sustainability-logo

Journal Browser

Journal Browser

Geographical Information Research for Eco-Environment Sustainable Development

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 6942

Special Issue Editors

College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
Interests: GIS/RS; spatial analysis; satellite image analysis; ecosystem services evaluation; LULC monitoring; hyperspectral remote sensing
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Interests: ecological environmental assessment; industrial assessment; industrial production sustainability; extreme enviroment (aerospace, deep sea, etc.)

E-Mail Website
Guest Editor
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Interests: earth system model; GIS; hydrology; climate change

Special Issue Information

Dear Colleagues,

(1) Introduction, including scientific background and highlighting the importance of this research area.

Increasing global crises, including climate change, the coronavirus pandemic and social conflicts, significantly jeopardize the 17 Sustainable Development Goals (SDGs) announced by the United Nation. The world’s eco-environment is suffering unprecedented change due to accelerated socio-economic development and the enhanced impact of human activities since the last century. To mitigate this, the development of an assessment approach and the better implementation of management practice of terrestrial and aquatic ecosystem system is an urgent matter.

On the global scale, an appropriate policy remains a significant challenge for each country to implement the 17 Sustainable Development Goals (SDGs) and 169 targets based on the Sustainable Development Report 2022, in terms of not only technology and data themselves, but also the usage, transformation, and better integration of scientific and technological innovation and digitalization.

Remote sensing (RS) and Geographic Information Science (GIS) can help in resolving this issue. With the introduction of these technologies, the assessment of the eco-environment has undergone revolutionary changes, broadening the research ideas of geographers, ecologists, and stakeholders.

(2) Aim of the Special Issue and how the subject relates to the journal scope.

Following the rapid development of big data in eco-environment studies, RS has become a well-known technology with the ability of fast data acquisition at large scales. Nowadays, RS technology has become an important technical means in eco-environmental protection. RS and GIS technology have substantially changed the traditional monitoring approach, improving the ability and efficiency of environmental protection omnidirectionally from qualitative analysis to a quantitative perspective.

Significant research progress has been seen in this field. The scientific community constantly make new breakthroughs and innovative achievements in RS and GIS science, helping to drive global ecological environment governance. Moreover, based on meteorology, oceanography, resources, the environment, and high-resolution earth observation satellite constellations and associated application systems, mobilizing innovation in scientific research, policy formulation, and action implementation improves research and application capabilities in ecological environmental sustainability, climate change, disaster prevention and mitigation, and resilient cities. Furthermore, we encourage the open access of scientific data, technology, and knowledge to the international community, helping to construct a global ecological civilization.

This Special Issue calls for submissions dedicated to RS and GIS technology in eco-environment assessment, mainly on a local and country scale. Papers focused on applications, case studies, and georeferenced data on eco-environment sustainability development are also welcome.

(3) Suggest themes.

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

  • Ecological environmental quality assessment model.
  • Spatiotemporal evolution characteristics of ecological environment analysis.
  • Ecosystem services assessment.
  • Estimation of ecosystem services value.
  • Trade-offs and synergies of ecosystem services.
  • Land use change monitoring and multi-scenario simulation.
  • Analysis of driving mechanisms of ecological environmental change.
  • Long-time series factor extraction and analysis.
  • Evaluation of the geological environmental bearing capacity.
  • Integration and innovation of spatiotemporal information and territorial spatial planning. 

I/We look forward to receiving your contributions.

