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Applications of GIS and Remote Sensing for Sustainable Spatial Planning

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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 (15 April 2023) | Viewed by 7189

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Special Issue Editors

Dr. Lia Bárbara Cunha Barata Duarte

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Guest Editor

1. Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
2. Institute of Earth Sciences, University of Porto, 4169-007 Porto, Portugal
Interests: GIS; GIS open source applications; spatial management; land use planning; spatial analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Ana Cláudia Teodoro

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Guest Editor

1. Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, 4169007 Porto, Portugal
2. Institute of Earth Sciences (ICT)-Porto Pole, University of Porto, 4169007 Porto, Portugal
Interests: remote sensing; image processing; environmental applications; geologic applications; GIS
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Beniamino Murgante

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Guest Editor

School of Engineering, University of Basilicata, 85100 Potenza, Italy
Interests: spatial planning; spatial simulation; geodemographics; urban modelling; geocomputation; urban simulation models; planning environmental studies on climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The study of sustainable development in any area depends on available knowledge regarding resource management and hazards. In recent years, remote sensing (RS) technology has enhanced significantly in terms of data acquisition time, sensor resolution, and accessibility, with, for instance, the emergence of the Google Earth Engine platform. This technology has also been widely applied when addressing sustainability challenges. Geographical information systems (GISs) also provide essential tools for implementing sustainable processes at different scales. In recent years, GIS technologies combined with satellite RS data have emerged as relevant geospatial tools for the sustainable monitoring and management of natural resources on Earth, providing support with a focus on natural resource management and the assessment of natural hazards.

This Special Issue of Sustainability aims to address the implementation and use of GISs combined with RS data/techniques for sustainable management using geospatial analysis in several areas, such as climate change, the environment, geology, agriculture, forestry, ecology, coastal ecosystems, etc. Its goal is to provide a platform for researchers aiming to publish high-quality original research papers and reviews focusing on a sustainable environment.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Spatial planning systems;
Urban planning;
Spatial analysis and modelling of natural hazards;
Environmental management;
Spatial and landscape planning;
Sustainable planning;
Ecosystem services analyses;
Performance-based planning.

We look forward to receiving your contributions.

Dr. Lia Bárbara Cunha Barata Duarte
Prof. Dr. Ana Cláudia Moreira Teodoro
Prof. Dr. Beniamino Murgante
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. 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 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

GIS
remote sensing
environmental sustainability
sustainable planning

Published Papers (6 papers)

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Research

25 pages, 11965 KiB

Open AccessArticle

Location Suitability Evaluation and Spatial Optimization of Self-Driving Camps in Xinjiang

by Cai Li and Chengjie Guo

Sustainability 2023, 15(14), 10820; https://doi.org/10.3390/su151410820 - 10 Jul 2023

Cited by 1 | Viewed by 905

Abstract

Irregular tourism seasons and insufficient momentum in the development of new tourism modes disrupt the supply and demand balance between the development of self-driving tourism and the number of corresponding service facilities in Xinjiang. This constrains the growth of regional comprehensive benefits. This paper constructs an index system for evaluating the location suitability of self-driving camps in Xinjiang by the Delphi method; obtains DEM data, GIS data, POI data, and statistical data; and uses a combination of subjective and objective evaluation to calculate index weights. ArcGIS raster analysis and the P-median model were used to study the location suitability and spatial optimization strategies for self-driving tourism camps in Xinjiang. The results of this study are as follows: (1) An evaluation system for the suitability of self-driving camp locations in Xinjiang is constructed from the supply side and the demand side. (2) Self-driving camps in Xinjiang have a large supply capacity gap between counties and cities. (3) The overall suitability of the demand for self-driving camps in Xinjiang is low to moderate. (4) There exists a spatial imbalance in the suitability of the supply and demand for self-driving tourism camps in Xinjiang. (5) A total of 65 campsites were proposed for self-driving tours in Xinjiang considering spatial optimization. (6) Xinjiang should strengthen the matching of self-driving camps with tourism resources and traffic routes, and produce self-driving tour business maps with complete self-driving tour supporting facilities and services. Full article

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

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18 pages, 20727 KiB

Open AccessArticle

The Agricultural Potential of a Region with Semi-Dry, Warm and Temperate Subhumid Climate Diversity through Agroecological Zoning

by Edgar Vladimir Gutiérrez Castorena, Gustavo Andrés Ramírez Gómez and Carlos Alberto Ortíz Solorio

