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Land
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Monitoring Land Cover Change: Towards Sustainability
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Monitoring Land Cover Change: Towards Sustainability

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 64983

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, Collections and Topics 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, Collections and Topics in MDPI journals
Dr. Chariton Kalaitzidis

E-Mail Website
Guest Editor
Program in Geoinformation in Environmental Management, Mediterranean Agronomic Institute of Chania, Hania, Greece
Interests: remote sensing for monitoring of vegetation and agricultural crops, primarily through field spectroscopy, unmanned airborne systems and satellite images
Special Issues, Collections and Topics 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 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 2020.

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

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 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 Use
  • Land Cover
  • Change Drivers
  • Sustainability
  • Urban Remote Sensing
  • Climate Change
  • UN SDGs
  • Earth Observation
  • Social Science Research
  • Monitoring Impacts
  • Water-Energy-Food Nexus

Published Papers (14 papers)

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Editorial

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2 pages, 181 KiB  
Editorial
Monitoring Land Cover Change: Towards Sustainability
by Ioannis Manakos, Garik Gutman and Chariton Kalaitzidis
Land 2021, 10(12), 1356; https://0-doi-org.brum.beds.ac.uk/10.3390/land10121356 - 09 Dec 2021
Cited by 1 | Viewed by 1694
Abstract
In 2015, the United Nations member states adopted the 2030 Agenda, within which the 17 Sustainable Development Goals (SDGs) were established, with many of these goals calling for further research into sustainability [...] Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)

