基于高分遥感影像的亚高寒草甸土壤水分含量反演
Soil Moisture Content Inversion of Subalpine Meadow Based on High-Resolution Remote Sensing Image
投稿时间：2023-09-05  修订日期：2024-04-29
DOI：
中文关键词:  土壤水分含量  植被供水指数法  土壤水分空间变异  青藏高原东北缘
英文关键词:soil moisture content  vegetation supply water index  spatial variability of soil moisture  Qinghai-Tibet Plateau
基金项目:黄河上游高寒草甸植物多样性变化的多尺度研究,国家自然科学基金项目（面上项目，重点项目，重大项目）32060279
作者单位邮编
张起鹏* 甘肃民族师范学院历史文化系 747000
田富恒 甘肃民族师范学院历史文化系 747000
卓玛兰草 甘肃民族师范学院历史文化系 
赵頔琛 甘肃民族师范学院历史文化系 
摘要点击次数: 448
全文下载次数: 0
中文摘要:
      通过高分卫星遥感影像计算植被供水指数来反演亚高寒草甸土壤水分含量，结合高分辨率遥感影像(GF-2)和中分辨率的遥感影像(Landsat-7)进行土壤水分反演模型建模验证，揭示高分遥感影像结合植被供水指数法在青藏高原东北缘亚高寒草甸草原上的适用性，同时分析研究区土壤水分含量分布及其影响因素。本文基于高分二号（GF-2）、Landsat-7影像数据，以甘南藏族自治州当周草原为研究区，利用植被供水指数（VSWI, vegetation supply water index）构建土壤水分反演模型得到研究区土壤水分含量反演图，通过半方差函数及主成分分析法探索研究区土壤水分空间分布及影响因素。结果表明：研究区土壤水分含量分布状态呈现出一定程度的空间变异，体现在整个研究区内以及各个地块之间，土壤水分含量值主要介于0.11%~60.44%之间。土壤水分含量与坡度、海拔、坡向、NDVI、地表温度均呈正相关关系，分布主要受到NDVI、坡向、坡度、海拔的影响。综上，利用植被供水指数法结合高分遥感影像监测土壤水分含量是可行的，基于GF-2遥感影像所建立的模型拟合度最优，比Landsat-7遥感影像更具优势。
英文摘要:
      This study aims to estimate soil moisture content in the subalpine meadow of the northeastern margin of the Qinghai-Tibet Plateau using high-resolution satellite remote sensing images and the vegetation supply water index (VSWI). The suitability of combining high-resolution remote sensing images (GF-2) with the VSWI method is explored, and the distribution of soil moisture content and its influencing factors are analyzed. The study uses GF-2 and Landsat-7 satellite images to construct a soil moisture inversion model based on the VSWI. The model is applied to the grasslands of Gannan Tibetan Autonomous Prefecture to obtain a soil moisture inversion map. The spatial distribution of soil moisture and its influencing factors are analyzed using semivariogram and principal component analysis. The findings indicate a certain degree of spatial variability in soil moisture content within the study area, ranging from 0.11% to 60.44%. Soil moisture content shows a positive correlation with slope, elevation, aspect, NDVI, and surface temperature. Utilizing the vegetation water supply index method in combination with high-resolution remote sensing images for soil moisture estimation is feasible, with the model based on GF-2 remote sensing image demonstrating the best fitting degree and outperforming the Landsat-7 remote sensing image.
  查看/发表评论  下载PDF阅读器