Sustainability 2023, 15(12), 9491; https://doi.org/10.3390/su15129491 - 13 Jun 2023

Viewed by 950

Abstract

The sustainability of the natural resources used in agricultural production is essential to meet the future food needs of the population. It is necessary to understand the characteristics of climate and soil changes through agroclimatic zoning models, even with non-existent or limited climatic and edaphic databases, to avoid a decline in production. The objective of the study was to determine the accuracy of the Global Agroecological Zoning (GAEZ), ECOCROP and Papadakis models for major cereals, vegetables and fruit trees in the state of Nuevo León, Mexico, using the databases of climatic stations and soil profiles collected by INEGI with random sampling in the field. The model with the best projection was ECOCROP, which predicted 37,609 km² of irrigated area for sorghum and 34,796 km² for wheat, in addition to identifying by soil characteristics rainfed areas with higher suitability for beans measuring 8470 km² and orange measuring 6175 km² with zoning predictions based on field information. In conclusion, the thematic maps obtained with ECOCROP had an accuracy greater than 50% for more than half of the crops analyzed, making it the best method for the study area. Therefore, the food production decisions of the producers must be directed towards cereal crops based on the projected area; however, it is necessary to establish an updating program and generate edaphoclimatic databases, updating thematic soil and climate maps with models that support the projections verified in the field. Full article

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

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25 pages, 16927 KiB

Open AccessArticle

Evaluation and Analysis of Development Status of Yellow River Beach Area Based on Multi-Source Data and Coordination Degree Model

by Jing Li, Yuefeng Lu, Xiwen Li, Rui Wang, Ying Sun, Yanru Liu and Kaizhong Yao

Sustainability 2023, 15(7), 6086; https://doi.org/10.3390/su15076086 - 31 Mar 2023

Cited by 2 | Viewed by 1174

Abstract

The Yellow River beach area is the basic component of the Yellow River Basin. Promoting the comprehensive improvement and high-quality development of the Yellow River beach area is an important guarantee of the long-term stability of the Yellow River and an important part of promoting the high-quality development and ecological protection of the Yellow River Basin. In this paper, four new indexes (flood risk intensity index, accessibility index, biological abundance index, and remote sensing ecological index) were extracted from geospatial data and remote sensing images, and a quantitative evaluation model (Ecology-Economy -Society-Flood, EESF) for the development of the Yellow River beach area were constructed based on social statistics, such as flood control and control in the beach area. The coordinated development level of the Yellow River beach area was evaluated by combining the “CRITIC–entropy weight method” and “‘single index quantification–multi-index synthesis–multi-criteria integration’ (SMI-P)—coordination degree model” methods. The spatial autocorrelation model was used to analyze the spatial distribution characteristics of the coordinated development level, and the global sensitivity and uncertainty analysis (GSUA) was carried out for the sensitivity and uncertainty of the parameters. Taking the Yellow River beach area in Shandong Province in 2009 and 2019 as the study object, the research results showed that during this period, the coordinated development level of the Yellow River beach area in Shandong Province showed a gradual upward trend, from 0.344 to 0.580, reaching a basic coordinated state; the overall coordinated development level of the beach area showed significant autocorrelation and small spatial heterogeneity. Grain production was the most sensitive parameter in the coordinated development model of the beach area. The beach area should rationally develop and utilize agricultural resources and promote the integration of ecological industries. Full article

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

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22 pages, 4808 KiB

Open AccessArticle

Recovery Assessment of Permanent Housing after the 2004 Tsunami in Thailand toward Sustainable Planning

by Daroonwan Kamthonkiat, Thanawan Leelawatthanaphong, Kessinee Unapumnuk and Tuong Thuy Vu

Sustainability 2023, 15(5), 4627; https://doi.org/10.3390/su15054627 - 05 Mar 2023

