On the public citation graph

Geological and terrain attributes for predicting soil classes using pixel- and geographic object-based image analysis in the Brazilian Cerrado

https://doi.org/10.1016/j.geoderma.2021.115315
0 signed · 60 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/hyp.3360050103openalex-snapshot
Digital terrain modelling: A review of hydrological, geomorphological, and biological applications
inferredcites →https://doi.org/10.1007/978-1-4614-6849-3openalex-snapshot
Applied Predictive Modeling
inferredcites →https://doi.org/10.1007/978-3-642-32408-6_106openalex-snapshot
Mapping of Flood-Plain by Processing of Elevation Data from Remote Sensing
inferredcites →https://doi.org/10.1007/s10980-011-9702-3openalex-snapshot
Associations between soil carbon and ecological landscape variables at escalating spatial scales in Florida, USA
inferredcites →https://doi.org/10.1007/s11749-016-0481-7openalex-snapshot
A random forest guided tour
inferredcites →https://doi.org/10.1016/b978-0-12-385036-2.00008-0openalex-snapshot
Influence of Topography on Soil Properties
inferredcites →https://doi.org/10.1016/b978-0-12-804632-6.00009-2openalex-snapshot
Influence of Topography on Soil Properties
inferredcites →https://doi.org/10.1016/c2023-0-51092-4openalex-snapshot
Digital Terrain Analysis
inferredcites →https://doi.org/10.1016/j.apgeog.2011.05.004openalex-snapshot
Topodata: Brazilian full coverage refinement of SRTM data
inferredcites →https://doi.org/10.1016/j.earscirev.2020.103359openalex-snapshot
Machine learning for digital soil mapping: Applications, challenges and suggested solutions
inferredcites →https://doi.org/10.1016/j.envsoft.2014.03.004openalex-snapshot
Holistic environmental soil-landscape modeling of soil organic carbon
inferredcites →https://doi.org/10.1016/j.geoderma.2009.10.007openalex-snapshot
Mapping continuous depth functions of soil carbon storage and available water capacity
inferredcites →https://doi.org/10.1016/j.geoderma.2013.09.023openalex-snapshot
Constructing a soil class map of Denmark based on the FAO legend using digital techniques
inferredcites →https://doi.org/10.1016/j.geoderma.2014.09.019openalex-snapshot
Machine learning for predicting soil classes in three semi-arid landscapes
inferredcites →https://doi.org/10.1016/j.geoderma.2015.07.017openalex-snapshot
Digital soil mapping: A brief history and some lessons
inferredcites →https://doi.org/10.1016/j.geoderma.2016.03.019openalex-snapshot
Digital soil mapping at local scale using a multi-depth Vis–NIR spectral library and terrain attributes
inferredcites →https://doi.org/10.1016/j.geoderma.2019.113884openalex-snapshot
From geological to soil parent material maps - A random forest-supported analysis of geological map units and topography to support soil survey in South Tyrol
inferredcites →https://doi.org/10.1016/j.geomorph.2017.02.015openalex-snapshot
Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran
inferredcites →https://doi.org/10.1016/j.isprsjprs.2013.09.014openalex-snapshot
Geographic Object-Based Image Analysis – Towards a new paradigm
inferredcites →https://doi.org/10.1016/s0016-7061(00)00043-4openalex-snapshot
An overview of pedometric techniques for use in soil survey
inferredcites →https://doi.org/10.1016/s0166-2481(06)31001-xopenalex-snapshot
Chapter 1 Spatial Soil Information Systems and Spatial Soil Inference Systems: Perspectives for Digital Soil Mapping
inferredcites →https://doi.org/10.1016/s1002-0160(17)60377-1openalex-snapshot
Classification of Soil Types Using Geographic Object-Based Image Analysis and Random Forests
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1038/s41598-018-28244-wopenalex-snapshot
Predicting reference soil groups using legacy data: A data pruning and Random Forest approach for tropical environment (Dano catchment, Burkina Faso)
inferredcites →https://doi.org/10.1038/s41598-019-50376-wopenalex-snapshot
Digital soil mapping including additional point sampling in Posses ecosystem services pilot watershed, southeastern Brazil
inferredcites →https://doi.org/10.1109/igarss.2015.7326785openalex-snapshot
SPT 3.1: A free software for automatic tuning of segmentation parameters in optical, hyperspectral and SAR images
inferredcites →https://doi.org/10.1111/2041-210x.12427openalex-snapshot
Very high‐resolution digital elevation models: are multi‐scale derived variables ecologically relevant?
inferredcites →https://doi.org/10.1139/cjss-2017-0128openalex-snapshot
Importance of terrain attributes in relation to the spatial distribution of soil properties at the micro scale: a case study
inferredcites →https://doi.org/10.1201/b16500-78openalex-snapshot
Lithology as a powerful covariate in digital soil mapping
inferredcites →https://doi.org/10.1371/journal.pone.0183742openalex-snapshot
Predicting active-layer soil thickness using topographic variables at a small watershed scale
inferredcites →https://doi.org/10.1590/0103-9016-2015-0131openalex-snapshot
Digital soil mapping using reference area and artificial neural networks
inferredcites →https://doi.org/10.1590/1678-992x-2017-0171openalex-snapshot
Preprocessing procedures and supervised classification applied to a database of systematic soil survey
inferredcites →https://doi.org/10.1590/1678-992x-2017-0300openalex-snapshot
Soil type spatial prediction from Random Forest: different training datasets, transferability, accuracy and uncertainty assessment
inferredcites →https://doi.org/10.1590/1678-992x-2019-0227openalex-snapshot
Digital soil class mapping in Brazil: a systematic review
inferredcites →https://doi.org/10.1590/18069657rbcs20170133openalex-snapshot
Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti
inferredcites →https://doi.org/10.1590/s0103-90162011000200006openalex-snapshot
Decision trees for digital soil mapping on subtropical basaltic steeplands
inferredcites →https://doi.org/10.1590/s1678-3921.pab2019.v54.00420openalex-snapshot
Prediction of soil classes in a complex landscape in Southern Brazil
inferredcites →https://doi.org/10.18483/ijsci.1127openalex-snapshot
Scale Effects of Physical Modelling of Anaerobic Treatment Plants in the Treatment of Cassava Wastewater
inferredcites →https://doi.org/10.2136/sssaj2010.0002openalex-snapshot
Updating Conventional Soil Maps through Digital Soil Mapping
inferredcites →https://doi.org/10.2193/2005-723openalex-snapshot
Quantifying Landscape Ruggedness for Animal Habitat Analysis: A Case Study Using Bighorn Sheep in the Mojave Desert
inferredcites →https://doi.org/10.3390/rs11242905openalex-snapshot
Mapping at 30 m Resolution of Soil Attributes at Multiple Depths in Midwest Brazil
inferredcites →https://doi.org/10.3390/rs12060961openalex-snapshot
A Meta-Methodology for Improving Land Cover and Land Use Classification with SAR Imagery
inferredcites →https://doi.org/10.5039/agraria.v14i2a5653openalex-snapshot
Predição de classes de solos com dados coletados em pixels delimitados por buffers em perfis de solo georreferenciados
inferredcites →https://doi.org/10.5772/intechopen.86109openalex-snapshot
Application of Topographic Analyses for Mapping Spatial Patterns of Soil Properties

