Special Issue "Monitoring Land Cover Change: Towards Sustainability"

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Dr. Ioannis Manakos
E-Mail Website
Guest Editor
Centre for Research and Technology Hellas, Information Technologies Institute, Hellas 6th km Harilaou-Thermi, 57001 Thessaloniki, Greece
Interests: earth observation; geoinformation technologies; big data; time series analysis; uncertainty handling; biodiversity monitoring; food security
Special Issues and Collections in MDPI journals
Dr. Garik Gutman
E-Mail Website
Guest Editor
NASA Headquarters, NASA Land-Cover/Land-Use Change Program, 300 E Street, SW Washington, DC 20546, USA
Interests: telecoupling of land use systems; Land-atmosphere processes; Land governance; Land change trade-offs for ecosystem services and biodiversity; Land management systems; Urban-rural interactions; Land use and conflict
Special Issues and Collections in MDPI journals
Dr. Chariton Kalaitzidis
E-Mail Website
Guest Editor
Program in Geoinformation in Environmental Management, Mediterranean Agronomic Institute of Chania
Interests: remote sensing for monitoring of vegetation and agricultural crops, primarily through field spectroscopy, unmanned airborne systems and satellite images
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The UN FAO (United Nations Food and Agriculture Organization), in its State of the World’s Land and Water Resources for Food and Agriculture (2014), confirmed that “land and water resources are central to agriculture and rural development, and are intrinsically linked to global challenges of food insecurity and poverty, climate change adaptation and mitigation, as well as degradation and depletion of natural resources that affect the livelihoods of millions of rural people across the world.” They also projected that food production will need to increase by 70 percent to feed the world’s growing population. Land and water resources are already under heavy stress from economic development, so that future agricultural production will need to be more efficient and sustainable. Land use is undergoing changes in many parts of the world and there is considerable interest in understanding the impacts of those changes and whether they are sustainable.

Earth observation data can now provide important information for research focusing on sustainability, better than ever. In particular, the increased availability of free and open data from multimodal sources of remote sensing systems is allowing the close monitoring of land-use change and develop relevant scenarios, in order to study the hydrological cycle, the carbon footprint of land utilization and the demand for food production. Remote sensing can provide information on the impacts of land-cover change on abiotic/biotic variables, associated with ecosystem functions and services, which are involved in the water-energy-food nexus.

This Special Issue emerged from contributions of the accepted abstracts at the 38th EARSeL Symposium and the 3rd joint EARSeL LULC & NASA LCLUC Workshop that took place, respectively, on 9–12 and 11–12 July, 2018, Chania, Greece. The topics linked to those events include:

  • New instruments and data processing methods
  • Geological, hydrological, land and ice applications
  • Climate and climate change
  • Agriculture and Forestry
  • Urban and Thermal remote sensing
  • Use of LIDAR and RADAR data for various applications
  • Applications employing UAVs and UASs
  • Synergy of remote sensing technologies for land-use change monitoring-
  • The role of earth observations within the Water–Energy–Food nexus
  • Social and behavioral aspects of land use supported by remote sensing observations
  • Advances and outlook in the processing and analysis of remotely sensed data

The Special Issue is now accepting relevant submissions, focused on any of the relevant topics and the scope of Land journal. Submissions will be accepted until the 31st of December 2019.

Dr. Ioannis Manakos
Dr. Garik Gutman
Dr. Chariton Kalaitzidis
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 papers will be 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 1000 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 Use
  • Land Cover
  • Change Drivers
  • Sustainability
  • Climate Change
  • UN SDGs
  • Earth Observation
  • Social Science Research
  • Monitoring Impacts
  • Water-Energy-Food Nexus

Published Papers (5 papers)

