning for sustainable urban development in africa : A spatial and multi-objective optimization approach
- 2019
-
Ingår i: Geodesy and Cartography. - : Vilnius Gediminas Technical University. - 2029-6991 .- 2029-7009. ; 45:1, s. 1-15
-
Tidskriftsartikel (refereegranskat)abstract
- Land-use planning, which requires finding a balance among different conflicting social, economic and environment factors, is a complex task needed everywhere, including Africa. One example is the city of Zanzibar in Tanzania, which is under special consideration for land-use revision. From one side, the city has high potentials for tourist industry and at the other side there are major challenges with the city structure and poor accessibilities. In order to prepare a proper land-use plan for the city, a variety of influencing conflicting factors needs to be considered and satisfied. This can be regarded as a common problem in many African cities, which are under development. This paper aims to address the problem by proposing and demonstrating the use of Geographical Information System (GIS) and multi-objective optimization for land-use planning, in Zanzibar as a case study. The measures which have been taken by Zanzibar government to address the development challenges through the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) were identified by studying related documents and interviewing experts. Based on these, two objective functions were developed for land-use planning. Optimum base land-use plans were developed and mapped by optimizing the objective functions using the NSGA-II algorithm. The results show that the proposed approach and outputs can considerably facilitate land-use planning in Zanzibar. Similar approaches are highly recommended for other cities in Africa which are under development.
|
|
| 31. |
|
|
| 32. |
- Mansourian, Ali, et al.
(författare)
-
Expert System to Enhance the Functionality of Clearinghouse Services
- 2011
-
Ingår i: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715. ; 35:2, s. 159-172
-
Tidskriftsartikel (refereegranskat)abstract
- Abstract in UndeterminedSpatial data clearinghouses are one of the key features of a spatial data infrastructure (SDI). However, recent research indicates that few national clearinghouses function well, as the spatial data resources available cannot be satisfactorily accessed or optimally used. To improve the functionality, we propose that clearinghouses to be complemented with expert systems and semantic matching. The expert system facilitates automatic determination of candidate datasets and the conversion of the available data to the required data. A schema translator is also used to find similar data that might be used in other disciplines or other datasets by semantic matching. In order to accomplish this, we have developed a method of identifying available data and methods for data conversion. The methodology is implemented using standardized map services. Practical tests show that the discovery of available data in the clearinghouse satisfying users' requirements is substantially increased, which is an important step forward in building future SDIs. (C) 2010 Elsevier Ltd. All rights reserved.
|
|
| 33. |
|
|
| 34. |
- Mansourian, Ali, et al.
(författare)
-
SDI planning using the system dynamics technique within a community of practice: lessons learnt from Tanzania
- 2015
-
Ingår i: Geo-Spatial Information Science. - : Informa UK Limited. - 1009-5020 .- 1993-5153. ; 18:2-3, s. 97-110
-
Tidskriftsartikel (refereegranskat)abstract
- There exist major challenges in accelerating the spatial data infrastructure (SDI) planning process in the developing countries as well as advocating for politicians to support the development of SDI, due to the high complexity of SDI, lack of knowledge and experience, and limited insight in the benefits. To address these challenges, a methodology for SDI planning in Tanzania, based on the system dynamics technique and the communities of practice concept, was adopted and applied within a community consisting of experts from stakeholder organizations. The groups gathered to develop an SDI plan, while they shared their knowledge and discussed their ideas that helped their understanding of SDI. By running the system dynamics model, the development of SDI over time could be simulated that gave the planning community an insight about the future effects of today’s plans and decisions. Finally, an optimum model could be developed by refinements and improvements done with the consensus of the SDI stakeholders. This model included the components and policies that are essential for a successful SDI implementation in Tanzania and can be used as a basis for SDI planning and help to gain political support. Lessons learnt from this research were promising regarding the usability of the methodology for SDI planning in comparable countries.
|
|
| 35. |
- Masoumi, Zohreh, et al.
