分类： 地球科学 >> 地理学 提交时间： 2022-12-12 合作期刊: 《干旱区科学》
摘要：Vegetation growth status is an important indicator of ecological security. The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment. Assessing the vegetation net primary productivity (NPP) of the Tarim River Basin can provide insights into the vegetation growth variations in the region. Therefore, based on the Google Earth Engine (GEE) cloud platform, we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin (except for the eastern Gobi and Kumutag deserts) from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors (air temperature and precipitation) using the Sen slope estimation method, coefficient of variation, and rescaled range analysis method. In terms of temporal characteristics, vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020, with the smallest value of 118.99 g C/(m2•a) in 2001 and the largest value of 155.07 g C/(m2•a) in 2017. Regarding the spatial characteristics, vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area. The annual average value of vegetation NPP was 133.35 g C/(m2•a), and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a) was 82,638.75 km2, accounting for 57.76% of the basin. The future trend of vegetation NPP was dominated by anti-continuity characteristic; the percentage of the area with anti-continuity characteristic was 63.57%. The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74% of the regions that passed the significance test, while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68% of the regions that passed the significance test. Hence, the effect of precipitation on vegetation NPP was greater than that of air temperature. The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.
分类： 环境科学技术及资源科学技术 >> 环境科学技术及资源科学技术其他学科 提交时间： 2022-03-24 合作期刊: 《干旱区科学》
摘要： Abstract: The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region, China has undergone in recent years may face some challenges in its ecological environment. Therefore, an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development. First, we constructed an improved remote sensing-based ecological index (RSEI) in 1990, 1995, 2000, 2005, 2010, 2015 and 2020 on the Google Earth Engine (GEE) platform and implemented change detection for their spatial distribution. Second, we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change (LUCC) data to analyze the reasons of RSEI changes. Finally, we investigated the applicability of improved RSEI to arid area. The results showed that mean of RSEI rose from 0.41 to 0.50, showing a slight upward trend. During the 30-a period, 2.66% of the regions improved significantly, 10.74% improved moderately and 32.21% improved slightly, respectively. The global Moran's I were 0.891, 0.889, 0.847 and 0.777 for 1990, 2000, 2010 and 2020, respectively, and the local indicators of spatial autocorrelation (LISA) distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis, and the low-low cluster was mainly distributed in the outer edge of the oasis. RSEI at the periphery of the oasis changes from low to high with time, with the fragmentation of RSEI distribution within the oasis increasing. Its distribution and changes are predominantly driven by anthropologic factors, including the expansion of artificial oasis into the desert, the replacement of desert ecosystems by farmland ecosystems, and the increase in the distribution of impervious surfaces. The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability. The high efficiency exhibited with this approach makes it convenient for rapid, high frequency and macroscopic monitoring of eco-environmental quality in study area.
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