| 1. |
- Miura, Y., et al.
(författare)
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SOIL MOISTURE MONITORING OF AGRICULTURAL FIELDS IN BURKINA FASO USING DUAL POLARIZED SENTINEL-1A DATA
- 2019
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Ingår i: International Geoscience and Remote Sensing Symposium (IGARSS). - : IEEE. - 9781538691540 ; , s. 7045-7048
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Konferensbidrag (refereegranskat)abstract
- We investigated the correlation between backscatter and soil moisture considering precipitation and crop effects using dual polarized Sentinel-1A data. The analyzed data consist of a time-series of 38 Sentinel-1A GRD images acquired on a 12-days repeat cycle from July 2017 to October 2018 over Sapone in Burkina Faso. We show that the temporal change of backscatter corresponds to the soil moisture content rather than crops.
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| 2. |
- Allard, Anna, et al.
(författare)
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Fångst av vegetationsdata och Natura 2000-habitat i fjällen genom flygbildstolkning i IRF med punktgittermetodik
- 2007
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- I denna rapport visas att flygbildstolkning med punktgittermetodik har stor potential för att ta fram tillförlitliga och kostnadseffektiva data på tillstånd och förändringar i fjällens vegetation. Projektet är finansierat av Naturvårdsverkets svenska miljöövervakning.Inom denna studie har följande delmål nåtts1) Utprovning av försöksdesign har gjorts med antal och fördelning av punkter, samt design och val av tolkningsvariabler.2) Ett operativt tolkningssystem för punktgittertolkning har tagits fram.3) Tolkningsprecisionen för olika variabler och Natura 2000-habitat är utvärderade mot fältdata.4) Metodens kvaliteter är utvärderade.5) Beräkning av tidsåtgång och kostnadsberäkningar är gjorda och ställda mot en polygonbaserad metod för översiktlig tolkning av NILS 5x5 km ruta.Förutom dessa delmål har även säkerheten ytterligare undersökts via ett personvariationstest av tolkade data.Resultaten från de tolkade fältpunkterna visar att överensstämmelsen med fältinventeringen är mycket god. Ett gott resultat fanns från testet med personvariation, med några få problemområden. Metoden har några begränsningar. För flygbildstolkning i punktgitter med den metodik som föreslås här förutsätts att det finns välutbildade tolkare. För en van vegetationstolkare krävs det i storleksordning en tilläggsutbildning på minst 1 månad i tolkning av fjällvegetation, inklusive fältbesök. En exempelsamling av bilder och ett antal nycklar för tolkning bör tas fram.Punktgittermetoden är operativt användbar, vissa kompletterande fältstudier behövs. Metoden har följande generella kvaliteter.Metoden är enkel att implementera.Punktgittermetoden är en kostnadseffektiv metod för att fånga landskapsdata. Den är snabbare än polygontolkning.Datafångst från en 5 x 5 km ruta kan göras på 1-3 dagar, beroende på antal punkter i gittret.Det är enkelt att bearbeta och analysera punktgitterdata.Precisionen i arealskattningarna kommer att kunna enkelt beräknas.Tolkningen i punktgitter kan verifieras genom jämförelse med NILS fältdata.Metoden är lämplig för förändringsstudier. Exempelvis kan den utgöra ett snabbt och effektivt sätt att statistiskt uppdatera information om area av vegetationstyper från vegetationskartorna över de svenska fjällen.Metoden kan fånga upp ovanligare naturtyper i 5 x 5 km ytan förutsatt att många punkter tolkas.Metoden kan användas för urval av objekt för riktade fältinventeringar till ovanligare habitat.Resultaten från metoden kan utgöra viktiga data för annan forskning, exempelvis som träningsdata till satellitbildsklassificeringar.
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| 3. |
- Axelsson, Arvid, et al.
