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Applications of Remote Sensing in Spatial Ecology
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Applications of Remote Sensing in Spatial Ecology

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 10690

Special Issue Editors

Dr. Eric Ariel L. Salas

E-Mail Website
Guest Editor
Agricultural Research and Development Program, College of Science and Engineering, Central State University, Wilberforce, OH, USA
Interests: environmental science; remote sensing; spatial ecology; biodiversity; GPS; GIS for natural resources; species distribution modeling; waveform LiDAR; hyperspectral imaging and spectroscopy; land use/land cover change monitoring; climate science
Dr. Kenneth G. Boykin

E-Mail Website
Guest Editor
Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces, NM, USA
Interests: herpetology; ecosystem services; spatial ecology

Special Issue Information

Dear Colleagues,

The study of spatial ecology offers a compelling opportunity to integrate robust ecological concepts with their application to habitat conservation and ecosystem services. Defining how a species responds to environmental conditions that affect its ecology is important for biodiversity preservation and the restoration of threatened habitats.

In recent years, spatial ecology has used remote sensing tools and datasets to analyze trends in a variety of research fields, including landscape ecology (e.g., the relationship of spatial patterns to ecological processes), conservation biology (flora and fauna), population ecology, and even carbon sequestration modeling.

This Special Issue welcomes articles that examine ecological topics using remote sensing datasets from satellites, aircraft, UAV, and other sources, including but not limited to:

  • Interactions between species, range analysis of several species, and how they use diverse habitats across landscapes;
  • Identification of the causes of species loss and the drivers of biodiversity change (e.g., climate, anthropogenic factors);
  • Development of algorithms for analyzing ecological data at various spatial scales;
  • Natural resource management (e.g., forestry, watershed, soil) and ecologically based agriculture concerns;
  • Numerous tools, such as Google Earth Engine.

Dr. Eric Ariel L. Salas
Dr. Kenneth G. Boykin
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. 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

  • species distribution modeling
  • ecosystem services
  • biodiversity conservation
  • spatial ecology
  • remote sensing

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (4 papers)

