Predicting suitable breeding areas for different locust species – A multi-scale approach accounting for environmental conditions and current land cover situation
Klein I. van der Woude S. Schwarzenbacher F. Muratova N. Slagter B. Malakhov D. Oppelt N. Kuenzer C.
March 2022Elsevier B.V.
International Journal of Applied Earth Observation and Geoinformation
2022#107
In this study, we present a fused multi-scale approach to model habitat suitability index (HSI) maps for three different locust species. The presented methodology was applied for the Italian locust (Calliptamus italicus, CIT) in Pavlodar oblast, Northern Kazakhstan, for the Moroccan locust (Dociostaurus maroccanus, DMA) in Turkistan oblast, South Kazakhstan and for the desert locust (Schistocerca gregaria) in Awash river basin, Ethiopia, Djibouti, Somalia. The main novelty is based on implementing results from ecological niche modelling (ENM) with time-series analyses of high spatial resolution remote sensing data (Sentinel-2) and further auxiliary datasets in a fused HSI model. Within the ENM important climatic variables (e.g. temperature, rainfall) and edaphic variables (e.g. sand and moisture contents) are included at a coarse spatial resolution. The analyses of Sentinel-2 time-series data enables mapping locust breeding habitats based on recent remotely sensed land observation at high spatial resolution and mirror the actual vegetation state, land use, land cover and in this way identify areas with favorable conditions for egg survival and breeding. The fused HSI results for year 2019 were validated based on ground field observation and reach area under curve (AUC) performance of 0.747% for CIT, 0.850% for DMA and 0.801% for desert locust. The innovation of this study is a multi-scale approach which accounts not only for climatic and environmental conditions but also for current vegetation and land management situation. This kind of up-to-date spatial detailed information on breeding suitability could enable area prioritization for risk assessment, monitoring and early intervention of locust pests.
Ecological niche model , Habitat suitability index , Incubation of egg-pods , Locust breeding habitat , Locust monitoring , Remote sensing , Sentinel-2
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German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Wessling, 82234, Germany
Wageningen University & Research (WUR), Netherlands
Research Institute of Ecological Problems, Al-Farabi Kazakh National University, Almaty, 050010, Kazakhstan
Joint Stock Company “National Center for Space Research and Technology”, Almaty, 050010, Kazakhstan
Department of Geography, Kiel University, Kiel, 24118, Germany
Institute of Geography and Geology, University of Wuerzburg, Wuerzburg, 97074, Germany
German Remote Sensing Data Center (DFD)
Wageningen University & Research (WUR)
Research Institute of Ecological Problems
Joint Stock Company “National Center for Space Research and Technology”
Department of Geography
Institute of Geography and Geology
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