Research

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14 pages, 3653 KiB  
Article
The Effects of Terrain Factors and Cultural Landscapes on Plateau Forest Distribution in Yushu Tibetan Autonomous Prefecture, China
by Naixin Cui, Huiting Zou, Moshi Zhang and Luo Guo
Land 2021, 10(4), 345; https://0-doi-org.brum.beds.ac.uk/10.3390/land10040345 - 30 Mar 2021
Cited by 5 | Viewed by 2224
Abstract
The Yushu Tibetan Autonomous Prefecture is a typical Tibetan plateau area, and its ecological environment is very fragile. It is necessary to explore the terrain and cultural factors for the protection of the local ecological environment. We mainly investigated and quantified the effect [...] Read more.
The Yushu Tibetan Autonomous Prefecture is a typical Tibetan plateau area, and its ecological environment is very fragile. It is necessary to explore the terrain and cultural factors for the protection of the local ecological environment. We mainly investigated and quantified the effect of terrain factors and two typical plateau cultural landscapes (temples and villages) on the spatiotemporal variation characteristics of four types of forest landscape in the Yushu Tibetan Autonomous Prefecture from 1990 to 2015 using remote sensing (RS) and geographic information system (GIS) technology. The results showed that, under the influence of terrain factors, forest landscapes were only distributed in places with an altitude of 5055 meters above sea level (masl) to 6300 masl, with a slope of 0–27°, and the largest distribution area was shrubbery. The area of the forest decreased with the increase in altitude, and it first rose and then decreased with the increase in slope. Regression analysis results showed that the influence of altitude on closed forest land and open forest land followed a polynomial function, while that on shrubbery followed a logarithmic function, and the impact of slope on the three forest landscapes followed the amplitude version of a Gaussian peak function. Considering cultural factors, temples and villages did not determine the forest distribution in the same way as natural factors do, but they motivated the amount of forest over spatiotemporal scales. Temples had a greater influence on forest protection than villages, and this positive impact was stronger within 6 km. The area of forest distributed around the temple accounts for more than 45.67% of the total forest area, and this area has not changed significantly in 25 years. In summary, altitude and slope affect the natural distribution of the forest, and temples affect the scale of forest distribution. These results reveal the impact of terrain factors and cultural landscapes on forest distribution and could motivate an even more effective management for sustainable forest development. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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28 pages, 12889 KiB  
Article
Response of Land Use Change to the Grain for Green Program and Its Driving Forces in the Loess Hilly-Gully Region
by Xiao Zhang, Yuanjie Deng, Mengyang Hou and Shunbo Yao
Land 2021, 10(2), 194; https://0-doi-org.brum.beds.ac.uk/10.3390/land10020194 - 14 Feb 2021
Cited by 13 | Viewed by 1985
Abstract
Implementation of the Grain for Green program (GGP) intensifies land use/cover change (LUCC) in the loess hilly-gully region. Clarifying the response of LUCC to the GGP and its driving forces are basic premises to implement the GGP more effectively for alleviating soil erosion [...] Read more.
Implementation of the Grain for Green program (GGP) intensifies land use/cover change (LUCC) in the loess hilly-gully region. Clarifying the response of LUCC to the GGP and its driving forces are basic premises to implement the GGP more effectively for alleviating soil erosion in this region. This study analyzed the spatio-temporal characteristics of conversion of cultivated land to forest land and grassland in two study periods of 2000–2010 and 2010–2018. The transition matrix model and the dynamic degree model were utilized to explore changes among cultivated land, forest land, and grassland based on the remote sensing (RS) and monitoring data of land use in 2000, 2010, and 2018. Secondly, further detection on driving forces of increase of forest land and grassland was conducted through the logistic regression model. Fourteen driving factors were selected: the GGP, elevation, slope, population density, GDP per land area, distance to city, distance to residential area, etc. The results revealed that: (1) Area of cultivated land was mainly transferred to forest land and grassland during two study periods. The conversion of cultivated land to forest land and grassland occupied 21.48% and 68.01% of outward-transferring area of cultivated land from 2000 to 2010, and accounted for 13.26% and 74.3% from 2010 to 2018; (2) From the results of the logistic regression model, elevation, the GGP, annual mean temperature, slope III (6–15°), and GDP per land area were the main driving forces from 2000 to 2010. Moreover, the most prominent driving forces were the GGP, elevation, rural population density, slope III (6–15°), and soil pH from 2010 to 2018. The findings of this study can help us better understand the conversion of cultivated land to forest land and grassland under the GGP and provide a scientific basis to facilitate sustainable development of land resources in the study area. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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15 pages, 7130 KiB  
