ABSTRACT:North China Plain is one of the most important agricultural regions in China with severe challenges of water shortage. Agriculture in the plain is very intensive. Farming in the region is a typical irrigation-supported system of winter wheat, followed by summer maize. Other important crops in the region include cotton, potatoes, soybean and various vegetables. Cultivation of these crops requires large amount of irrigation water to support harvest. However, water resource is very limited due to high evaporation and unbalanced precipitation. Though annual precipitation of the region is about 600-800mm, water shortage has been a common social-economic problem in the region, resulted from rapid increase of economic development and intensive farming. Both surface and underground water resources in the region have been over-extracted to meet the rapid increase of various demands on water, leading to omens of water scarcity disasters in the region. The ground water level has felled down at a rate of about 1m per year in recent decades. Consequently, several big fluvial crateriforms have been observed in the region, corresponding to over-pumping ground water for years. Since agriculture consists of the largest component of water uses, mapping irrigation area for estimation of agricultural water demand is urgently required to improve the administration of water resource for effective utilization in the region. In this paper, we present our systematic investigation of mapping the irrigation area in the plain using MODIS remote sensing data. Since water demand for irrigation is generally related with the cropping systems during the season when rainfall is few, we have to examine the cropping structure of the region so that the important cropping systems requiring irrigation can be identified. Spectral behaviors of the cropping systems in MODIS data have to be investigated for construction of algorithm to identification of the systems in the MODIS images. Winter wheat has been identified as the main cropping systems requiring intensive irrigation during the growing season from March to early June. The normalized difference of vegetation index (NDVI) has been widely used to identify green vegetation in remote sensing images. Since winter wheat and forest is the main green vegetation during the March and April when other crops has not been planted, change trend of NDVI of farmland and forest can be used to identify winter wheat and forest, which can then be used as the input for irrigation mapping. Then Vegetation Supply Water Index (VSWI) has been used in this paper for identifying irrigated area in winter wheat field. VSWI is the ratio of NDVI and temperature. It combines the information of temperature and growing condition of vegetation together, which can indicate humidity of soil more exactly.According to our study in North China plain, irrigation area can be properly mapped for estimation of agricultural water demand using the MODIS data. Total irrigation area of the region is about 5.9 million hectares in 2006...

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