Mapping grain crop land productivity that associated soil quality and crop field management are needed over intensively
cropped regions such as the North China Plain to support science and policy application focused on understanding the
current and potential capacity of regional food support. In this study, the crop growth dynamic presenting by time series
field Greenness derived from MODIS 250 m data and soil moisture condition assessing by Normalized Difference Water
Index (NDWI) derived by MODIS 250 m and 500 m data were combined to detect the temporal and spatial variability
of productivity of winter wheat-summer maize field in the period 2000 to 2008 in Hebei and Shandong Province in
North China Plain. Annual average NDVI levels, average levels of nine years and coefficients of variation of levels in
the main growing season indicated corresponding crop growth condition and clearly presented spatial distribution of crop
growth. Both the levels of NDWI and the coefficients of variation of the levels have almost same pattern of spatial
distribution and correlations between two indexes levels were very high. The results of analysis of levels and coefficients
of variation of levels of NDVI and NDWI shows the combination analysis of two indexes can be used to assess the levels
of land productivity with a high spatial or temporal resolution .
The evapotranspiration (ET) is one of the most important components of the water cycle in semi-arid Taihang Mountain region of North China. Due to significant changes in topography, the ET of this semi-arid region tends to vary dramatically both in time and space, which renders the accurate estimation of yearly or seasonal ET a difficult task. In current study, based on rGIS-ET v1.0, a regional ET model, by adding module of adjusting surface temperature in terrain, solar radiance terrain correction, and shaded relief, we improved the rGIS-ET a remote sensing model on ArcGIS platform for mapping ET distribution in such a semi-arid mountain area. With DEM of 30 meter and climate data, we run the model to estimate daily ET in mountain area using Landsat data. The ET distribution pattern estimated from Landsat data by rGIS-ET v2.0, was integrated into SWAT method to calculated daily ET at a high spatial resolution in the sub-watersheds. With input of the daily ET, SWAT simulated the annual flow of the component of water balance at sub-watersheds from 1995 to 2003. The variations of flows of annual ET were significant amount the sub-watersheds and the variations of ET flow may cause the variation of other components flow.
In this work, we integrate a popular remote sensing technique with ArcGIS to build a tool bar, named rGIS-ET, for
estimating regional evapotranspiration (ET) from Landsat data and MODIS data with improved resolution. The
development of rGIS-ET enables quick processing of large amount of remote sensing and other spatial data. It also
provides user-friendly interfaces for modelling, output display and result analyses. Both surface temperatures and albedo
were key parameters for calculating ET using Surface Energy Balance Algorithm. We adopted algorithms for estimating
surface temperatures and albedo of winter wheat and summer maize field from MODIS data at 250 m spatial resolution
to improve the resolutions of ET map of MODIS. We apply improved rGIS-ET to eight plain counties of Shijiazhuang
city, a typical agricultural region in North China Plain, to demonstrate its utility for calculating regional ET and
evaluating agriculture water resource usage. The improved ET map of MODIS could represent the spatial variation of
crop ET much better than that without improved.
Moderate Resolution Imaging Spectroradiometer (MODIS) data are widely used to compute regional evapotranspiration (ET) at 1000-m spatial resolution. However, due to the fact that the village densities in most counties in North China Plain are higher than 0.5 per km2, the crop ET mapping at 1000-m resolution computed using MODIS data often fails to differentiate the crop field from the residential area, thus resulted in inaccurate ET estimation. In this study, we analyzed relationship between crop ET and MODIS-normalized difference vegetation index (NDVI) and deduced ET equations to calculating winter wheat and summer corn ET from NDVI. The equations were tested using measured data and proved that they are reliable. The equations were applied using MODIS 250 m spatial resolution NDVI and mapped crop ET at 250 m resolution. Compared with ET map from high resolution Landsat, the improved resolution ET map can described the spatial variations of regional crop ET in a similar pattern.
The evapotranspiration (ET) is one of the most important components of the water cycle in semi-arid Taihang Mountain region of North China. The spatial distribution and seasonal variation of ET will directly impact the stream flow volume and the amount of lateral recharges to the aquifers of mountain front plain. Due to significant changes in topography, the ET of this semi-arid region tends to vary dramatically both in time and space, which renders the accurate estimation of yearly or seasonal ET a difficult task. In current study, based on rGIS-ET v1.0, a regional ET model, by adding module of adjusting surface temperature in terrain, solar radiance terrain correction, and shaded relief, we improved the rGIS-ET a remote sensing model on ArcGIS platform for mapping ET distribution in such a semi-arid mountain area. With DEM of 30 meter and climate data, we run the model to estimate daily ET in mountain area using Landsat data and MODIS data, respectively. The results of model application shows that model could correct the errors of ET value caused by elevation and terrain significantly while Landsat data was used. While MODIS data was used, the model could not do terrain correction accurately for MODIS has a low spatial resolution, but MODIS data with a high temporal resolution could be used to estimate the temporal variation of ET in a mountain area.
Sustainable management of water resources requires reliable information on regional evapotranspiration (ET) distribution, which is the largest output component of the hydrological cycle in North China Plain (NCP). In this work, we integrate a popular remote sensing technique with ArcGIS to build a ArcMap tool bar, named rGIS-ET, for estimating regional ET from Landsat TM/ETM+ data. The development of rGIS-ET enables quick processing of large amount of remote sensing and other spatial data. It also provides user-friendly interfaces for modeling, output display and result analyses. We use daily ET measurements from a weighting lysimeter in our experimental station to verify the performance of rGIS-ET. The verification confirms the reliability of ET calculation, whose errors during crop growing season are less than 10 %. We apply rGIS-ET to Luancheng County, a typical agricultural region in NCP, to demonstrate its utility for calculating regional ET and estimating agriculture water needs and ground water usage, both of which are critical to the design of an effective water resources management program for achieving sustainable development.
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