2016
DOI: 10.1007/s40808-016-0160-4
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Spatial analysis of soil properties using GIS based geostatistics models

Abstract: Accurate assessment of the spatial variability of soil properties is key component of the agriculture ecosystem and environment modeling. The main objective of the present study is to measure the soil properties and their spatial variability. A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability. In November 2014 a total of 32 soil samples were collected in the field through random sampling in Medinipur Sadar block of Paschim Medinipur… Show more

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Cited by 78 publications
(38 citation statements)
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“…There are various methods for interpolation of spatial distribution of SOC, TN and soil pH, such as inverse distance weighting (IDW) and ordinary kriging (OK) [9][10][11][12][13]. In recent years, researchers have suggested a combination of regression and spatial interpolation, called regression kriging (RK), to determine the spatial distribution of soil characteristics [14][15][16][17][18][19][20][21].…”
Section: Introductionmentioning
confidence: 99%
“…There are various methods for interpolation of spatial distribution of SOC, TN and soil pH, such as inverse distance weighting (IDW) and ordinary kriging (OK) [9][10][11][12][13]. In recent years, researchers have suggested a combination of regression and spatial interpolation, called regression kriging (RK), to determine the spatial distribution of soil characteristics [14][15][16][17][18][19][20][21].…”
Section: Introductionmentioning
confidence: 99%
“…where γ(h) is the semivariance, h is the lag distance, Z is the parameter of the water property, N(h) is the number of pairs of locations separated by a lag distance h, Z(x i ), and Z (x i + h) are values of Z at positions x i and x i + h (Wang and Shao 2013;Shit et al 2016). The empirical semivariograms obtained from the data were fitted by theoretical semivariogram models to produce geostatistical parameters, including nugget variance (C0), structured variance (C1), sill variance (C0 + C1), and distance parameter (k).…”
Section: Geostatistical Analysismentioning
confidence: 99%
“…The principal issue of the ecological modeling is the precise assessment of the spatial variability of soil properties (Shit et al, 2016). An inverse distance weighting or ordinary kriging are the effective approaches for interpolation of the spatial patterns of soil properties (Uygur et al, 2010;Göl et al, 2017;Tang et al, 2017).…”
Section: Introductionmentioning
confidence: 99%