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基于Google Earth Engine的青藏高原土地沙化模拟与动态评估
引用本文:李作成,张路,欧阳志云,胡金明.基于Google Earth Engine的青藏高原土地沙化模拟与动态评估[J].生态学报,2023,43(4):1526-1536.
作者姓名:李作成  张路  欧阳志云  胡金明
作者单位:云南大学国际河流与生态安全研究院, 昆明 650000;中国科学院生态环境研究中心, 北京 100000
基金项目:第二次青藏高原综合科学考察研究(2019QZKK0308);中国科学院先导专项(XDA20020402);国家自然科学基金项目(42171285)
摘    要:青藏高原广布的高寒草原和高寒草甸,在气候变暖以及超载放牧等人类活动的影响下面临着沙化的风险,并且高寒干旱的气候条件使得高原草地生态系统极为脆弱,发生沙化后修复难度极大,对高原土地沙化时空动态评估极为必要。但目前针对大范围进行长时间快速沙化模拟监测的方法存在不足,通过对比实验构建了基于植被状况-地表反射率-土壤湿度(NDVI-Albedo-Wet)三维数据空间的沙化遥感模拟监测模型,利用Google Earth Engine遥感大数据对模型进行了代码实现,最终分析了青藏高原土地沙化时空格局的动态变化。结果揭示了青藏高原土地沙化总体缓解但问题依然存在的现象,具体体现在:(1)沙化总面积逐年减少,平均每年减少的面积达到55.13万hm2,但沙化模拟数据显示有大量的未沙化土地向轻度沙化转移。(2)沙化程度总体上趋于逆转状态,但部分区域土地沙化问题不断出现,主要分布于“一江两河”、唐古拉山南麓、柴达木盆地周边以及昌都地区,在三江源和川西甘南地区也有零星分布。

关 键 词:青藏高原  土地沙化  模拟监测  时空格局  Google  Earth  Engine
收稿时间:2022/3/9 0:00:00
修稿时间:2022/7/12 0:00:00

Land desertification simulation and dynamic assessment of Qinghai-Tibet Plateau based on Google Earth engine
LI Zuocheng,ZHANG Lu,OUYANG Zhiyun,HU Jinming.Land desertification simulation and dynamic assessment of Qinghai-Tibet Plateau based on Google Earth engine[J].Acta Ecologica Sinica,2023,43(4):1526-1536.
Authors:LI Zuocheng  ZHANG Lu  OUYANG Zhiyun  HU Jinming
Institution:Institute of International Rivers and Ecological Safety, Yunnan University, Kunming 650000, China;Eco-Environmental Research Center, Chinese Academy of Sciences, Beijing 100000, China
Abstract:The widespread alpine grasslands and alpine meadows on the Qinghai-Tibet Plateau face the risk of desertification under the influence of climate warming and human activities such as overloaded grazing. Moreover, the alpine and arid climate conditions make the plateau grassland ecosystem extremely fragile and difficult to repair after desertification. It is very necessary to evaluate the spatio-temporal dynamics of land desertification on the Plateau. However, the current method of large-scale rapid desertification simulation monitoring for a long time is insufficient. In this paper, a spatial desertification remote sensing monitoring model based on the vegetation condition-surface reflectance-soil moisture (NDVI-Albedo-Wet) three-dimensional data is constructed through comparative experiments, and the Google Earth Engine remote sensing big data platform is used to implement the model through code. Finally, the dynamic assessment of the long-term spatial pattern of land desertification on the Qinghai-Tibet Plateau is realized. The results reveal the overall mitigation trend of land desertification on the Qinghai-Tibet Plateau, but problems still exist. Specifically, it reflected that:(1) the total area of desertification is decreasing year by year, with an average annual reduction of 551300 hectares, but the desertification simulation data of each phase show that a large number of non-desertification land is transferred to mild desertification. (2) The degree of desertification tends to reverse on the whole, but the problem of land desertification in some regions continues to appear, mainly distributed in "one river and two rivers", the southern foot of Tanggula Mountain, the surrounding area of Tsaidam Basin and Qamdo area. It is also sporadically distributed in Sanjiangyuan, western Sichuan and southern Gansu.
Keywords:Qinghai-Tibet Plateau  land desertification  simulation monitoring  spatio-temporal pattern  Google Earth Engine
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