Armed conflicts are globally widespread and can strongly influence societies and the environment. One open question is how armed conflicts affect land use, particularly agriculture. The Syrian civil war is an on-going armed conflict with tragic humanitarian and environmental consequences, including the displacement of more than five million refugees. However, it remains unknown how the Syrian civil war has affected crop cultivation, despite the importance of crop production for the economy and for food security. This is unfortunate because such information is much needed to assess the consequences of the conflicts for food security in the region and to target humanitarian aid. Remote sensing provides a great tool for monitoring cropland change, especially in war-torn areas where ground measurements are hazardous. Yet, the heterogeneity of cropland in the Mediterranean poses substantial challenges: The region is characterized by diverse crop composition, stretching from cereals (e.g., wheat, barley) to tree crops (e.g., nuts, olive). Mapping such diversity using remote sensing imagery is difficult because of the overlap of spectral signatures. Further, to understand the effects of armed conflicts, knowledge about the type and timing of cropland changes such as abandonment and expansion is much needed. However, consistent maps of cropland changes, and robust approaches for detecting the timing of such changes, are lacking.We propose to develop much-needed algorithms to map the extent of the cropland cultivation and the timing of its changes in the area influenced by the Syrian civil war, including Syria, southern Turkey, and northern Jordan. Specifically, we will leverage the potential of optical and radar time series to capture the heterogeneity and dynamics of cropland in our study area. We will use the resulting maps to assess the determinants and causes for the observed changes using statistical analysis and social science. Specifically, we aim to: 1. Evaluate spectral-temporal statistics and textural features from Landsat, Sentinel-1, and Sentinel-2 to map cropland (i.e., cereals, tree crops, and other crops) and non-cropland for 2020. 2. Develop a signature generalization approach to generate consistent 30-m annual cropland time series, and detect the timing of cropland abandonment and expansion between 2005 and 2020 using a temporal segmentation approach. 3. Test the hypotheses that the Syrian civil war caused cropland abandonment in conflicted areas (H1), and that the war caused cropland expansion in the areas (e.g., Jordan, Turkey) where the refugees are settled (H2). This research will advance cropland mapping and change detection using multi-sensor imagery in heterogeneous environments such as the Mediterranean region. The outcome of this research will shed light on cropland changes and provide a better understanding of the role of the Syrian civil war in these changes. Such understanding is crucial to target humanitarian support, and to inform future investments in agriculture. The proposed research is aligned with the goals and themes of the NASA Earth Science program by using NASA’s satellite assets to develop new algorithms and products, and to help institutions make better decisions that reduce food insecurity and contribute to understanding environmental change.
LCLUC is a NASA program.
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