(författare)
-
Dynamic urban land-use change management using multi-objective evolutionary algorithms
- 2020
-
Ingår i: Soft Computing: A Fusion of Foundations, Methodologies and Applications. - : Springer Science and Business Media LLC. - 1432-7643. ; 24:6, s. 4165-4190
-
Tidskriftsartikel (refereegranskat)abstract
- Frequent land-use changes in urban areas require an efficient and dynamic approach to reform and update detailed plans by re-arrangement of surrounding land-uses in case of change in one or several urban land-uses. However, re-arrangement of land-uses is problematic, since a variety of conflicting criteria must be considered and satisfied. This paper proposes and examines a two-step approach to resolve the issue. The first step adopts a multi-objective optimization technique to obtain an optimal arrangement of surrounding land-uses in case of change in one or several urban land-uses, whereas the second step uses clustering analysis to produce appropriate solutions for decision makers from the outputs of the first step. To present and assess the approach, a case study was conducted in Tehran, the capital of Iran. To satisfy the first step, four conflicting objective functions including maximization of consistency, maximization of dependency, maximization of suitability and maximization of compactness were defined and optimized using non-dominated sorting genetic algorithm. Per-capita demand was also employed as a constraint in the optimization process. Clustering analysis based on ant colony optimization was used to satisfy the second step. The results of the optimization were satisfactory both from a convergence and from a repeatability point of view. Furthermore, the objective functions of optimized arrangements were better than existing land-use arrangement in the area, with the per-capita demand deficiency significantly compensated. The approach was also communicated to urban planners in order to assess its usefulness. In conclusion, the proposed approach can extensively support and facilitate decision making of urban planners and policy makers in reforming and updating existing detailed plans after land-use changes.
|
|
| 36. |
- Masoumi, Zohreh, et al.
(författare)
-
Using an Evolutionary Algorithm in Multiobjective Geographic Analysis for Land Use Allocation and Decision Supporting
- 2017
-
Ingår i: Geographical Analysis. - : Wiley. - 0016-7363. ; 49:1, s. 58-83
-
Tidskriftsartikel (refereegranskat)abstract
- Usually, allocation of resources is an optimization problem which involves a variety of conflicting economic, social, and ecological objectives. In such a process, advanced geographic analyst tool for manipulation of spatial data and satisfaction of multiple objectives is essential to the success of decision-making. The present research intends to demonstrate the application of a multiobjective optimization method based on NSGA-II (we call it HNSGA-II), along with Geographical Information System (GIS) to select suitable sites for the establishment of large industrial units. Having defined the elements of HNSGA-II for the site selection of industrial units, the method is tested on the data of Zanjan province, Iran, as the case study. The results showed that the proposed approach can easily find a variety of optimized solutions, giving the decision-makers the possibility to opt for the most propitious solution. Using this method, the achievement level regarding each objective function can be studied for any of the nondominated solutions.
|
|
| 37. |
- Nakasi, Rose, et al.
(författare)
-
A web-based intelligence platform for diagnosis of malaria in thick blood smear images : A case for a developing country
- 2020
-
Ingår i: Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. - 2160-7516 .- 2160-7508. - 9781728193601 ; 2020-June, s. 4238-4244
-
Konferensbidrag (refereegranskat)abstract
- Malaria is a public health problem which affects developing countries world-wide. Inadequate skilled lab technicians in remote areas of developing countries result in untimely diagnosis of malaria parasites making it hard for effective control of the disease in highly endemic areas. The development of remote systems that can provide fast, accurate and timely diagnosis is thus a necessary innovation. With availability of internet, mobile phones and computers, rapid dissemination and timely reporting of medical image analytics is possible. This study aimed at developing and implementing an automated web-based Malaria diagnostic system for thick blood smear images under light microscopy to identify parasites. We implement an image processing algorithm based on a pre-trained model of Faster Convolutional Neural Network (Faster R-CNN) and then integrate it with web-based technology to allow easy and convenient online identification of parasites by medical practitioners. Experiments carried out on the online system with test images showed that the system could identify pathogens with a mean average precision of 0.9306. The system holds the potential to improve the efficiency and accuracy in malaria diagnosis, especially in remote areas of developing countries that lack adequate skilled labor.
|
|
| 38. |
- Ndagijimana, Albert, et al.
