：The Qinghai−Tibet Plateau (QTP) is among the most sensitive regions to global environmental change worldwide. Although the climate change and engineering construction on the QTP have jointly modified the regional vegetation activity, little is known about how vegetation variation responds. Using Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data during 2000−2021, this study investigated the spatiotemporal variation of vegetation activity and the compound effects of climate change and construction along the G318 highway on the QTP (TG318) through the integration of trend, residual, and partial correlation analyses, as well as structural equation modeling. The results showed that the growing season EVI increased significantly at a rate of about 0.0020/year in the western QTP after reconstruction, but fluctuated in the east. Reconstruction generally had a significant effect on the growing season EVI, with contributions of 7.67%, 19.12%, 18.24%, and −4.15% in different sections of TG318, whereas climate change contributed −10.14% to 8.84% of the total variation. The growing season EVI negatively correlated with snow cover and minimum temperature in humid and sub-humid regions, whereas positively related to vapor pressure in semi-arid regions. Moreover, there existed an obvious lag effect of climate change on the growing season EVI, with lag time generally decreasing from west to east and apparent heterogeneity among different months and regions. These findings would help better understand the environmental impacts along the engineering corridors and provide a scientific basis for ecological conservation in the QTP region.

Well-facilitied capital farmland construction is an important measure to enhance the ability to ensure food security and accelerate new-style the modernization agriculture. Hyperspectral remote sensing can be provide data basis and technical support for realization the construction of well-facilitied capital farmland，to provide a reference for exploring the optimization of well-facilitied capital farmland construction area. Taking Xinzheng City of main grain producing areas in Henan province as the research object, using field sampling and indoor hyperspectral spectroscopy (350~2500 nm) combined, the spectral transformations such as Continuum removal（ CR） are carried out after the Savitzky-Golay（ SG） convolution smoothing, the best hyperspectral bands as the common index of the soil properties were selected by the correlation analysis and Fuzzy clustering maximum tree，focused on 405~431nm、781nm~831nm、1044~1087nm、1251~1410nm、1836~1898nm、2080nm~2201nm、2324~2395nm. The hyperspectral inversion model had been built by Panel date model of fixed effect variable coefficient based on the ordinary least squares estimation method ( OLS), that is about the panel data of PH、SOM、AN、AP、AK、Fe、Cr、Cd、Zn、Cu、Pb of 116 samples in Xinzheng City. The results showed that: The Panel date model significantly overall, the goodness of fit is higher (in the model, 2 =0.9991， F = 2195.67）. The result of precision test indicates that models performed well in modeling and predicting with a good ability of quantificational prediction, with RPD values were greater than 2.5.