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Land
Special Issues
Land Degradation and Soil Mapping
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Land Degradation and Soil Mapping

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land – Observation and Monitoring".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 2385

Special Issue Editors

Dr. Zahn Münch

E-Mail Website
Guest Editor
Department Geography and Environmental Studies, Stellenbosch University, Stellenbosch 7602, South Africa
Interests: land cover
Prof. Dr. Adriaan van Niekerk

E-Mail Website
Guest Editor
Centre for Geographical Analysis, Department of Geography & Environmental Studies, Stellenbosch University, Stellenbosch 7600, South Africa
Interests: agricultural applications of remotely sensed data (mostly multispectral and multitemporal imagery); e.g., crop type mapping and monitoring of salt accumulation; water use and crop conditions; land cover mapping; object-based image analysis (OBIA); machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Zama Eric Mashimbye

E-Mail Website
Guest Editor
Department of Geography & Environmental Studies, Stellenbosch University, Stellenbosch 7600, South Africa
Interests: remote sensing of agriculture digital soil mapping; soil degradation; object-based remote sensing; hyperspectral remote sensing; land cover & land use dynamics

Special Issue Information

Dear Colleagues,

We invite you to submit your papers for publication in this Special Issue of Land, “Land Degradation and Soil Mapping”. Land degradation is viewed as a major threat to ecosystem functions and services. Its adverse local effects, coupled with negative environmental and social impacts, pose significant challenges to communities at both the local and global levels. Predictive soil maps generated using geospatial techniques are considered as one of the most effective representations of specific features of soil conditions.

This Special Issue aims to publish high-quality scientific contributions regarding land degradation and soil mapping on a local, regional, or global scale. It will contain theoretical/methodological advances and operational and applied studies, covering many disciplinary fields. Research areas may include (but are not limited to) the following:

  • Land degradation neutrality: mapping, measuring, and monitoring;
  • Digital soil mapping;
  • Desertification control;
  • Land use optimization;
  • Sustainable soil management practices.

Dr. Zahn Münch
Prof. Dr. Adriaan van Niekerk
Dr. Zama Eric Mashimbye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land degradation
  • digital soil mapping
  • predictive mapping
  • land use management
  • soil management
  • sustainable agriculture
  • ecosystem restoration

Published Papers (2 papers)

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Research

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18 pages, 5583 KiB  
Article
Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network
by Xianglong Fan, Pan Gao, Li Zuo, Long Duan, Hao Cang, Mengli Zhang, Qiang Zhang, Ze Zhang, Xin Lv and Lifu Zhang
Land 2023, 12(10), 1897; https://doi.org/10.3390/land12101897 - 10 Oct 2023
Viewed by 822
Abstract
Accurate soil quality evaluation is an important prerequisite for improving soil management systems and remediating soil pollution. However, traditional soil quality evaluation methods are cumbersome to calculate, and suffer from low efficiency and low accuracy, which often lead to large deviations in the [...] Read more.
Accurate soil quality evaluation is an important prerequisite for improving soil management systems and remediating soil pollution. However, traditional soil quality evaluation methods are cumbersome to calculate, and suffer from low efficiency and low accuracy, which often lead to large deviations in the evaluation results. This study aims to provide a new and accurate soil quality evaluation method based on graph convolution network (GCN). In this study, soil organic matter (SOM), alkaline hydrolysable nitrogen (AN), available potassium (AK), salinity, and heavy metals (iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn)) were determined and evaluated using the soil quality index (SQI). Then, the graph convolution network (GCN) was first introduced in the soil quality evaluation to construct an evaluation model, and its evaluation results were compared with those of the SQI. Finally, the spatial distribution of the evaluation results of the GCN model was displayed. The results showed that soil salinity had the largest coefficient of variation (86%), followed by soil heavy metals (67%) and nutrients (30.3%). The soil salinization and heavy metal pollution were at a low level in this area, and the soil nutrients and soil quality were at a high level. The evaluation accuracy of the GCN model for soil salinity/heavy metals, soil nutrients, and soil quality were 0.91, 0.84, and 0.90, respectively. Therefore, the GCN model has a high accuracy and is feasible to be applied in the soil quality evaluation. This study provides a new, simple, and highly accurate method for soil quality evaluation. Full article
(This article belongs to the Special Issue Land Degradation and Soil Mapping)
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Review

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16 pages, 3710 KiB  
Review
Bibliometric Analysis of Land Degradation Studies in Drylands Using Remote Sensing Data: A 40-Year Review
by Diêgo P. Costa, Stefanie M. Herrmann, Rodrigo N. Vasconcelos, Soltan Galano Duverger, Washinton J. S. Franca Rocha, Elaine C. B. Cambuí, Jocimara S. B. Lobão, Ellen M. R. Santos, Jefferson Ferreira-Ferreira, Mariana Oliveira, Leonardo da Silva Barbosa, André T. Cunha Lima and Carlos A. D. Lentini
Land 2023, 12(9), 1721; https://doi.org/10.3390/land12091721 - 04 Sep 2023
Viewed by 1203
Abstract
Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. [...] Read more.
Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. We examined 1527 Scopus-indexed publications to identify geographic and thematic hotspots, extracting leading authors, journals, and institutions. China leads in publications, followed by the US, Germany, and Australia. The US has the highest citation count. Collaboration networks involve the US, China, and European countries. There has been an exponential increase in remote sensing of land degradation in drylands (RSLDD) publications since 2011. Key journals include “International Journal of Remote Sensing” and “Remote Sensing of Environment”. The analysis highlights the growing interest in the field, driven by Australia, the US, and China. Key areas of study are vegetation dynamics and land use change. Future perspectives for this scientific field involve promoting collaboration and exploring emerging technologies for comprehensive land degradation and desertification research. Full article
(This article belongs to the Special Issue Land Degradation and Soil Mapping)
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