(författare)
-
Childhood stunting is highly clustered in Northern Province of Rwanda : A spatial analysis of a population-based study
- 2024
-
Ingår i: Heliyon. - : Elsevier. - 2405-8440. ; 10:2
-
Tidskriftsartikel (refereegranskat)abstract
- Background: In Northern Province, Rwanda, stunting is common among children aged under 5 years. However, previous studies on spatial analysis of childhood stunting in Rwanda did not assess its randomness and clustering, and none were conducted in Northern Province. We conducted a spatial-pattern analysis of childhood undernutrition to identify stunting clusters and hotspots for targeted interventions in Northern Province. Methods: Using a household population-based questionnaire survey of the characteristics and causes of undernutrition in households with biological mothers of children aged 1–36 months, we collected anthropometric measurements of the children and their mothers and captured the coordinates of the households. Descriptive statistics were computed for the sociodemographic characteristics and anthropometric measurements. Spatial patterns of childhood stunting were determined using global and local Moran's I and Getis-Ord Gi* statistics, and the corresponding maps were produced. Results: The z-scores of the three anthropometric measurements were normally distributed, but the z-scores of height-for-age were generally lower than those of weight-for-age and weight-for-height, prompting us to focus on height-for-age for the spatial analysis. The estimated incidence of stunting among 601 children aged 1–36 months was 27.1 %. The sample points were interpolated to the administrative level of the sector. The global Moran's I was positive and significant (Moran's I = 0.403, p < 0.001, z-score = 7.813), indicating clustering of childhood stunting across different sectors of Northern Province. The local Moran's I and hotspot analysis based on the Getis-Ord Gi* statistic showed statistically significant hotspots, which were strongest within Musanze district, followed by Gakenke and Gicumbi districts. Conclusion: Childhood stunting in Northern Province showed statistically significant hotspots in Musanze, Gakenke, and Gicumbi districts. Factors associated with such clusters and hotspots should be assessed to identify possible geographically targeted interventions.
|
|
| 39. |
- Nduwayezu, Gilbert, et al.
(författare)
-
Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest : A case study in Rwanda
- 2023
-
Ingår i: Geospatial health. - 1970-7096. ; 18:1
-
Tidskriftsartikel (refereegranskat)abstract
- As found in the health studies literature, the levels of climate association between epidemiological diseases have been found to vary across regions. Therefore, it seems reasonable to allow for the possibility that relationships might vary spatially within regions. We implemented the geographically weighted random forest (GWRF) machine learning method to analyze ecological disease patterns caused by spatially non-stationary processes using a malaria incidence dataset for Rwanda. We first compared the geographically weighted regression (WGR), the global random forest (GRF), and the geographically weighted random forest (GWRF) to examine the spatial non-stationarity in the non-linear relationships between malaria incidence and their risk factors. We used the Gaussian areal kriging model to disaggregate the malaria incidence at the local administrative cell level to understand the relationships at a fine scale since the model goodness of fit was not satisfactory to explain malaria incidence due to the limited number of sample values. Our results show that in terms of the coefficients of determination and prediction accuracy, the geographical random forest model performs better than the GWR and the global random forest model. The coefficients of determination of the geographically weighted regression (R2), the global RF (R2), and the GWRF (R2) were 4.74, 0.76, and 0.79, respectively. The GWRF algorithm achieves the best result and reveals that risk factors (rainfall, land surface temperature, elevation, and air temperature) have a strong non-linear relationship with the spatial distribution of malaria incidence rates, which could have implications for supporting local initiatives for malaria elimination in Rwanda.
|
|
| 40. |
- Niyomubyeyi, Olive, et al.
(författare)
-
A Comparative Study of Four Metaheuristic Algorithms, AMOSA, MOABC, MSPSO, and NSGA-II for Evacuation Planning
- 2020
-
Ingår i: Algorithms. - : MDPI AG. - 1999-4893. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- Evacuation planning is an important activity in disaster management to reduce the effects of disasters on urban communities. It is regarded as a multi-objective optimization problem that involves conflicting spatial objectives and constraints in a decision-making process. Such problems are difficult to solve by traditional methods. However, metaheuristics methods have been shown to be proper solutions. Well-known classical metaheuristic algorithms—such as simulated annealing (SA), artificial bee colony (ABC), standard particle swarm optimization (SPSO), genetic algorithm (GA), and multi-objective versions of them—have been used in the spatial optimization domain. However, few types of research have applied these classical methods, and their performance has not always been well evaluated, specifically not on evacuation planning problems. This research applies the multi-objective versions of four classical metaheuristic algorithms (AMOSA, MOABC, NSGA-II, and MSPSO) on an urban evacuation problem in Rwanda in order to compare the performances of the four algorithms. The performances of the algorithms have been evaluated based on the effectiveness, efficiency, repeatability, and computational time of each algorithm. The results showed that in terms of effectiveness, AMOSA and MOABC achieve good quality solutions that satisfy the objective functions. NSGA-II and MSPSO showed third and fourth-best effectiveness. For efficiency, NSGA-II is the fastest algorithm in terms of execution time and convergence speed followed by AMOSA, MOABC, and MSPSO. AMOSA, MOABC, and MSPSO showed a high level of repeatability compared to NSGA-II. It seems that by modifying MOABC and increasing its effectiveness, it could be a proper algorithm for evacuation planning.
|
|
| 41. |
- Niyomubyeyi, Olive, et al.
