干旱区生态环境知识资源中心(Arid): Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images

Arid

DOI	10.1007/s12517-020-05837-2
	Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images
	Bidgoli, Reza Dehghani; Koohbanani, Hamidreza; Keshavarzi, Ali; Kumar, Vinod
通讯作者	Bidgoli, RD
来源期刊	ARABIAN JOURNAL OF GEOSCIENCES
ISSN	1866-7511
EISSN	1866-7538
出版年	2020
卷号	13 期号:17
英文摘要	Monitoring of soil surface moisture is an imperative factor in water and energy cycle. Due to the variability of soil characteristics such as topography, vegetation, and climate dynamics, this important factor varies with respect to time and place. Measuring methods can provide soil moisture information in a wide range of short intervals with reasonable accuracy. In present research, Landsat 8 satellite data with various soil moisture content estimation methods were tested. In order to evaluate the accuracy of each method, the real-field data used 80 samples of volumetric soil moisture content in suburban areas of Semnan city that were collected at the time of satellite passage of the area. Some of the indicators used in this study are normalized vegetation index, NDTI index, NDMI index, PSMI index (use full form of these indices), surface temperature, and SMSWIR index. The SMSWIR index with correlation coefficient was 0.78, and the correlation coefficient of regression model was 0.61, and RMSE was 3.69. The results of the regression model and real data were estimated to be 3.69, which are recommended for assessing surface soil moisture in arid and desert regions. Three indicators of SMSWIR index, NDTI index, and NDMI index with a small difference are not suitable indices for measuring soil moisture content in desert areas with vegetation cover. By employing multivariable regression models, soil moisture model was also prepared by using the studied indices. The findings of this research indicate that the simultaneous correlation model is superior to the surface soil moisture mapping.
英文关键词	Remote sensing SMSWIR LST Landsat Multivariate regression models
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000570873200003
WOS关键词	PERPENDICULAR DROUGHT INDEX ; DIGITAL COUNT DATA ; TEMPERATURE ; SPACE ; RETRIEVALS
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326373
作者单位	[Bidgoli, Reza Dehghani] Univ Kashan, Dept Rangeland & Watershed Management, Kashan, Iran; [Koohbanani, Hamidreza] Univ Semnan, Fac Desert Studies, Semnan, Iran; [Keshavarzi, Ali] Univ Tehran, Dept Soil Sci, Lab Remote Sensing & GIS, POB 4111, Karaj 3158777871, Iran; [Kumar, Vinod] DAV Univ, Dept Bot, Jalandhar 144012, Punjab, India
推荐引用方式 GB/T 7714	Bidgoli, Reza Dehghani,Koohbanani, Hamidreza,Keshavarzi, Ali,et al. Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images[J],2020,13(17).
APA	Bidgoli, Reza Dehghani,Koohbanani, Hamidreza,Keshavarzi, Ali,&Kumar, Vinod.(2020).Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images.ARABIAN JOURNAL OF GEOSCIENCES,13(17).
MLA	Bidgoli, Reza Dehghani,et al."Measurement and zonation of soil surface moisture in arid and semi-arid regions using Landsat 8 images".ARABIAN JOURNAL OF GEOSCIENCES 13.17(2020).