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Land
Special Issues
Land Degradation and Land Productivity Assessment Using Remote Sensing
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Land Degradation and Land Productivity Assessment Using Remote Sensing

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

Deadline for manuscript submissions: 21 June 2024 | Viewed by 2965

Special Issue Editors

Dr. Franklin Javier Paredes Trejo

E-Mail Website
Guest Editor
Department of Civil Engineering, University of the Western Plains Ezequiel Zamora, San Carlos 2201, Venezuela
Interests: large-scale droughts; remote sensing; climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Barlin Orlando Olivares

E-Mail Website
Guest Editor
Program in Agronomy Food Forestry and Rural Development Engineering, University of Cordoba, 14014 Córdoba, Spain
Interests: smart-integrated disease management; sustainable land management; machine learning; agrometeorology; drought; soil quality; plant pathology
Special Issues, Collections and Topics in MDPI journals
Dr. Humberto Barbosa

E-Mail Website
Guest Editor
Satellite Image Analysis and Processing Laboratory, Institute of Atmospheric Sciences, Federal University of Alagoas, Maceio 57010, Brazil
Interests: soil degradation monitoring; satellite-based vegetation indices; remote sensing; climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Deyanira Lobo

E-Mail Website
Guest Editor
Institute of Soil Science, Central University of Venezuela, Maracay 2103, Venezuela
Interests: soil and water conservation; land degradation; sustainable soil management practices; land evaluation

Special Issue Information

Dear Colleagues,

Land degradation is the decline of the quality and productivity of land; which can occur for various reasons; including intensive use; land use/cover change; agricultural expansion; deforestation; grazing intensification; and drought. Land degradation can have serious consequences; including reduced crop yield; increased vulnerability to natural disasters; loss of important functions; and decreased ability to support biodiversity.

Remote sensing is a powerful tool that can be used to assess land degradation and land productivity. Remote sensing involves the use of satellite or aerial imagery to gather information about the Earth’s surface from a distance. This information can be used to create detailed maps and to monitor changes in land cover and land use over time.

Many techniques can be used in remote sensing for land degradation and productivity assessment; such as multispectral analysis and vegetation indices (e.g.; NDVI). These techniques can be used to identify changes in land cover; soil erosion; and other drivers of land productivity degradation.

Overall; remote sensing is an important tool for monitoring and contributing to the mitigation of land degradation; as it allows for the identification of problem areas and the implementation of appropriate management strategies.

For this Special Issue; we invite papers related to; but not limited to; the following topics:

  • Development of high-resolution satellite imagery and machine learning algorithms for the improved detection and mapping of soil degradation;
  • Use of unmanned aerial vehicles (UAVs) for rapid and cost-effective soil degradation assessment;
  • Integration of multispectral; radar; and thermal data from satellite sensors for more comprehensive soil degradation monitoring;
  • Evaluation of the effectiveness of different vegetation indices and soil moisture algorithms in detecting soil degradation;
  • Assessment of the impacts of climate change on soil degradation and the potential for remote sensing to aid in adaptation efforts;
  • Examination of the use of remote sensing data in conjunction with ground-based measurements for more accurate soil degradation assessment;
  • Development of real-time monitoring systems for early warning of soil degradation events;
  • Investigation of the potential for remote sensing to aid in the assessment and rehabilitation of degraded soils;
  • Comparison of different remote sensing platforms and sensors for soil degradation monitoring;
  • Integration of remote sensing data with other sources of information; such as meteorological data and socio-economic data; for a more comprehensive understanding of soil degradation processes.

Dr. Franklin Javier Paredes Trejo
Dr. Barlin Orlando Olivares
Dr. Humberto Barbosa
Dr. Deyanira Lobo
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
  • desertification
  • drought
  • soil erosion
  • land use/cover change
  • machine learning
  • unmanned aerial vehicles (UAVs)
  • vegetation indices

Published Papers (2 papers)

