Special Issue "Space for Sustainability: Using Data from Earth Observation to Support Sustainable Development Indicators"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 1 October 2021.

Special Issue Editors

Prof. Dr. Stephen Morse
E-Mail Website
Guest Editor
Chair in Systems Analysis for Sustainability Centre for Environmental Strategy, University of Surrey, Guildford Surrey GU2 7XH, UK
Interests: sustainability assessment; sustainability indicators; natural resource management; earth observation; participatory techniques
Special Issues and Collections in MDPI journals
Prof. Dr. Richard Murphy
E-Mail Website
Co-Guest Editor
Centre for Environment and Sustainability, University of Surrey, Guildford GU2 7XH, UK
Interests: bioenergy and biomaterials; life cycle assessment
Special Issues and Collections in MDPI journals
Ms. Ana Andries
E-Mail Website
Co-Guest Editor
Centre for Environment and Sustainability (CES), University of Surrey, Guildford, Surrey GU2 7XH, UK
Interests: Earth Observation; Satellite Systems; Geographical Information Systems; Indicators

Special Issue Information

Dear Colleagues,

Global progress towards living sustainably is now urgent. Actions for sustainability are typically informed through the use of indicator-based frameworks encompassing diverse attributes of the environmental, social and economic dimensions of ‘sustainability’. Reporting on such indicators is embedded in frameworks such as the United Nations Sustainable Development Goals (SDGs) with  the primary responsibilities for reporting carried by national and local governments. Additionally, many businesses and public bodies (e.g. universities, health services) are increasingly under internal and external pressure to similarly report via these sustainability indicators, especially as part of the SDGs, and such reporting is of increasing interest to investors and the financial services sectors from a risk and assurance perspective. However, the use of these indicator-based frameworks face many challenges. One of the most significant of these  is the challenge of acquiring  sufficient, timely and good quality data to populate these indicators via ‘conventional’ methods (e.g. surveys at the local, national or corporate level) as this is often expensive and time consuming. Many developing regions, in particular, suffer from a lack of resources or established systems for such data collection and, indeed, it is also proving to be challenging for more developed economies.

One approach to address this issue of data provision for indicators of  Sustainable Development (SD) is the use of Earth Observation (EO). EO-based data, geospatial information and ‘big data’ can support the population of sustainability indicators at all scales, and the integration of these sources is a step forward in advancing the well-being of our societies. While EO derived data have been used for many years to assess important issues such as deforestation and changes in land use, their use to address more socio-economic issues (e.g. inequality, poverty, corruption, health care) within SD remains limited. Nonetheless, EO tools and technologies are developing rapidly with an expanding range of capabilities, resolutions, frequency, data power, accuracy etc., and this is anticipated to continue into the foreseeable future.

This Special Issue in the journal Sustainability aims to present the current ‘state of play’ with regard to the use of EO data for SD indicators, and given the rapid progress in the field it provides a timely and welcome milestone in the journey. The editors welcome contributions that explore progress to date and how this informs potential for future use of EO derived data for many aspects of SD and that provide cutting-edge examples of where EO can provide insights, particularly for a number of the socio-economic dimensions of SD that have proved to be challenging to assess. This could include, but is not limited to, the following applications:

  • Applications of EO in tracking the state of socio-economic issues at sub-national, national and regional levels;
  • Integration of EO with survey data;
  • Filling traditional data gaps using EO data;
  • Assessing inequalities, poverty, food insecurity, water scarcity using EO data

Papers submitted should include an uncertainty assessment of the approach and ideally a cost-effectiveness analysis that might highlight the usefulness of using EO data.

We very much look forward to your submissions.

Prof. Dr. Stephen Morse
Prof. Dr. Richard Murphy
Ms. Ana Andries
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. Sustainability 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 1900 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

  • Earth Observation
  • Sustainable Development
  • Indicators
  • Data Management and Use
  • Socio-Economic
  • Big Data