Article
Three Decades of Land Cover Change in East Africa
by Eric L. Bullock, Sean P. Healey, Zhiqiang Yang, Phoebe Oduor, Noel Gorelick, Steve Omondi, Edward Ouko and Warren B. Cohen
Land 2021, 10(2), 150; https://0-doi-org.brum.beds.ac.uk/10.3390/land10020150 - 03 Feb 2021
Cited by 35 | Viewed by 4724
Abstract
Population growth rates in Sub-Saharan East Africa are among the highest in the world, creating increasing pressure for land cover conversion. To date, however, there has been no comprehensive assessment of regional land cover change, and most long-term trends have not yet been [...] Read more.
Population growth rates in Sub-Saharan East Africa are among the highest in the world, creating increasing pressure for land cover conversion. To date, however, there has been no comprehensive assessment of regional land cover change, and most long-term trends have not yet been quantified. Using a designed sample of satellite-based observations of historical land cover change, we estimate the areas and trends in nine land cover classes from 1998 to 2017 in Ethiopia, Kenya, Uganda, Malawi, Rwanda, Tanzania, and Zambia. Our analysis found an 18,154,000 (±1,580,000) ha, or 34.8%, increase in the area of cropland in East Africa. Conversion occurred primarily from Open Grasslands, Wooded Grasslands, and Open Forests, causing a large-scale reduction in woody vegetation classes. We observed far more conversion (by approximately 20 million hectares) of woody classes to less-woody classes than succession in the direction of increasing trees and shrubs. Spatial patterns within our sample highlight regional land cover conversion hotspots, such as the Central Zambezian Miombo Woodlands, as potential areas of concern related to the conservation of natural ecosystems. Our findings reflect a rapidly growing population that is moving into new areas, with a 43.5% increase in the area of Settlements over the three-decade period. Our results show the areas and ecoregions most impacted by three decades of human development, both spatially and statistically. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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23 pages, 11166 KiB  
Article
Evaluating the Potentiality of Sentinel-2 for Change Detection Analysis Associated to LULUCF in Wallonia, Belgium
by Odile Close, Sophie Petit, Benjamin Beaumont and Eric Hallot
Land 2021, 10(1), 55; https://0-doi-org.brum.beds.ac.uk/10.3390/land10010055 - 09 Jan 2021
Cited by 10 | Viewed by 3265
Abstract
Land Use/Cover changes are crucial for the use of sustainable resources and the delivery of ecosystem services. They play an important contribution in the climate change mitigation due to their ability to emit and remove greenhouse gas from the atmosphere. These emissions/removals are [...] Read more.
Land Use/Cover changes are crucial for the use of sustainable resources and the delivery of ecosystem services. They play an important contribution in the climate change mitigation due to their ability to emit and remove greenhouse gas from the atmosphere. These emissions/removals are subject to an inventory which must be reported annually under the United Nations Framework Convention on Climate Change. This study investigates the use of Sentinel-2 data for analysing lands conversion associated to Land Use, Land Use Change and Forestry sector in the Wallonia region (southern Belgium). This region is characterized by one of the lowest conversion rates across European countries, which constitutes a particular challenge in identifying land changes. The proposed research tests the most commonly used change detection techniques on a bi-temporal and multi-temporal set of mosaics of Sentinel-2 data from the years 2016 and 2018. Our results reveal that land conversion is a very rare phenomenon in Wallonia. All the change detection techniques tested have been found to substantially overestimate the changes. In spite of this moderate results our study has demonstrated the potential of Sentinel-2 regarding land conversion. However, in this specific context of very low magnitude of land conversion in Wallonia, change detection techniques appear to be not sufficient to exceed the signal to noise ratio. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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21 pages, 5401 KiB  
Article
Tracking Urban Expansion Using Random Forests for the Classification of Landsat Imagery (1986–2015) and Predicting Urban/Built-Up Areas for 2025: A Study of the Kumasi Metropolis, Ghana
by Bernard Fosu Frimpong and Frank Molkenthin
Land 2021, 10(1), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/land10010044 - 05 Jan 2021
Cited by 9 | Viewed by 4871
Abstract
Kumasi is a nodal city and functions as the administrative and economic capital of the Ashanti region in Ghana. Rapid urbanization has been experienced inducing the transformation of various Land Use Land Cover (LULC) types into urban/built-up areas in Kumasi. This paper aims [...] Read more.