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.4678585openalex-extracted
Interpretation of Subsurface Stratigraphic Variations from Limited Boreholes Using Pixel Bi-Lstm
inferred← citeshttps://doi.org/10.1007/978-3-031-20667-2_28openalex-snapshot
Concluding Remarks and Outlook
inferred← citeshttps://doi.org/10.1016/b978-0-44-333376-7.00011-2openalex-snapshot
Geomorphometry 2.0: a brief guide
inferred← citeshttps://doi.org/10.1016/b978-0-44-333376-7.00044-6openalex-snapshot
Full list of references
inferred← citeshttps://doi.org/10.1016/j.compag.2023.108322openalex-snapshot
Improvement of data imbalance for digital soil class mapping in Eastern China
inferred← citeshttps://doi.org/10.1016/j.daach.2024.e00350openalex-snapshot
Predictive modeling in geoarchaeology: An evaluation of machine learning algorithms and topographic variables on the Serranópolis City - Brazil
inferred← citeshttps://doi.org/10.1016/j.geodrs.2025.e00922openalex-snapshot
Optimizing soil texture spatial prediction in the Brazilian Cerrado: Insights from random forest and spectral data
inferred← citeshttps://doi.org/10.1016/j.jag.2025.104384openalex-snapshot
Remote sensing image interpretation of geological lithology via a sensitive feature self-aggregation deep fusion network
inferred← citeshttps://doi.org/10.1016/j.mex.2023.102052openalex-snapshot
Multicriteria spatial model to prioritize degraded areas for landscape restoration through agroforestry
inferred← citeshttps://doi.org/10.1016/j.pedsph.2026.02.014openalex-snapshot
Soil class mapping with severely limited sample data: an explicit rule of soil-landscape relationships in complex terrain
inferred← citeshttps://doi.org/10.1071/sr25209openalex-snapshot
Digital soil mapping in the Eastern Amazon: algorithm performance and classification uncertainty in hydromorphic and well-drained landscapes
inferred← citeshttps://doi.org/10.14393/sn-v35-2023-66034openalex-snapshot
O papel de fatores naturais e antrópicos na variabilidade da perda de solos no estado de Goiás entre 1985 e 2018
inferred← citeshttps://doi.org/10.14393/sn-v35-2023-66034xopenalex-snapshot
The role of natural and anthropic factors in the variability of soil loss in the state of Goiás between 1985 and 2018
inferred← citeshttps://doi.org/10.18268/bsgm2025v77n3a121025openalex-snapshot
Exploring topographic variables in gully erosion susceptibility mapping in Central Brazil
inferred← citeshttps://doi.org/10.20502/rbgeomorfologia.v24i00.2368openalex-snapshot
Análise multiescalar aplicada à avaliação de erosão hídrica linear para área tropical subúmida situada na região Sudoeste do estado de Goiás - Brasil
inferred← citeshttps://doi.org/10.2139/ssrn.5049600openalex-snapshot
Soil Class Mapping with Severely Limited Sample Data: A Conceptual Model of Soil-Landscape Relationships in Complex Terrain
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.