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Articles | Volume XXXIX-B8
https://doi.org/10.5194/isprsarchives-XXXIX-B8-375-2012
https://doi.org/10.5194/isprsarchives-XXXIX-B8-375-2012
30 Jul 2012
 | 30 Jul 2012

IMPLEMENTATION OF AN AGRICULTURAL ENVIRONMENTAL INFORMATION SYSTEM (AEIS) FOR THE SANJIANG PLAIN, NE-CHINA

Q. Zhao, S. Brocks, V. Lenz-Wiedemann, Y. Miao, R. Jiang, X. Chen, F. Zhang, and G. Bareth

Keywords: GIS, Spatial, Decision Support, Modelling, Agriculture, Environment, Farming

Abstract. The Sino-German Project between the China Agricultural University and the University of Cologne, Germany, focuses on regional agro-ecosystem modelling. One major focus of the cooperation activity is the establishment of joint rice field experiment research in Jiansanjiang, located in the Sanjiang Plain (Heilongjiang Province, north-eastern part of China), to investigate the different agricultural practices and their impact on yield and environment. An additional task is to set-up an Agricultural Environmental Information System (AEIS) for the Sanjiang Plain (SJP), which covers more than 100 000 km2. Research groups from Geography (e.g. GIS & Remote Sensing) and Plant Nutrition (e.g. Precision Agriculture) are involved in the project. The major aim of the AEIS for the SJP is to provide information about (i) agriculture in the region, (ii) the impact of agricultural practices on the environment, and (iii) simulation scenarios for sustainable strategies. Consequently, the AEIS for the SJP provides information for decision support and therefore could be regarded as a Spatial Decision Support System (SDSS), too. The investigation of agricultural and environmental issues has a spatial context, which requires the management, handling, and analysis of spatial data. The use of GIS enables the capture, storage, analysis and presentation of spatial data. Therefore, GIS is the major tool for the set-up of the AEIS for the SJP. This contribution presents the results of linking agricultural statistics with GIS to provide information about agriculture in the SJP and discusses the benefits of this method as well as the integration of methods to produce new data.