干旱区生态环境知识资源中心(Arid): Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images

Arid

DOI	10.3390/rs12162587
	Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images
	Nie, Yan; Tan, Ying; Deng, Yuqin; Yu, Jing
通讯作者	Yu, J
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2020
卷号	12 期号:16
英文摘要	As a basic agricultural parameter in the formation, transformation, and consumption of surface water resources, soil moisture has a very important influence on the vegetation growth, agricultural production, and healthy operation of regional ecosystems. The Aksu river basin is a typical semi-arid agricultural area which seasonally suffers from water shortage. Due to the lack of knowledge on soil moisture change, the water management and decision-making processes have been a difficult issue for local government. Therefore, soil moisture monitoring by remote sensing became a reasonable way to schedule crop irrigation and evaluate the irrigation efficiency. Compared to in situ measurements, the use of remote sensing for the monitoring of soil water content is convenient and can be repetitively applied over a large area. To verify the applicability of the typical drought index to the rapid acquisition of soil moisture in arid and semi-arid regions, this study simulated, compared, and validated the effectiveness of soil moisture inversion. GF-1 WFV images, Landsat 8 OLI images, and the measured soil moisture data were used to determine the Perpendicular Drought Index (PDI), the Modified Perpendicular Drought Index (MPDI), and the Vegetation Adjusted Perpendicular Drought Index (VAPDI). First, the determination coefficients of the correlation analyses on the PDI, MPDI, VAPDI, and measured soil moisture in the 0-10, 10-20, and 20-30 cm depth layers based on the GF-1 WFV and Landsat 8 OLI images were good. Notably, in the 0-10 cm depth layers, the average determination coefficient was 0.68; all models met the accuracy requirements of soil moisture inversion. Both indicated that the drought indices based on the Near Infrared (NIR)-Red spectral space derived from the optical remote sensing images are more sensitive to soil moisture near the surface layer; however, the accuracy of retrieving the soil moisture in deep layers was slightly lower in the study area. Second, in areas of vegetation coverage, MPDI and VAPDI had a higher inversion accuracy than PDI. To a certain extent, they overcame the influence of mixed pixels on the soil moisture spectral information. VAPDI modified by Perpendicular Vegetation Index (PVI) was not susceptible to vegetation saturation and, thus, had a higher inversion accuracy, which makes it performs better than MPDI's in vegetated areas. Third, the spatial heterogeneity of the soil moisture retrieved by the GF-1 WFV and Landsat 8 OLI image were similar. However, the GF-1 WFV images were more sensitive to changes in the soil moisture, which reflected the actual soil moisture level covered by different vegetation. These results provide a practical reference for the dynamic monitoring of surface soil moisture, obtaining agricultural information and agricultural condition parameters in arid and semi-arid regions.
英文关键词	soil moisture typical drought index inversion model optical image
类型	Article
语种	英语
开放获取类型	DOAJ Gold
收录类别	SCI-E
WOS记录号	WOS:000565441800001
WOS关键词	WATER-CONSUMPTION ; RIVER-BASIN ; VEGETATION ; SURFACE ; TEMPERATURE ; SPACE ; ZONE ; GF-1
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325991
作者单位	[Nie, Yan; Tan, Ying; Deng, Yuqin] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430062, Peoples R China; [Yu, Jing] Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China
推荐引用方式 GB/T 7714	Nie, Yan,Tan, Ying,Deng, Yuqin,et al. Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images[J],2020,12(16).
APA	Nie, Yan,Tan, Ying,Deng, Yuqin,&Yu, Jing.(2020).Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images.REMOTE SENSING,12(16).
MLA	Nie, Yan,et al."Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images".REMOTE SENSING 12.16(2020).