Dr. Xiaoai Dai
Dr. Zekun Wang
Dr. Yuanzhi Yao
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

  • ecological assessment
  • ecosystem services
  • remote sensing/GIS
  • LULC
  • sustainable development

Published Papers (5 papers)

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

Research

29 pages, 9332 KiB  
Article
Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China
by Jianwen Zeng, Xiaoai Dai, Wenyu Li, Jipeng Xu, Weile Li and Dongsheng Liu
Sustainability 2024, 16(4), 1447; https://doi.org/10.3390/su16041447 - 8 Feb 2024
Cited by 1 | Viewed by 1571
Abstract
The environmental quality of a mining city has a direct impact on regional sustainable development and has become a key indicator for assessing the effectiveness of national environmental policies. However, against the backdrop of accelerated urbanization, increased demand for resource development, and the [...] Read more.
The environmental quality of a mining city has a direct impact on regional sustainable development and has become a key indicator for assessing the effectiveness of national environmental policies. However, against the backdrop of accelerated urbanization, increased demand for resource development, and the promotion of the concept of ecological civilization, mining cities are faced with the major challenge of balancing economic development and ecological environmental protection. This study aims to deeply investigate the spatial and temporal variations of environmental quality and its driving mechanisms of mineral resource-based cities. This study utilizes the wide coverage and multitemporal capabilities of MODIS optical and thermal infrared remote sensing data. It innovatively develops the remote sensing ecological index (RSEI) algorithm on the PIE-Engine cloud platform to quickly obtain the RSEI, which reflects the quality of the ecological environment. The spatial and temporal evolution characteristics of the environmental quality in seven typical mining cities in China from 2001 to 2022 were analyzed. Combined with the vector mine surface data, the spatial and temporal variability of the impacts of mining activities on the ecological environment were quantitatively separated and explored. In particular, the characteristics of mining cities were taken into account by creating buffer zones and zoning statistics to analyze the response relationship between RSEI and these factors, including the distance to the mining area and the percentage of the mining area. In addition, the drivers and impacts of RSEI in 2019 were analyzed through Pearson correlation coefficients pixel by pixel with 10 factors, including natural, economic, and mining. Regression modeling of RSEI in 2019 was performed using the random forest (RF) model, and these drivers were ranked in order of importance through random forest factor importance assessment. The results showed that (1) the ecological quality of mining cities changed significantly during the study period, and the negative impacts of mining activities on the ecological environment were significant. (2) The areas with low RSEI values were closely related to the mining areas and cities. (3) The RSEI in the mining areas of mining cities was generally lower than the average level of the cities. The RSEI gradually increased as the distance to the mine site increased. (4) The increase in the size of the mine area initially exacerbates the impact on the ecological environment, but the impact is weakened beyond a certain threshold. (5) The distance to the mining area is the most important factor affecting the quality of the ecological environment, followed by DEM, GDP, and precipitation. This study is of great importance for advancing sustainable development in mining cities and formulating sustainable strategies. Full article
Show Figures

Figure 1

24 pages, 5658 KiB  
Article
The Impact of Land Use/Cover Change on Ecological Environment Quality and Its Spatial Spillover Effect under the Coupling Effect of Urban Expansion and Open-Pit Mining Activities
by Haobei Liu, Qi Wang, Na Liu, Hengrui Zhang, Yifei Tan and Zhe Zhang
Sustainability 2023, 15(20), 14900; https://doi.org/10.3390/su152014900 - 16 Oct 2023
Viewed by 1059
Abstract
Suburban open-pit mining concentration areas are both the frontline of urban expansion and the main battlefield in mineral resource development. These dual forces have resulted in significant land use/cover changes (LUCC), which play a crucial role in determining the ecological environment quality (EEQ). [...] Read more.
Suburban open-pit mining concentration areas are both the frontline of urban expansion and the main battlefield in mineral resource development. These dual forces have resulted in significant land use/cover changes (LUCC), which play a crucial role in determining the ecological environment quality (EEQ). However, research examining how LUCC affects EEQ under the coupled impact of these two development events is currently lacking. In this study, the response of EEQ to LUCC was evaluated using Landsat images from 2000, 2010, and 2020 for the southern suburban open-pit mining concentration area in Jinan City. A relative contribution index was used to address the ecological and environmental effects of non-dominant land use/cover types, and the impact of LUCC on EEQ and its spatial spillover effects were revealed by also carrying out a buffer zone analysis. The findings of this study indicate that: (1) the dominant land use/cover types that influence the EEQ spatial pattern are farmland, grassland, and construction land. Among them, the area of farmland was the largest, with more than 1800 km2. Changes in non-dominant land use/cover types to mining land and mine rehabilitation made the most significant relative contribution to the changes in EEQ, i.e., 0.0735 and 0.0184, respectively. (2) The transformation of farmland into construction land and mining land and woodland into mining land was shown to exacerbate the deterioration of the EEQ in the study area, with a deterioration area of 1367.54 km2 and spatial spillovers of up to 1000 m. (3) Returning farmland to woodland and grassland, as well as returning mine rehabilitation, were found to be the main factors contributing to the improvement of EEQ in the study area, with an improvement area of 1335.67 km2 and spatial spillover extending from 500 to 800 m. (4) Nevertheless, uneven changes in land use/cover continue to aggravate the agglomerative effect of EEQ deterioration. Further refinement and enhancement of the methods and standards of ecological governance are urgently needed to counterbalance the uneven spatial spillover effects between ecological degradation and improvement. This study provides a scientific reference for the promotion of ecological protection and sustainable development in mining cities. Full article
Show Figures

