Special Issue "Earth Observations for Sustainable Development Goals"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 April 2022.

Special Issue Editors

Dr. Joan Masó
E-Mail Website
Guest Editor
CREAF—Centre for Ecological Research and Forestry Applications, 08193 Barcelona, Spain
Interests: remote sensing; land cover; sustainable development; citizen science
Special Issues and Collections in MDPI journals
Dr. Ivette Serral
E-Mail Website
Guest Editor
Centre for Ecological Research and Forestry Applications, 08193 Barcelona, Spain
Interests: GIS; remote sensing; standars; environmental management
Special Issues and Collections in MDPI journals
Dr. Alaitz Zabala Torres
E-Mail Website
Guest Editor
Departament de Geografia, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
Interests: data; metadata; web semantics; remote sensing; signal processing
Special Issues and Collections in MDPI journals

Special Issue Information

Earth observation (EO) provides extensive data, from radar to optical sensors, and from satellite (RS) to airborne. Spatial coverage and revisiting the periods of observations are significantly increasing with new sensors and platforms, allowing for observing the same area from huge and diverse spatial, spectral, and temporal perspectives, with a large range of thematic applications. In turn, there are hundreds of multi-lateral environment agreements addressing societal and economic development. In 2015, the United Nations approved the Sustainable Development Goals (SDGs), which define a safe operating space for humanity through 17 goals articulated in 169 targets and 240 indicators to measure progress.

EO has been proven to be a valuable source for Earth monitoring. However, some studies suggest that the current indicator framework is biased to socioeconomic variables, and only a few of them can be inferred by EO only. It is clear that currently, the intersection between SDG and EO has some limitations. To what extent? The following Special Issue aims to shed some light on aspects, including but not limited to, the following:

  1. How can EO contribute to calculate SDG indicators?
  2. How can EO be used to increase granularity (spatial resolution) of UN statistics?
  3. How EO detects EVs useful to create indicators?
  4. How can EO be used to understand the natural mechanism that affect sustainability (e.g., ecosystem services)?
  5. How can EO be used to detect and characterize the extension of human activities (e.g., pollution, human settlements, etc)?
  6. How SDGs offer a useful framework to show gaps in current remote sensing constellations?
  7. Propose other indicators that could be better extracted from RS. 

Dr. Joan Masó
Dr. Ivette Serral
Dr. Alaitz Zabala Torres
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2400 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

  • Sustainability
  • Earth observation
  • Monitoring
  • Indications
  • Modelling
  • Pressures

Published Papers (2 papers)

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Research

Article
Improvement of a Dasymetric Method for Implementing Sustainable Development Goal 11 Indicators at an Intra-Urban Scale
Remote Sens. 2021, 13(14), 2835; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13142835 - 19 Jul 2021
Viewed by 488
Abstract
Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and [...] Read more.
Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and their sub-indicators. When provided at the intra-urban scale, these essential variables can facilitate the extraction of population flows, including both local and regular migrant components. This paper discusses a modification of the dasymetric method implemented in our previous work, aimed at improving the population density estimation. The novelties of our paper include the introduction of building height information and site-specific weight values for population density correction. Based on the proposed improvements, selected indicators/sub-indicators of four SDG 11 targets were updated or newly implemented. The output density map error values are provided in terms of the mean absolute error, root mean square error and mean absolute percentage indicators. The values obtained (i.e., 2.3 and 4.1 people, and 8.6%, respectively) were lower than those of the previous dasymetric method. The findings suggest that the new methodology can provide updated information about population fluxes and processes occurring over the period 2011–2020 in the study site—Bari city in southern Italy. Full article
(This article belongs to the Special Issue Earth Observations for Sustainable Development Goals)
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Article
Integrating Remote Sensing and a Markov-FLUS Model to Simulate Future Land Use Changes in Hokkaido, Japan
Remote Sens. 2021, 13(13), 2621; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13132621 - 03 Jul 2021
Viewed by 652
Abstract
As the second largest island in Japan, Hokkaido provides precious land resources for the Japanese people. Meanwhile, as the food base of Japan, the gradual decrease of the agricultural population and more intensive agricultural practices on Hokkaido have led its arable land use [...] Read more.
As the second largest island in Japan, Hokkaido provides precious land resources for the Japanese people. Meanwhile, as the food base of Japan, the gradual decrease of the agricultural population and more intensive agricultural practices on Hokkaido have led its arable land use to change year by year, which has also caused changes to the whole land use pattern of the entire island of Hokkaido. To realize the sustainable use of land resources in Hokkaido, past and future changes in land use patterns must be investigated, and target-based land use planning suggestions should be given on this basis. This study uses remote sensing and GIS technology to analyze the temporal and spatial changes of land use in Hokkaido during the past two decades. The types of land use include cultivated land, forest, waterbody, construction, grassland, and others, by using the satellite images of the Landsat images in 2000, 2010, and 2019 to achieve this goal to make classification. In addition, this study used the coupled Markov-FLUS model to simulate and analyze the land use changes in three different scenarios in Hokkaido in the next 20 years. Scenario-based situational analysis shows that the cultivated land in Hokkaido will drop by about 25% in 2040 under the natural development scenario (ND), while the cultivated land area in Hokkaido will remain basically unchanged in cultivated land protection scenario (CP). In forest protection scenario (FP), the area of forest in Hokkaido will increase by 1580.8 km2. It is believed that the findings reveal that the forest land in Hokkaido has been well protected in the past and will be protected well in the next 20 years. However, in land use planning for future, Hokkaido government and enterprises should pay more attention to the protection of cultivated land. Full article
(This article belongs to the Special Issue Earth Observations for Sustainable Development Goals)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Title: Modeling of physical accessibility to public green spaces in Switzerland

