Remote Sensing of Surface Water and Soil Moisture

2013 ◽  
pp. 119-142 ◽  
Author(s):  
Alain Pietroniro ◽  
Jessika Töyrö ◽  
Robert Leconte ◽  
Geoff Kite
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Water

Airborne remote sensing for groundwater studies in Prairie environment

1969 ◽  
Vol 6 (4) ◽  
pp. 737-741 ◽  
Author(s):  
M. E. Chase
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Water ◽  
Ground Truth ◽  
Infrared Photography ◽  
Black And White ◽  
Remote Sensors ◽  
Infrared Scanning ◽  
Southern Alberta ◽  
Lake Deposits

A deficiency of groundwater in an area of prairieland in southern Alberta prompted a survey by airborne remote sensors. Panchromatic and black and white true infrared photography coverages were obtained and studied, but were found to be of limited value. An infrared scanning survey, using the 2.5–5.6 μ band was flown at the same time and found to be more informative. Conditions of ground truth were not ideal, making the results less conclusive than desired. Till covers most of the area, with lake deposits in the eastern section. Soil moisture changes were registered on the imagery, but the depths of overburden to which these changes were recorded on the surface are unknown, due to the condition variations between the time of the survey and the drilling. Vegetation, surface water, soil moisture, and saline sloughs were found to have the strongest thermal signatures. Problems encountered in the survey are discussed and recommendations to eliminate them are given.

scholarly journals Detection of Groundwater in Iraq-Wasit Governorate Using Remote Sensing and GIS

2021 ◽  
Vol 2114 (1) ◽  
pp. 012091
Author(s):  
Ali Sadeq Bahet ◽  
Mutasim Ibrahim Malik
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Water ◽  
Vegetation Cover ◽  
Ground Cover ◽  
Underground Water ◽  
Remote Sensing And Gis ◽  
Moisture Index ◽  
Water Index ◽  
Soil Moisture Index

Abstract The groundwater in Iraq has been studied for the need for it due to the shortage of surface water levels.The vegetation cover index, the soil moisture index, and the surface water index were used to detect the presence of groundwater in Wasit Governorate, Iraq. Those indicators that appear on the ground cover and indicate the presence of groundwater in the study area were compared with the coordinates of wells underground water. The results were identical with information obtained from the Ministry of Water Resources.

scholarly journals Integration of Microwave and Optical/Infrared Derived Datasets from Multi-Satellite Products for Drought Monitoring

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1504
Author(s):  
Zhengdong Wang ◽  
Peng Guo ◽  
Hong Wan ◽  
Fuyou Tian ◽  
Linjiang Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Water ◽  
Land Surface ◽  
North China ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Sensing Data ◽  
Dryness Index

Drought is among the most common natural disasters in North China. In order to monitor the drought of the typically arid areas in North China, this study proposes an innovative multi-source remote sensing drought index called the improved Temperature–Vegetation–Soil Moisture Dryness Index (iTVMDI), which is based on passive microwave remote sensing data from the FengYun (FY)3B-Microwave Radiation Imager (MWRI) and optical and infrared data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and takes the Shandong Province of China as the research area. The iTVMDI integrated the advantages of microwave and optical remote sensing data to improve the original Temperature–Vegetation–Soil Moisture Dryness Index (TVMDI) model, and was constructed based on the Modified Soil-Adjusted Vegetation Index (MSAVI), land surface temperature (LST), and downscaled soil moisture (SM) as the three-dimensional axes. The global land data assimilation system (GLDAS) SM, meteorological data and surface water were used to evaluate and verify the monitoring results. The results showed that iTVMDI had a higher negative correlation with GLDAS SM (R = −0.73) than TVMDI (R = −0.55). Additionally, the iTVMDI was well correlated with both precipitation and surface water, with mean correlation coefficients (R) of 0.65 and 0.81, respectively. Overall, the accuracy of drought estimation can be significantly improved by using multi-source satellite data to measure the required surface variables, and the iTVMDI is an effective method for monitoring the spatial and temporal variations of drought.

Soil moisture retrieval from remote sensing measurements: Current knowledge and directions for the future

2021 ◽  
pp. 103673
Author(s):  
Zhao-Liang Li ◽  
Pei Leng ◽  
Cheng-Hu Zhou ◽  
Kun-Shan Chen ◽  
Fang-Cheng Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Current Knowledge ◽  
The Future

scholarly journals Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images

2020 ◽  
Vol 12 (16) ◽  
pp. 2587
Author(s):  
Yan Nie ◽  
Ying Tan ◽  
Yuqin Deng ◽  
Jing Yu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Arid Regions ◽  
Drought Index ◽  
Dynamic Monitoring ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Rapid Acquisition ◽  
Semi Arid ◽  
Soil Moisture Inversion

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.

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