分类： 地球科学 >> 地理学 提交时间： 2023-02-07 合作期刊: 《干旱区科学》
摘要： With the acceleration of urbanization, changes in the urban ecological environment and landscape pattern have led to a series of prominent ecological environmental problems. In order to better coordinate the balanced relationship between city and ecological environment, we selected land use change data to evaluate the habitat quality in Hohhot City of China, which is of great practical significance for regional urban and economic development. Thus, the integrated valuation of ecosystem services and tradeoffs (InVEST) and Cellular Automata-Markov (CA-Markov) models were used to analyze, predict, and explore the Spatiotemporal evolution path and characteristics of urban land use, and forecast the typical evolution pattern of land use in 2030. The results showed that the land use types in Hohhot City changed significantly from 2000 to 2020, and the biggest change took place in cultivated land, grassland, shrub, and artificial surface. The decrease of cultivated land area and the increase of artificial surface area were the main impact trend of land use change. The average value of habitat quality had been decreasing continuously from 2000 to 2020, and the values of habitat degradation were 0.2605, 0.2494, and 0.2934 in 2000, 2010, and 2020, respectively, showing a decreasing trend. The decrease of habitat quality was caused by the needs of economic development and urban construction, as well as the impact of land occupation. During this evolution, many cultivated land and urban grassland had been converted into construction land. The simulated land use changes in 2030 are basically the same as those during 20002020, and the habitat quality will still be declining. The regional changes are influenced by the urban rapid development and industrial layout. These results can provide decision-making reference for regional urban planning and management as well as habitat quality evaluation.
分类： 地球科学 >> 地理学 提交时间： 2025-01-14 合作期刊: 《干旱区科学》
摘要： Studying the spatiotemporal variation and driving mechanisms of vegetation net primary productivity (NPP) in the Guanzhong Plain Urban Agglomeration (GPUA) of China is highly important for regional green and low-carbon development. This study used the Theil-Sen trend analysis, Mann-Kendall trend test, coefficient of variation, Hurst index, and machine learning method (eXtreme Gradient Boosting and SHapley Additive exPlanations (XGBoost-SHAP)) to analyze the spatiotemporal variation of NPP in the GPUA from 2001 to 2020 and reveal its response to climate change and human activities. The results found that during 2001–2020, the averageNPP in the GPUA showed a significant upward trend, with an annual growth rate of 10.84 g C/(m2•a). The multi-year average NPP in the GPUA was 484.83 g C/(m2•a), with higher values in the southwestern Qinling Mountains and lower values in the central and northeastern cropland and built-up areas. The average coefficient of variation of NPP in the GPUA was 0.14, indicating a relatively stable state overall, but 72.72% of the study area showed weak anti-persistence, suggesting that NPP in most areas may have declined in the short term. According to XGBoost-SHAP analyses, elevation, land use type and precipitation were identified as the main driving factors of NPP. Appropriate precipitation and higher temperatures promote NPP growth, whereas extreme climates, high population density, and nighttime lighting inhibit NPP. This study has important theoretical and practical significance for achieving regional sustainable development, offers a scientific basis for formulating effective ecological protection and restoration strategies, and promotes green, coordinated, and sustainable development in the GPUA.
分类： 地球科学 >> 地理学 提交时间： 2021-11-11 合作期刊: 《干旱区科学》
摘要： Land use/cover change (LUCC) is becoming more and more frequent and extensive as a result of human activities, and is expected to have a major impact on human welfare by altering ecosystem service value (ESV). In this study, we utilized remote sensing images and statistical data to explore the spatial-temporal changes of land use/cover types and ESV in the northern slope economic belt of the Tianshan Mountains in Xinjiang Uygur Autonomous Region, China from 1975 to 2018. During the study period, LUCC in the study region varied significantly. Except grassland and unused land, all the other land use/cover types (cultivated land, forestland, waterbody, and construction land) increased in areas. From 1975 to 2018, the spatial-temporal variations in ESV were also pronounced. The total ESV decreased by 4.00×108 CNY, which was primarily due to the reductions in the areas of grassland and unused land. Waterbody had a much higher ESV than the other land use/cover types. Ultimately, understanding the impact of LUCC on ESV and the interactions among ESV of different land use/cover types will help improve existing land use policies and provide scientific basis for developing new conservation strategies for ecologically fragile areas.
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