scholarly journals Retrieving Surface Soil Water Content Using a Soil Texture Adjusted Vegetation Index and Unmanned Aerial System Images

2021 ◽  
Vol 13 (1) ◽  
pp. 145
Author(s):  
Haibin Gu ◽  
Zhe Lin ◽  
Wenxuan Guo ◽  
Sanjit Deb
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Texture ◽  
Vegetation Index ◽  
Surface Soil ◽  
Field Scale ◽  
Thermal Images ◽  
Model Based ◽  
Dryness Index

Surface soil water content (SWC) is a major determinant of crop production, and accurately retrieving SWC plays a crucial role in effective water management. Unmanned aerial systems (UAS) can acquire images with high temporal and spatial resolutions for SWC monitoring at the field scale. The objective of this study was to develop an algorithm to retrieve SWC by integrating soil texture into a vegetation index derived from UAS multispectral and thermal images. The normalized difference vegetation index (NDVI) and surface temperature (Ts) derived from the UAS multispectral and thermal images were employed to construct the temperature vegetation dryness index (TVDI) using the trapezoid model. Soil texture was incorporated into the trapezoid model based on the relationship between soil texture and the lower and upper limits of SWC to form the texture temperature vegetation dryness index (TTVDI). For validation, 128 surface soil samples, 84 in 2019 and 44 in 2020, were collected to determine soil texture and gravimetric SWC. Based on the linear regression models, the TTVDI had better performance in estimating SWC compared to the TVDI, with an increase in R2 (coefficient of determination) by 14.5% and 14.9%, and a decrease in RMSE (root mean square error) by 46.1% and 10.8%, for the 2019 and 2020 samples, respectively. The application of the TTVDI model based on high-resolution multispectral and thermal UAS images has the potential to accurately and timely retrieve SWC at the field scale.

Quantifying field-scale surface soil water content from proximal GPR signal inversion in the time domain

2010 ◽  
Vol 8 (6) ◽  
pp. 483-491 ◽  
Author(s):  
Khan Zaib Jadoon ◽  
Sébastien Lambot ◽  
Benedikt Scharnagl ◽  
Jan van der Kruk ◽  
Evert Slob ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Time Domain ◽  
Surface Soil ◽  
Field Scale ◽  
The Time Domain ◽  
Scale Surface ◽  
Signal Inversion

scholarly journals The Applicability of the Cosmic Ray Neutron Sensor to Simultaneously Monitor Soil Water Content and Biomass in an Acacia mearnsii Forest

Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 48 ◽  
Author(s):  
Thigesh Vather ◽  
Colin S. Everson ◽  
Trenton E. Franz
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Epithermal Neutron ◽  
Cosmic Ray ◽  
Field Scale ◽  
Area Index ◽  
Neutron Intensity

Soil water content is an important hydrological parameter, which is difficult to measure at a field scale due to its spatial and temporal heterogeneity. The Cosmic Ray Neutron Sensor (CRNS) is a novel and innovative approach to estimate area-averaged soil water content at an intermediate scale, which has been implemented across the globe. The CRNS is moderated by all hydrogen sources within its measurement footprint. In order to isolate the soil water content signal from the neutron intensity, the other sources of hydrogen need to be accounted for. The CRNS’s applications are not only limited to soil water content estimation, as it can potentially be used to monitor biomass. The Two-Streams clear-felling provided the unique opportunity to monitor the cosmic ray neutron intensities before, during, and after the clear-felling. The cadmium-difference method was used to obtain the pure thermal and epithermal neutron intensities from the bare and moderated detectors. The study concluded that the presence of biomass within the site reduced the epithermal neutron intensity by 12.43% and the N0 value by 13.8%. The use of the neutron ratio to monitor biomass was evaluated and changes in the neutron ratio coincided with biomass changes and resulted in a high correlation (R2 of 0.868) with the normalized difference vegetation index (NDVI) and (R2 of 0.817) leaf area index (LAI). The use of the CRNS to simultaneously monitor soil water content and biomass will be beneficial in providing more reliable soil water content estimates, provide biomass estimates at a field scale, and aid in understanding the dynamics between soil water content and vegetation.

