Earth Observations for Sustainable Development Goals

A special issue of Geomatics (ISSN 2673-7418).

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 7330

Special Issue Editors

CREAF—Centre for Ecological Research and Forestry Applications, 08193 Barcelona, Spain
Interests: remote sensing; land cover; sustainable development; citizen science
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Guest Editor
Centre for Ecological Research and Forestry Applications, 08193 Barcelona, Spain
Interests: GIS; remote sensing; standars; environmental management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Departament de Geografia, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
Interests: data; metadata; web semantics; remote sensing; signal processing
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Special Issue Information

Dear Colleagues,

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. 

You may choose our Joint Special Issue in Remote Sensing.

Dr. Joan Masó
Dr. Ivette Serral
Dr. Alaitz Zabala Torres
Guest Editors

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Keywords

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

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Published Papers (1 paper)

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Research

16 pages, 4444 KiB  
Article
Modelling Physical Accessibility to Public Green Spaces in Switzerland to Support the SDG11
by Camille Chênes, Gregory Giuliani and Nicolas Ray
Geomatics 2021, 1(4), 383-398; https://doi.org/10.3390/geomatics1040022 - 28 Sep 2021
Cited by 13 | Viewed by 6052
Abstract
Urban sprawl has a strong impact on the provision and use of green spaces and, consequently, on the benefits that society can derive from these natural ecosystems, especially in terms of public health. In looking at the Sustainable Development Goals and other regional [...] Read more.
Urban sprawl has a strong impact on the provision and use of green spaces and, consequently, on the benefits that society can derive from these natural ecosystems, especially in terms of public health. In looking at the Sustainable Development Goals and other regional policy frameworks, there is a strong need for quantifying access to green spaces. This study presents and applies a methodology to model the physical accessibility at national and sub-national scales to public green spaces (i.e., urban green spaces and forests) in Switzerland, using AccessMod and ArcGIS travel time functions. We found that approximately 75% and 36% of the Swiss population can access the nearest urban green space within 5 min and 15 min, respectively, using motorized transport. For motorized access to the nearest forest patch, 72% and 52% of the population are within 5 min and 15 min, respectively. When considering only the main urban areas, approximately 55% of the population can walk to the nearest urban green space within 5 min. However, a high heterogeneity in access exists at cantonal and municipal levels, depending on road density, green space density, and population distribution. Despite some possible challenges in correctly delineating public green spaces, our methodology offers a replicable approach offering not only insights into sustainable urban development, but also the facilitation of comparison with other European countries. Full article
(This article belongs to the Special Issue Earth Observations for Sustainable Development Goals)
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