We propose to investigate the growth of cities and the dryland system land use transitions in Central Asia as a result of China’s Belt and Road initiative, a large planned series of Chinese investments in the region. Our research questions are as follows:
1. How have past investment and infrastructure developments (1995-2014) led to varying patterns of urbanization, resource, and population flows, and changing land use across Central Asian cities? How will the ongoing development of the BRI, and/or proximity to BRI connected cities impact the emerging urban ecosystems, microbial and human ecologies in these areas going forward (2014-2020)?
2. What are the economic and social effects of BRI investments on urban and peri-urban areas in Central Asia? How far improved is connectivity between cities, and what impact is this likely to have on patterns of land use, zoonotic disease risks, agriculture, and economic development?
3. What new infectious disease risks exist and how will they impact economic growth? To what extent is BRI-connectivity creating uneven patterns of rural-urban development and how might this impact urbanization, growth, and population health in the future?

Our main goal is to monitor abandoned agriculture, fallow fields, and grasslands with combined satellite images from Landsat and Sentinel-2. Our objectives are: 1) Analyze Landsat and Sentinel-2 data from single years to classify active agriculture, hayfields, and both non-woody and woody herbaceous cover; 2) analyze Landsat data from multiple years to classify a) non-woody herbaceous cover into non-woody abandoned agriculture, fallow fields, and grasslands, b) woody herbaceous cover into woody abandoned agriculture and permanent grasslands, and c) active agriculture in permanent agriculture and areas that were re-cultivated; 3) conduct a rigorous accuracy assessment and uncertainty analyses, and evaluate the robustness of the developed algorithms and their potential for operational use in the future, and 4) explore the effects of a) temperature data from TIRS, b) texture information, and c) fire detection on the mapping accuracy of abandoned agriculture.