(författare)
-
An improved non-dominated sorting biogeography-based optimization algorithm for multi-objective land-use allocation: a case study in Kigali-Rwanda
- 2024
-
Ingår i: Geo-Spatial Information Science. - : Informa UK Limited. - 1009-5020 .- 1993-5153. ; , s. 1-15
-
Tidskriftsartikel (refereegranskat)abstract
- With the continuous increase of rapid urbanization and population growth, sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers. Multi-objective land-use allocation can be regarded as a complex spatial optimization problem that aims to achieve the possible trade-offs among multiple and conflicting objectives. This paper proposes an improved Non-dominated Sorting Biogeography-Based Optimization (NSBBO) algorithm for solving the multi-objective land-use allocation problem, in which maximum accessibility, maximum compactness, and maximum spatial integration were formulated as spatial objectives; and space syntax analysis was used to analyze the potential movement patterns in the new urban planning area of the city of Kigali, Rwanda. Efficient Non-dominated Sorting (ENS) algorithm and crossover operator were integrated into classical NSBBO to improve the quality of non-dominated solutions, and local search ability, and to accelerate the convergence speed of the algorithm. The results showed that the proposed NSBBO exhibited good optimal solutions with a high hypervolume index compared to the classical NSBBO. Furthermore, the proposed algorithm could generate optimal land use scenarios according to the preferred objectives, thus having the potential to support the decision-making of urban planners and stockholders in revising and updating the existing detailed master plan of land use.
|
|
| 42. |
- Niyomubyeyi, Olive, et al.
(författare)
-
Evacuation planning optimization based on a multi-objective artificial bee colony algorithm
- 2019
-
Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 8:3
-
Tidskriftsartikel (refereegranskat)abstract
- Evacuation is an important activity for reducing the number of casualties and amount of damage in disaster management. Evacuation planning is tackled as a spatial optimization problem. The decision-making process for evacuation involves high uncertainty, conflicting objectives, and spatial constraints. This study presents a Multi-Objective Artificial Bee Colony (MOABC) algorithm, modified to provide a better solution to the evacuation problem. The new approach combines random swap and random insertion methods for neighborhood search, the two-point crossover operator, and the Pareto-based method. For evacuation planning, two objective functions were considered to minimize the total traveling distance from an affected area to shelters and to minimize the overload capacity of shelters. The developed model was tested on real data from the city of Kigali, Rwanda. From computational results, the proposed model obtained a minimum fitness value of 5.80 for capacity function and 8.72 × 10 8 for distance function, within 161 s of execution time. Additionally, in this research we compare the proposed algorithm with Non-Dominated Sorting Genetic Algorithm II and the existing Multi-Objective Artificial Bee Colony algorithm. The experimental results show that the proposed MOABC outperforms the current methods both in terms of computational time and better solutions with minimum fitness values. Therefore, developing MOABC is recommended for applications such as evacuation planning, where a fast-running and efficient model is needed.
|
|
| 43. |
- Olsson, Per-Ola, et al.
(författare)
-
Exploring the potential to use in-between pixel variability for early detection of bark beetle attacked trees
- 2023. - 35
-
Ingår i: 26th AGILE Conference on Geographic Information Science “Spatial data for design”. ; 4:1
-
Konferensbidrag (refereegranskat)abstract
- The European spruce bark beetle (Ips typographus L.) is a major disturbance agent in Norway spruce (Picea abies (L.) Karst) forests in Europe and it is estimated that a changing climate will result in more severe outbreaks in the future. To reduce the risk of large outbreaks it is important to have methods that enable early detection of bark beetle attacks to help forest managers to prevent population build-up, e.g by sanitary cutting. Several studies have been devoted to early detection of bark beetle attacks with Sentinel-2 data with a focus on spectral properties and vegetation indices for early detection with pixel-based methods. In this study we explore the potential to use changes in variability between pixels in windows of different sizes (3×3, 4×4 and 5×5 pixels). We compute the coefficient of variation for four vegetation indices (NDVI, NDWI, CCI and NDRS) in a time-series of Sentinel-2 data during a bark beetle outbreak in Sweden that was triggered by a drought in 2018. The results indicate that CCI is the most promising index for early detection and that the variability between pixels increase in windows with attacked trees from late July when the main swarming was the second week of May.
|
|
| 44. |
- Omidipoor, Morteza, et al.