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Earth Observation for Monitoring, Reporting, and Verification within Environmental Land Management Policy
Sustainability 2021, 13(16), 9105; https://doi.org/10.3390/su13169105 - 14 Aug 2021
Viewed by 268
Abstract
The main aim of the new agricultural scheme, Environmental Land Management, in England is to reward landowners based on their provision of ‘public goods’ while achieving the goals of the 25 Year Environment Plan and commitment to net zero emission by 2050. Earth [...] Read more.
The main aim of the new agricultural scheme, Environmental Land Management, in England is to reward landowners based on their provision of ‘public goods’ while achieving the goals of the 25 Year Environment Plan and commitment to net zero emission by 2050. Earth Observation (EO) satellites appear to offer an unprecedented opportunity in the process of monitoring, reporting, and verification (MRV) of this scheme. In this study, we worked with ecologists to determine the habitat–species relationships for five wildlife species in the Surrey Hills ‘Area of Outstanding Natural Beauty’ (AONB), and this information was used to examine the extent to which EO satellite imagery, particularly very high resolution (VHR) imagery, could be used for habitat assessment, via visual interpretation and automated methods. We show that EO satellite products at 10 m resolution and other geospatial datasets enabled the identification and location of broadly suitable habitat for these species and the use of VHR imagery (at 1–4 m spatial resolution) allowed valuable insights for remote assessment of habitat qualities and quantity. Hence, at a fine scale, we obtained additional habitats such as scrub, hedges, field margins, woodland and tree characteristics, and agricultural practices that offer an effective source of information for sustainable land management. The opportunities and limitations of this study are discussed, and we conclude that there is considerable scope for it to offer valuable information for land management decision-making and as support and evidence for MRV for incentive schemes. Full article
Show Figures

Figure 1

Article
Implications for Tracking SDG Indicator Metrics with Gridded Population Data
Sustainability 2021, 13(13), 7329; https://doi.org/10.3390/su13137329 - 30 Jun 2021
Viewed by 1050
Abstract
Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial scales needed to monitor SDG progress. While the increasing abundance [...] Read more.
Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial scales needed to monitor SDG progress. While the increasing abundance of Earth observation-derived gridded population products provides analysis-ready population estimates, end users lack clear use criteria to track SDGs indicators. In fact, recent comparisons of gridded population products identify wide variation across gridded population products. Here we present three case studies to illuminate how gridded population datasets compare in measuring and monitoring SDGs to advance the “fitness for use” guidance. Our focus is on SDG 11.5, which aims to reduce the number of people impacted by disasters. We use five gridded population datasets to measure and map hazard exposure for three case studies: the 2015 earthquake in Nepal; Cyclone Idai in Mozambique, Malawi, and Zimbabwe (MMZ) in 2019; and flash flood susceptibility in Ecuador. First, we map and quantify geographic patterns of agreement/disagreement across gridded population products for Nepal, MMZ, and Ecuador, including delineating urban and rural populations estimates. Second, we quantify the populations exposed to each hazard. Across hazards and geographic contexts, there were marked differences in population estimates across the gridded population datasets. As such, it is key that researchers, practitioners, and end users utilize multiple gridded population datasets—an ensemble approach—to capture uncertainty and/or provide range estimates when using gridded population products to track SDG indicators. To this end, we made available code and globally comprehensive datasets that allows for the intercomparison of gridded population products. Full article
Show Figures

Figure 1

Article
Challenges in Using Earth Observation (EO) Data to Support Environmental Management in Brazil
Sustainability 2020, 12(24), 10411; https://doi.org/10.3390/su122410411 - 12 Dec 2020
Cited by 1 | Viewed by 787
Abstract
This paper presents the results of research designed to explore the challenges involved in the use of Earth Observation (EO) data to support environmental management Brazil. While much has been written about the technology and applications of EO, the perspective of end-users of [...] Read more.
This paper presents the results of research designed to explore the challenges involved in the use of Earth Observation (EO) data to support environmental management Brazil. While much has been written about the technology and applications of EO, the perspective of end-users of EO data and their needs has been under-explored in the literature. A total of 53 key informants in Brasilia and the cities of Rio Branco and Cuiaba were interviewed regarding their current use and experience of EO data and the expressed challenges that they face. The research builds upon a conceptual model which illustrates the main steps and limitations in the flow of EO data and information for use in the management of land use and land cover (LULC) in Brazil. The current paper analyzes and ranks, by relative importance, the factors that users identify as limiting their use of EO. The most important limiting factor for the end-user was the lack of personnel, followed by political and economic context, data management, innovation, infrastructure and IT, technical capacity to use and process EO data, bureaucracy, limitations associated with access to high-resolution data, and access to ready-to-use product. In general, users expect to access a ready-to-use product, transformed from the raw EO data into usable information. Related to this is the question of whether this processing is best done within an organization or sourced from outside. Our results suggest that, despite the potential of EO data for informing environmental management in Brazil, its use remains constrained by its lack of suitably trained personnel and financial resources, as well as the poor communication between institutions. Full article
Show Figures

Figure 1

Back to TopTop