A geographically weighted regression kriging approach for mapping soil organic carbon stock

Geoderma ◽  
2012 ◽  
Vol 189-190 ◽  
pp. 627-634 ◽  
Author(s):  
Sandeep Kumar ◽  
Rattan Lal ◽  
Desheng Liu
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Geographically Weighted Regression ◽  
Carbon Stock ◽  
Weighted Regression ◽  
Regression Kriging ◽  
Soil Organic Carbon Stock ◽  
Organic Carbon Stock ◽  
Kriging Approach

scholarly journals Geospatial modeling approaches for mapping topsoil organic carbon stock in northern part of Mongolia

2019 ◽  
pp. 4-17
Author(s):  
Samdandorj M ◽  
Purevdorj Ts
Keyword(s):  
Organic Carbon ◽  
Root Mean Square Error ◽  
Geographically Weighted Regression ◽  
Carbon Stock ◽  
Vegetation Index ◽  
Weighted Regression ◽  
Mean Square ◽  
Regression Kriging ◽  
Soc Stock ◽  
Organic Carbon Stock

Soil organic carbon (SOC) is one of the most important indicators of soil quality and agricultural productivity. This paper presents the application of Regression Kriging (RK), geographically weighted regression (GWR) and Geographically Weighted Regression Kriging (GWRK) for prediction of topsoil organic carbon stock in Tarialan. A total of 25 topsoil (0-30 cm) samples were collected from Tarialan soum of Khuvsgul aimag in Mongolia. In this study, seven independent variables were used including normalised difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), normalised difference moisture index (NDMI), land surface temperature (LST) and terrain factors (DEM, Slope, Aspect). We used root-mean-square error (RMSE), mean error (ME) and determination coefficient (R2) to evaluate the performance of these methods. Validation results showed that performance of the GWRK, GWR, and RK approaches were good with not only low values of root-mean-square error (1.38 kg/m2, 1.48 kg/m2, 0.69 kg/m2), mean error (0.28 kg/m2, -0.22 kg/m2, 0.17 kg/m2) but also high values of R2 (0.76, 0.72, 0.94). The estimated SOC stock values ranged from 0.28-16.26 kg/m2, 0.72–15.24 kg/m2, 0.16–15.83 kg/m2 using GWRK, GWR, RK approaches in the study area. The highest average SOC stock value was in the wetland (6.47 kg/m2, 6.08 kg/m2, 6.44 kg/m2) and the lowest was in cropland (1.63 kg/m2, 1.48 kg/m2, 1.80 kg/m2) using these approaches. According to the validation, GWRK, GWR, and RK approaches produced satisfactory results for estimating and mapping SOC stock. However, Regression Kriging was the best model, followed by GWRK and GWR to predict topsoil organic carbon stock in Tarialan.

Geospatial modeling approaches for mapping topsoil organic carbon stock in northern part of Mongolia

2020 ◽  
Author(s):  
Samdandorj Manaljav ◽  
Purevdorj Tserengunsen
Keyword(s):  
Organic Carbon ◽  
Root Mean Square Error ◽  
Geographically Weighted Regression ◽  
Carbon Stock ◽  
Vegetation Index ◽  
Weighted Regression ◽  
Mean Square ◽  
Regression Kriging ◽  
Soc Stock ◽  
Organic Carbon Stock

<p>Soil organic carbon (SOC) is one of the most important indicators of soil quality and agricultural productivity. This paper presents the application of Regression Kriging (RK), Geographically Weighted Regression (GWR) and Geographically Weighted Regression Kriging (GWRK) for prediction of topsoil organic carbon stock in Tarialan. A total of 25 topsoil (0-30 cm) samples were collected from Tarialan soum of Khuvsgul aimag in Mongolia. In this study, seven independent variables were used including normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), normalized difference moisture index (NDMI), land surface temperature (LST) and terrain factors (DEM, Slope, Aspect). We used root mean square error (RMSE), mean error (ME) and determination coefficient (R<sup>2</sup>) to evaluate the performance of these methods. Validation results showed that performance of the GWRK, GWR, and RK approaches were good with not only low values of root-mean-square error (1.38 kg m<sup>-2</sup>, 1.48 kg m<sup>-2</sup>, 0.69 kg m<sup>-2</sup>), mean error (0.28 kg m<sup>-2</sup>, -0.22 kg m<sup>-2</sup>, 0.17 kg m<sup>-2</sup>) but also high values of R<sup>2</sup> (0.76, 0.72, 0.94). The estimated SOC stock values ranged from 0.28-16.26 kg m<sup>-2</sup>, 0.72–15.24 kg m<sup>-2</sup>, 0.16–15.83 kg m<sup>-2</sup> using GWRK, GWR, RK approaches in the study area. The highest average SOC stock value was in the wetland (6.47 kg m<sup>-2</sup>, 6.08 kg m<sup>-2</sup>, 6.44 kg m<sup>-2</sup>) and the lowest was in cropland (1.63 kg m<sup>-2</sup>, 1.48 kg m<sup>-2</sup>, 1.80 kg m<sup>-2</sup>) using these approaches. According to the validation, GWRK, GWR, and RK approaches produced satisfactory results for estimating and mapping SOC stock. However, Regression Kriging was the best model, followed by GWRK and GWR to predict topsoil organic carbon stock in Tarialan.</p>