(författare)
-
Knowledge discoveryweb service for spatial data infrastructures
- 2021
-
Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge DiscoveryWeb Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.
|
|
| 45. |
- Pilehforooshha, Parastoo, et al.
(författare)
-
A new model combining building block displacement and building block area reduction for resolving spatial conflicts
- 2021
-
Ingår i: Transactions in GIS. - : Wiley. - 1361-1682 .- 1467-9671. ; 25, s. 1366-1395
-
Tidskriftsartikel (refereegranskat)abstract
- Applying pre-processing and geometric transformation, for the generalization of building blocks, can lead to spatial conflicts which are mainly resolved by displacement. However, the conflicts may not be resolved, due to the insufficient space for displacement or the existence of other objects that prevent displacement. This article proposes a novel model combining building block displacement and building block area reduction for resolving spatial conflicts. In this model, first the immune genetic algorithm with improved objective function, with the goal of minimizing the total conflicting area, is used for displacement. Second, a building block area reduction model is applied to reduce the area of the unresolved conflicting building blocks. For this, a building segment partitioning model is developed for partitioning the boundaries of conflicting building blocks. Then, the conflicting segments are locally simplified for more adaptation to the initial generalized ones. We generalized two datasets from scale 1:25 to 1:50k and then used the datasets with scale 1:50k to assess the proposed model. The results demonstrate that the proposed model has improved the correctness and completeness by 3.62 and 4.24% for dataset 1 and 5.67 and 7.92% for dataset 2, respectively, compared to one of the recent models for resolving conflicts.
|
|
| 46. |
- Pilesjo, Petter, et al.
(författare)
-
Features of the international MSC educational programme in environmental management and modelling
- 2018
-
Ingår i: Geodesy and Cartography. - : Vilnius Gediminas Technical University. - 2029-6991 .- 2029-7009. ; 44:4, s. 134-139
-
Tidskriftsartikel (refereegranskat)abstract
- “International Msc Educational Programme in Environmental Management and Modelling” (GeoNetC) is a European Commission funded project under ERASMUS+: Higher Education – International Capacity Building programme (Project No 561967-EPP-1-2015-1-SE-EPPKA2-CBHE-JP). It began in October 2015 and ended in October 2018. Initiated by the Lund University and partners from the Middle East countries, the GeoNetC project is an ambitious project aiming to match labour market needs with geospatial education offer both in Europe and Middle East countries. The aim of this three-year project is to enable European universities to exchange best practices and innovation with each other and with Middle Eastern universities regarding the mismatch between Europe’s geospatial education and training and the geospatial education in Middle East countries. There is a growing need for well-trained students at all levels – vocational, bachelors, masters – in the field of geospatial technologies. Obviously there is a growing number of jobs available in land surveying, mapping data collection, data processing, data delivery and turning data into information in both European and Middle East countries. Through cooperation, all partners will improve the quality of their respective academic programs. The European partners will make their courses more attractive and well adjusted for students from the Middle East. As well, they will increase the general quality and add state-of-the-art learning components to their offerings, and the partners from the region will significantly increase the academic level and quality in the education they provide. There will be spin-offs into other subjects than environment/Geomatics, since both the pedagogic models developed (e.g. e-Learning) and communication and administrative tools can be used throughout the partner universities. Therefore, this partnership cooperation will be of great value to Partner Countries as well as to Programme Countries. A number of distance learning courses/modules are developed jointly by partner institutions in Europe and the Middle East. The main aim of the network is to promote the use of spatial information and earth observation for environmental management and modelling through capacity building and institutional development, via a network in which all partners would contribute from their own positions of strength. All 13 modules are following EU higher education standards regarding e.g. ECTS, and learning outcomes. The outcome of the project, in terms of courses/modules, will be freely used among the partners, with the possibilities of offering individual courses or a whole MSc programme, whether individually or together. All produced material was evaluated/quality controlled by an external evaluation group of independent experts within environmental management and modelling, higher education, as well as pedagogy.
|
|
| 47. |
- Pilesjö, Petter, et al.
