Monitoring the response of vegetation dynamics to ecological engineering in the Mu Us Sandy Land of China from 1982 to 2014.

The Mu Us Sandy Land (MUSL) has undergone climate changes and shifts in human activities driven by a series of ecological restoration projects in recent decades. We analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging and Spectroradiometer (MODIS) datasets during the past 33 years. The results show that (1) the vegetation in 53.46% of the MUSL exhibited an upward trend, and 34.45% of the area displayed a large increase, mainly in the eastern part of the MUSL region, including most of Shenmu County, Yuyang District, Hengshan County, and Jingbian County. (2) By the end of 2014, the rapid increase in vegetation encompassed 16.85% of the total area of the study region due to the construction of ecological engineering projects. (3) Based on the residual regression method, the area of positive effects accounted for 55.07% of the total area, and the vegetation in the study area was positively affected by human activities. Our study suggests that these multiple ecological restoration programs contributed to the accelerated greening trend in the MUSL region and highlights the importance of human intervention in regional vegetation growth under climate change conditions.

Monitoring coal mine changes and their impact on landscape patterns in an alpine region: a case study of the Muli coal mine in the Qinghai-Tibet Plateau.

The Muli coal mine is the largest open-cast coal mine in the Qinghai-Tibet Plateau, and it consists of two independent mining sites named Juhugeng and Jiangcang. It has received much attention due to the ecological problems caused by rapid expansion in recent years. The objective of this paper was to monitor the mining area and its surrounding land cover over the period 1976-2016 utilizing Landsat images, and the network structure of land cover changes was determined to visualize the relationships and pattern of the mining-induced land cover changes. In addition, the responses of the surrounding landscape pattern were analysed by constructing gradient transects. The results show that the mining area was increasing in size, especially after 2000 (increased by 71.68 km2), and this caused shrinkage of the surrounding lands, including alpine meadow wetland (53.44 km2), alpine meadow (6.28 km2) and water (6.24 km2). The network structure of the mining area revealed the changes in lands surrounding the mining area. The impact of mining development on landscape patterns was mainly distributed within a range of 1-6 km. Alpine meadow wetland was most affected in Juhugeng, while alpine meadow was most affected in Jiangcang. The results of this study provide a reference for the ecological assessment and restoration of the Muli coal mine land.

[Analysis and modeling of hyperspectral singularity in rice under Cd pollution].

In order to detect the Cd stress levels of rice growing in natural environment fast and accurately, based on wavelet transform technology in the visible light and near-infrared region (NIR), a method of identifying stress levels of rice under Cd pollution was explored. The hyperspectral data, biochemical parameters and heavy metals concentration in folium were collected for the rice growing in natural farmlands. Wavelet transform of hyperspectral reflectance (350-1 300 nm) was performed by using Daubechies 5 mother function and wavelet energy coefficients of spectral reflectance were extracted. In addition, the model between wavelet energy coefficient and Cd content was established. The result showed that the wavelet coefficients of the fifth decomposition level (d5) proved successful for detecting Cd pollution of rice; the singularity range of rice located in the region around 550-810 nm of spectral signal under Cd pollution; and the singularity amplitude was 0.04; The centre of modulus maxima located at 700 nm. Regression model based on third level wavelet energy coefficient can estimate the Cd content of rice accurately with the coefficient of determination (R2) of 0.958, and root mean square error (RMSE) of 0.122. It can be concluded that the singularity analysis technology applying wavelet transform to reflectance has been shown to be very promising in detecting rice under Cd pollution effectively, and wavelet energy coefficients can estimate Cd content of rice, and provide important reference for detecting other metal-induced stress on crop.