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Applications of Remote Sensing in Ecosystem Functioning and Biodiversity Monitoring

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 4598

Special Issue Editors


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Guest Editor
Forest Science and Technology Center of Catalonia, Crta. Antiga St Llorenç de Morunys km 2, 25280 Solsona, Catalonia, Spain
Interests: landscape ecology; fire ecology; environmental management; conservation biology; remote sensing; geographic information science
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GRUMETS Research Group, CREAF Bellaterra (Cerdanyola del Vallès), E08193 Catalonia, Spain
Interests: spatial analysis geostatistics; remote sensing applications to land cover dynamics and monitoring of vegetation and water resources
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Research Center in Biodiversity and Genetic Resources (CIBIO), University of Porto, Porto, Portugal
Interests: global change; biodiversity monitoring; landscape ecology, ecoinformatics; species distributions; remote sensing; earth observation
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1. Assoc. Prof., CIBIO/InBIO—Research Centre in Biodiversity and Genetic Resources, Universidade do Porto, Campus de Vairão, Rua Padre Armando Quintas, 7, 4485-661 Vairão, Portugal
2. Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua Campo Alegre s/n, 4169-007 Porto, Portugal
Interests: environmental management; remote sensing; ecosystem services; ecological modeling; predictive ecology
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Area of Ecology, Department of Botany, Ecology and Plant Physiology, Faculty of Sciences, University of Cordoba, Campus de Rabanales, 14014 Córdoba, Spain
Interests: biodiversity monitoring; earth observation; ecological niche modelling; ecosystem functioning; plant ecology
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Botany Department. Faculty of Sciences Av. Fuentenueva, s/n. 18071. Granada. Spain
Interests: botany; remote sensing; ecosystem services; Earth observation; ecosystem services; ecosystem ecology
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Special Issue Information

Dear Colleagues,

Remote sensing has emerged as a valuable tool for monitoring ecosystem functioning and biodiversity. The synergies between the increasingly available open access satellite images and cloud-based platforms for planetary-scale geospatial analysis offer an unprecedented opportunity to incorporate ecosystem processes and disturbances that have been so far largely neglected in ecological modeling and monitoring. Remote sensing enables the quantification and monitoring of various ecosystem properties, attributes, and functions, including primary productivity, carbon dynamics, water availability, and nutrient cycling at various spatial and temporal scales. As technology advances and remote sensing data become increasingly accessible, the integration of remote sensing with other ecological disciplines will continue to advance our understanding of ecosystems and support effective conservation and management strategies.

This Special Issue is devoted to exploring ‘Applications of remote sensing in ecosystem functioning and biodiversity monitoring’. We extend an invitation to researchers to submit innovative, integrative, and cross-scale approaches that will enhance our ability to monitor biodiversity and ecosystems holistically and functionally across terrestrial, freshwater, and marine environments. We enthusiastically welcome studies that integrate remote sensing products of surface energy balance and nutrient cycles with state-of-the-art techniques to assess and comprehend ecosystem functioning at various spatial and temporal scales.

In particular, we encourage submissions that utilize high-temporal-resolution data to map and monitor seasonal dynamics and interannual changes in diverse aspects of ecosystem functioning and biodiversity patterns. Such contributions may encompass mapping intra- and inter-annual land cover and vegetation dynamics, quantifying changes in carbon and nutrient cycling (e.g., primary productivity), and investigating various aspects of biodiversity such as phenological and seasonal dynamics, as well as abrupt shifts in habitat availability and population dynamics.

We highly encourage contributions that address the integration of different remote sensing sensors and data with other valuable sources, such as ground-based observations, citizen science data, or genetic and molecular data. The fusion of multiple data streams enables researchers to augment the monitoring capacity of ecosystem functioning and biodiversity across different spatiotemporal scales, enabling a more comprehensive understanding of ecological processes.

