1. |
- Abdi, A. M., et al.
(författare)
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First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems
- 2019
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 78, s. 249-260
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Tidskriftsartikel (refereegranskat)abstract
- The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO 2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO 2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GöR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3–65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation (R 2 ), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The GöR model produced R 2 = 0.73, RMSE = 1.45 g C m −2 d −1 , and BIC = 678; the T-G model produced R 2 = 0.68, RMSE = 1.57 g C m −2 d −1 , and BIC = 707; the MOD17 model produced R 2 = 0.49, RMSE = 1.98 g C m −2 d −1 , and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R 2 = 0.77, RMSE = 1.32 g C m −2 d −1 , and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.
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2. |
- Ardö, Jonas, et al.
(författare)
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MODIS EVI-based net primary production in the Sahel 2000–2014
- 2018
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 65, s. 35-45
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Tidskriftsartikel (refereegranskat)abstract
- Africa is facing resource problems due to increasing demand combined with potential climate-induced changes in supply. Here we aim to quantify resources in terms of net primary production (NPP [g C m−2 yr−1]) of vegetation in the Sahel region for 2000–2014.Using time series of the enhanced vegetation index (EVI) from MODIS, NPP was estimated for the Sahel region with a 500 × 500 m spatial resolution and 8-day temporal resolution. The estimates were based on local eddy covariance flux measurements from six sites in the Sahel region and the carbon use efficiency originating from a dynamic vegetation model.No significant NPP change was found for the Sahel as a region but, for sub-regions, significant changes, both increasing and decreasing, were observed. Substantial uncertainties related to NPP estimates and the small availability of evaluation data makes verification difficult. The simplicity of the methodology used, dependent on earth observation only, is considered an advantage.
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4. |
- Bhardwaj, Anshuman, et al.
(författare)
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A review on remotely sensed land surface temperature anomaly as an earthquake precursor
- 2017
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier. - 1569-8432 .- 1872-826X. ; 63, s. 158-166
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Tidskriftsartikel (refereegranskat)abstract
- The low predictability of earthquakes and the high uncertainty associated with their forecasts make earthquakes one of the worst natural calamities, capable of causing instant loss of life and property. Here, we discuss the studies reporting the observed anomalies in the satellite-derived Land Surface Temperature (LST) before an earthquake. We compile the conclusions of these studies and evaluate the use of remotely sensed LST anomalies as precursors of earthquakes. The arrival times and the amplitudes of the anomalies vary widely, thus making it difficult to consider them as universal markers to issue earthquake warnings. Based on the randomness in the observations of these precursors, we support employing a global-scale monitoring system to detect statistically robust anomalous geophysical signals prior to earthquakes before considering them as definite precursors.
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6. |
- Bohlin, Inka, et al.
(författare)
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Quantifying post-fire fallen trees using multi-temporal lidar
- 2017
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 0303-2434 .- 1569-8432. ; 63, s. 186-195
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Tidskriftsartikel (refereegranskat)abstract
- Massive tree-felling due to root damage is a common fire effect on burnt areas in Scandinavia, but has so far not been analyzed in detail. Here we explore if pre- and post-fire lidar data can be used to estimate the proportion of fallen trees. The study was carried out within a large (14,000 ha) area in central Sweden burnt in August 2014, where we had access to airborne lidar data from both 2011 and 2015. Three data-sets of predictor variables were tested: POST (post-fire lidar metrics), D1F (difference between post- and pre-fire lidar metrics) and combination of those two (POST_DIF). Fractional logistic regression was used to predict the proportion of fallen trees. Training data consisted of 61 plots, where the number of fallen and standing trees was calculated both in the field and with interpretation of drone images. The accuracy of the best model was tested based on 100 randomly selected validation plots with a size of 25 x 25 m.Our results showed that multi-temporal lidar together with field-collected training data can be used for quantifying post-fire tree felling over large areas. Several height-, density- and intensity metrics correlated with the proportion of fallen trees. The best model combined metrics from both datasets (POST DIF), resulting in a RMSE of 0.11. Results were slightly poorer in the validation plots with RMSE of 0.18 using pixel size of 12.5 m and RMSE of 0.15 using pixel size of 6.25 m. Our model performed least well for stands that had been exposed to high-intensity crown fire. This was likely due to the low amount of echoes from the standing black tree skeletons. Wall-to-wall maps produced with this model can be used for landscape level analysis of fire effects and to explore the relationship between fallen trees and forest structure, soil type, fire intensity or topography.