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Research

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29 pages, 11308 KiB  
Article
Assessing the Impact of Climate and Human Activities on Ecosystem Services in the Loess Plateau Ecological Screen, China
by Changwen Wei, Jiaqin Zeng, Jiping Wang, Xuebing Jiang, Yongfa You, Luying Wang, Yiming Zhang, Zhihong Liao and Kai Su
Remote Sens. 2023, 15(19), 4717; https://doi.org/10.3390/rs15194717 - 26 Sep 2023
Cited by 5 | Viewed by 2293
Abstract
The ecosystem services (ES) can be influenced by various environmental factors. In order to efficiently allocate resources and manage ecosystems, it is important to understand the mechanisms by which these environmental effects impact the interactions and trade-offs among different ES. While previous studies [...] Read more.
The ecosystem services (ES) can be influenced by various environmental factors. In order to efficiently allocate resources and manage ecosystems, it is important to understand the mechanisms by which these environmental effects impact the interactions and trade-offs among different ES. While previous studies have primarily examined the impact of individual environmental factors on ES, the intricate mechanisms underlying the effects of multiple environmental factors have been largely overlooked. In this study, we adopted a path analysis approach that considered interactions among explanatory variables. We analyzed multiple geospatial datasets from various sources, including remote sensing and climate data, to examine the main drivers—precipitation, temperature, FVC (fractional vegetation cover), NPP (net primary productivity), human activities, and altitude—affecting five ecosystem services: carbon sequestration service (C), habitat provision service (HP), soil conservation service (SCS), sand-stabilization service (SSS), and water conservation service (WCS) in arid and semi-arid mountainous regions. Our investigation found that all five ES have shown an upward trajectory over the past two decades. The most significant growth was observed in C, which increased by 39.4%. Among the environmental factors examined, precipitation has been identified as the predominant factor influencing the ES and the synergies and trade-offs among ES. The influence of precipitation on SCS reached a coefficient of 0.726. Human activity factors had the greatest influence on HP of the five ES with a path coefficient of 0.262. Conversely, temperature exhibited a suppressive influence on ES. The impact of factors such as NPP and altitude on ES was comparatively modest. Notably, human activities assumed a substantial contributory role in shaping the relationship encompassing WCS. It is worth noting that individual factors exerted differential effects on ES along distinct environmental gradients, including anthropogenic gradients. In this context, the combination of high altitude and substantial FVC demonstrated a notable contribution to WCS. Our study can provide valuable insights for the management of ES which can be utilized to optimize the regulation of the Loess Plateau Ecological Screen (LPES) ecological construction and promote regional sustainable development. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Spatial Ecology)
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25 pages, 8624 KiB  
Article
How to Optimize High-Value GEP Areas to Identify Key Areas for Protection and Restoration: The Integration of Ecology and Complex Networks
by Luying Wang, Siyuan Wang, Xiaofei Liang, Xuebing Jiang, Jiping Wang, Chuang Li, Shihui Chang, Yongfa You and Kai Su
Remote Sens. 2023, 15(13), 3420; https://doi.org/10.3390/rs15133420 - 6 Jul 2023
Cited by 4 | Viewed by 2495
Abstract
Identifying and protecting key sites of ecological assets and improving spatial connectivity and accessibility are important measures taken to protect ecological diversity. This study takes Guangxi as the research area. Based on the gross ecosystem product (GEP), the ecological source is identified, and [...] Read more.
Identifying and protecting key sites of ecological assets and improving spatial connectivity and accessibility are important measures taken to protect ecological diversity. This study takes Guangxi as the research area. Based on the gross ecosystem product (GEP), the ecological source is identified, and the initial ecological network (EN) is constructed by identifying the ecological corridor with the minimum cumulative resistance model. The internal defects of the initial ecological network are extracted using the circuit theory, the priority areas for restoration and protection with clear spatial positions are determined according to the complex network analysis, and the network’s performance before and after optimization is comprehensively evaluated. The results show that 456 initial ecological sources and 1219 ecological corridors have been identified, forming the initial ecological network of Guangxi. Based on the circuit theory, 168 ecological barriers, 83 ecological pinch points, and 71 ecological stepping stones were extracted for network optimization. After optimizing the ecological network, there are 778 ecological sources with a total area of 73,950.56 km2 and 2078 ecological corridors with a total length of 23,922.07 km. The GEP of the optimized structure is 13.33% higher than that of the non-optimized structure. The priority areas for protection are distributed in a large area, and the attached GEP reaches USD 118 billion, accounting for 72% of the total GEP attached to the optimized ecological source area. The priority areas for restoration are scattered in small patches, with a GEP of USD 19.27 billion. The robustness and connectivity of the optimized ecological network have been improved obviously. This study attempts to identify key sites of ecological assets and the priority regions for restoration and conservation using genuine geographical location and reference materials for regional ecological network optimization and implementation. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Spatial Ecology)
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16 pages, 3766 KiB  
Article
Comparison of Forest Restorations with Different Burning Severities Using Various Restoration Methods at Tuqiang Forestry Bureau of Greater Hinggan Mountains
by Guangshuai Zhao, Erqi Xu, Xutong Yi, Ye Guo and Kun Zhang
Remote Sens. 2023, 15(10), 2683; https://doi.org/10.3390/rs15102683 - 22 May 2023
Cited by 5 | Viewed by 1769
Abstract
Forest disturbances and restoration are key processes in carbon transmission between the terrestrial surface and the atmosphere. In boreal forests, fire is the most common and main disturbance. The reconstruction process for post-disaster vegetation plays an essential role in the restoration of a [...] Read more.
Forest disturbances and restoration are key processes in carbon transmission between the terrestrial surface and the atmosphere. In boreal forests, fire is the most common and main disturbance. The reconstruction process for post-disaster vegetation plays an essential role in the restoration of a forest’s structure and function, and it also maintains the ecosystem’s health and stability. Remote sensing monitoring could reflect dynamic post-fire features of vegetation. However, there are still major differences in the remote sensing index in terms of regional feasibility and sensibility. In this study, the largest boreal primary coniferous forest area in China, the Greater Hinggan Mountains forest area, was chosen as the sampling area. Based on time series data from Landsat-5 TM surface reflectance (SR) and data obtained from sample plots, the burned area was extracted using the Normalized Burn Ratio (NBR). We used the pre- and post-fire difference values (dNBR) and compared them with survey data to classify the burn severity level. The Normalized Difference Vegetation Index (NDVI) (based on spectrum combination) and the Disturbance Index (DI) (based on Tasseled-Cap transformation) were chosen to analyze the difference in the degree of burn severity and vegetation restoration observed using various methods according to the sequential variation feature from 1986 to 2011. The results are as follows: (1) The two remote sensing indexes are both sensitive to fire and the burn severity level. When a fire occurred, the NDVI value for that year decreased dramatically while the DI value increased sharply. Alongside these findings, we observed that the rangeability and restoration period of the two indexes is significantly positively correlated with the degree of burn severity. (2) According to these two indexes, natural vegetation restoration was faster than the restoration achieved using artificial methods. However, compared with the NDVI, the DI showed a clearer improvement in restoration, as the restoration period the DI could evaluate was longer in two different ways: the NDVI illustrated great changes in the burn severity in the 5 years post-fire, while the DI was able to show the changes for more than 20 years. Additionally, from the DI, one could identify felling activities carried out when the artificial restoration methods were initially applied. (3) From the sample-plot data, there were few differences in forest canopy density—the average was between 0.55 and 0.6—between the diverse severity levels and restoration methods after 33 years of recovery. The average diameter at breast height (DBH) and height values of trees in naturally restored areas decreased with the increase in burn severity, but the values were obviously higher than those in artificially restored areas. This indicates that both the burn severity level and restoration methods have important effects on forest restoration, but the results may also have been affected by other factors. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Spatial Ecology)
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Review