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Research

13 pages, 2368 KiB  
Article
Spatial and Temporal Distribution of the Ecosystem Provisioning Service and Its Correlation with Food Production in the Songhua River Basin, Northeastern China
by Yuhan Zhao, Hui Yang, Chunyu Zhu and Jiansheng Cao
Land 2024, 13(4), 451; https://doi.org/10.3390/land13040451 - 02 Apr 2024
Viewed by 510
Abstract
Provisioning services are essential components of ecosystem services. Food production is usually a driver of land use change, which has the effect on altering the provisioning services of ecosystems. As one of the main areas of food production in China, the provisioning services [...] Read more.
Provisioning services are essential components of ecosystem services. Food production is usually a driver of land use change, which has the effect on altering the provisioning services of ecosystems. As one of the main areas of food production in China, the provisioning services of the Songhua River Basin (SHRB) should be taken seriously. In view of this, it is urgent to carry out a study on the assessment of provisioning services in the SHRB to provide data support and scientific reference for the optimization of the spatial pattern of land use in the basin, the sustainable development of agriculture, and the formulation of differentiated protection policies. In this study, based on the equivalent factor method for the unit area value and spatial autocorrelation with the Moran’s I, we assessed the provisioning services values (PSV) of the SHRB every ten years during the period of 2000–2020 under different land use types and analyzed the relationships between different PSV and the production of four different food types, including rice, wheat, corn, and soja. The main conclusions are as follows: (1) From 2000 to 2020, the area of paddy fields in the SHRB increased and then decreased, while the area of dry lands continued to increase. The land use transfer matrix showed a significant expansion of paddy fields (+0.55 × 104 km2), shrinkage of grassland (−0.72 × 104 km2), and loss of water body (−0.43 × 104 km2) in the SHRB from 2000 to 2020; (2) The PSV in the SHRB showed an increasing trend from 2000 to 2020, growing by 16.73 × 1010 RMB, with the growth in 2010–2020 being greater than in 2000–2010. The order of increase in each type of PSV was: water supply > food supply > raw material supply; (3) Spatially, the increase in PSV per unit and total PSV in the SHRB was lesser in the center and greater in the east and west. Meanwhile, the spatial distribution of various PSV showed that the value of unit area food supply was higher in the central and eastern plains, while the raw material supply and water supply were higher in the western and eastern hilly areas. (4) In terms of spatial correlation, the distribution of soja production with the total PSV, food supply, raw materials supply, and water supply services values were positively spatially correlated. However, the production of rice, wheat, and corn with the total PSV, food supply, and raw materials supply services values were negatively spatially correlated. Cluster analysis revealed that changing the crop cultivation structure could protect the ecosystem and increase the value of ecosystem services. Full article
(This article belongs to the Special Issue Land Degradation and Land Productivity Assessment Using Remote Sensing)
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19 pages, 6079 KiB  
Article
Impact of Drought on Land Productivity and Degradation in the Brazilian Semiarid Region
by Franklin Paredes-Trejo, Humberto Alves Barbosa, Gabriel Antunes Daldegan, Ingrid Teich, César Luis García, T. V. Lakshmi Kumar and Catarina de Oliveira Buriti
Land 2023, 12(5), 954; https://doi.org/10.3390/land12050954 - 25 Apr 2023
Cited by 6 | Viewed by 1734
Abstract
The Brazilian semiarid region (BSR) has faced severe drought over the last three decades, which has led to a significant decline in land productivity, posing a considerable threat to food security and the local economy and communities. The United Nations Convention to Combat [...] Read more.
The Brazilian semiarid region (BSR) has faced severe drought over the last three decades, which has led to a significant decline in land productivity, posing a considerable threat to food security and the local economy and communities. The United Nations Convention to Combat Desertification (UNCCD) has proposed the use of Earth observation-derived vegetation indices for monitoring land degradation across regions. In this study, we aim to evaluate three comprehensive UNCCD-recommended land productivity dynamic (LPD) approaches in the BSR by utilizing the standardized precipitation–evapotranspiration index (SPEI) at 12-month time scales as a benchmark drought index obtained from ground-based measurements. Our findings indicate that the LPD methods utilizing residual trends analysis (RESTREND), Trends.Earth (TE), and the Food and Agricultural Organization’s World Overview of Conservation Approaches and Technologies (FAO-WOCAT) are best suited for identifying degraded land areas in the BSR region compared to other approaches. However, it is advisable to use these methods with caution, since they do not fully capture the impact of drought on vegetation and may result in underestimating the extent of degraded areas. The RESTREND-based LPD, TE, and FAO-WOCAT estimate that the BSR region reached 213,248 km2, 248,075 km2, and 246,783 km2 of degraded land, respectively, between 2001 and 2015. These findings may be valuable for decision-makers involved in land management and conservation efforts in the Sertão region of Brazil. Full article
(This article belongs to the Special Issue Land Degradation and Land Productivity Assessment Using Remote Sensing)
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