Reliable crop type maps from satellite data are an essential prerequisite for quantifying crop growth, health, and yields. However, such maps do not exist for most parts of Africa, where smallholder ...farming is the dominant system. Prevalent cloud cover, small farm sizes, and mixed cropping systems pose substantial challenges when creating crop type maps for sub-Saharan Africa. In this study, we provide a mapping scheme based on freely available Sentinel-2A/B (S2) time series and very high-resolution SkySat data to map the main crops—maize and potato—and intercropping systems including these two crops on the Jos Plateau, Nigeria. We analyzed the spectral-temporal behavior of mixed crop classes to improve our understanding of inter-class spectral mixing. Building on the Framework for Operational Radiometric Correction for Environmental monitoring (FORCE), we preprocessed S2 time series and derived spectral-temporal metrics from S2 spectral bands for the main temporal cropping windows. These STMs were used as input features in a hierarchical random forest classification. Our results provide the first wall-to-wall crop type map for this key agricultural region of Nigeria. Our cropland identification had an overall accuracy of 84%, while the crop type map achieved an average accuracy of 72% for the five relevant crop classes. Our crop type map shows distinctive regional variations in the distribution of crop types. Maize is the dominant crop, followed by mixed cropping systems, including maize–cereals and potato–maize cropping; potato was found to be the least prevalent class. Plot analyses based on a sample of 1166 fields revealed largely homogeneous mapping patterns, demonstrating the effectiveness of our classification system also for intercropped classes, which are temporally and spatially highly heterogeneous. Moreover, we found that small field sizes were dominant in all crop types, regardless of whether or not intercropping was used. Maize–legume and maize exhibited the largest plots, with an area of up to 3 ha and slightly more than 10 ha, respectively; potato was mainly cultivated on fields smaller than 0.5 ha and only a few plots were larger than 1 ha. Besides providing the first spatially explicit map of cropping practices in the core production area of the Jos Plateau, Nigeria, the study also offers guidance for the creation of crop type maps for smallholder-dominated systems with intercropping. Critical temporal windows for crop type differentiation will enable the creation of mapping approaches in support of future smart agricultural practices for aspects such as food security, early warning systems, policies, and extension services.
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Air temperatures in the Arctic have increased substantially over the last decades, which has extensively altered the properties of the land surface. Capturing the state and dynamics of Land Surface ...Temperatures (LSTs) at high spatial detail is of high interest as LST is dependent on a variety of surficial properties and characterizes the land–atmosphere exchange of energy. Accordingly, this study analyses the influence of different physical surface properties on the long-term mean of the summer LST in the Arctic Mackenzie Delta Region (MDR) using Landsat 30 m-resolution imagery between 1985 and 2018 by taking advantage of the cloud computing capabilities of the Google Earth Engine. Multispectral indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Tasseled Cap greenness (TCG), brightness (TCB), and wetness (TCW) as well as topographic features derived from the TanDEM-X digital elevation model are used in correlation and multiple linear regression analyses to reveal their influence on the LST. Furthermore, surface alteration trends of the LST, NDVI, and NDWI are revealed using the Theil-Sen (T-S) regression method. The results indicate that the mean summer LST appears to be mostly influenced by the topographic exposition as well as the prevalent moisture regime where higher evapotranspiration rates increase the latent heat flux and cause a cooling of the surface, as the variance is best explained by the TCW and northness of the terrain. However, fairly diverse model outcomes for different regions of the MDR (R2 from 0.31 to 0.74 and RMSE from 0.51 °C to 1.73 °C) highlight the heterogeneity of the landscape in terms of influential factors and suggests accounting for a broad spectrum of different factors when modeling mean LSTs. The T-S analysis revealed large-scale wetting and greening trends with a mean decadal increase of the NDVI/NDWI of approximately +0.03 between 1985 and 2018, which was mostly accompanied by a cooling of the land surface given the inverse relationship between mean LSTs and vegetation and moisture conditions. Disturbance through wildfires intensifies the surface alterations locally and lead to significantly cooler LSTs in the long-term compared to the undisturbed surroundings.
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Aim
Large carnivores are currently recolonizing parts of their historical ranges in Europe after centuries of persecution and habitat loss. Understanding the mechanisms driving these recolonizations ...is important for proactive conservation planning. Using the brown bear (Ursus arctos) and the Iberian lynx (Lynx pardinus) as examples, we explore where and when large carnivores are likely to expand into human‐dominated landscapes and how varying levels of resistance due to human pressure might impact this recolonization process.
Location
Iberian Peninsula.
Methods
We used ensembles of species distribution models to relate species occurrence data to climate, topography and satellite‐based land‐cover predictors at a 10 km spatial resolution. Resulting predictions of suitable habitat areas were fed into a dispersal model to simulate range expansion over the 10 time‐steps for different human pressure scenarios. Finally, we overlaid predictions with protected areas to highlight areas that are likely key for future connectivity, but where human pressures might hamper dispersal.
