The meteorological factors for building the plastic-sunlight greenhouse were derived by analyzing the microclimate of
the greenhouse, and the meteorological conditions required by the vegetables and the production reducing caused by the
low temperature and spare sunlight were studied. The percentage of days without any sunshine hours from October to
March of next year was selected as the sunlight factor, the average temperature in the coldest month as the temperature
factor, and the altitude of the site was taken into account also. The area suitable for building plastic-sunlight greenhouse
was regionlized by the comprehensive methods and supported by GIS (Geographic Information system) technology. The
results showed that the central and east part of Hebei province is suitable and south part is moderately suitable, and not
suitable in the north of Hebei Province for plastic-sunlightgreenhouse.
Droughts hazard that occurrs frequently in nature and has a great impact on agriculture. Timely monitoring and
assessment of drought conditions are critical to mitigate its effects. By using NOAA/AVHRR satellite data, in current
study, we derived the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI) and land
surface temperature (LST), and analyzed the spatial characteristics of vegetation indexes and land surface temperature.
The temperature vegetation dryness index (TVDI) was used to monitor the winter wheat drought conditions from March
to May of 2005 in the middle-south part of Hebei Province, China. The results showed that SAVI was better than NDVI
for representing the winter wheat growth condition in spring. The correlation of soil moisture with TVDI based on SAVI
was greater than that of based on NDVI. The analysis of TVDI and soil moisture data from weather stations'
measurement demonstrated that a better correlation existed between TVDI and relative humidity of soil at 10cm and
20cm. TVDI therefore can be used as a good indicator for operational drought monitoring.
Temperature vegetation dryness index (TVDI) is a simple and effective methods for drought monitoring. In this study, the statistic characteristics of MODIS-EVI and MODI-NDVI at two different times were analyzed and compared. NDVI reaches saturation in well-vegetated areas while EVI has no such a shortcoming. In current study, we used MODIS-EVI as vegetation index for TVDI. The analysis of vegetation index and land surface temperature at different latitudes and different times showed that there was a zonal distribution of land surface parameters. It is therefore necessary to calculate the TVDI with a zonal distribution. Compared with TVDI calculated for the whole region, the zonal calculation of TVDI increases the accuracy of regression equations of wet and dry edge, improves the correlations of TVDI and measured soil moisture, and the effectiveness of the large scale drought monitoring using remote sensing data.
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.