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Remote Sensing
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Monitoring and Modelling of Dynamics in Tropical Coastal Systems
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Monitoring and Modelling of Dynamics in Tropical Coastal Systems

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 12446

Special Issue Editors

Prof. Dr. Farid Dahdouh-Guebas

E-Mail Website
Guest Editor
Université Libre de Bruxelles - ULB, Systems Ecology and Resource Management Research Unit, Ave F.D. Roosevelt 50, CPi 264/1, B-1050 Brussels, Belgium
Interests: mangrove forests; vegetation dynamics; remote sensing; social-ecological systems
Dr. Viviana Otero

E-Mail Website
Guest Editor
Flanders Marine Institute, InnovOcean site, Wandelaarkaai 7, B-8400 Ostend, Belgium
Interests: remote sensing; unmanned aerial vehicles; modelling; differential equations; mangrove dynamics; plankton dynamics

Special Issue Information

Dear Colleagues,

Tropical coastal systems include mangrove forests, seagrass beds, rocky shores, coral reefs, and their associated waters. They face an uncertain future in our era of climate change and coastal development. Economic gains are often prioritised over the short- and long-term ecosystem functions and services that these tropical coastal systems provide.

In order to mitigate or halt losses in marine and terrestrial biodiversity, shoreline protection, carbon storage, and fisheries to name but a few, snap-shot assessments, monitoring and/or modelling and forecasting methods are essential. Interdisciplinary methods and platforms such as remote sensing and geographical information systems provide an excellent way to assess not only the sessile parts of coastal system (such as vegetation), but also the mobile parts (such as migrating organisms and sediments).

This Special Issue on monitoring and modelling of dynamics in tropical coastal systems aims to bring together studies on the different components of the various tropical coastal systems. It welcomes impact studies executed at one particular moment in time or as before-after comparisons, long-term monitoring of resident or migratory organisms such as plants and animals, modelling and forecasting of interactions between system components such as competition, and so forth.

Prof. Dr. Farid Dahdouh-Guebas
Dr. Viviana Otero
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

  • mangrove
  • seagrass
  • coral
  • rocky shore
  • tropical
  • impact
  • monitoring
  • modelling

Published Papers (3 papers)