Results
We found widespread suitable habitat for both species (bear: 30,000 km2, lynx: 170,000 km2), yet human pressure limits potential range expansions. For brown bears, core habitats between the Cantabrian and Pyrenean populations remained unconnected despite suitable habitat in between. For lynx, we predicted higher range expansion potential, although high human pressures in southern coastal Spain negatively affected expansion potential.
Main conclusions
Our results highlight that the recolonization potential of brown bears and lynx in the Iberian Peninsula is likely more constrained by lower permeability of landscapes due to human pressure than by habitat availability, a situation likely emblematic for large carnivores in many parts of the world. More generally, our approach provides a simple tool for conservation planners and managers to identify where range expansion is likely to occur and where proactively managing to allow large carnivores to safely disperse through human‐dominated landscapes can contribute to viable large carnivore populations.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Earth observation analysis workflows commonly require mass processing of time series data, with data volumes easily exceeding terabyte magnitude, even for relatively small areas of interest. Cloud ...processing platforms such as Google Earth Engine (GEE) leverage accessibility to satellite image archives and thus facilitate time series analysis workflows. Instant visualization of time series data and integration with local data sources is, however, currently not implemented or requires coding customized scripts or applications. Here, we present the GEE Timeseries Explorer plugin which grants instant access to GEE from within QGIS. It seamlessly integrates the QGIS user interface with a compact widget for visualizing time series from any predefined or customized GEE image collection. Users can visualize time series profiles for a given coordinate as an interactive plot or visualize images with customized band rendering within the QGIS map canvas. The plugin is available through the QGIS plugin repository and detailed documentation is available online (https://geetimeseriesexplorer.readthedocs.io/).
The contribution highlights the use of Landsat spectral-temporal metrics (STMs) for the detection of surface anomalies that are potentially related to buried near-surface paleogeomorphological ...deposits in the Nile Delta (Egypt), in particular for a buried river branch close to Buto. The processing was completed in the Google Earth Engine (GEE) for the entire Nile Delta and for selected seasons of the year (summer/winter) using Landsat data from 1985 to 2019. We derived the STMs of the tasseled cap transformation (TC), the Normalized Difference Wetness Index (NDWI), and the Normalized Difference Vegetation Index (NDVI). These features were compared to historical topographic maps of the Survey of Egypt, CORONA imagery, the digital elevation model of the TanDEM-X mission, and modern high-resolution satellite imagery. The results suggest that the extent of channels is best revealed when differencing the median NDWI between summer (July/August) and winter (January/February) seasons (ΔNDWI). The observed difference is likely due to lower soil/plant moisture during summer, which is potentially caused by coarser-grained deposits and the morphology of the former levee. Similar anomalies were found in the immediate surroundings of several Pleistocene sand hills (“geziras”) and settlement mounds (“tells”) of the eastern delta, which allowed some mapping of the potential near-surface continuation. Such anomalies were not observed for the surroundings of tells of the western Nile Delta. Additional linear and
meandering ΔNDWI anomalies were found in the eastern Nile Delta in the immediate surroundings of the ancient site of Bubastis (Tell Basta), as well as several kilometers north of Zagazig. These anomalies might indicate former courses of Nile river branches. However, the ΔNDWI does not provide an unambiguous delineation.
The contribution highlights the use of Landsat spectral-temporal metrics (STMs) for the detection of surface anomalies that are potentially related to buried near-surface paleogeomorphological ...deposits in the Nile Delta (Egypt), in particular for a buried river branch close to Buto. The processing was completed in the Google Earth Engine (GEE) for the entire Nile Delta and for selected seasons of the year (summer/winter) using Landsat data from 1985 to 2019. We derived the STMs of the tasseled cap transformation (TC), the Normalized Difference Wetness Index (NDWI), and the Normalized Difference Vegetation Index (NDVI). These features were compared to historical topographic maps of the Survey of Egypt, CORONA imagery, the digital elevation model of the TanDEM-X mission, and modern high-resolution satellite imagery. The results suggest that the extent of channels is best revealed when differencing the median NDWI between summer (July/August) and winter (January/February) seasons (1NDWI). The observed difference is likely due to lower soil/plant moisture during summer, which is potentially caused by coarser-grained deposits and the morphology of the former levee. Similar anomalies were found in the immediate surroundings of several Pleistocene sand hills (“geziras”) and settlement mounds (“tells”) of the eastern delta, which allowed some mapping of the potential near-surface continuation. Such anomalies were not observed for the surroundings of tells of the western Nile Delta. Additional linear and meandering 1NDWI anomalies were found in
the eastern Nile Delta in the immediate surroundings of the ancient site of Bubastis (Tell Basta), as well as several kilometers north of Zagazig. These anomalies might indicate former courses of Nile river branches. However, the 1NDWI does not provide an unambiguous delineation.
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