Viewed by 1170

Abstract

In this study, a recovery assessment of the permanent housing and living conditions in the aftermath of the 2004 Tsunami in Phang-nga Province, Thailand, was conducted using geoinformatics technologies, field observations, and living-related parameters from basic minimum need (BMN) data retrieved from the Ministry of Interior. In the results, 29 permanent housing projects were mapped, classified into five sizes (very small, small, medium, large, and very large), and overlaid with the tsunami-inundated zone visually interpreted from satellite images. Thirteen out of twenty-nine projects were reconstructed in the inundation zone (in situ), while the rest were relocated to higher ground. Permanent houses were rebuilt in 18 communities in three patterns: single-story or one-story houses (511 houses), single-story and raised-basement houses (58 houses), and two-story houses (712 houses). The selected BMN’s living-related parameters, such as sufficient water for household consumption (dimension: dwelling), employment of people between 15 and 60 years old (dimension: economy), and participation in communities’ activities (dimension: participation), which covered 2002–2015 at the community-based level, were compared annually to its criterion and indicated as passing or not passing the standard. The reconstructed communities recovered (passing the requirements) within four years of transferring to the reconstructed houses. Full article

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

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11 pages, 4886 KiB

Open AccessArticle

Evaluation of Geological Disaster Sensitivity in Shuicheng District Based on the WOE-RF Model

by Zefang Zhang, Zhikuan Qian, Yong Wei, Xing Zhu and Linjun Wang

Sustainability 2022, 14(23), 16247; https://doi.org/10.3390/su142316247 - 05 Dec 2022

Viewed by 977

Abstract

To improve the prevention and control of geological disasters in Shuicheng District, 10 environmental factors—slope, slope direction, curvature, NDVI, stratum lithology, distance from fault, distance from river system, annual average rainfall, distance from road and land use—were selected as evaluation indicators by integrating factors such as landform, basic geology, hydrometeorology and engineering activities. Based on the weight of evidence, random forest, support vector machine and BP neural network algorithms were introduced to build WOE-RF, WOE-SVM and WOE-BPNN models. The sensitivity of Shuicheng District to geological disasters was evaluated using the GIS platform, and the region was divided into areas of extremely high, high, medium, low and extremely low sensitivity to geological disasters. By comparing and analyzing the ROC curve and the distribution law of the sensitivity index, the AUC evaluation accuracy of the WOE-RF, WOE-SVM and WOE-BPNN models was 0.836, 0.807 and 0.753, respectively; the WOE-RF model was shown to be the most effective. In the WOE-RF model, the extremely high-, high-, medium-, low- and extremely low-sensitivity areas accounted for 15.9%, 16.9%, 19.3%, 21.0% and 26.9% of the study area, respectively. The extremely high- and high-sensitivity areas are mainly concentrated in areas with large slopes, broken rock masses, river systems and intensive human engineering activity. These research results are consistent with the actual situation and can provide a reference for the prevention and control of geological disasters in this and similar mountainous areas. Full article

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

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24 pages, 4123 KiB

Open AccessArticle

Dynamic Monitoring of the Ecological Vulnerability for Multi-Type Ecological Functional Areas during 2000–2018

by Xingming Yuan and Bing Guo

Sustainability 2022, 14(23), 15987; https://doi.org/10.3390/su142315987 - 30 Nov 2022

Viewed by 974

Abstract

Studies that consider both the differences of evaluation systems and index weights among different ecological areas in different study periods for ecological vulnerability evaluation have not been reported yet. In addition, the comparability of vulnerability assessment results among different study areas is poor. This paper proposed a novel quantitative vulnerability evaluation method for multi-type and multi-temporal ecological functional areas using a dynamic weighting method: Three-River Source region grassland–wetland ecological functional area (TRSR), Guiqiandian karst rocky desertification control ecological functional area (GQD), Hunshandake desertification control ecological functional area (HSDK), and Chuandian forest and biodiversity ecological functional area (CD), and then introduced net primary productivity (NPP) to realize the determination of multi-type ecological vulnerability thresholds, which is helpful to compare the vulnerability evaluation results of different ecological functional areas in a unified and comparable level. The proposed novel quantitative vulnerability evaluation method had higher applicability in vulnerability assessment for multi-type ecological functional areas (91.1% for TRSR, 91.9% for HSDK, 91.7% for CD, and 94.2% for GQD) based on the dynamic weight determination method. The determination of vulnerability thresholds based on NPP could provide a comparable level to investigate the spatial distribution patterns of ecological vulnerability in multi-type ecological functional areas for different periods. The average ecological vulnerability of the TRSR, GQD, and CD was classified as mild vulnerability, while that of the HSDK was classified as moderate vulnerability. The research results could provide a novel method for the support of ecological protection for multi-type ecological zones on a national scale. Full article

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

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