Figure 1

18 pages, 5903 KiB  
Article
Spatiotemporal Distribution Characteristics and Their Driving Forces of Ecological Service Value in Transitional Geospace: A Case Study in the Upper Reaches of the Minjiang River, China
by Fengran Wei, Mingshun Xiang, Lanlan Deng, Yao Wang, Wenheng Li, Suhua Yang and Zhenni Wu
Sustainability 2023, 15(19), 14559; https://doi.org/10.3390/su151914559 - 7 Oct 2023
Cited by 1 | Viewed by 865
Abstract
Ecosystem service value (ESV) is a key indicator for evaluating ecosystem services. Thus, a unique quantitative assessment instrument that comprehensively and objectively evaluates ESV is of great significance for protecting regional ecosystems and achieving sustainable development. Based on data for meteorology, hydrology, soil [...] Read more.
Ecosystem service value (ESV) is a key indicator for evaluating ecosystem services. Thus, a unique quantitative assessment instrument that comprehensively and objectively evaluates ESV is of great significance for protecting regional ecosystems and achieving sustainable development. Based on data for meteorology, hydrology, soil use, and land use, this paper comprehensively employs the InVEST model, spatial autocorrelation, and geographic detectors to study the spatiotemporal characteristics and driving forces of spatial variations in ESV in the upper reaches of the Minjiang River. The results indicate the following: (1) The ecosystem service capacity of the study area has continuously improved, with the ecosystem service value (ESV) increasing by USD 4.078 billion over 20 years. Soil conservation has made the most significant contribution to the growth of ESV, accounting for over 85%. (2) The distribution of ESV exhibits a “lower in the northwest, higher in the southeast” trend. The Moran’s I value for each year exceeds 0.7, indicating characteristics of High–High and Low–Low aggregation. (3) Slope plays a dominant role in causing the spatial differentiation of ESV, contributing 30.9%. Slope is followed by HAI at 19.7% and the urbanization rate at 16.8%. Rainfall has the least impact at 4%. (4) The results from the multi-factorial interactions reveal that all factors experience synergistic enhancement effects when interacting. The spatiotemporal differentiation of ESV is the result of multiple factors acting in conjunction, underscoring the importance of coordinated efforts in ecological restoration and comprehensive environmental management in the upper reaches of the Minjiang River. The methodology of this research could be applied to assess the impact of natural changes and human activities on ESV. The findings offer theoretical support for regional resource and environmental management, as well as ecological compensation decision making. Full article
Show Figures