(författare)
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Tree species classification using Sentinel-2 imagery and Bayesian inference
- 2021
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432 .- 0303-2434. ; 100
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Tidskriftsartikel (refereegranskat)abstract
- The increased temporal frequency of optical satellite data acquisitions provides a data stream that has the potential to improve land cover mapping, including mapping of tree species. However, for large area operational mapping, partial cloud cover and different image extents can pose challenges. Therefore, methods are needed to assimilate new images in a straightforward way without requiring a total spatial coverage for each new image. This study shows that Bayesian inference applied sequentially has the potential to solve this problem. To test Bayesian inference for tree species classification in the boreo-nemoral zone of southern Sweden, field data from the study area of Remningstorp (58°27′18.35″ N, 13°39′8.03″ E) were used. By updating class likelihood with an increasing number of combined Sentinel-2 images, a higher and more stable cross-validated overall accuracy was achieved. Based on a Mahalanobis distance, 23 images were automatically chosen from the period of 2016 to 2018 (from 142 images total). An overall accuracy of 87% (a Cohen’s kappa of 78.5%) was obtained for four tree species classes: Betula spp., Picea abies, Pinus sylvestris, and Quercus robur. This application of Bayesian inference in a boreo-nemoral forest suggests that it is a practical way to provide a high and stable classification accuracy. The method could be applied where data are not always complete for all areas. Furthermore, the method requires less reference data than if all images were used for classification simultaneously.
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| 4. |
- Bargues Tobella, Aida, et al.
(författare)
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The effect of trees on preferential flow and soil infiltrability in an agroforestry parkland in semiarid Burkina Faso
- 2014
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Ingår i: Water Resources Research. - 0043-1397 .- 1944-7973. ; 50, s. 3342-3354
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Tidskriftsartikel (refereegranskat)abstract
- Water scarcity constrains the livelihoods of millions of people in tropical drylands. Tree planting in these environments is generally discouraged due to the large water consumption by trees, but this view may neglect their potential positive impacts on water availability. The effect of trees on soil hydraulic properties linked to groundwater recharge is poorly understood. In this study, we performed 18 rainfall simulations and tracer experiments in an agroforestry parkland in Burkina Faso to investigate the effect of trees and associated termite mounds on soil infiltrability and preferential flow. The sampling points were distributed in transects each consisting of three positions: (i) under a single tree, (ii) in the middle of an open area, and (iii) under a tree associated with a termite mound. The degree of preferential flow was quantified through parameters based on the dye infiltration patterns, which were analyzed using image analysis of photographs. Our results show that the degree of preferential flow was highest under trees associated with termite mounds, intermediate under single trees, and minimal in the open areas. Tree density also had an influence on the degree of preferential flow, with small open areas having more preferential flow than large ones. Soil infiltrability was higher under single trees than in the open areas or under trees associated with a termite mound. The findings from this study demonstrate that trees have a positive impact on soil hydraulic properties influencing groundwater recharge, and thus such effects must be considered when evaluating the impact of trees on water resources in drylands.
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| 5. |
- Brownstein, Catherine A., et al.
(författare)
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An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
- 2014
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Ingår i: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:3, s. R53-
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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| 6. |
- Elsik, Christine G., et al.
(författare)
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The Genome Sequence of Taurine Cattle : A Window to Ruminant Biology and Evolution
- 2009
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 324:5926, s. 522-528
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Tidskriftsartikel (refereegranskat)abstract
- To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
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| 7. |
- Forsman, Mona, et al.
(författare)
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Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths : a simulation study
- 2018
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Ingår i: ISPRS journal of photogrammetry and remote sensing (Print). - Amsterdam : Elsevier. - 0924-2716 .- 1872-8235. ; 135, s. 84-92
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Tidskriftsartikel (refereegranskat)abstract
- In this study we have investigated why diameters of tree stems, which are approximately cylindrical, are often overestimated by mobile laser scanning. This paper analyzes the physical processes when using ground-based laser scanning that may contribute to a bias when estimating cylinder diameters using circle-fit methods. A laser scanner simulator was implemented and used to evaluate various properties, such as distance, cylinder diameter, and beam width of a laser scanner-cylinder system to find critical conditions. The simulation results suggest that a positive bias of the diameter estimation is expected. Furthermore, the bias follows a quadratic function of one parameter - the relative footprint, i.e., the fraction of the cylinder width illuminated by the laser beam. The quadratic signature opens up a possibility to construct a compensation model for the bias.