(författare)
-
Root system estimation based on satellite remote sensing : An applied study in Eastern Uganda
- 2018
-
Ingår i: Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden.
-
Konferensbidrag (refereegranskat)abstract
- The density of roots is an important factor influencing the rate and magnitude of landslides. Due to the increased variability in climate, mainly rainfall, Eastern Uganda is severely struck by an increasing number of these mass movements, often with human casualties as one of the negative impacts. The aim of this study is to explore the possibility to estimate the depth and density of the root system influencing the resistance to landslides, from satellite remote sensing data. 104 samples were collected in field, where the root system was classified into 5 different classes, from non-existing to dense and deep (forest). The study was carried out in the Mount Elgon area located at the Ugandan-Kenyan border. The field data were then compared with 30 m Landsat TM data, in order to investigate possible links between reflectance (single bands as well as indices) and ground truth data. The results indicate that, following this methodology, it is not possible to estimate the root system density based on the remotely sensed data, since the maximum Cohen’s kappa value of 0.081 is judged deficient.
|
|
| 48. |
- Rajabi, Mohammadreza, et al.
(författare)
-
A spatially explicit agent-based modeling approach for the spread of Cutaneous Leishmaniasis disease in central Iran, Isfahan
- 2016
-
Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152. ; 82, s. 330-346
-
Tidskriftsartikel (refereegranskat)abstract
- Cutaneous Leishmaniasis (CL) is an endemic vector-borne disease in the Middle East and a worldwide public health problem. The spread of CL is highly associated with the socio-ecological interactions of vectors, hosts and the environment. The heterogeneity of these interactions has hindered CL modeling for healthcare preventive measures in endemic areas. In this study, an agent-based model (ABM) is developed to simulate the dynamics of CL spread based on a Geographic Automata System (GAS). A Susceptible-Exposed-Infected-Recovered (SEIR) approach together with Bayesian modeling has been applied in the ABM to explore the spread of CL. The model is then adapted locally for Isfahan Province, an endemic area in central Iran. The results from the model indicate that desertification areas are the main origin of CL, and riverside population centers have the potential to host more sand fly exposures and should receive more preventive measures from healthcare authorities. The results also show that healthcare service accessibility prevented exposures from becoming infected and areas with new inhabitants experienced more infections from same amount of sand fly exposures.
|
|
| 49. |
- Rajabi, Mohammadreza, et al.
(författare)
-
Comparing Knowledge-Driven and Data-Driven Modeling methods for susceptibility mapping in spatial epidemiology : a case study in Visceral Leishmaniasis
- 2014
-
Ingår i: Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6. ; , s. 1-5
-
Konferensbidrag (refereegranskat)abstract
- The aim of this study is to compare knowledge-driven and data-driven methods for susceptibility mapping in spatial epidemiology. Our comparison focuses on one of the arguably most important requisites in such models, namely predictability. We compare one data-driven modelling method called Radial Basis Functional Link Net (RBFLN - a well-established Neural Network method) with two knowledge-driven modelling methods, Fuzzy AHP_OWA and Fuzzy GIS-based group decision making (multi criteria decision making methods). These methods are compared in the context of a concrete case study, namely the environmental modelling of Visceral Leishmaniasis (VL) for predictive mapping of risky areas. Our results show that, at least in this particular application, RBFLN model offers the best predictive accuracy
|
|
| 50. |
- Rajabi, Mohammadreza, et al.
(författare)
-
Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks : a case study in north-western Iran
- 2014
-
Ingår i: Geospatial health. - : PAGEPress Publications. - 1970-7096 .- 1827-1987. ; 9:1, s. 179-191
-
Tidskriftsartikel (refereegranskat)abstract
- Visceral leishmaniasis (VL) is a potentially fatal vector-borne zoonotic disease, which has become an increasing public health problem in the north-western part of Iran. This work presents an environmental health modelling approach to map the potential of VL outbreaks in this part of the country. Radial basis functional link networks is used as a data-driven method for predictive mapping of VL in the study area. The high susceptibility areas for VL outbreaks account for 36.3% of the study area and occur mainly in the north (which may affect the neighbouring countries) and South (which is a warning for other provinces in Iran). These parts of the study area have many nomadic, riverside villages. The overall accuracy of the resultant map was 92% in endemic villages. Such susceptibility maps can be used as reconnaissance guides for planning of effective control strategies and identification of possible new VL endemic areas.
|
|