Kumasi is a nodal city and functions as the administrative and economic capital of the Ashanti region in Ghana. Rapid urbanization has been experienced inducing the transformation of various Land Use Land Cover (LULC) types into urban/built-up areas in Kumasi. This paper aims at tracking spatio-temporal LULC changes utilizing Landsat imagery from 1986, 2013 and 2015 of Kumasi. The unique contribution of this research is its focus on urban expansion analysis and the utilization of Random Forest (RF) Classifier for satellite image classification. Change detection, urban land modelling and urban expansion in the sub-metropolitan zones, buffers, density decay curve and correlation analysis were methodologies adopted for our study. The classifier yielded better accuracy compared to earlier works in Ghana. The evaluation of LULC changes indicated that urban/built-up areas are continually increasing at the expense of agricultural and forestlands. The urban/built-up areas occupied 4622.49 hectares (ha) (23.78%), 13,447.50 ha (69.18%) and 14,004.60 ha (72.05%) in 1986, 2013 and 2015, respectively of the 19,438 ha area of Kumasi. Projection indicated that urban/built-up areas will occupy 15,490 ha (79.70%) in 2025. The urban expansion was statistically significant. The results revealed the importance of spatial modeling for environmental management and city planning. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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18 pages, 3928 KiB  
Communication
Exploring Forest Change Spatial Patterns in Papua New Guinea: A Pilot Study in the Bumbu River Basin
by Willie Doaemo, Midhun Mohan, Esmaeel Adrah, Shruthi Srinivasan and Ana Paula Dalla Corte
Land 2020, 9(9), 282; https://0-doi-org.brum.beds.ac.uk/10.3390/land9090282 - 20 Aug 2020
Cited by 10 | Viewed by 4545
Abstract
Papua New Guinea is a country in Oceania that hosts unique rain forests and forest ecosystems which are crucial for sequestering atmospheric carbon, conserving biodiversity, supporting the livelihood of indigenous people, and underpinning the timber market of the country. As a result of [...] Read more.
Papua New Guinea is a country in Oceania that hosts unique rain forests and forest ecosystems which are crucial for sequestering atmospheric carbon, conserving biodiversity, supporting the livelihood of indigenous people, and underpinning the timber market of the country. As a result of urban sprawl, agricultural expansion, and illegal logging, there has been a tremendous increase in land-use land cover (LULC) change happening in the country in the past few decades and this has triggered massive deforestation and forest degradation. However, only a few studies have ventured into quantifying the long-term trends and their associated spatial patterns—and have often presented contrasting responses. Herein, we intended to assess the extent of deforestation and the rate of urbanization that happened in the past 33 years (1987–2020) in the Bumbu river basin in Papua New Guinea using satellite imagery—for the years 1987, 2002, 2010, and 2020—and Geographic Information System (GIS) tools. On performing image classification, land use maps were developed and later compared with Google Earth’s high-resolution satellite images for accuracy assessment purposes. For probing into the spatial aspects of the land-use change issues, the study area was divided into four urban zones and four forest zones according to the four main cardinal directions centered in the urban and forest area centers of the 1987 image; subsequently, the rate of urban area expansion in each urban zone was separately calculated. From our preliminary analysis and literature survey, we observed several hurdles regarding the classification of regenerative forests and mixed pixels and gaps in LULC studies that have happened in Papua New Guinea to date. Through this communication paper, we aim to disseminate our preliminary results, which highlight a rapid increase in urban extent from 14.39 km2 in 1987 to 23.06 km2 in 2020 accompanied by a considerable decrease in forest extent from 76.29 km2 in 1987 to 59.43 km2 in 2020; this observation favors the presumption that urban and agricultural land expansion is happening at the cost of forest cover. Moreover, strategies for addressing technical issues and for integrating land-use change with various socioeconomic and environmental variables are presented soliciting feedback. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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26 pages, 13675 KiB  
Article
30 Years of Land Cover Change in Connecticut, USA: A Case Study of Long-Term Research, Dissemination of Results, and Their Use in Land Use Planning and Natural Resource Conservation
by Chester Arnold, Emily Wilson, James Hurd and Daniel Civco
Land 2020, 9(8), 255; https://0-doi-org.brum.beds.ac.uk/10.3390/land9080255 - 31 Jul 2020
Cited by 23 | Viewed by 5420
Abstract
Remotely sensed land cover data can be a tremendous resource to land use decision makers, yet there is often a disconnect between the worlds of remote sensing and local government. The Connecticut’s Changing Landscape project is focused on bridging this gap. The project [...] Read more.
