Prediction of Soil Organic Matter Using Ordinary Kriging Combined With the Clustering of Self-organizing Map

YunXiang, Huang; Ye, Huichun; Zhang, Liping; Zhang, Shiwen; Shen, Chongyang; Zhen, Li; Huang, Yuanfang

doi:10.1097/ss.0000000000000196

Cited by 9 publications

(2 citation statements)

References 56 publications

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“…where n is the number of observation points, λ i are the weights and z(x i ) is the known value of variable Z at sampling site x i [52]. The interpolation variance σ ok in each point is calculated based on the following equation:…”

Section: Geostatistical Analysismentioning

confidence: 99%

Spatiotemporal Dynamics of Water Table Depth Associated with Changing Agricultural Land Use in an Arid Zone Oasis

Ainiwaer

Ding

Wang

et al. 2019

Water

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Investigating spatiotemporal dynamics and varying relationships between water table depth (WTD) and land use changes is critical for efficient groundwater management and land use planning in arid zones. The primary objective of the present study is to combine satellite and field measured data to quantitatively analyze variations in WTD and its relationship with land use change in the Ogan–Kucha River Oasis in the northwest arid zones of China, and reveal the spatial heterogeneity and variations in the abovementioned relationship at spatiotemporal scales. The spatiotemporal variations in WTD and land use change at different time intervals (1997–2007, 2007–2017, and 1997–2017) were analyzed based on geostatistical analysis methods and grid cell approaches. The relationships between land use types and changes in WTD were assessed using correlation and ordinary least square analyses. The relationships between spatiotemporal variations in WTD and land use change were explored using local level geographically weighted regression. The results indicated that influences of human activity on the variation of WTD have gradually increased, and that WTD has declined rapidly in most parts of the study area. The spatial distribution of WTD exhibited significant spatiotemporal heterogeneity, and WTD was lower in the inner parts of the oasis and shallower in the oasis-desert ecotone. The WTD decline rates in the irrigation area were much higher than those in the oasis-desert ecotone. The cultivated land area has expanded markedly, whereas the shrub covered area has shrunk rapidly. Changes in WTD were positively correlated with changes in cultivated land area, and the expansion center of cultivated land has gradually moved from upstream of the alluvial fan to downstream of the alluvial fan and to the oasis-desert ecotone. The relationships between changes in cultivated land and WTD in the ecotone were more prominent than those in the inner parts of the oasis. Therefore, agricultural land expansion and planning in the study area should be integrated based on spatiotemporal changes in the groundwater depth to maintain the stability of groundwater systems and sustainable groundwater exploitation.

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Section: Geostatistical Analysismentioning

confidence: 99%

Spatiotemporal Dynamics of Water Table Depth Associated with Changing Agricultural Land Use in an Arid Zone Oasis

Ainiwaer

Ding

Wang

et al. 2019

Water

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“…Geo-information could provide intuitive assessment results for decision makers. Researches (Yang et al, 2014;Huang et al, 2017) have indicated that deep data mining is possible when SOM and geo-information are combined. Wang et al (2015) assessed the spatial characteristics of heavy metal-contaminated sediment to determine the contaminated hotspots by using SOM and factor analysis (FA).…”

Section: Introductionmentioning

confidence: 99%

Exploring the database of a soil environmental survey using a geo-self-organizing map: A pilot study

et al. 2019

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A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topological distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.

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Combination of geostatistics and self-organizing maps for the spatial analysis of groundwater level variations in complex hydrogeological systems

Varouchakis

Solomatine

Perez

et al. 2023

Stoch Environ Res Risk Assess

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Successful modelling of the groundwater level variations in hydrogeological systems in complex formations considerably depends on spatial and temporal data availability and knowledge of the boundary conditions. Geostatistics plays an important role in model-related data analysis and preparation, but has specific limitations when the aquifer system is inhomogeneous. This study combines geostatistics with machine learning approaches to solve problems in complex aquifer systems. Herein, the emphasis is given to cases where the available dataset is large and randomly distributed in the different aquifer types of the hydrogeological system. Self-Organizing Maps can be applied to identify locally similar input data, to substitute the usually uncertain correlation length of the variogram model that estimates the correlated neighborhood, and then by means of Transgaussian Kriging to estimate the bias corrected spatial distribution of groundwater level. The proposed methodology was tested on a large dataset of groundwater level data in a complex hydrogeological area. The obtained results have shown a significant improvement compared to the ones obtained by classical geostatistical approaches.

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Prediction of Soil Organic Matter Using Ordinary Kriging Combined With the Clustering of Self-organizing Map

Cited by 9 publications

References 56 publications

Spatiotemporal Dynamics of Water Table Depth Associated with Changing Agricultural Land Use in an Arid Zone Oasis

Spatiotemporal Dynamics of Water Table Depth Associated with Changing Agricultural Land Use in an Arid Zone Oasis

Exploring the database of a soil environmental survey using a geo-self-organizing map: A pilot study

Combination of geostatistics and self-organizing maps for the spatial analysis of groundwater level variations in complex hydrogeological systems

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