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Diversity
Special Issues
Application of GIScience and Remote Sensing in Biodiversity Conservation
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Special Issue "Application of GIScience and Remote Sensing in Biodiversity Conservation"

A special issue of Diversity (ISSN 1424-2818). This special issue belongs to the section "Biodiversity Conservation".

Deadline for manuscript submissions: 31 December 2023 | Viewed by 652

Special Issue Editors

Dr. James Magidi

E-Mail Website
Guest Editor
Geomatics Department, Tshwane University of Technology, Pretoria 0001, South Africa
Interests: geomatics; GeoSpatial technology; GeoAnalytics GIS; remote sensing
Dr. Tsitsi Bangira

E-Mail Website
Guest Editor
Centre for Transformative Agricultural and Food Systems, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, 4041, South Africa
Interests: physical geography; spatial analysis; mapping; environmental impact assessment; Satellite image analysis; image processing; GIS
Dr. Matlhogonolo Kelepile

E-Mail Website
Guest Editor
Department of Environmental Science, University of Botswana, 0022 Gaborone, Botswana
Interests: spatial epidemiology; GIS; population geography; medical geography

Special Issue Information

Dear Colleagues,

Geospatial technology (Geographical Information System (GIS) and Remote Sensing) entails the collection, manipulation, management, analysis, retrieval and display of geospatial information. Geospatial technology deals with remotely sensed data from unmanned aerial vehicles, aircraft and satellites. The remotely sensed data is used to assess, monitor, quantify and map the properties of the Earth's land, water and human societies. Geospatial techniques such as spatial statistics are quite crucial in the analysis of spatial patterns/trends of terrestrial and aquatic biodiversity. The latest trends in computer innovation such as Machine Learning, Deep learning, Artificial Intelligence, Big Data Science and Cloud Computing offers a great opportunity in the conservation of biodiversity. This is helping in addressing the Sustainable Development Goals (SGDs) that pertains to biodiversity, conservation, water and climate change. There are challenges that are affecting biodiversity (terrestrial and aquatic), and these includes population increase, pollution, urbanisation, urban sprawl and many others. There are many approaches that has been used by researchers, planners and decision makers to help conserve biodiversity. So, this Special Issue aims to report the recent advances and trends in the collection, management, and analysis of geospatial data in conservation biodiversity at local and regional scale.

Dr. James Magidi
Dr. Tsitsi Bangira
Dr. Matlhogonolo Kelepile
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. Diversity is an international peer-reviewed open access monthly 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 2600 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

  • geospatial technology
  • remote sensing
  • geographic information systems
  • spatial statistics
  • machine learning and deep learning
  • cloud computing
  • big data science
  • image processing
  • spatial ecology, landscape ecology, sustainable development goals (SDGs)

Published Papers (1 paper)

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Research

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Article
A Study on Spatiotemporal Changes of Ecological Vulnerability in Yunnan Province Based on Interpretation of Remote Sensing Images
by
Zisheng Yang
,
Shiqin Yang
,
Renyi Yang
and
Qiuju Wu
Diversity 2023, 15(9), 963; https://doi.org/10.3390/d15090963 - 26 Aug 2023
Viewed by 252
Abstract
The inherent ecological environment of mountainous regions is highly fragile, and the degree of sustainable development is low. There has not yet been a multi-phase ecological vulnerability evaluation (EVE) study based on remote sensing (RS) and GIS for mountainous provinces, for which there [...] Read more.
The inherent ecological environment of mountainous regions is highly fragile, and the degree of sustainable development is low. There has not yet been a multi-phase ecological vulnerability evaluation (EVE) study based on remote sensing (RS) and GIS for mountainous provinces, for which there is an urgent need to establish a system that is appropriate, practicable and easily operated and applied. In this study, an integrated “RS and GIS + multi-phase land use/cover change (LUCC) + practically quantitative theory and methods of EVE” approach was adopted for analysis based on the interpretation results of five phases of the land use/land cover (LULC) RS images of Yunnan, with 129 counties being considered as the evaluation units. The organic combination of quantitative multi-index comprehensive evaluation (QMCE) and qualitative comprehensive analysis (QCA) methods was adopted to perform quantitative calculations of a system of county-level evaluation indicators which includes “innate” natural ecological vulnerability (INEV), land use ecological vulnerability (LUEV) and land cover ecological vulnerability (LCEV); the degree of ecological vulnerability (DEV) was assessed for the 129 counties within the province during the five study phases (1980, 1990, 2000, 2010 and 2020). The spatiotemporal variation characteristics and laws of DEV from 1980 to 2020 in the whole province and 129 counties were revealed, aiming to provide a basis for meeting the SDGs for mountainous provinces. The results are as follows: (1) Overall, INEV is high because of the high mountains and steep slopes, and the entire province is classified as “highly vulnerable” on average. In terms of counties, more than 79.07% are classified as “moderately vulnerable”, “highly vulnerable” and “very highly vulnerable”. (2) The degree of LUEV and LCEV caused by acquired human socioeconomic activities was higher in 1980. However, after a series of ecological measures in the past 40 years, the values of DEVLU and DEVLC in the whole province and counties in 2020 have decreased to different degrees. Accordingly, the degree of overall ecological vulnerability of Yunnan province and counties decreased significantly from 1980 to 2020. The basic law of change is that the number of counties with high DEV decreases significantly, while the number of counties with low DEV increases significantly. (3) The regional difference in the DEV of Yunnan province is large. In general, the degree of ecological vulnerability is lower in the southern, southwestern, western and central areas of Yunnan and higher in the northwest high mountain canyon, northeast mountain areas and east and southeast karst areas. (4) Overall, the DEV in Yunnan province is currently still high. There is an urgent need to enhance the construction of ecological civilization across the whole province and take effective measures to protect the ecological environment according to local conditions, so as to steadily reduce the DEV. Full article
(This article belongs to the Special Issue Application of GIScience and Remote Sensing in Biodiversity Conservation)
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