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29 pages, 5844 KiB  
Review
A Review of Forest Height Inversion by PolInSAR: Theory, Advances, and Perspectives
by Cheng Xing, Hongmiao Wang, Zhanjie Zhang, Junjun Yin and Jian Yang
Remote Sens. 2023, 15(15), 3781; https://doi.org/10.3390/rs15153781 - 29 Jul 2023
Cited by 8 | Viewed by 3006
Abstract
Forests cover approximately one-third of the Earth’s land surface and constitute the core region of the carbon cycle on Earth. The paramount importance and multi-purpose applications of forest monitoring have gained widespread recognition over recent decades. Polarimetric synthetic aperture radar interferometry (PolInSAR) has [...] Read more.
Forests cover approximately one-third of the Earth’s land surface and constitute the core region of the carbon cycle on Earth. The paramount importance and multi-purpose applications of forest monitoring have gained widespread recognition over recent decades. Polarimetric synthetic aperture radar interferometry (PolInSAR) has been demonstrated as a promising technique to retrieve the forest height over large areas with a limited cost. This paper presents an overview of forest height inversion (FHI) techniques based on PolInSAR data. Firstly, we introduce the basic theories of PolInSAR and FHI procedures. Next, we review the established data-based algorithms for single-baseline data and describe innovative techniques related to multi-baseline data. Then, the model-based algorithms are also introduced with their corresponding forest scattering models under multiple data acquisition modes. Subsequently, a case study is presented to demonstrate the applicable scenarios and advantages of different algorithms. Model-based algorithms can provide accurate results when the scene and forest properties are well understood and the model assumptions are valid. Data-based algorithms, on the other hand, can handle complex scattering scenarios and are generally more robust to uncertainties in the input parameters. Finally, the prospect of forest height inversion was analyzed. It is our hope that this review will provide guidelines to future researchers to enhance further FHI algorithmic developments. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Spatial Ecology)
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