[Ecological Environment Dynamical Evaluation of Hutuo River Basin Using Remote Sensing].

Hutuo River Basin straddles Shanxi and Hebei provinces, and Hutuo River was once cut off due to economic development and urban expansion after 2000; however, with the national emphasis on ecological civilization and the implementation of the South-North Water Diversion Project, the ecological protection of Hutuo River Basin has been significantly improved. MODIS data, Landsat data, and night light remote sensing data were selected based on the google earth engine (GEE) platform, and a new evaluation index system was generated by combining the biological richness index, vegetation cover index, land stress index, and pollution load index in the ecological environment index (EI) and the humidity index in the remote sensing ecological index (RSEI), using the variation coefficient method and entropy weighting method to assign weights to these indices. An ecological environment evaluation model was constructed to evaluate and classify the ecological environment quality of Hutuo River Basin from 2000 to 2020, and the driving factors were interpreted by using geographic probes. The results showed that:① on a time scale, the ecological environment of Hutuo River Basin was in a decline period from 2000 to 2015 and a recovery period from 2015 to 2020. From a grid scale, the ecological environment quality in the central part of the basin showed a state of improvement year by year, and in the western and eastern parts of the basin, the ecological environment quality in the decline period decreased year by year, whereas the ecological environment quality in the recovery period improved. ② Hot spot analysis showed that the spatial distribution of the ecological environment quality in Hutuo River Basin was high in the middle and low on both sides. Cold spot regions were mainly located in major cities and towns in the eastern and southern parts and scattered in the river valley area on the west side. ③ Geodetection analysis showed that the single factor detection drivers were mainly population density, vegetation net primary productivity (NPP), fractional vegetation cover (FVC), and geomorphological type. The dominant factor of cross-detection was "geomorphological type + FVC." With the deepening of ecological civilization construction and the implementation of Hutuo River Protection Regulations, in combination with different factors such as the natural environment and social characteristics in this basin, the research on ecological environment evaluation in Hutuo River Basin can provide data support for proposing localized policies to improve the ecological environment.

[Vegetation change of Yamzho Yumco Basin in southern Tibet based on SPOT-VGT NDVI].

The area we studied is Lake Yamzho Yumco Basin (28 degrees 27'-29 degrees 12'N, 90 degrees 08'-91 degrees 45'E), the largest inland lake basin in southern Tibetan Plateau, China. Using the SPOT-VGT NDVI vegetation index from 1998 to 2007 in the basin, the temporal and spatial variation characteristics of NDVI and its correlation with the major climatic factors (air temperature, precipitation) were analyzed. The results show that the average NDVI of the lake basin ranges from 0.12 to 0.31 and its seasonal change is obvious; the NDVI begins to rise rapidly in May and reaches the maximum value in early September. The average NDVI of the basin shows the slow increasing trend during 1998 to 2007, and it indicates that the eco-environment of the basin is recovering. The high value of NDVI has close relationships with water supply, altitude and vegetation types, so NDVI is relatively high near water sources and is the highest in meadow grassland. The summer air temperature and precipitation are the important climate elements that influence the vegetation in the basin, and the linear correlation coefficients between NDVI and air temperature and precipitation are 0.7 and 0.71, respectively. In recent years, warm and humid trend of the local climate is prevailing to improve the ecological environment in Yamzho Yumco Basin.

[Atmospheric correction of hyperion hyperspectral image based on FLAASH].

Atmospheric correction of remote sensing image is the premise of quantitative remote sensing. The present paper evaluated the capability of FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes)in ENVI software to make atmospheric correction for EO-1 Hyperion hyperspectral image. Hyperion hyperspecreal image of Zhangye city in Heihe River valley of Gansu province, China was acquired on September 10, 2007. Canopy spectra, biochemical component and GPS data of 41 plots were measured in near real-time during the satellite overpass. Hyperion hyperspectral image was geometrically corrected using Lansat-7 ETM+ image, then DN values were transformed to radiance and apparent reflectance, and atmospheric correction of Hyperion image was made using FLAASH. The resulting radiance, apparent reflectance and reflectance after FLAASH of four typical objects, including corn, water body, desert and building, were compared. ASD spectra of corn were resampled to Hyperion corresponding bands using Gaussian filter function. The comparison between ASD resampled spectra and Hyperion spectra after FLAASH demonstrated that the atmospheric correction using FLAASH is very effective and these two spectra are consistent with each other and the correlation coefficient reached 0.987.