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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 20865

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Special Issue Editors

Prof. Dr. Suhong Liu

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Guest Editor

Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: remote sensing (RS); geographic information system (GIS)

Dr. Nijat Kasim

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Guest Editor

College of Biology and Geography, Yili Normal University, Yining 835000, China
Interests: agricultural remote sensing (ARS)

Dr. Hao Li

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Guest Editor

College of Resources and Environment Science, Xinjiang University, Urumqi 830046, China
Interests: vegetation remote sensing

Special Issue Information

Dear Colleagues,

Remote sensing (RS) and geographic information systems (GISs) are important means to acquire and process geographical data. Many previous studies have fully demonstrated their unique advantages in solving resource and environmental problems. Sustainable development is an important concept proposed to coordinate human development and the natural environment. To improve the lives of people all over the world, the United Nations has put forward 17 Sustainable Development Goals, such as to end poverty in all its forms everywhere, achieve zero hunger, ensure healthy lives, and promote wellbeing for all at all ages. At present, the speed and scale of this progress have not reached the level required to achieve the Sustainable Development Goals. In addition, global climate change, irrational development activities, and the outbreak of COVID-19 have all posed severe challenges to the realization of the Sustainable Development Goals (SDGs). The Sustainable Development Goals Report 2020 points out that data innovation is needed in the time of COVID-19, and we believe that the advantages of RS and GIS in data mining will help to achieve the SDGs. Therefore, we have launched this Special Issue entitled “Applications of GIS and Remote Sensing for Sustainable Development” to promote the application of remote sensing in sustainable development, fully tap into the potential of GIS in solving sustainable development problems, and show the broad prospects of remote sensing and GIS in achieving Sustainable Development Goals.

Prof. Dr. Suhong Liu
Dr. Nijat Kasim
Dr. Hao Li
Guest Editors

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Keywords

remote sensing (RS)
geographic information system (GIS)
sustainable development
Sustainable Development Goals (SDGS)
resources
environment

Published Papers (4 papers)

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Research

21 pages, 6256 KiB

Open AccessArticle

Spatial Equity Priority Modeling of Elementary and Middle Schools through GIS Techniques, El-Taif City, Saudi Arabia

by Mona S. Ramadan, Nesren Khairy, Haya M. Alogayell, Ibtesam I. Alkadi, Ismail Y. Ismail and Rasha H. Ramadan

Sustainability 2022, 14(19), 12057; https://0-doi-org.brum.beds.ac.uk/10.3390/su141912057 - 23 Sep 2022

Viewed by 1630

Abstract

Spatial equity in the delivery of educational services is a critical element in creating healthful and joyful living circumstances in cities. The spatial distribution of public elementary and middle schools for girls in El-Taif city was investigated in this study using a variety of tools. Mean Center, Central Feature, Standard Distance, Directional Distribution, Point Density, Kernel Density, Nearest Neighbor Analysis, Ripley’s K Function, Moran Index, Buffer Zone, and Hotspot analysis are spatial techniques in Geographic Information Systems, which were used to analyze and show the spatial distribution of current public elementary and middle schools for females. Furthermore, the sufficiency and/or shortage of elementary and middle schools according to the criteria of the Ministry of Municipal and Rural Affairs (MOMRA) were studied to establish the regions with shortage or overcapacity. The findings reveal that the city’s population and public elementary and middle school numbers were not spread equally. Some districts had an overabundance and concentration of elementary and middle schools, particularly in older, fully developed, and densely inhabited districts, while most new north and eastern districts had a scarcity of schools. Furthermore, half of the districts lack public elementary and middle schools. Consequently, the study finished by developing a spatial equality priority model for public elementary and middle schools to find and highlight problem areas that require future corrective action and are a priority for spatial equality. In order to contribute to achieving goal 4 of the UN-Habitat Sustainable Development Goals, which aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”, the model recommended that decision-makers supply elementary schools and middle schools in districts where a shortage was present and improve the equal distribution of elementary schools around the city. Full article

(This article belongs to the Special Issue Applications of GIS and Remote Sensing for Sustainable Development)

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19 pages, 3066 KiB

Open AccessArticle

Towards a Circular Economy Development for Household Used Cooking Oil in Guayaquil: Quantification, Characterization, Modeling, and Geographical Mapping

by José Hidalgo-Crespo, César I. Alvarez-Mendoza, Manuel Soto and Jorge Luis Amaya-Rivas

Sustainability 2022, 14(15), 9565; https://0-doi-org.brum.beds.ac.uk/10.3390/su14159565 - 04 Aug 2022

Cited by 2 | Viewed by 2438

Abstract

The objective of the present study was to quantify, geo-locate, model, and characterize domestic used cooking oil (dUCO) generation for the city of Guayaquil. For this reason, and as a prerequisite for the proper planning of municipal cooking oil waste management in the city, we carried out 14-day fieldwork involving 532 households from different parishes of Guayaquil, combined with a survey to acquire data on their demographic and socioeconomic statistics. The artisanal characterization was further executed to 40 subsamples of dUCO to determine the density, moisture, solids content, and the volatile-matter characteristics present. Additionally, the Geographic Information System (GIS) was used to map the used cooking oil generation hotspots for the city, adding the Geographical Position System (GPS) of each participating household during the data acquisition. Finally, a multiple-regression model was proposed to establish correlations between the dUCO generated and five independent variables, such as household size, socioeconomic group, tenure status, education level, and income. Results showed that the per capita daily dUCO-generation rate was found to be 4.30 g/day/c or 4.99 mL/day/c, with a density of 0.86 g/mL. Filterable solids represented 0.37% for the entire dUCO collected sample, while separable water and grease represented 1.58% and 0.014%, respectively. In addition, the percentage of the volatile matter was found to be 7.7% ± 2.1% of the filtered dUCO. Using GIS mapping, we found that the areas near tourism sites have a higher dUCO generation value, considering the household survey. Following the developed multiple-regression model developed, it was found that household size and the socioeconomic group have the maximum effect on generating used cooking oil. Full article

