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Prediction of soil properties by using geographically weighted regression at a regional scale

https://doi.org/10.1071/sr16177
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Outgoing claims: the papers this work cites, builds on, or argues with.

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The in(a/tan/β) index: How to calculate it and how to use it within the topmodel framework
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Nonstationary models for exploring and mapping monthly precipitation in the United Kingdom
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Assessment and prediction of overall environmental quality of Zhuzhou City, Hunan Province, China
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Incorporating spatial non-stationarity of regression coefficients into predictive vegetation models
inferredcites →https://doi.org/10.1007/s11442-011-0873-2openalex-snapshot
The scaling method of specific catchment area from DEMs
inferredcites →https://doi.org/10.1007/s12303-014-0023-9openalex-snapshot
Re-tooling of regression kriging in R for improved digital mapping of soil properties
inferredcites →https://doi.org/10.1016/j.agwat.2009.10.012openalex-snapshot
Managing natural resources of watersheds in the semi-arid tropics for improved soil and water quality: A review
inferredcites →https://doi.org/10.1016/j.apgeochem.2011.04.014openalex-snapshot
Towards spatial geochemical modelling: Use of geographically weighted regression for mapping soil organic carbon contents in Ireland
inferredcites →https://doi.org/10.1016/j.apgeog.2013.04.002openalex-snapshot
Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging
inferredcites →https://doi.org/10.1016/j.compag.2010.04.011openalex-snapshot
Site-specific management units in a commercial maize plot delineated using very high resolution remote sensing and soil properties mapping
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2007.08.009openalex-snapshot
The geography of mortality in the Atlanta metropolitan area
inferredcites →https://doi.org/10.1016/j.eja.2010.04.005openalex-snapshot
Soil properties estimation by inversion of a crop model and observations on crops improves the prediction of agro-environmental variables
inferredcites →https://doi.org/10.1016/j.geoderma.2007.11.003openalex-snapshot
Key soil and topographic properties to delineate potential management classes for precision agriculture in the European loess area
inferredcites →https://doi.org/10.1016/j.geoderma.2010.05.001openalex-snapshot
Prediction of soil properties using fuzzy membership values
inferredcites →https://doi.org/10.1016/j.geoderma.2011.07.012openalex-snapshot
Spatial prediction of soil organic matter using terrain indices and categorical variables as auxiliary information
inferredcites →https://doi.org/10.1016/j.geoderma.2012.05.022openalex-snapshot
A geographically weighted regression kriging approach for mapping soil organic carbon stock
inferredcites →https://doi.org/10.1016/j.geoderma.2015.06.024openalex-snapshot
Mapping soil organic carbon content by geographically weighted regression: A case study in the Heihe River Basin, China
inferredcites →https://doi.org/10.1016/j.jag.2005.06.009openalex-snapshot
Effects of detailed soil spatial information on watershed modeling across different model scales
inferredcites →https://doi.org/10.1016/j.jaridenv.2009.08.003openalex-snapshot
Spatial prediction of soil moisture content using multiple-linear regressions in a gully catchment of the Loess Plateau, China
inferredcites →https://doi.org/10.1016/j.jhydrol.2012.06.021openalex-snapshot
A review of the methods available for estimating soil moisture and its implications for water resource management
inferredcites →https://doi.org/10.1016/j.landusepol.2009.01.004openalex-snapshot
Soil-specific agro-ecological strategies for sustainable land use – A case study by using MicroLEIS DSS in Sevilla Province (Spain)
inferredcites →https://doi.org/10.1016/j.scitotenv.2008.09.031openalex-snapshot
Examining spatially varying relationships between land use and water quality using geographically weighted regression I: Model design and evaluation
inferredcites →https://doi.org/10.1016/j.soilbio.2010.05.031openalex-snapshot
Belowground carbon allocation patterns in a dry Mediterranean ecosystem: A comparison of two models
inferredcites →https://doi.org/10.1016/j.still.2008.08.010openalex-snapshot
Factors determining soil nutrient distribution in a small-scaled watershed in the purple soil region of Sichuan Province, China
inferredcites →https://doi.org/10.1016/s0016-7061(00)00048-3openalex-snapshot
Improving soil hydromorphy prediction according to DEM resolution and available pedological data
inferredcites →https://doi.org/10.1016/s0016-7061(03)00223-4openalex-snapshot
On digital soil mapping
inferredcites →https://doi.org/10.1016/s0022-1694(01)00390-0openalex-snapshot
Effects of spatial detail of soil information on watershed modeling
inferredcites →https://doi.org/10.1016/s0301-4797(02)90590-6openalex-snapshot
Assessment and prediction of overall environmental quality of Zhuzhou City, Hunan Province, China
inferredcites →https://doi.org/10.1068/a3768openalex-snapshot
Testing the Importance of the Explanatory Variables in a Mixed Geographically Weighted Regression Model
inferredcites →https://doi.org/10.1071/sr11134openalex-snapshot
Effects of land use and topographical attributes on soil properties in an agricultural landscape
inferredcites →https://doi.org/10.1080/02626667909491834openalex-snapshot
A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant
inferredcites →https://doi.org/10.1080/02693799008941527openalex-snapshot
Terrain position as mapped from a gridded digital elevation model