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| 8. |
- Gilichinsky, Michael, et al.
(författare)
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Application of national forest inventory for remote sensing classification of ground lichen in nothern Sweden
- 2010
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Ingår i: ISPRS Archives. - : International Society for Photogrammetry and Remote Sensing. ; 38-4-8, s. 146-152
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Konferensbidrag (refereegranskat)abstract
- Lichen is a major forage resource for reindeer and may constitute up to 80% of a reindeer's winter diet. The reindeer grazing area in Sweden covers almost half of the country, with reindeer using mountainous areas in the summer and forested areas in the winter. Knowledge about the spatial distribution of ground lichens is important for both practical and sustainable decisionmaking purposes. Since the early 1980s, remote sensing research of lichen cover in northern environments has focused on reindeer grazing issues. The objective of the present study was to use lichen information from the Swedish Forest Inventory (NFI) for classification of satellite data into ground lichen classes. The classification procedure was focused on using of NFI plots as training sets for supervised classification of the ground lichen cover in purpose to classify areas with different lichen coverage. The present research has shown the advantage of use forest inventory plot data by assessment of three methods: mahalanobis distance (MD) classification, maximum likelihood (ML) classification and spectral mixture analysis (SMA). The results of this study demonstrate high classification accuracy of SPOT imagery in distinction between lichenabundant and lichen-poor areas by mahalanobis distance classifier (overall accuracy 84.3%, kappa=0.68). The highest classification accuracy for Landsat scene was achieved by maximumlikelihood classification (overall accuracy 76.8%, kappa=0.53). The continuation research on more detailed fragmentation of lichen cover into fractions is proposed.
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| 9. |
- Gilichinsky, Michael, et al.
(författare)
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Mapping ground lichens using forest inventory and optical satellite data
- 2011
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Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 0143-1161 .- 1366-5901. ; 32:2, s. 455-472
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Tidskriftsartikel (refereegranskat)abstract
- Lichen is a major forage resource for reindeer and may constitute up to 80% of areindeer’s winter diet. The reindeer grazing area in Sweden covers almost half of thecountry, with reindeer using mountainous areas in the summer and forested areas inthe winter. Knowledge about the spatial distribution of ground lichens is importantfor both practical and decision-making purposes. Since the early 1980s, remotesensing research of lichen cover in northern environments has focused on reindeergrazing issues. The objective of this study was to use lichen information collected inthe Swedish National Forest Inventory (NFI) as training data to classify opticalsatellite images into ground lichen cover classes. The study site was located within thereindeer husbandry area in northern Sweden and consisted of the common areabetween two contiguous Satellite Pour l’Observation de la Terre (SPOT)-5 scenesand one Landsat-7 Enhanced Thematic Mapper Plus (ETMþ) scene. Three classificationmethods were tested: Mahalanobis distance, maximum likelihood andspectral mixture analysis. Post-classification calibration was applied using a membershipprobability threshold in order to match the NFI-measured proportions oflichen coverage classes. The classification results were assessed using an independentlycollected field dataset (229 validation areas). The results demonstrated highclassification accuracy of SPOT imagery for the classification of lichen-abundantand lichen-poor areas when using theMahalanobis distance classifier (overall accuracy84.3%, kappa ¼ 0.68). The highest classification accuracy for Landsat wasachieved using a maximum likelihood classification (overall accuracy 76.8%, kappa¼ 0.53). These results provided an initial indication of the utility of NFI data astraining data in the process of mapping lichen classes over large areas.
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| 10. |
- Husson, Eva, et al.
(författare)
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Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation
- 2017
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Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs) can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM) created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a) Growth forms including the classes of water, nymphaeid, and helophyte; and (b) dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each) with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%-21% for growth-forms and 3%-30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities for operative mapping,
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