Figure 1

24 pages, 10183 KiB  
Article
Habitat Quality Assessment under the Change of Vegetation Coverage in the Tumen River Cross-Border Basin
by Yue Wang, Donghe Quan, Weihong Zhu, Zhehao Lin and Ri Jin
Sustainability 2023, 15(12), 9269; https://doi.org/10.3390/su15129269 - 8 Jun 2023
Viewed by 1380
Abstract
The continuous deterioration of terrestrial ecosystems has led to the destruction of many biological habitats in recent years. The Tumen River cross-border basin, an important biological habitat, is also affected by this changing situation. Assessing habitat quality (HQ) is crucial for restoring and [...] Read more.
The continuous deterioration of terrestrial ecosystems has led to the destruction of many biological habitats in recent years. The Tumen River cross-border basin, an important biological habitat, is also affected by this changing situation. Assessing habitat quality (HQ) is crucial for restoring and protecting habitats, and vegetation plays a significant role in this process. In this study, we used geographical detector (GD) to extract fraction vegetation coverage (FVC) features and quantify the contribution of driving factors. By coupling vegetation cover and land use data, we assessed HQ. Our findings reveal a declining trend in FVC from 2000 to 2020, which mainly assumed a spatial pattern inclined from northeast and southwest to southeast. Human activities and natural factors interacted to cause these changes in FVC, with human activities having a more significant impact. Vegetation and land use changes led to a decline in the basin’s HQ index. This study highlights the crucial role of FVC in HQ and provides a relevant scientific reference for optimizing the evaluation of HQ in the Tumen River cross-border basin and promoting the sustainable development of regional ecology. Full article
Show Figures

Figure 1

18 pages, 14158 KiB  
Article
Regional-Scale Topsoil Organic Matter Estimation Based on a Geographic Detector Model Using Landsat Data, Pingtan Island, Fujian, China
by Junjun Fang, Xiaomei Li, Jinming Sha, Taifeng Dong, Jiali Shang, Eshetu Shifaw, Yung-Chih Su and Jinliang Wang
Sustainability 2023, 15(11), 8511; https://doi.org/10.3390/su15118511 - 24 May 2023
Viewed by 1018
Abstract
Understanding the spatial distribution of soil organic matter (SOM) is important for land use management, but conventional sampling methods require significant human and financial resources. How to map SOM and monitor its changes using a limited number of sample points combined with remote [...] Read more.
Understanding the spatial distribution of soil organic matter (SOM) is important for land use management, but conventional sampling methods require significant human and financial resources. How to map SOM and monitor its changes using a limited number of sample points combined with remote sensing techniques that provide long-time series data is crucial. This study aimed to generate a regional-scale near-surface SOM map using 70 soil samples and covariate environmental factors extracted mainly from Landsat 8 OLI. Firstly, the sensitivity of each environmental factor to SOM was tested using a geographic detector model (GDM). Secondly, the tested factors were selected for modeling and mapping by ordinary least squares (OLS) and geographically weighted regression kriging (GWRK). The performance of these two models was compared. Finally, the mapping results of the better model (GWRK) were compared and analyzed with the traditional interpolation results based solely on sampling points to verify the rationality of the proposed method. The results show that three environmental factors, ratio vegetation index (RVI), differential vegetation index (DVI), and terrain roughness (TR), have a strong influence on the spatial variability of SOM. Using these three factors in combination with the GWRK method, a more accurate and refined spatial distribution map of SOM can be obtained. Comparing the SOM maps of GWRK and the traditional interpolation method, the results show that the accuracy of GWRK (R2 = 0.405; mean absolute error = 0.637, and root mean square error = 0.813) is higher than that of traditional interpolation methods (R2 = 0.291, MAE = 0.609, and RMSE = 0.863). The spatial recognition rate (fineness) of SOM patches at all levels using the GWRK method increased by more than 73 times compared to the traditional kriging. We conclude that the combination of limited SOM samples, environmental variables, GDM, and GWRK is a pragmatic approach for estimating regional-scale SOM. Full article
Show Figures

Figure 1

Back to TopTop