Soil moisture measurement techniques for remote sensing ground truth: evaluation and performance test of soil moisture sensors

1997 ◽  
Author(s):  
Teferi D. Tsegaye ◽  
Charles A. Laymon ◽  
William L. Crosson ◽  
Tommy L. Coleman ◽  
Narayan B. Rajbhandari
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Performance Test ◽  
Measurement Techniques ◽  
Ground Truth ◽  
Moisture Measurement ◽  
Soil Moisture Sensors ◽  
And Performance ◽  
Soil Moisture Measurement

scholarly journals Assessment of spectral indexes for estimating soil water content in the Brazilian Pantanal

2021 ◽  
Vol 43 ◽  
pp. e48
Author(s):  
Victor Hugo de Morais Danelichen ◽  
Osvaldo Alves Pereira ◽  
Marcelo Sacardi Biudes ◽  
José De Souza Nogueira
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial And Temporal Variability ◽  
Mato Grosso ◽  
Moisture Measurement ◽  
Brazilian Pantanal ◽  
Soil Moisture Measurement

The Pantanal is the largest floodplain of the globe occupying 138,183 km2 in Brazil. The fundamental ecological factor of interaction between the Pantanal ecosystems is the flooding regime. Connected to properties of the soil-plant-atmosphere system, knowledge on the soil water content becomes increasingly necessary. The high temporal and spatial variability of water content in the soil caused by the vast heterogeneity of soil texture, vegetation, topography and climate makes it a difficult physical variable to be measured. However, its spatial and temporal variability can be determined by recent modern techniques of remote sensing based on data obtained by microwave or infrared sensors. Thus, the aim of this study was to evaluate the accuracy of vegetation and soil water indexes through satellite images from Landsat 5 in the northern Brazilian Pantanal. The study was conducted in a pasture, experimental site in the Northern Pantanal in Mato Grosso state. Soil moisture was measured using a TDR probe installed at 10 cm depth in the period from 2009 to 2011. For comparison, spectral indexes and the surface temperature provided by Geological Survey (USGS) were used, these indexes are derived from bands ratios of satellite reflectance products Landsat 5 TM. The data evaluation was performed using some indicators: accuracy - Willmott index, Root Mean Square Error and the Mean Absolute Error. This study demonstrated that the application of remote sensing in the management of water resources is very promising. The indexes correlated with soil moisture measurement. Among the soil water indexes the NBR-2 showed related to soil moisture measurement. For both types of soils EVI had the highest determination coefficient, lowest errors and highest Willmott’s index of agreement.

Soil Moisture Measurement by the Dielectric Method

2019 ◽  
Vol 52 (7) ◽  
pp. 822-833 ◽  
Author(s):  
P. P. Bobrov ◽  
T. A. Belyaeva ◽  
E. S. Kroshka ◽  
O. V. Rodionova
Keyword(s):  
Soil Moisture ◽  
Dielectric Method ◽  
Moisture Measurement ◽  
Soil Moisture Measurement
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