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遥感技术与应用  2022, Vol. 37 Issue (6): 1460-1471    DOI: 10.11873/j.issn.1004-0323.2022.6.1460
土壤水分专栏     
基于LST-VI特征空间的喀斯特地区土壤水分时空变化研究
晏红波1,2(),李浩1,卢献健1,2(),王佳华1
1.桂林理工大学 测绘地理信息学院,广西 桂林 541004
2.广西空间信息与测绘重点实验室,广西 桂林 541004
Spatial-temporal Variation of Soil Moisture in Karst Area based on LST-VI Feature Space
Hongbo Yan1,2(),Hao Li1,Xianjian Lu1,2(),Jiahua Wang1
1.College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541004,China
2.Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541004,China
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摘要:

地表土壤水分是陆地系统地气能量交换的关键参数,而喀斯特地区地表土壤水分是推动岩溶作用,影响土壤流失,造成喀斯特石漠化的重要因子,准确确定喀斯特地区地表土壤水分的分布及其动态变化对喀斯特地区生态地质环境安全及区域气候变化意义重大。以广西典型喀斯特地貌区为研究对象,利用MODIS地表温度数据和植被指数数据,构建LST-VI特征空间,首先比较不同植被指数(NDVI、EVI、SAVI、FVC)在喀斯特地区的适用性,得出FVC为研究区LST-VI特征空间的最优植被指数因子,而后在归一化的T*-FVC特征空间内分析得出森林、农田和喀斯特山区3种典型的下垫面类型下土壤水分指标M0随时间的运动轨迹和规律,以及其空间分布变化及原因。结果表明:相同的下垫面类型下土壤水分指标M0在T*-FVC特征空间中随时间的运动轨迹和规律相似,说明下垫面类型是影响土壤水分变化的重要因素。空间分布上,广西M0值域分布具有夏季小于冬季,西南部小于东北部,喀斯特地区小于非喀斯特地区的特征,农田M0季节变化较明显。总体上,利用归一化的T*-FVC特征空间实现了喀斯特地区土壤水分的时空动态变化监测。

关键词: 喀斯特土壤水分地表温度植被指数LST-VI特征空间    
Abstract:

Surface soil moisture is a key parameter of terrestrial systems in terms of ground-air energy exchange, and the surface soil moisture in karst areas is an important factor to promote karst action, affect the soil erosion, and cause karst rocky desertification. Therefore, it is of great significance to accurately determine the distribution of surface soil moisture and its dynamic change in karst areas to the safety of ecological and geological environment and regional climate change. Taking the typical karst area of Guangxi as the study area the LST-VI feature space was constructed using MODIS surface temperature data and vegetation index data. Firstly, the applicability of the four different vegetation indices (NDVI, EVI, SAVI, and FVC) in karst areas was compared, and FVC is selected as the optimal vegetation index for the LST-VI feature space in the study area. The soil moisture index M0 based on the uniform normalized T*-FVC feature space is derived. The track and regularity of M0 with time under different underlying surface types such as forest, farmland and karst areas are studied in detail,as well as the spatial distribution changes of M0 and the causes. The results show that the track and regularity of M0 with time is similar under the same underlying surface type in the T*-FVC feature space, indicating that the underlying surface type is an important factor affecting the change of soil moisture. In terms of spatial distribution, the distribution of M0 in Guangxi has the characteristics of being smaller in summer than in winter, smaller in southwest than in northeast, smaller in karst than in non-karst areas, and the seasonal variation of M0 in farmland is evident. Overall, the spatio-temporal dynamic change of soil moisture in karst areas has been achieved using the normalized T * -FVC feature space.

Key words: Karst    Soil moisture    Land surface temperature    Vegetation index    LST-VI feature space
收稿日期: 2022-04-19 出版日期: 2023-02-15
ZTFLH:  TP79  
基金资助: 广西自然科学基金项目“基于高分影像的喀斯特地区土壤水分反演关键问题研究”(2022GXNSFBA035639);广西空间信息与测绘重点实验室开放基金“广西地区农业干旱遥感监测及预警方法研究”(桂科能19-050-11-23),国家自然科学基金项目“地基和星载GNSS-R融合的花岗岩滑坡高时空分辨率土壤湿度反演研究”(42064003)
通讯作者: 卢献健     E-mail: 56403075@qq.com;2008056@glut.edu.cn
作者简介: 晏红波(1983-),女,河北唐山人,博士,副教授,主要从事遥感影像智能处理与应用研究。E?mail:56403075@qq.com
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引用本文:

晏红波,李浩,卢献健,王佳华. 基于LST-VI特征空间的喀斯特地区土壤水分时空变化研究[J]. 遥感技术与应用, 2022, 37(6): 1460-1471.

Hongbo Yan,Hao Li,Xianjian Lu,Jiahua Wang. Spatial-temporal Variation of Soil Moisture in Karst Area based on LST-VI Feature Space. Remote Sensing Technology and Application, 2022, 37(6): 1460-1471.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.6.1460        http://www.rsta.ac.cn/CN/Y2022/V37/I6/1460

图1  广西喀斯特地貌集中区审图号:GS(2019)3333号
图2  广西气象站点分布图审图号:GS(2019)3333号
图3  LST-VI三角形特征空间示意图
图4  LST-VI梯形特征空间示意图
图5  T*-VI特征空间示意图
图6  土壤水分变化分析试验像元点分布审图号:GS(2019)3333号
图7  数据处理流程
图8  地表温度与4种植被指数的特征空间
图9  剔除异常值后的地表温度与4种植被指数的特征空间
数据类型指数干湿边拟合方程R2
原始特征空间NDVI干边y=-11.106 5*x+28.677 80.94
湿边y=-4.578 2*x+18.113 50.40
EVI干边y=2.265 2*x+23.360 30.17
湿边y=3.258 9*x+14.314 90.39
FVC干边y=-6.923 5*x+24.931 70.91
湿边y=-2.992 7*x+16.870 60.46
SAVI干边y=-22.731 4*x+28.932 20.92
湿边y=-4.946 0*x+15.761 30.22
剔除温度异常值的特征空间NDVI干边y=-10.879 6*x+28.036 50.97
湿边y=-5.671 6*x+19.309 40.73
EVI干边y=1.824 5*x+22.834 60.21
湿边y=3.134 7*x+15.149 20.58
FVC干边y=-7.568 5*x+24.587 00.96
湿边y=-3.126 7*x+17.636 70.69
SAVI干边y=-19.954 9*x+27.508 40.89
湿边y=-1.72 9*x+15.708 10.04
表1  4种植被指数与地表温度的特征空间干湿边拟合方程
图10  森林、农田、喀斯特山区M0随时间变化轨迹图
图11  广西地区不同时期的M0空间分布图
图12  广西2009年—2010年各期M0值域百分比统计图
站点编号站名经度/°纬度/°
59001隆林105.3524.78
59037都安108.123.93
59044沙塘109.324.4
59211百色106.623.9
59227天等107.1523.08
59228平果107.5823.31
59249贵港109.6123.11
59266苍梧111.2523.41
59426扶绥107.922.55
59431南宁108.2222.63
59453玉林110.1622.65
59632钦州108.6221.95
59023河池108.0524.7
表2  气象站站点信息
图13  土壤水分指标M0与实测值的关系图
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