Remote sensing of soil organic matter of farmland with hyperspectral image

2017 ◽  
Author(s):  
Xiaohe Gu ◽  
Lei Wang ◽  
Guijun Yang ◽  
Liyan Zhang
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Hyperspectral Image

scholarly journals Some Peculiarities of Arable Soil Organic Matter Detection Using Optical Remote Sensing Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2313
Author(s):  
Elena Prudnikova ◽  
Igor Savin
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Spectral Reflectance ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Optical Remote Sensing ◽  
Test Field ◽  
Sensing Data ◽  
Sentinel 2

Optical remote sensing only provides information about the very thin surface layer of soil. Rainfall splash alters soil surface properties and its spectral reflectance. We analyzed the impact of rainfall on the success of soil organic matter (SOM) content (% by mass) detection and mapping based on optical remote sensing data. The subject of the study was the arable soils of a test field located in the Tula region (Russia), their spectral reflectance, and Sentinel-2 data. Our research demonstrated that rainfall negatively affects the accuracy of SOM predictions based on Sentinel-2 data. Depending on the average precipitation per day, the R2cv of models varied from 0.67 to 0.72, RMSEcv from 0.64 to 1.1% and RPIQ from 1.4 to 2.3. The incorporation of information on the soil surface state in the model resulted in an increase in accuracy of SOM content detection based on Sentinel-2 data: the R2cv of the models increased up to 0.78 to 0.84, the RMSEcv decreased to 0.61 to 0.71%, and the RPIQ increased to 2.1 to 2.4. Further studies are necessary to identify how the SOM content and composition of the soil surface change under the influence of rainfall for other soils, and to determine the relationships between rainfall-induced SOM changes and soil surface spectral reflectance.

scholarly journals Monitoring changes of soil organic matter and total nitrogen in cultivated land in Guangxi by remote sensing

2014 ◽  
Vol 34 (18) ◽  
Author(s):  
李燕丽 LI Yanli ◽  
潘贤章 PAN Xianzhang ◽  
王昌昆 WANG Changkun ◽  
刘娅 LIU Ya ◽  
赵其国 ZHAO Qiguo
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Total Nitrogen ◽  
Cultivated Land

scholarly journals The Estimation of Soil Organic Matter Variation in Arid and Semi-Arid Lands Using Remote Sensing Data

2019 ◽  
Vol 10 (05) ◽  
pp. 576-588
Author(s):  
Majed Ibrahim ◽  
Fatima Ghanem ◽  
Afnan Al-Salameen ◽  
Abdallah Al-Fawwaz
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Remote Sensing Data ◽  
Arid Lands ◽  
Sensing Data ◽  
Semi Arid

Spatial stochastic model for predicting soil organic matter using remote sensing data

2020 ◽  
pp. 1-32
Author(s):  
Javed Mallick ◽  
Mohd Ahmed ◽  
Saeed Dhafer Alqadhi ◽  
Ibrahim I. Falqi ◽  
Muneer Parayangat ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Stochastic Model ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Spatial Stochastic Model

scholarly journals High-Spectral Resolution Remote Sensing of Soil Organic Carbon Dynamics

2021 ◽  
Vol 13 (7) ◽  
pp. 1293
Author(s):  
Bas van Wesemael ◽  
Sabine Chabrillat ◽  
Florian Wilken
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Structure ◽  
High Spectral Resolution ◽  
High Fertility ◽  
Water Holding ◽  
Soil Organic Carbon Dynamics

Soil organic matter (SOM) is essential for preserving a healthy soil that provides good soil structure and high fertility and water -holding capacity [...]

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