Explaining and assessing the spatial and temporal patterns of low productivity arable land and land abandonment - using satellite observation and socioeconomic data of the irrigated lowlands of Central Asia

Abstract

Since the 1950s farmland in Central Asia has been widely expanded to increase the production of cotton. Nevertheless, the productivity of irrigated farmland is partly declining, already in the Soviet time. This development particularly affects the sub-region of the Amu Darya and Syr Dary rivers. Despite dedicated approaches to understand these processes, such as the creation of an indicator system to assess the agricultural production, many uncertainties still remains. One of the unknown variables is, which site-specific trends causing changes in the agricultural production and ultimately lead to the abandonment of farmland. A problem here is the lack of spatial data, especially since the collapse of the Soviet Union and after the formation of the new national states. The present PhD thesis deals with the detection of spatial and temporal patterns of land abandonment using remote sensing (RS) and geographic information systems (GIS). Socio-economic data in addition shall also help to explain the abandonment of farmland. The study areas are located in Uzbekistan in the Khorezm Oblast and in Karakalpakstan. The research objectives are for one thing the classification of abandoned fields with high-resolution remote sensing data (Landsat). The spatial patterns and timing of land abandonment in Central Asia is largely unknown until today and has not been quantified yet. For this purpose preselected fields are examined with a transect-square procedure to determine the current status of succession and vegetation cover fraction on abandoned arable land.