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Remote Sensing in Applied Ecology (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".

Deadline for manuscript submissions: 20 May 2025 | Viewed by 4840

Special Issue Editor

Dr. Jun Ma

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Guest Editor
Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, No. 2005, Songhu Road, Shanghai 200438, China
Interests: landscape ecology; ecological remote sensing; geographic information system and application; land use
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

After the resounding success of our first edition, we are thrilled to launch the second edition of the Special Issue “Remote Sensing in Applied Ecology”.

Currently, the research in applied ecology tends to be performed on larger spatio-temporal scales, but traditional methods of ecological data acquisition (sample survey, site observation, etc.) struggle to meet the needs of applied ecology research for spatial and temporal data. As a piece of long-term and large-scale automatic observation equipment, a remote sensing sensor provides optimal conditions for solving the problem of data acquisition and processing in applied ecological research. This Special Issue focuses on the application of multi-source, long-term, and large-scale remote sensing data to solve the problems of applied ecology and aims to contribute to the further development of applied ecology.

This Special Issue mainly focuses on the application of multi-source, long-term, and large-scale remote sensing data to solve problems in applied ecology and utilizes remote sensing data and methods to facilitate progress in applied ecology.

Within this specialized subject, researchers are invited to focus on the following aspects:

  • Remote sensing data in forest ecosystem management and the application of carbon cycle assessments;
  • Remote sensing data in urban environment (heat, water, vegetation, etc.) monitoring and the evaluation of this application; and
  • Applications of remote sensing in the evaluation of regional sustainable development.

Dr. Jun Ma
Guest Editor

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. Remote Sensing 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 2700 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 applications
  • remote sensing data
  • spatio-temporal scales
  • ecosystems
  • sustainable development