Dr. Adrián Regos
Dr. Lluís Pesquer Mayos
Dr. João Gonçalves
Dr. João P. Honrado
Dr. Salvador Arenas-Castro
Prof. Dr. Domingo Alcaraz-Segura
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

  • primary productivity
  • surface energy balance
  • water and nutrient cycle
  • seasonal dynamics and abrupt changes
  • intra- and interannual changes in species distributions
  • ecosystem functional characterization at different spatial scales

Published Papers (2 papers)

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19 pages, 14020 KiB  
Article
Aboveground Biomass Estimation and Time Series Analyses in Mongolian Grasslands Utilizing PlanetScope Imagery
by Margad-Erdene Jargalsaikhan, Dorj Ichikawa, Masahiko Nagai, Tuvshintogtokh Indree, Vaibhav Katiyar, Davaagerel Munkhtur and Erdenebaatar Dashdondog
Remote Sens. 2024, 16(5), 869; https://doi.org/10.3390/rs16050869 - 29 Feb 2024
Viewed by 2376
Abstract
Mongolia, situated in central Asia and bordered by Russia to the north and China to the south, experiences a semi-arid climate across most of its territory. Grasslands are pivotal in Mongolia’s agricultural sustainability and food security, facing rapid changes in the last two [...] Read more.
Mongolia, situated in central Asia and bordered by Russia to the north and China to the south, experiences a semi-arid climate across most of its territory. Grasslands are pivotal in Mongolia’s agricultural sustainability and food security, facing rapid changes in the last two decades that underscore the ongoing need for innovative approaches to assess vegetation conditions. This study aims to evaluate grassland biomass measurement and prediction through the analysis of high-resolution satellite data. By conducting a time series assessment of grazing-induced changes in vegetation dynamics at the long-term monitoring sites of the Botanic Garden and Research Institute, Mongolian Academy of Sciences, we seek to refine our understanding. The investigation covers biomass estimation across various Mongolian grassland landscapes, encompassing desert, steppe, and mountain regions. Spanning the grassland growing season from May 2020 to October 2023, the research leveraged diverse ground data types, including surface reflectance measurements, geographic coordinates for satellite data correction, and aboveground dry biomass. These components were instrumental in developing a biomass estimation model reliant on establishing correlations between the satellite-derived Normalized Difference Vegetation Index and biomass. The predicted biomass facilitated the time series map analysis and dynamic analysis. The PlanetScope surface reflectance correlates strongly at 0.97 with field measurements, indicating robust relations. Biomass and the Normalized Difference Vegetation Index show correlations of 0.82 for dry grassland, 0.80 for mountain grassland, and 0.65 for desert grassland, with a combined correlation coefficient of 0.62, revealing distinct characteristics across these grasslands. Time series dynamic analysis reveals rising biomass differences between grazed and ungrazed areas, suggesting potential grassland degradation. Variations in the slope coefficient of biomass differences among grassland types indicate differing degradation patterns, emphasizing the need for effective grazing management practices to sustain and conserve Mongolian grasslands. This highlights the potential of remote sensing in monitoring and managing grassland ecosystems. Full article
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15 pages, 3716 KiB  
Technical Note
Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity
by Lingling Liu, Jeffrey R. Smith, Amanda H. Armstrong, Domingo Alcaraz-Segura, Howard E. Epstein, Alejandra Echeverri, Kelley E. Langhans, Rafael J. P. Schmitt and Rebecca Chaplin-Kramer
Remote Sens. 2023, 15(23), 5593; https://doi.org/10.3390/rs15235593 - 1 Dec 2023
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Abstract
Satellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and as a predictor for [...] Read more.
Satellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and as a predictor for ecosystem functioning, ecosystem services, and resilience. However, the impact of key methodological choices on patterns of EFTs and EFD have not been formally assessed. Using Costa Rica as a study system, we compared EFTs and EFD, derived from MODIS and Landsat data using different methodological assumptions, at both national and local extents. Our results showed that the regional spatial patterns of EFTs and EFD derived from 250 m MODIS and 30 m Landsat are notably different. The selection of sensors for deriving EFTs and EFD is dependent on the study area, data quality, and the research objective. Given its finer spatial resolution, Landsat has greater capacity to differentiate more EFTs than MODIS, though MODIS could be a better choice in frequently cloudy areas due to its shorter revisiting time. We also found that the selection of spatial extent used to derive EFD is critical, as smaller extents (e.g., at a local rather than a national scale) can show much higher diversity. However, diversity levels derived at smaller extents appear to be nested within the diversity levels derived at larger extents. As EFTs and EFD continue to develop as a tool for ecosystem ecology, we highlight the important methodological choices to ensure that these metrics best fit research objectives. Full article
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