Author list: Camille Chênes, Gregory Giuliani, Nicolas Ray

Affiliation: Institute for Environmental Sciences (CC, GG, NR) & Institute of Global Health (NR), University of Geneva, Switzerland

Abstract: Since the 19th century, urbanization has grown exponentially, and the number of people living in cities has steadily increased. In Europe, 73% of the population is already located in urban areas. Urban sprawl has a strong impact on the provision and use of green spaces and, as a consequence, on the benefits that society can derive from these natural ecosystems, particularly in terms of public health.

Indicator 11.7.1 of the United Nations Sustainable Development Goal (SDG) seeks to assess the amount of surface dedicated to public space, and particularly to green spaces. Accordingly, this study aims to evaluate the accessibility of public green spaces for the Swiss population, using remote sensing and cadastral data.

The results showed that 26.7% of the Swiss population has access to a public park in less than 5 minutes for a travel scenario combining pedestrian and motorized travel. Similarly, 44.4% of the population has access to forests, using the same travel scenario and time threshold. Finally, 40% of the swiss urban population has access to a public park in less than 5 minutes by walk.

This study presents a simple and easily transposable methodology whose results offer not only indications in terms of land management, but also facilitate comparison with other countries, providing a standardized methodology at national scale to inform SDG 11.7.1.

2. Author list: Rabone M, Wiethase J, Clark PF, Ndongo, PAM, Lawton S, Cumberlidge N, Emery AM.

Title: Modelling schistosomiasis and paragonimiasis distribution and the Sustainable Development Goals, utilising satellite data to improve health outcomes

3. Title: EO Applications for contribution of the Sustainable Development Goals Indicators in Bulgaria

Author list: Adelina Aleksieva-Petrovaa, b, Irena Mladenovaa, c, Katya Dimitrovaa, Kamen Iliev a, Atanas Georgieva, Anna Dyankovaa

a Risk Space Transfer – Technology Transfer Office, Bulgarian Academy of Sciences (RST-TTO), 1113 Sofia, Bulgaria

b  Department of Computer Systems, Technical University of Sofia, 1000 Sofia, Bulgaria

c  Faculty of Economics and Business Administration, Sofia University "St. Kliment Ohridski", 1000 Sofia, Bulgaria 

Abstract: Earth Observation (EO) is one of the priority sectors for the development of the Bulgarian space sector, and is taking its respective role in the Bulgarian Space Strategy and in strengthening the cooperation of the country with the European Space Agency (ESA). EO applications provide important inputs to governments in planning, implementing and monitoring the progress of the 2030 Agenda for Sustainable Development. Along with other UN countries, Bulgaria has committed to all 17 Sustainable Development Goals (SDG) and reflected them in its strategic documents, and EO data could significantly help authorities in achieving and monitoring the progress to the targets. This paper analyzes EO applications contribution to the SDGs in Bulgaria. It starts with review of latest empirical and theoretical research in this area. The next section of the paper describes the research methods and selection criteria for SDG and applicable indicators. The EO-supported indicators are mapped to the targets set in the National Development Programme Bulgaria 2030. The third section of the paper provides empirical support to EO applications in Bulgaria. Additional measurement indicators of social, environmental, and economic benefit are identified based on work in the area of transfer of aero-space technologies, and especially EO. The paper discusses two specific pilot projects’ results in the field of EO. The first explores the creation of a national geo-spatial database (GSDB) for monitoring of natural disasters and accidents, and the second is a showcase for use of EO data for water quality monitoring. Based on the experience and investigations of the current status of measurement of the SDGs indicators, a further GSDB is being developed in the frame of the National Research Programme “Smart crop production”. This GSDB is based on the SDGs indicators and focused on EO-derived data for land use and land classification, and aims to support the Bulgarian agriculture sector modernization.

The article findings present how the above three projects’ results in EO thematic applications can be used along two objectives. First, demonstrate the applicability of EO data to measure the respective SDGs indicators in Bulgaria. And second, how EO can support the SDG indicators identified in the National Development Programme Bulgaria 2030. As examples three main case studies using EO in the area of water quality monitoring, disaster mapping and agriculture and discuss how these examples are contributed the SDG indicators in Bulgaria. The last section is a summary of the paper and future research directions.

Keywords: AI, EO, agriculture, Sustainable Development Goals indicators, National Research Program

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