scholarly journals Assessment of Spatial Variability and Mapping of Soil Texture in Western of Syria using Geographic Information System Techniques (GIS)

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Khozama Barakat AL-Saleh
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Texture ◽  
Texture Mapping ◽  
Cropping Patterns ◽  
Digital Maps ◽  
Silty Loam ◽  
Weight Method ◽  
Clay Percentage ◽  
Inverse Distance

The study aimed to study the spatial variability of soil texture for soils around AL-Basel Lake in Safita Region which located in Tartous Governorate west of Syrian Arab Republic. Spatial maps of soil properties are invaluable in agricultural Production for assessing soil quality, planning land use and determining the suitability of cropping patterns. Geostatistics has been extensively used for quantifying the spatial pattern of soil properties and Inverse Distance Weight technique are proving sufficiently robust for estimating values at unsampled locations. The experiment was conducted on the soils of villages around AL-Basel lake The aim of this work is to study the spatial variability of soil texture. For this purpose ,90 Samples were collected. Results of Laboratory analysis of studied indexes were imported into ArcGis9.3 software and presented in form of Digital Maps that show the spatial Distribution of soil texture using Geostatistical Analyst and Inverse Distance Weight method was used in the Spatial Interpolation. Results of texture analysis showed that the soils have a texture between Loam and Silty Loam. Geostatistical analyst was used for unsampled points. Since 70.94 % of study area has Sand percentage (30-40) %, for Silt 57.73 % of study area has Silt percentage (40-50)% ,for Clay 71.97% of study area has Clay percentage (10-20)%,81.76% of study area has loam texture. This study thus provided a methodology that can help improve the accuracy and efficiency of soil texture mapping in areas using.

Mapping the Spatial Variability of Soil Properties: A Comparative Study of Spatial Interpolation Methods in Northeast China

2014 ◽  
Vol 535 ◽  
pp. 483-488 ◽  
Author(s):  
Xiao Yan Li ◽  
Hong Li ◽  
Hui Jia Liu
Keyword(s):  
Soil Properties ◽  
Human Activity ◽  
Ordinary Kriging ◽  
Northeast China ◽  
Prediction Methods ◽  
Regression Kriging ◽  
Hybrid Techniques ◽  
Soil Variables ◽  
Weight Method ◽  
Inverse Distance

We analyzed the variance characteristics of soil organic matter (SOM), total nitrogen (TN), extractable phosphorus (EP), and extractable potassium (EK), in Jiutai County, Northeast China, and compared different prediction methods for mapping of these four soil variables. The prediction methods used were geostatistical interpolation (ordinary kriging), inverse distance weight method, and the hybrid techniques (regression-kriging). A modified jackknifing method involving 40% partitions was used to examine the stability of validate the indices. Root mean square error (RMSE) was used as validation index, and mean RMSE was used to judge the prediction quality. The results showed that the hybrid interpolation regression-kriging cant be used in the region influenced by frequent and high-intensity human activity when the relationship between soil properties and environment factors were not obvious. The ordinary kriging was found to be the best method to fit the experimental semivariogram of SOM and EK. The inverse distance weight method fit well to predict the distribution of TN and EP. For SOM and EK, results showed that data values in the western part were higher than those in the eastern part. However, for TN and EP, there is no clear trend. Water and tillage erosion caused by human activity has weakened the structural influence and elevation and slope played key roles in the distribution of soil variables in the local area.

Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

2014 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Set Foong Ng ◽  
Pei Eng Ch’ng ◽  
Yee Ming Chew ◽  
Kok Shien Ng
Keyword(s):  
Soil Properties ◽  
Lagrange Multipliers ◽  
Unbiased Estimator ◽  
Soil Property ◽  
Minimum Variance ◽  
Distance Method ◽  
True Value ◽  
A Site ◽  
Method Of Lagrange Multipliers ◽  
Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

Effect of Slope Mesorelief on the Spatial Variability of Soil Properties and Vegetation Index Based on Remote Sensing Data

2019 ◽  
Vol 55 (9) ◽  
pp. 1329-1337
Author(s):  
N. V. Gopp ◽  
T. V. Nechaeva ◽  
O. A. Savenkov ◽  
N. V. Smirnova ◽  
V. V. Smirnov
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Sensing Data

Spatial Variability of Rainfed Wheat Production Under the Influence of Topography and Soil Properties in Loess-Derived Soils, Northern Iran

2020 ◽  
Vol 14 (4) ◽  
pp. 597-608
Author(s):  
Mohammad Ajami ◽  
Ahmad Heidari ◽  
Farhad Khormali ◽  
Mojtaba Zeraatpisheh ◽  
Manouchehr Gorji ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Northern Iran ◽  
Wheat Production ◽  
Rainfed Wheat

scholarly journals Land Uses, Altitude and Texture Effects on Soil Parameters. A Comparative Study in Two Districts of Nagaland, Northeast India

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 171
Author(s):  
Gaurav Mishra ◽  
Rosa Francaviglia
Keyword(s):  
Soil Properties ◽  
Soil Texture ◽  
Soil Parameters ◽  
Available Phosphorus ◽  
Land Uses ◽  
Management Options ◽  
Available N ◽  
P Content ◽  
Significant Difference ◽  
Soc Stocks

Northeast (NE) India is a typical tropical ecosystem with a luxuriant forest vegetation cover, but nowadays forests are under stress due to exploitation and land use changes, which are known to affect soil health and productivity. However, due to a scarcity of data, the influence of land uses and altitude on soil properties of this peculiar ecosystem is poorly quantified. This study presents the changes in soil properties in two districts of Nagaland (Mon and Zunheboto) in relation to land uses (forest, plantation, jhum and fallow jhum), altitude (<500 m, 500–1000 m, >1000 m) and soil texture (coarse, medium, fine). For this, a random soil sampling was performed in both the districts. Results indicated that soil organic carbon (SOC) stocks and available potassium (K) were significantly influenced by land uses in the Mon district, while in Zunheboto a significant difference was observed in available phosphorus (P) content. SOC stocks showed an increasing trend with elevation in both districts. The influence of altitude on P was significant and the maximum concentration was at lower elevations (<500 m). In Mon, soil texture significantly affected SOC stocks and the available N and P content. The variability in soil properties due to land uses, altitudinal gradients and textural classes can be better managed with the help of management options, which are still needed for this ecosystem.

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