Grazing exclosures increase soil organic carbon stock at a rate greater than “4 per 1000” per year across agricultural landscapes in Northern Ethiopia

2021 ◽  
Vol 782 ◽  
pp. 146821
Author(s):  
Florent Noulèkoun ◽  
Emiru Birhane ◽  
Habtemariam Kassa ◽  
Alemayehu Berhe ◽  
Zefere Mulaw Gebremichael ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Stock ◽  
Agricultural Landscapes ◽  
Northern Ethiopia ◽  
Soil Organic Carbon Stock ◽  
Organic Carbon Stock

Assessment of soil organic carbon stock in the upper Yangtze River basin

2013 ◽  
Vol 10 (5) ◽  
pp. 866-872 ◽  
Author(s):  
Xiao-guo Wang ◽  
Bo Zhu ◽  
Ke-ke Hua ◽  
Yong Luo ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
River Basin ◽  
Yangtze River ◽  
Carbon Stock ◽  
Yangtze River Basin ◽  
Soil Organic Carbon Stock ◽  
Upper Yangtze River ◽  
Organic Carbon Stock ◽  
The Upper Yangtze River

Soil organic carbon stock in different urban land uses: high stock evidence in urban parks

2019 ◽  
Vol 23 (1) ◽  
pp. 159-171 ◽  
Author(s):  
Claudia Canedoli ◽  
Chiara Ferrè ◽  
Davide Abu El Khair ◽  
Emilio Padoa-Schioppa ◽  
Roberto Comolli
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Stock ◽  
Urban Parks ◽  
Urban Land ◽  
Land Uses ◽  
Soil Organic Carbon Stock ◽  
Organic Carbon Stock

scholarly journals Assessment of Soil Organic Carbon Stock of Temperate Coniferous Forests in Northern Kashmir

2015 ◽  
Vol 4 (1) ◽  
pp. 161-178
Author(s):  
Davood A. Dar ◽  
Bhawana Pathak ◽  
M. H. Fulekar
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Quality ◽  
Carbon Stock ◽  
Temperate Forest ◽  
Temperate Forests ◽  
Forest Site ◽  
Soil Organic Carbon Stock ◽  
Organic Carbon Stock

 Soil organic carbon (SOC) estimation in temperate forests of the Himalaya is important to estimate their contribution to regional, national and global carbon stocks. Physico chemical properties of soil were quantified to assess soil organic carbon density (SOC) and SOC CO2 mitigation density at two soil depths (0-10 and 10-20 cms) under temperate forest in the Northern region of Kashmir Himalayas India. The results indicate that conductance, moisture content, organic carbon and organic matter were significantly higher while as pH and bulk density were lower at Gulmarg forest site. SOC % was ranging from 2.31± 0.96 at Gulmarg meadow site to 2.31 ± 0.26 in Gulmarg forest site. SOC stocks in these temperate forests were from 36.39 ±15.40 to 50.09 ± 15.51 Mg C ha-1. The present study reveals that natural vegetation is the main contributor of soil quality as it maintained the soil organic carbon stock. In addition, organic matter is an important indicator of soil quality and environmental parameters such as soil moisture and soil biological activity change soil carbon sequestration potential in temperate forest ecosystems.DOI: http://dx.doi.org/10.3126/ije.v4i1.12186International Journal of Environment Volume-4, Issue-1, Dec-Feb 2014/15; page: 161-178

scholarly journals Soil organic carbon stock under different land use types in Kersa Sub Watershed, Eastern Ethiopia

2018 ◽  
Vol 13 (24) ◽  
pp. 1248-1256 ◽  
Author(s):  
Mohammed Muktar ◽  
Bedadi Bobe ◽  
Kibret Kibebew ◽  
Mulat Yared
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Stock ◽  
Eastern Ethiopia ◽  
Soil Organic Carbon Stock ◽  
Land Use Types ◽  
Organic Carbon Stock

Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon

2017 ◽  
Vol 20 ◽  
pp. 76-91 ◽  
Author(s):  
Huichun Ye ◽  
Wenjiang Huang ◽  
Shanyu Huang ◽  
Yuanfang Huang ◽  
Shiwen Zhang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Geographically Weighted Regression ◽  
Weighted Regression ◽  
Regression Kriging

Land Use Effects on Sample Size Requirements for Soil Organic Carbon Stock Estimations

Soil Science ◽  
2011 ◽  
Vol 176 (2) ◽  
pp. 110-114 ◽  
Author(s):  
Sriroop Chaudhuri ◽  
Eugenia M. Pena-Yewtukhiw ◽  
Louis M. McDonald ◽  
Jeffrey Skousen ◽  
Mark Sperow
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Sample Size ◽  
Carbon Stock ◽  
Soil Organic Carbon Stock ◽  
Land Use Effects ◽  
Organic Carbon Stock
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