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Open AccessArticle
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota
Land 2019, 8(4), 57; https://doi.org/10.3390/land8040057 - 03 Apr 2019
Abstract
The growing demand for biofuel production increased agricultural activities in South Dakota, leading to the conversion of grassland to cropland. Although a few land change studies have been conducted in this area, they lacked spatial details and were based on the traditional bi-temporal [...] Read more.
The growing demand for biofuel production increased agricultural activities in South Dakota, leading to the conversion of grassland to cropland. Although a few land change studies have been conducted in this area, they lacked spatial details and were based on the traditional bi-temporal change detection that may return incorrect rates of conversion. This study aimed to provide a more complete view of land conversion in South Dakota using a trajectory-based analysis that considers the entire satellite-based land cover/land use time series to improve change detection. We estimated cropland expansion of 5447 km2 (equivalent to 14% of the existing cropland area) between 2007 and 2015, which matches much more closely the reports from the National Agriculture Statistics Service—NASS (5921 km2)—and the National Resources Inventory—NRI (5034 km2)—than an estimation from the bi-temporal approach (8018 km2). Cropland gains were mostly concentrated in 10 counties in northern and central South Dakota. Urbanizing Lincoln County, part of the Sioux Falls metropolitan area, is the only county with a net loss in cropland area over the study period. An evaluation of land suitability for crops using the Soil Survey Geographic Database (SSURGO) indicated a scarcity in high-quality arable land available for cropland expansion. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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Open AccessArticle
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss
Land 2019, 8(1), 14; https://doi.org/10.3390/land8010014 - 10 Jan 2019
Abstract
Despite global recognition of the social, economic and ecological impacts of deforestation, the world is losing forests at an alarming rate. Global and regional efforts by policymakers and donors to reduce deforestation need science-driven information on where forest loss is happening, and where [...] Read more.
Despite global recognition of the social, economic and ecological impacts of deforestation, the world is losing forests at an alarming rate. Global and regional efforts by policymakers and donors to reduce deforestation need science-driven information on where forest loss is happening, and where it may happen in the future. We used spatially-explicit globally-consistent variables and global historical tree cover and loss to analyze how global- and regional-scale variables contributed to historical tree cover loss and to model future risks of tree cover loss, based on a business-as-usual scenario. Our results show that (1) some biomes have higher risk of tree cover loss than others; (2) variables related to tree cover loss at the global scale differ from those at the regional scale; and (3) variables related to tree cover loss vary by continent. By mapping both tree cover loss risk and potential future tree cover loss, we aim to provide decision makers and donors with multiple outputs to improve targeting of forest conservation investments. By making the outputs readily accessible, we anticipate they will be used in other modeling analyses, conservation planning exercises, and prioritization activities aimed at conserving forests to meet national and global climate mitigation targets and biodiversity goals. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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Open AccessArticle
Use of Sentinel-2 and LUCAS Database for the Inventory of Land Use, Land Use Change, and Forestry in Wallonia, Belgium
Land 2018, 7(4), 154; https://doi.org/10.3390/land7040154 - 08 Dec 2018
Cited by 1
Abstract
Due to its cost-effectiveness and repeatability of observations, high resolution optical satellite remote sensing has become a major technology for land use and land cover mapping. However, inventory compilers for the Land Use, Land Use Change, and Forestry (LULUCF) sector are still mostly [...] Read more.
Due to its cost-effectiveness and repeatability of observations, high resolution optical satellite remote sensing has become a major technology for land use and land cover mapping. However, inventory compilers for the Land Use, Land Use Change, and Forestry (LULUCF) sector are still mostly relying on annual census and periodic surveys for such inventories. This study proposes a new approach based on per-pixel supervised classification using Sentinel-2 imagery from 2016 for mapping greenhouse gas emissions and removals associated with the LULUCF sector in Wallonia, Belgium. The Land Use/Cover Area frame statistical Survey (LUCAS) of 2015 was used as training data and reference data to validate the map produced. Then, we investigated the performance of four widely used classifiers (maximum likelihood, random forest, k-nearest neighbor, and minimum distance) on different training sample sizes. We also studied the use of the rich spectral information of Sentinel-2 data as well as single-date and multitemporal classification. Our study illustrates how open source data can be effectively used for land use and land cover classification. This classification, based on Sentinel-2 and LUCAS, offers new opportunities for LULUCF inventory of greenhouse gas on a European scale. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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Open AccessArticle
Combined Use of Optical and Synthetic Aperture Radar Data for REDD+ Applications in Malawi
Land 2018, 7(4), 116; https://doi.org/10.3390/land7040116 - 10 Oct 2018
Cited by 2
Abstract
Recent developments in satellite data availability allow tropical forest monitoring to expand in two ways: (1) dense time series foster the development of new methods for mapping and monitoring dry tropical forests and (2) the combination of optical data and synthetic aperture radar [...] Read more.
Recent developments in satellite data availability allow tropical forest monitoring to expand in two ways: (1) dense time series foster the development of new methods for mapping and monitoring dry tropical forests and (2) the combination of optical data and synthetic aperture radar (SAR) data reduces the problems resulting from frequent cloud cover and yields additional information. This paper covers both issues by analyzing the possibilities of using optical (Sentinel-2) and SAR (Sentinel-1) time series data for forest and land cover mapping for REDD+ (Reducing Emissions from Deforestation and Forest Degradation) applications in Malawi. The challenge is to combine these different data sources in order to make optimal use of their complementary information content. We compare the results of using different input data sets as well as of two methods for data combination. Results show that time-series of optical data lead to better results than mono-temporal optical data (+8% overall accuracy for forest mapping). Combination of optical and SAR data leads to further improvements: +5% in overall accuracy for land cover and +1.5% for forest mapping. With respect to the tested combination methods, the data-based combination performs slightly better (+1% overall accuracy) than the result-based Bayesian combination. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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Open AccessProject Report
Detection of Urban Development in Uyo (Nigeria) Using Remote Sensing
Land 2019, 8(6), 102; https://doi.org/10.3390/land8060102 - 25 Jun 2019
Abstract
Uyo is one of the fastest-growing cities in Nigeria. In recent years, there has been a widespread change in land use, yet to date, there is no thorough mapping of vegetation change across the area. This study focuses on land use change, urban [...] Read more.
Uyo is one of the fastest-growing cities in Nigeria. In recent years, there has been a widespread change in land use, yet to date, there is no thorough mapping of vegetation change across the area. This study focuses on land use change, urban development, and the driving forces behind natural vegetation loss in Uyo. Based on time series Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) image data, the relationships between urban land development and its influencing factors from 1985 to 2018 were analyzed using remote sensing (RS) and time series data. The results show eight land use cover classes. Three of these (forest, swamp vegetation, and mixed vegetation) are related to natural vegetation, and three (sparse built-up, dense built-up, and borrow pit) are direct consequences of urban infrastructure development changes to the landscape. Swamp vegetation, mixed vegetation, and forest are the most affected land use classes. Thus, the rapid growth of infrastructure and industrial centers and the rural and urban mobility of labor have resulted in an increased growth of built-up land. Additionally, the growth pattern of built-up land in Uyo corresponds with socioeconomic interviews conducted in the area. Land use changes in Uyo could be attributed to changes in economic structure, urbanization through infrastructure development, and population growth. Normalized difference vegetation index (NDVI) analysis shows a trend of decreasing vegetation in Uyo, which suggests that changes in economic structure represent a key driver of vegetation loss. Furthermore, the implementation of scientific and national policies by government agencies directed at reducing the effects of urbanization growth should be strengthened, in order to calm the disagreement between urban developers and environmental managers and promote sustainable land use. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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