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7. |
- Haas, Jan, et al.
(författare)
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Satellite monitoring of urbanization and environmental impacts : A comparison of Stockholm and Shanghai
- 2015
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432 .- 1872-826X. ; 38, s. 138-149
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Tidskriftsartikel (refereegranskat)abstract
- This study investigates urbanization and its potential environmental consequences in Shanghai andStockholm metropolitan areas over two decades. Changes in land use/land cover are estimated fromsupport vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix fea-tures. Landscape metrics are used to investigate changes in landscape composition and configurationand to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbaniza-tion is calculated by urbanization indices and the resulting impacts on the environment are quantified byecosystem services. Growth of urban areas and urban green spaces occurred at the expense of croplandin both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120%in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover changewas a 12% urban expansion that mostly replaced agricultural areas. From the landscape metrics results,it appears that fragmentation in both study regions occurred mainly due to the growth of high densitybuilt-up areas in previously more natural/agricultural environments, while the expansion of low densitybuilt-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted inecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to thedecrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very lit-tle. Total urban growth in Shanghai was 1768 km2and 100 km2in Stockholm. The developed methodologyis considered a straight-forward low-cost globally applicable approach to quantitatively and qualitativelyevaluate urban growth patterns that could help to address spatial, economic and ecological questions inurban and regional planning.
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8. |
- Huesca, Margarita, et al.
(författare)
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Ecosystem functional assessment based on the "optical type" concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation
- 2015
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 43, s. 132-148
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Tidskriftsartikel (refereegranskat)abstract
- Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MOD IS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found. Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability. (C) 2015 Elsevier B.V. All rights reserved.
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9. |
- Karlson, Martin, et al.
(författare)
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Assessing the potential of multi-seasonal WorldView-2 imagery for mapping West African agroforestry tree species
- 2016
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432 .- 0303-2434 .- 1872-826X. ; 50:August, s. 80-88
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Tidskriftsartikel (refereegranskat)abstract
- High resolution satellite systems enable efficient and detailed mapping of tree cover, with high potential to support both natural resource monitoring and ecological research. This study investigates the capability of multi-seasonal WorldView-2 imagery to map five dominant tree species at the individual tree crown level in a parkland landscape in central Burkina Faso. The Random Forest algorithm is used for object based tree species classification and for assessing the relative importance of WorldView-2 predictors. The classification accuracies from using wet season, dry season and multi-seasonal datasets are compared to gain insights about the optimal timing for image acquisition. The multi-seasonal dataset produced the most accurate classifications, with an overall accuracy (OA) of 83.4%. For classifications based on single date imagery, the dry season (OA = 78.4%) proved to be more suitable than the wet season (OA = 68.1%). The predictors that contributed most to the classification success were based on the red edge band and visible wavelengths, in particular green and yellow. It was therefore concluded that WorldView- 2, with its unique band configuration, represents a suitable data source for tree species mapping in West African parklands. These results are particularly promising when considering the recently launched WorldView-3, which provides data both at higher spatial and spectral resolution, including shortwave infrared bands.
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10. |
- Martínez, B., et al.
(författare)
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Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products
- 2018
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 65, s. 124-136
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Tidskriftsartikel (refereegranskat)abstract
- The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m−2 day−1; MBE = −0.63 g m−2 day−1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m−2 day−1) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m−2 day−1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to −3.0 g m−2 day−1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.
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