Using soil surface gray level to determine surface soil water content

2010 ◽  
Vol 53 (10) ◽  
pp. 1527-1532 ◽  
Author(s):  
YuanJun Zhu ◽  
YunQiang Wang ◽  
MingAn Shao
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Surface Soil ◽  
Soil Surface ◽  
Gray Level

Evaluating Surface-Soil Water Content by Measuring Reflectance

1975 ◽  
Vol 39 (2) ◽  
pp. 238-242 ◽  
Author(s):  
E. L. Skidmore ◽  
J. D. Dickerson ◽  
H. Schimmelpfennig
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Surface Soil

scholarly journals INFLUÊNCIA DA TEXTURA E PROFUNDIDADE DO SOLO NA CALIBRAÇÃO DA SONDA DE NÊUTRONS

Irriga ◽  
1998 ◽  
Vol 3 (1) ◽  
pp. 6-12
Author(s):  
Reginaldo Ferreira Santos ◽  
Reimar Carlesso
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Texture ◽  
Correlation Coefficients ◽  
Regression Equations ◽  
Transparent Plastic ◽  
Neutron Probe ◽  
Calibration Curves ◽  
Santa Maria

INFLUÊNCIA DA TEXTURA E PROFUNDIDADE DO SOLO NA CALIBRAÇÃO DA SONDA DE NÊUTRONS   Reginaldo Ferreira SantosDepartamento de Engenharia Rural - UNESP, CP: 237 - CEP:18603 970, Botucatu, SP Reimar CarlessoDepartamento de. Engenharia da Universidade Federal de Santa Maria, - UFSM, Campus Universitário, CEP: 97119 900, Santa Maria - RS  1 RESUMO A sonda de nêutrons é um equipamento usado na determinação do conteúdo de água do solo baseado no espalhamento e atenuação de nêutrons rápidos. Para tanto, há necessidade de calibração no campo e, conseqüentemente, verificar a influência da textura e da profundidade do solo e determinar as curvas de calibração em relação ao conteúdo de umidade. O trabalho foi desenvolvido na Universidade Federal de Santa Maria em um conjunto de lisímetros, protegidos das precipitações pluviométricas com plástico transparente. Foram usados três solos de diferentes texturas e quatro repetições e em três profundidades (10, 30 e 50 cm) a partir da superfície do solo. Foram determinadas as equações de regressão lineares entre as contagens propiciadas pela sonda e o conteúdo de umidade do solo respectivos pelo método gravimétrico. Os resultados demonstraram que houve interferência da textura e da profundidade do solo, analisados conjuntamente, nas curvas de calibração, sendo que os valores observados e os estimados variaram entre 0,02 e 0,06 cm3/ cm3 do conteúdo de água do solo e os coeficientes de correlação foram 0,86, 0,95 e 0,89 para os solos de textura argilosa, franco-argilo-siltoso e franco-arenoso, respectivamente. Já para os fatores textura e profundidade dos solos, analisados separadamente, as diferenças entre os valores observados no campo e os estimados, variaram entre 0,0 e 0,02 cm31cm3 do conteúdo de água do solo e apresentaram coeficientes de correlação entre 0,97 e 1,0. UNITERMOS: sonda de nêutrons. umidade do solo. textura e profundidade do solo  SANTOS, R.F., CARLESSO, R. Soil texture and depth influence on the neutron probe calibration   2 SUMMARY  The neutron probe is an equipment used on determination of the soil water content, based on the fast neutron attenuation. Therefore, there is a calibration need in the field and, consequently, to verify the soil texture and depth influence for to determining the calibration curves in relation to the water content. The study was developed at Santa Maria's Federal University in a lisímeter group, protected from the rains with transparent plastic. Three different soil textures, three depths (10, 30 and 50 cm from the soil surface) and four replicates were used. Linear regression equations between neutron counts and soil water contents were made. The results showed that there was interference of the texture and depth of the soil, analyzed jointly, on the calibration curves, and the observed and estimated values varied from 0,02 to 0,06 cm3 / cm3 of the soil water content and the correlation coefficients were 0,86, 0,95 and 0,89 for clayay, franc-silt-clayay and franc-sandy, respectively. For soil texture and depth, analyzed separately, the differences among the values observed in the field and the estimated ones, varied from 0,0 to 0,02 cm3/cm3 soil water content and presented correlation coefficients between 0,97 and 1,0. KEYWORDS: neutron probe, soil water content, soil texture and depth.

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

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