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Research

22 pages, 59347 KiB  
Article
Using Historical Archives and Landsat Imagery to Explore Changes in the Mangrove Cover of Peninsular Malaysia between 1853 and 2018
by Lavaniadevi Gopalakrishnan, Behara Satyanarayana, Danyang Chen, Giovanna Wolswijk, A. Aldrie Amir, Michiel B. Vandegehuchte, Aidy B. Muslim, Nico Koedam and Farid Dahdouh-Guebas
Remote Sens. 2021, 13(17), 3403; https://doi.org/10.3390/rs13173403 - 27 Aug 2021
Cited by 9 | Viewed by 3958
Abstract
Archive records such as maps, journals, books, sketches, cadastre and notarial documents have been underutilised in describing past and present changes in ecological systems, such as mangrove forests. Historical records can be invaluable information sources for baseline establishment, to undertake long-term study on [...] Read more.
Archive records such as maps, journals, books, sketches, cadastre and notarial documents have been underutilised in describing past and present changes in ecological systems, such as mangrove forests. Historical records can be invaluable information sources for baseline establishment, to undertake long-term study on mangrove dynamics and enhance the historical land cover and land-use dynamics of a country. In this study, we explore these untapped information reservoirs, used complementarily with remote sensing techniques, to explain the dynamics of the mangrove systems in Peninsular Malaysia. The archives in the United Kingdom, the Netherlands, Malaysia and Singapore were explored and mined for related information on the mangrove systems in Peninsular Malaysia from past centuries. Most historical records found in this study were used to validate the mangrove presence in Peninsular Malaysia since 1853 while two records from 1944 and 1954 were used to quantify the mangrove cover extent. A significant finding of this study was the oldest record found in 1853 that attested to the presence of a mangrove system on the mainland Penang of Peninsular Malaysia which was not identified again as such in records post-1853. Remote sensing data, specifically Landsat images, were used to determine the mangrove extent in Peninsular Malaysia for the years 1988, 1992, 2002, 2012 and 2018. By complementing the historical records with remote sensing information, we were able to validate the mangrove presence in Peninsular Malaysia since 1853 and determine the gain/loss of mangrove systems over the last 74 years. Peninsular Malaysia has lost over 400 km2 of mangrove forests, equivalent to 31% of its original extent between 1944 and 2018. This is a significant loss for Peninsular Malaysia which has less than 1% mangrove cover of its total land area presently. Full article
(This article belongs to the Special Issue Monitoring and Modelling of Dynamics in Tropical Coastal Systems)
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22 pages, 7182 KiB  
Article
Distinguishing Original and Non-Original Stands at the Zhanjiang Mangrove National Nature Reserve (P.R. China): Remote Sensing and GIS for Conservation and Ecological Research
by Juan Durango-Cordero, Behara Satyanarayana, Jonathan Cheung-Wai Chan, Jan Bogaert and Farid Dahdouh-Guebas
Remote Sens. 2021, 13(14), 2781; https://doi.org/10.3390/rs13142781 - 15 Jul 2021
Cited by 3 | Viewed by 3021
Abstract
The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected [...] Read more.
The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected for Zhanjiang Mangrove National Nature Reserve (ZMNNR) in P.R. China. First, satellite images of Corona (1967) and GeoEye-1 (2009) were overlaid to identify original (1967) and non-original (2009) mangrove stands. Second, in both stands a total of 75 in situ plots (25 m2) were measured for ground-truthing of tree structural parameters including height, density, basal area and Complexity Index (CI). From temporal satellite data, we identify 236.12 ha of original mangrove and 567.88 ha of non-original mangrove in the reserve. Averaged measurements of the original mangrove stands, i.e., stem density (1164 nos. 0.1 ha−1), basal area (90.3 m2 0.1 ha−1) and CI (100.59), indicated that they were in a state of maturity and less disturbed compared to the non-original mangroves (density, 1241 nos. 0.1 ha−1; basal area, 4.92 m2 0.1 ha−1 and CI, 55.65). The Kruskal–Wallis test showed significant differentiation between the original and non-original mangrove tree structural parameters: Kandelia obovata’s density, X2 = 34.78, d.f. = 1, p = 0.001; basal area, X2 = 108.15, d.f. = 1, p = 0.001; Rizhopora stylosa’s density, X2 = 64.03, d.f. = 1, p = 0.001; basal area, X2 = 117.96, d.f. = 1, p = 0.001. The latter is also evident from the clustering plots generated from the Principal Component Analysis (PCA). Vegetation dynamics at the ZMNNR also enabled us to compare the species composition and distribution patterns with other Indo-West Pacific regions. Overall, the present study not only highlights the advantage of >50 years old satellite data but also provide a benchmark for future ecological research, conservation and management of the ZMNNR. Full article
(This article belongs to the Special Issue Monitoring and Modelling of Dynamics in Tropical Coastal Systems)
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28 pages, 10410 KiB  
Article
Eleven Years of Mangrove–Mudflat Dynamics on the Mud Volcano-Induced Prograding Delta in East Java, Indonesia: Integrating UAV and Satellite Imagery
by Sebrian Mirdeklis Beselly, Mick van der Wegen, Uwe Grueters, Johan Reyns, Jasper Dijkstra and Dano Roelvink
Remote Sens. 2021, 13(6), 1084; https://doi.org/10.3390/rs13061084 - 12 Mar 2021
Cited by 15 | Viewed by 4737
Abstract
This article presents a novel approach to explore mangrove dynamics on a prograding delta by integrating unmanned aerial vehicle (UAV) and satellite imagery. The Porong Delta in Indonesia has a unique geographical setting with rapid delta development and expansion of the mangrove belt. [...] Read more.
This article presents a novel approach to explore mangrove dynamics on a prograding delta by integrating unmanned aerial vehicle (UAV) and satellite imagery. The Porong Delta in Indonesia has a unique geographical setting with rapid delta development and expansion of the mangrove belt. This is due to an unprecedented mud load from the LUSI mud volcanic eruption. The mangrove dynamics analysis combines UAV-based Structure from Motion (SfM) photogrammetry and 11 years (2009–2019) satellite imagery cloud computing analysis by Google Earth Engine (GEE). Our analysis shows unique, high-spatiotemporal-resolution mangrove extent maps. The SfM photogrammetry analysis leads to a 3D representation of the mangrove canopy and an estimate of mangrove biophysical properties with accurate height and individual position of the mangroves stand. GEE derived vegetation indices resulted in high (three-monthly) resolution mangrove coverage dynamics over 11 years (2009–2019), yielding a value of more than 98% for the overall, producer and consumer accuracy. Combining the satellite-derived age maps and the UAV-derived spatial tree structure allowed us to monitor the mangrove dynamics on a rapidly prograding delta along with its structural attributes. This analysis is of essential value to ecologists, coastal managers, and policymakers. Full article
(This article belongs to the Special Issue Monitoring and Modelling of Dynamics in Tropical Coastal Systems)
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