Remote Sensing

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Prof. Laurence Hubert-Moy

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Guest Editor

LETG - UMR CNRS 6554/University of Rennes, Rennes, France
Interests: remote sensing; environmental modeling; wetlands; image analysis

Dr. Sébastien Rapinel

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Guest Editor

LETG - UMR CNRS 6554/University of Rennes, Rennes, France
Interests: wetlands; natural vegetation; remote sensing; object-based analysis; conservation

Special Issue Information

Dear Colleagues,

The Habitat Directive (92/43/EEC) determines the rules for plant biodiversity conservation in Europe, with the requirements for natural habitats’ conservation status being updated every 6 years since 1995. However, the major current issues for its applicability in each member state are still related to: (1) The definition and interpretation of the 233 habitat types listed in Annex I of the Habitat Directive, and (2) the mapping of habitat types on national coverage.

Recent advances in numerical analysis of vegetation data and ecological modeling, as well as the extensive availability of Earth Observation data with high temporal and spatial resolutions, provide a promising avenue for an operational implementation of the Habitat Directive. On one hand, predictive modeling of plant species and communities is an approach rapidly increasing in popularity in European biogeographical regions. On the other hand, new low-cost or free satellite time-series with high spatial and spectral resolutions, such as Sentinel-1/2 data, are available to monitor natural habitats. Links between remote sensing and ecological research communities are now strengthening with the integration of reference vegetation databases (European Vegetation Archive, VegFrance, etc.) in remote-sensing-based models (machine learning classification, fuzzy approach, optimal transport approach, time-series classifiers, etc.).

In this context, the French Ministry of the Environment launched the CarHAB program, which aims to map terrestrial natural habitats over national territory using reference vegetation data and Earth Observation images. In this Special Issue, we invite original contributions in one or more of the topics below. Both specific cases and comparative studies carried out in European regions and their overseas territories are encouraged. Typical papers are expected to address the following topics:

Mapping and monitoring of habitat conservation status;
Integrating satellite data in ecosystem modeling;
Multiscale analysis (plant species/vegetal associations/habitats/vegetation series);
Development of vegetation typologies;
Reproducibility of satellite-based classification models;
Integrating vegetation reference data in satellite images classification (unbalanced classes, weak sampling, temporal shifts, etc.).

Prof. Laurence Hubert-Moy
Dr. Sébastien Rapinel
Guest Editors

Manuscript Submission Information

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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

Plant communities
Essential Biodiversity Variables (EBVs)
Ecological Modelling
Big data
Uncertainty
National mapping
Change detection
Long-term monitoring
Remote sensing
Satellite time-series
Conservation status
Natura 2000

Published Papers (1 paper)

Research

36 pages, 8447 KiB

Open AccessArticle

Mapping Succession in Non-Forest Habitats by Means of Remote Sensing: Is the Data Acquisition Time Critical for Species Discrimination?

by Katarzyna Osińska-Skotak, Aleksandra Radecka, Hubert Piórkowski, Dorota Michalska-Hejduk, Dominik Kopeć, Barbara Tokarska-Guzik, Wojciech Ostrowski, Adam Kania and Jan Niedzielko

Remote Sens. 2019, 11(22), 2629; https://doi.org/10.3390/rs11222629 - 10 Nov 2019

Cited by 12 | Viewed by 2782

Abstract

The process of secondary succession is one of the most significant threats to non-forest (natural and semi-natural open) Natura 2000 habitats in Poland; shrub and tree encroachment taking place on abandoned, low productive agricultural areas, historically used as pastures or meadows, leads to changes to the composition of species and biodiversity loss, and results in landscape transformations. There is a perceived need to create a methodology for the monitoring of vegetation succession by airborne remote sensing, both from quantitative (area, volume) and qualitative (plant species) perspectives. This is likely to become a very important issue for the effective protection of natural and semi-natural habitats and to advance conservation planning. A key variable to be established when implementing a qualitative approach is the remote sensing data acquisition date, which determines the developmental stage of trees and shrubs forming the succession process. It is essential to choose the optimal date on which the spectral and geometrical characteristics of the species are as different from each other as possible. As part of the research presented here, we compare classifications based on remote sensing data acquired during three different parts of the growing season (spring, summer and autumn) for five study areas. The remote sensing data used include high-resolution hyperspectral imagery and LiDAR (Light Detection and Ranging) data acquired simultaneously from a common aerial platform. Classifications are done using the random forest algorithm, and the set of features to be classified is determined by a recursive feature elimination procedure. The results show that the time of remote sensing data acquisition influences the possibility of differentiating succession species. This was demonstrated by significant differences in the spatial extent of species, which ranged from 33.2% to 56.2% when comparing pairs of maps, and differences in classification accuracies, which when expressed in values of Cohen’s Kappa reached ~0.2. For most of the analysed species, the spring and autumn dates turned out to be slightly more favourable than the summer one. However, the final recommendation for the data acquisition time should take into consideration the phenological cycle of deciduous species present within the research area and the abiotic conditions. Full article

(This article belongs to the Special Issue Remote Sensing for EU Habitats Directive Application)

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