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基于卫星遥感数据的 LCM 模型的土地利用/覆被变化驱动因素及未来预测——以中国甘肃省为例。

Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China.

机构信息

College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China.

School of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.

出版信息

Sensors (Basel). 2020 May 12;20(10):2757. doi: 10.3390/s20102757.

Abstract

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

摘要

土地利用和覆盖变化(LUCC)是影响全球环境、气候变化和可持续发展的重要问题。检测和预测 LUCC 这一动态过程及其驱动因素,有助于制定适合当地情况的有效土地利用和规划政策,从而支持当地社会经济发展和全球环境保护。本研究以甘肃省为例,探讨了 1980 年至 2018 年的 LUCC 格局及其驱动机制,并利用综合 LCM(逻辑细胞自动机-马尔可夫链)模型和卫星遥感数据预测了 2030 年的土地利用和覆盖情况。结果表明,与第一阶段(1980 年至 2005 年)相比,第二阶段(2005 年至 2018 年)的 LUCC 格局更为合理。这是因为第二阶段通过生态工程保护了大面积的绿地。1980 年至 2018 年,自然因素是影响甘肃土地利用和覆盖变化的主要力量,而社会经济因素的影响并不显著,因为经济发展缓慢。景观指数分析表明,在生态保护情景下,2030 年的土地利用和覆盖预测将比历史趋势情景更为有利。此外,本研究结果表明,LCM 模型可以很好地检测干旱半干旱地区的 LUCC。本研究有望为未来的土地利用规划和管理提供理论指导,并为干旱半干旱地区的 LUCC 分析提供新的方法学参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bce/7285483/9debd690b648/sensors-20-02757-g001.jpg

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