inferredcites →https://doi.org/10.1080/02693799508902047openalex-snapshot
Soil-landscape modelling and spatial prediction of soil attributes
inferredcites →https://doi.org/10.1086/276538openalex-snapshot
Proceedings of the Indiana Academy of Sciences for 1895
inferredcites →https://doi.org/10.1111/j.0016-7363.2005.00671.xopenalex-snapshot
GeoDa : An Introduction to Spatial Data Analysis
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Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems
inferredcites →https://doi.org/10.1111/j.1538-4632.1996.tb00936.xopenalex-snapshot
Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity
inferredcites →https://doi.org/10.2136/sssaj1993.03615995005700020026xopenalex-snapshot
Soil Attribute Prediction Using Terrain Analysis
inferredcites →https://doi.org/10.2136/sssaj2000.6462046xopenalex-snapshot
Modeling Soil–Landscape and Ecosystem Properties Using Terrain Attributes
inferredcites →https://doi.org/10.2136/sssaj2003.0264openalex-snapshot
Analyzing Digital Terrain Attributes to Predict Soil Attributes for a Relatively Large Area
inferredcites →https://doi.org/10.2136/sssaj2004.0322openalex-snapshot
Soil Carbon Storage Estimation in a Forested Watershed using Quantitative Soil‐Landscape Modeling
inferredcites →https://doi.org/10.2136/sssaj2009.0158openalex-snapshot
Predicting the Spatial Variation of the Soil Organic Carbon Pool at a Regional Scale
inferredcites →https://doi.org/10.2747/1548-1603.49.6.915openalex-snapshot
Comparison of Geographically Weighted Regression and Regression Kriging for Estimating the Spatial Distribution of Soil Organic Matter
inferredcites →https://doi.org/10.3724/sp.j.1047.2009.00737openalex-snapshot
Simple Digital Terrain Analysis Software(SimDTA 1.0) and Its Application in Fuzzy Classification of Slope Positions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4666578openalex-extracted
Spatial-Temporal Variations of Soil Organic Carbon and Driving Factors in Guangdong, China (2009-2023)
inferred← citeshttps://doi.org/10.1007/978-981-16-0917-6_3openalex-snapshot
Soil Organic Carbon: Past, Present, and Future Research
inferred← citeshttps://doi.org/10.1007/978-981-97-6635-2_3openalex-snapshot
Digital Soil Mapping: A Tool for Sustainable Soil Management
inferred← citeshttps://doi.org/10.1007/s00477-021-01986-2openalex-snapshot
Exploring spatial distributions of increments in soil heavy metals and their relationships with environmental factors using GWR
inferred← citeshttps://doi.org/10.1007/s10109-022-00387-5openalex-snapshot
Geographically weighted regression with the integration of machine learning for spatial prediction
inferred← citeshttps://doi.org/10.1007/s12665-023-10919-xopenalex-snapshot
Digital mapping of selected soil properties using machine learning and geostatistical techniques in Mashhad plain, northeastern Iran
inferred← citeshttps://doi.org/10.1016/b978-0-443-13293-3.00014-2openalex-snapshot
Digital soil mapping using geospatial data and machine learning techniques
inferred← citeshttps://doi.org/10.1016/j.apgeog.2019.102129openalex-snapshot
Spatial prediction and mapping of soil pH across a tropical afro-montane landscape
inferred← citeshttps://doi.org/10.1016/j.fecs.2024.100212openalex-snapshot
Terrain or climate factor dominates vegetation resilience? Evidence from three national parks across different climatic zones in China
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.05.031openalex-snapshot
Digital soil mapping algorithms and covariates for soil organic carbon mapping and their implications: A review
inferred← citeshttps://doi.org/10.1016/j.geoderma.2020.114246openalex-snapshot
Refining benchmarks for soil organic carbon in Australia’s temperate forests
inferred← citeshttps://doi.org/10.1016/j.geoderma.2020.114792openalex-snapshot
Comparison of multivariate methods for arsenic estimation and mapping in floodplain soil via portable X-ray fluorescence spectroscopy
inferred← citeshttps://doi.org/10.1051/e3sconf/202343101005openalex-snapshot
Assessing fertility complexity of Agro-gray soil on the East European Plain using correlation-regression analysis
inferred← citeshttps://doi.org/10.1071/sr18319openalex-snapshot
Digital mapping of topsoil pH by random forest with residual kriging (RFRK) in a hilly region
inferred← citeshttps://doi.org/10.1080/10106049.2021.1871667openalex-snapshot
Estimating and mapping of soil organic matter content in a typical river basin of the Qinghai-Tibet Plateau
inferred← citeshttps://doi.org/10.1080/13658816.2025.2580414openalex-snapshot
Second-dimension outliers for spatial prediction
inferred← citeshttps://doi.org/10.1111/sum.12981openalex-snapshot
Estimating the spatial distribution of soil volumetric water content in an agricultural field employing remote sensing and other auxiliary data under different tillage management practices
inferred← citeshttps://doi.org/10.3390/f12060673openalex-snapshot
Spatiotemporal Changes in Vegetation Cover and Its Influencing Factors in the Loess Plateau of China Based on the Geographically Weighted Regression Model
inferred← citeshttps://doi.org/10.3390/land13071096openalex-snapshot
Spatial–Temporal Variations in Soil Organic Carbon and Driving Factors in Guangdong, China (2009–2023)
inferred← citeshttps://doi.org/10.3390/rs17091597openalex-snapshot
Estimating Soil Attributes for Yield Gap Reduction in Africa Using Hyperspectral Remote Sensing Data with Artificial Intelligence Methods: An Extensive Review and Synthesis
inferred← citeshttps://doi.org/10.3390/su15118511openalex-snapshot
Regional-Scale Topsoil Organic Matter Estimation Based on a Geographic Detector Model Using Landsat Data, Pingtan Island, Fujian, China
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