摘要
土地盐碱化导致大面积土地资源的丧失,威胁生态的可持续发展,严重破坏了我们赖以生存的环境,因此用遥感手段监测土壤盐碱化有很大的现实意义。地面受不同的植被所覆盖,特别是在大尺度下植被类型纷繁复杂,利用遥感数据通过传统的NDVI-T s特征空间来反演大尺度下土壤湿度时往往会增大反演误差。本文使用landsat8数据,考虑到不同植被对NDVI-T s特征空间的影响,分别建立了农田和草地覆盖下的特征空间,并结合地面实际测量的土壤湿度数据,分析干旱植被指数(TVDI)与实际土壤含水量的相关性,并以此来反映传统NDVI-T s特征空间引起的在大尺度反演土壤湿度的误差。结果发现:整体区域为0.16,农田为0.22,草地为0.35;并分别通过了0.01、0.1、0.05水平的显著性检验。从以上的结论我们可以得到:在利用TVDI反演大尺度土壤湿度时,不能将所有的植被类型一起作为NDVI-T s特征空间来计算TVDI,不同的植被类型需要分开以提高土壤湿度反演的精度。
The soil salinization results in the loss of a large area of land resources ,and is a direct threat to the ecological sustainable de-velopment ,and also damages to the natural environment for human survival seriously .So it has a very important practical significance to use remote sensing technology in soil salinization monitoring .Ground is covered by different vegetation ,so the retrieval of soil moisture of traditional NDVI-Ts space increases the error especially in large-scale.In this paper ,taking corn farmland and grassland of saline as cases,firstly make use of landsat8 data for the retrieval of the land surface temperature T s(Land surface temperature) by split window algorithm combined with the ground test station meteorological data .And then establish the NDVI ( Normalized Difference Vegetation In-dex)-Ts feature space under two types of land use .Use the NDVI-Ts space to calculate the TVDI ( Temperature Vegetation Dryness In-dex) .Combined with the actual measured surface soil moisture data to calculate the correlation coefficients between actual soil moisture and TVDI:the whole area is 0.16,farmland is 0.22,grassland is 0.35;and the correlation coefficients got through the 0.01,0.1,0.05 significance level respectively .Lastly analyze the soil moisture retrieval error by different NDVI-Ts feature space.From the above conclu-sion:Separating different types of land use increase the soil moisture retrieval accuracy .
出处
《土壤与作物》
2013年第4期157-163,共7页
Soils and Crops
基金
国家自然科学基金(40576077)
国家自然科学基金(41271351)