Remotely sensed land cover data can be a tremendous resource to land use decision makers, yet there is often a disconnect between the worlds of remote sensing and local government. The Connecticut’s Changing Landscape project is focused on bridging this gap. The project analyzes changes to the state’s landscape using Landsat-derived 30-m land cover and cross-correlation analysis. It includes seven dates spanning 30 years, from 1985 to 2015. During this period an additional 4.7 percent of the state was converted to development-related land covers, with corresponding losses to forest and agricultural land. New development was for the most part in attenuated patterns rather than concentrated near existing developed areas. Additional land cover analyses were conducted of agricultural areas, riparian corridors, core forest, and watershed imperviousness, to more closely examine issues of sustainability. Particular care is taken to make research findings accessible, understandable, and usable for the public through traditional outreach methods, and increasingly through internet mapping technology. As a result, the project has become a widely used resource informing the work of state, regional and local governments, nonprofit organizations, and researchers. A more concerted effort to integrate research and outreach is needed to ensure that land cover research has an impact on issues of land use and sustainability. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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20 pages, 7718 KiB  
Article
Analysis of Land-Use Change between 2012–2018 in Europe in Terms of Sustainable Development
by Piotr Gibas and Agnieszka Majorek
Land 2020, 9(2), 46; https://0-doi-org.brum.beds.ac.uk/10.3390/land9020046 - 08 Feb 2020
Cited by 20 | Viewed by 4015
Abstract
This article presents methodology of land use change assessment in the context of sustainable development and the results of its application based on the transformations that occurred in individual areas of Europe in the years 2012–2018. This method is based on data from [...] Read more.
This article presents methodology of land use change assessment in the context of sustainable development and the results of its application based on the transformations that occurred in individual areas of Europe in the years 2012–2018. This method is based on data from the CORINE (CO-oRdination of INformation on Environment) Land Cover program) and local government units presenting the degree of urbanization (DEGURBA). The transformations taking place in space were evaluated and reduced to economic, social, and environmental dimensions. We then analyzed the results in terms of space (covering almost all of Europe) and in terms of division (large cities, small towns, suburbs, and rural areas). Results indicate that development of the economic dimension most often takes place at the expense of natural resources. It was also determined that the higher the population density, the greater the sustainable development differentiation level in the analyzed dimensions, of which the social dimension was characterized by the lowest differentiation and the economic dimension was highest. The development of rural areas was found to be less sustainable than large urban centers. Interpretation of the results also leads to the conclusion that areas of Europe are very diverse in terms of sustainable development. However, the method itself, despite the imperfections observed by the authors, may be used in further or similar studies. Full article
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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11 pages, 1493 KiB  
Article
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota
by Lan H. Nguyen, Deepak R. Joshi and Geoffrey M. Henebry
Land 2019, 8(4), 57; https://0-doi-org.brum.beds.ac.uk/10.3390/land8040057 - 03 Apr 2019
Cited by 11 | Viewed by 3465
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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14 pages, 4572 KiB  
Article
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss
by Jennifer Hewson, Stefano C. Crema, Mariano González-Roglich, Karyn Tabor and Celia A. Harvey
Land 2019, 8(1), 14; https://0-doi-org.brum.beds.ac.uk/10.3390/land8010014 - 10 Jan 2019
Cited by 19 | Viewed by 8258
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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16 pages, 7102 KiB  
Article
Use of Sentinel-2 and LUCAS Database for the Inventory of Land Use, Land Use Change, and Forestry in Wallonia, Belgium
by Odile Close, Beaumont Benjamin, Sophie Petit, Xavier Fripiat and Eric Hallot
Land 2018, 7(4), 154; https://0-doi-org.brum.beds.ac.uk/10.3390/land7040154 - 08 Dec 2018
Cited by 22 | Viewed by 5596
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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17 pages, 3410 KiB  
Article
Combined Use of Optical and Synthetic Aperture Radar Data for REDD+ Applications in Malawi
by Manuela Hirschmugl, Carina Sobe, Janik Deutscher and Mathias Schardt
Land 2018, 7(4), 116; https://0-doi-org.brum.beds.ac.uk/10.3390/land7040116 - 10 Oct 2018
Cited by 22 | Viewed by 4738
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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Other

Jump to: Editorial, Research

13 pages, 4102 KiB  
Project Report
Detection of Urban Development in Uyo (Nigeria) Using Remote Sensing
by Etido Essien and Samimi Cyrus
Land 2019, 8(6), 102; https://0-doi-org.brum.beds.ac.uk/10.3390/land8060102 - 25 Jun 2019
Cited by 18 | Viewed by 8037
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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