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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19 pages, 11735 KiB  
Article
Global Distribution and Local Variation of Pre-Rain Green-Up in Tropical Dryland
by Shuyi Huang, Yirong Sang, Zhanzhang Cai and Feng Tian
Remote Sens. 2025, 17(8), 1377; https://doi.org/10.3390/rs17081377 - 12 Apr 2025
Viewed by 247
Abstract
Pre-rain green-up is a distinctive phenological phenomenon observed in arid and semi-arid regions, featuring the sprouting of plants before the onset of the rainy season. This phenomenon indicates the intricate controls of vegetation phenology other than precipitation, yet its global distribution patterns and [...] Read more.
Pre-rain green-up is a distinctive phenological phenomenon observed in arid and semi-arid regions, featuring the sprouting of plants before the onset of the rainy season. This phenomenon indicates the intricate controls of vegetation phenology other than precipitation, yet its global distribution patterns and underlying causes remain unclear. In this study, we used remotely sensed phenology and rainfall data to map the global distribution of pre-rain green-up vegetation for the first time in arid and semi-arid savanna areas. The results revealed that over one-third of pre-rain green-up vegetation is in mountainous regions. Furthermore, to explore the potential effect of groundwater accessibility on pre-rain green-up, we employed high-resolution imagery to quantify phenological parameters and analyzed the relationship between pre-rain green-up and elevation at the watershed scale in a typical mountainous pre-rain green-up region in Africa. We found that within the pre-rain green-up area, 60.64% of sub-watersheds show a significant negative correlation (p < 0.05) between the start of the season (SOS) and elevation, indicating that the SOS occurs earlier at higher elevations despite the complex spatial variability overall. Our study provides a global picture of the pre-rain green-up phenomenon in tropical drylands and suggests that tree internal water regulation mechanisms rather than groundwater accessibility control the pre-rain green-up. Full article
(This article belongs to the Special Issue Remote Sensing in Applied Ecology (Second Edition))
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21 pages, 5905 KiB  
Article
Study on the Evolution of the Mountain Ecological Environment Based on Remote Sensing and Water Footprints: Case Study of Northwestern Sichuan, Southwest China
by Lei Huang, Jiangtao Xiao, Zhiquan Zhou and Ping Ren
Remote Sens. 2024, 16(23), 4412; https://doi.org/10.3390/rs16234412 - 25 Nov 2024
Viewed by 695
Abstract
The unique geographical conditions in southwestern China lead to a fragile ecological balance and uneven geographical distribution of water resources. This study takes the Aba Tibetan and Qiang Autonomous Prefecture as its research subject, investigating the connection between water resources and the ecological [...] Read more.
The unique geographical conditions in southwestern China lead to a fragile ecological balance and uneven geographical distribution of water resources. This study takes the Aba Tibetan and Qiang Autonomous Prefecture as its research subject, investigating the connection between water resources and the ecological environment in the Aba Tibetan and Qiang Autonomous Prefecture, which is of paramount importance. Given this, the current study constructs the remote sensing ecological index and water footprint for the period spanning from 2000 through 2020, analyses the coordination status of the two by using the coupling coordination degree, and then combines it with a detector to determine the primary drivers impacting the state of the ecological environment. The outcomes reveal that: (1) The ecological environment of the Aba Tibetan and Qiang Autonomous Prefecture gradually improved from 2000 through 2020, and the excellent ecological environment area observed within the study’s scope is primarily focused in the eastern part. The poor ecological environment area is focused mainly in the northwestern part within the study’s scope. (2) The total water footprint of the Aba Tibetan and Qiang Autonomous Prefecture has increased year by year, with agricultural water consumption comprising an immense 78% proportion, dominating the total water footprint. (3) The coupled coordination degree of the remote sensing ecological index and the water footprint shows a rising trend in general, turning from a barely coordinated stage to an intermediate coordinated stage. (4) The geodetector results show that all factor interactions were dual-factor enhancement or nonlinear enhancement, and the WET, NDBSI and NDVI factors contributed the most. The above results can provide important guidance for utilizing water resources and protecting the ecological environment in the Aba Tibetan and Qiang Autonomous Prefecture. Full article
(This article belongs to the Special Issue Remote Sensing in Applied Ecology (Second Edition))
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25 pages, 28178 KiB  
Article
Assessment of Vegetation Drought Loss and Recovery in Central Asia Considering a Comprehensive Vegetation Index
by Wanqiang Han, Jianghua Zheng, Jingyun Guan, Yujia Liu, Liang Liu, Chuqiao Han, Jianhao Li, Congren Li, Xurui Mao and Ruikang Tian
Remote Sens. 2024, 16(22), 4189; https://doi.org/10.3390/rs16224189 - 10 Nov 2024
Viewed by 2540
Abstract
In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought’s impact [...] Read more.
In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought’s impact on vegetation may overlook vegetation features and introduce increased uncertainty. We applied the enhanced vegetation index (EVI), fraction of vegetation cover (FVC), gross primary production (GPP), leaf area index (LAI), and our constructed remote sensing vegetation index (RSVI) to assess vegetation drought in Central Asia. We analyzed the differences in drought experiences for different climatic regions and vegetation types and vegetation loss and recovery following drought events. The results indicate that during drought years (2012 and 2019), the differences in vegetation drought across climatic regions were considerable. The vegetation in arid, semiarid, and Mediterranean climate regions was more susceptible to drought. The different indices used to assess vegetation loss exhibited varying degrees of dynamic changes, with vegetation in a state of mild drought experiencing more significantly during drought events. The different vegetation assessment indices exhibited significant variations during the drought recovery periods (with a recovery period of 16 days: EVI of 85%, FVC of 50%, GPP of 84%, LAI of 61%, and RSVI of 44%). Moreover, the required recovery periods tended to decrease from arid to humid climates, influenced by both climate regions and vegetation types. Sensitivity analysis indicated that the primary climatic factors leading to vegetation loss varied depending on the assessment indices used. The proposed RSVI demonstrates high sensitivity, correlation, and interpretability to dry–wet variations and can be used to assess the impact of drought on vegetation. These findings are essential for water resource management and the implementation of measures that mitigate vegetation drought. Full article
(This article belongs to the Special Issue Remote Sensing in Applied Ecology (Second Edition))
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13 pages, 4959 KiB  
Technical Note
Spatiotemporal Variations in Compound Extreme Events and Their Cumulative and Lagged Effects on Vegetation in the Northern Permafrost Regions from 1982 to 2022
by Yunxia Dong, Guimin Liu, Xiaodong Wu, Lin Wang, Haiyan Xu, Sizhong Yang, Tonghua Wu, Evgeny Abakumov, Jun Zhao, Xingyuan Cui and Meiqi Shao
Remote Sens. 2025, 17(1), 169; https://doi.org/10.3390/rs17010169 - 6 Jan 2025
Cited by 1 | Viewed by 909
Abstract
The northern permafrost regions are increasingly experiencing frequent and intense extreme events, with a rise in the occurrence of compound extreme events. Many climate-related hazards in these areas are driven by such compound events, significantly affecting the stability and functionality of vegetation ecosystems. [...] Read more.
The northern permafrost regions are increasingly experiencing frequent and intense extreme events, with a rise in the occurrence of compound extreme events. Many climate-related hazards in these areas are driven by such compound events, significantly affecting the stability and functionality of vegetation ecosystems. However, the cumulative and lagged effects of compound extreme events on vegetation remain unclear, which may lead to an underestimation of their actual impacts. This study provides a comprehensive analysis of the spatiotemporal variations in compound extreme events and the vegetation response to these events in the northern permafrost regions from 1982 to 2022. The primary focus of this study is on examining the cumulative and lagged effects of compound extreme climate events on the Kernel Normalized Difference Vegetation Index (kNDVI) during the growing seasons. The results indicate that in high-latitude regions, the frequency of extreme high temperature–precipitation compound events and high temperature–drought compound events have increased in 58.0% and 67.0% of the areas, respectively. Conversely, the frequency of extreme low temperature–drought compound events and extreme low temperature–precipitation compound events has decreased in 70.6% and 57.2% of the areas, with the high temperature–drought compound events showing the fastest increase. The temporal effects of compound extreme events on kNDVI vary with vegetation type; they produce more cumulative and lagged effects compared with single extreme high-temperature events and fewer effects compared with single extreme precipitation events, with compound events significantly affecting forest and grassland ecosystems. Notably, extreme high temperature–precipitation compound events exhibit the strongest cumulative and lagged effects on vegetation, while extreme low temperature–drought compound events influence wetland and shrubland areas within the same month. This study underscores the importance of a multivariable perspective in understanding vegetation dynamics in permafrost regions. Full article
(This article belongs to the Special Issue Remote Sensing in Applied Ecology (Second Edition))
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