From remote sensing to web mapping - integrated geoinformation for land use monitoring in Central Asia

Abstract

Irrigation agriculture is of a major socio-economic importance for the Central Asian countries Afghanistan, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan. Remote agricultural areas, the lack of harmonized agricultural statistics, the intensification of agriculture combined with water scarcity as well as unsustainable water use management make the integrated and combined use of Remote Sensing and Web GIS a very valuable technique for crop monitoring and to support the mitigation of those problems. Thus, within the frame of the Central Asian Water project (CAWa), a web-based mapping platform, the Water Use Efficiency Monitor in Central Asia (WUEMoCA), is being currently developed. It is comprised of a coherent and automated interdisciplinary processing chain starting from the automated download of Terra MODIS data and the computation of NDVI time series. A subsequent land use classification and crop yield estimation via machine learning algorithms for image processing provides a retrospective crop inventory for all years between 2000 and 2016 so far. Parallely, the near-real time early estimation of the current agricultural vegetation condition provides information about phenological anomalies and drought-affected regions. The systematic storage of these large amounts of processed multitemporal MODIS data requires the deployment of a spatial database with supportive raster analysis functionalities such as PostgreSQL/PostGIS in which all results are spatially aggregated on administrative levels such as water use associations, state districts and state provinces. Morover, the connectivity between a GeoServer and PostGIS is natively integrated, allowing for the automatic creation of Web Map Services (WMS) directly from the database. Interactive maps are visualized in a client application based on the mapping framework OpenLayers which is tailored for the specific needs of Central Asian water management. This makes a web-based presentation of all results possible. At last, the use of a PostGIS database also provides the possibility to establish a land use indicator system for all administrative levels with secondary information such as land use coefficient, crop diversity, land use intensity and irrigated crop acreage. The CAWa project is a part of the Berlin Process and funded by the German Federal Foreign Office.