摘要
研究增强型植被指数基于Landsat-8数据反演土壤水分的可行性及适用性,分析研究区土壤水分总体分布,提高该地区应对干旱灾害的能力。基于温度植被干旱指数方法,以淮河流域上游地区作为研究区,基于2017年2月的Landsat-8影像,分别计算了地表温度、归一化植被指数、增强型植被指数,基于TVDI构建了两种土壤水分反演模型。研究比较了:1) EVI在TM数据中的应用特点;2)研究区土壤含水率的空间分布特征;3)两种模型反演结果的差异。结果表明:1)基于TM数据计算的EVI总体明显低于NDVI,但不同时间段的结果并不总是低于NDVI;2)基于EVI的模型结果精度低于基于NDVI模型结果。3)两种模型结果与植被覆盖度、地表温度的关系均为负相关,其中,基于EVI的模型结果与地表温度的负相关程度极高,即基于EVI的模型结果受植被影响较小,受温度影响程度高。
To study the feasibility and applicability of enhanced vegetation index based on Landsat 8 data to retrieve soil moisture,and to analyze the distribution characteristics of soil moisture in this area,so as to improve the ability to deal with drought disasters in this area.Based on the temperature vegetation dryness index method and Landsat 8 image in February 2017,two TVDI soil moisture inversion models were constructed. The following are studied:(1) the application characteristics of EVIin TM data;(2) the spatial distribution characteristics of soil moisture in the study area;(3) the difference between the inversion results of the two models. The results show that:(1) The EVI based on TM data was significantly lower than that based on NDVI,but the results of different time periods were not always lower than that of NDVI.(2) the accuracy of the model based on EVIis lower than that based on NDVI.(3) the results of the two models were negatively correlated with vegetation coverage and surface temperature,and the results of the EVI-based model were highly negatively correlated with surface temperature,that is,the EVI-based model was less affected by vegetation and more affected by temperature.
作者
杨茹
高超
查芊郁
阮甜
YANG Ru;GAO Chao;ZHA Qianyu;RUAN Tian(School of Geography and Tourism,Anhui Normal University,Wuhu 241000,China;Department of Geography and Spatial Information Technology,Ningbo University,Ningbo 315000,China)
出处
《测绘与空间地理信息》
2020年第2期33-37,共5页
Geomatics & Spatial Information Technology
基金
国家自然科学基金“不同空间尺度农业旱涝灾害气象因子致灾阈值的确定——以淮河上游地区为例”(41571018)
国家自然科学基金“复杂下垫面条件下冬小麦干旱机制辨析及干旱灾害风险研判——以淮河上游地区为例”(41871024)资助。