(This article belongs to the Special Issue Applications of GIS and Remote Sensing for Sustainable Development)

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20 pages, 5721 KiB

Open AccessArticle

Landscape Analysis of Cobalt Mining Activities from 2009 to 2021 Using Very High Resolution Satellite Data (Democratic Republic of the Congo)

by Chloe Brown, Doreen S. Boyd and Siddharth Kara

Sustainability 2022, 14(15), 9545; https://0-doi-org.brum.beds.ac.uk/10.3390/su14159545 - 03 Aug 2022

Cited by 6 | Viewed by 10485

Abstract

The cobalt mining sector is well positioned to be a key contributor in determining the success of the Democratic Republic of the Congo (DRC) in meeting the Sustainable Development Goals (SDGs) by 2030. Despite the important contribution to the DRC’s economy, the rapid expansion of mining operations has resulted in major social, health, and environmental impacts. The objective of this study was to quantitatively assess the cumulative impact of mining activities on the landscape of a prominent cobalt mining area in the DRC. To achieve this, an object-based method, employing a support vector machine (SVM) classifier, was used to map land cover across the city of Kolwezi and the surrounding mining areas, where long-term mining activity has dramatically altered the landscape. The research used very high resolution (VHR) satellite imagery (2009, 2014, 2019, 2021) to map the spatial distribution of land cover and land cover change, as well as analyse the spatial relationship between land cover classes and visually identified mine features, from 2009 to 2021. Results from the object-based SVM land cover classification produced an overall accuracy of 85.2–90.4% across the time series. Between 2009 and 2021, land cover change accounted to: rooftops increasing by 147.2% (+7.7 km²); impervious surface increasing by 104.7% (+3.35 km²); bare land increasing by 85.4% (+33.81 km²); exposed rock increasing by 56.2% (+27.46 km²); trees decreasing by 4.5% (−0.34 km²); shrub decreasing by 38.4% (−26.04 km²); grass and cultivated land decreasing by 27.1% (−45.65 km²); and water decreasing by 34.6% (−3.28 km²). The co-location of key land cover classes and visually identified mine features exposed areas of potential environmental pollution, with 91.6% of identified water situated within a 1 km radius of a mine feature, and vulnerable populations, with 71.6% of built-up areas (rooftop and impervious surface class combined) situated within a 1 km radius of a mine feature. Assessing land cover patterns over time and the interplay between mine features and the landscape structure allowed the study to amplify the findings of localised on-the-ground research, presenting an alternative viewpoint to quantify the true scale and impact of cobalt mining in the DRC. Filling geospatial data gaps and examining the present and past trends in cobalt mining is critical for informing and managing the sustainable growth and development of the DRC’s mining sector. Full article

(This article belongs to the Special Issue Applications of GIS and Remote Sensing for Sustainable Development)

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17 pages, 4131 KiB

Open AccessArticle

Global Food Security Assessment during 1961–2019

by Jingpeng Guo, Kebiao Mao, Zijin Yuan, Zhihao Qin, Tongren Xu, Sayed M. Bateni, Yinghui Zhao and Caixia Ye

Sustainability 2021, 13(24), 14005; https://0-doi-org.brum.beds.ac.uk/10.3390/su132414005 - 18 Dec 2021

Cited by 16 | Viewed by 3618

Abstract

Quantified components of the global food system are used to assess long-term global food security under a series of socio-economic, epidemic normalization and climate change scenarios. Here, we evaluate the global food security including the global farming system as well as the global food trade, reserve and loss systems from 1961 to 2019, and analyze their temporal and spatial characteristics by using the global food vulnerability (GFV) model. The spatio–temporal patterns of the vulnerability of the global food system were consistent with the GFSI. As food production and consumption vary greatly in different countries which have continued for a long time, food exports from many developed agricultural countries have compensated for food shortages in most countries (about 120 net grain-importing countries). As a result, many countries have relied heavily on food imports to maintain their domestic food supplies, ultimately causing the global food trade stability to have an increasing impact on the food security of most countries. The impact of global food trade on global food security increased from 9% to 17% during 1961–2019, which has increased the vulnerability of the global food system. The food damage in the United States, Russia, China, and India has varied significantly, and global cereal stocks have fluctuated even more since 2000. From 1961 to 2019, the food system security of some Nordic countries significantly improved, while the food system security of most African countries significantly deteriorated. Most countries with high food insecurity are located in Africa and South Asia. In order to cope with extreme events, these countries need to strengthen and improve their own food production and storage systems, which will help the World Food and Agriculture Organization to formulate relevant food policies and maintain sustainable development. Full article

(This article belongs to the Special Issue Applications of GIS and Remote Sensing for Sustainable Development)

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