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Remote Sensing
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Remote Sensing in Mangroves III
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Special Issue "Remote Sensing in Mangroves III"

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

Deadline for manuscript submissions: 30 June 2023 | Viewed by 2049

Special Issue Editor

Dr. Chandra Giri

E-Mail Website
Guest Editor
Office of Research and Development, United States Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA
Interests: mangrove forests mapping and monitoring using high-resolution satellite data; global and continental land cover mapping and monitoring using multi-spectral, multi-temporal, and multi-platform remotely sensed data; image pre-processing, classification, and validation using cloud computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to overwhelming support and interest from all of you, we are introducing the 3rd edition of the Special Issue on “Remote Sensing in Mangroves” https://www.mdpi.com/journal/remotesensing/special_issues/remote_sensing_mangroves. I would like to thank all the authors and co-authors in the previous editions, who made Volumes 1 and 2 a grand success.   

Mangrove forests are in constant flux due to both natural and anthropogenic forces. The changing mangroves will have important consequences to coastal communities. At present, the conversion of mangroves to other land uses is the dominant factor responsible for the change; however, sea level rise and natural disasters such as hurricanes are becoming increasingly dominant. Observation and monitoring of the distribution and dynamics of mangroves is central to a wide range of scientific investigations conducted in both terrestrial and marine ecosystems.

Recent advancements in remote sensing data availability, image-processing methodologies, computing and information technology, and human resources development have provided an opportunity to observe and monitor mangroves from local to global scales on a regular basis. The spectral, spatial, and temporal resolution of remote sensing data and their availability have improved, making it possible to observe and monitor mangroves in unprecedented spatial thematic and temporal detail. Novel remote sensing platforms such as unmanned aerial vehicles, and emerging sensors such as Fourier transform infrared spectroscopy and Lidar can now be used for mangrove monitoring. Furthermore, it is now possible to store and analyze large volumes of data using cloud computing.

The journal Remote Sensing announces a Special Issue dedicated to the observation and monitoring of mangroves using remote sensing from local to global scales. The Special Issue will broadly cover the application of remote sensing using optical (multi-spectral and hyperspectral), radar, and Lidar data obtained from multiple platforms including ground, air, and space. Research papers are expected to use the latest techniques to acquire, manage, exploit, process, and analyze a wide variety of remote sensing data for mangrove forest applications. Both research papers and innovative review papers are invited.

High-quality contributions emphasizing (but not limited to) the topic areas listed below are solicited for the Special Issue:

  • Application of aerial and ground remote sensing, photography, multi-spectral, multi-temporal and multi-resolution, satellite data, synthetic aperture radar (SAR) data, hyperspectral data, and Lidar data.
  • Application of advanced image pre-processing for geometric, radiometric, and atmospheric correction, cloud removal, and image mosaicking.
  • Application of advanced image classification and validation techniques including supervised and unsupervised classification.
  • Application of advanced image storage, retrieval, processing, and distribution techniques such as networked data transmission and distributed computing.
  • Application of remote sensing to derive spatio-temporal information on mangrove forests distribution, species discrimination, forest density, forest health, mangrove expansion and contraction, and other ongoing changes in mangrove ecosystems.

Dr. Chandra Giri
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 2500 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 forests
  • mangrove change
  • mapping
  • monitoring
  • remote sensing
  • image processing

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Published Papers (2 papers)

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Article
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA)
by
Hannah C. Turner
,
Gillian L. Galford
,
Norgis Hernandez Lopez
,
Armando Falcón Méndez
,
Daily Yanetsy Borroto-Escuela
,
Idania Hernández Ramos
and
Patricia González-Díaz
Remote Sens. 2023, 15(10), 2495; https://doi.org/10.3390/rs15102495 - 09 May 2023
Viewed by 909
Abstract
Mangrove forests provide a range of ecosystem services but may be increasingly threatened by climate change in the North Atlantic due to high-intensity storms. Hurricane Irma (Category 5) hit the northern coast of Cuba in September 2017, causing widespread damage to mangroves; losses [...] Read more.
Mangrove forests provide a range of ecosystem services but may be increasingly threatened by climate change in the North Atlantic due to high-intensity storms. Hurricane Irma (Category 5) hit the northern coast of Cuba in September 2017, causing widespread damage to mangroves; losses have not yet been extensively documented due to financial and logistical constraints for local scientists. Our team estimated Irma’s impacts on Cuban ecosystems in a coastal and upland study area spanning over 1.7 million ha. We developed a multi-resolution time series “vegetation anomaly” approach, where post-disturbance observations in photosynthetically active vegetation (Enhanced Vegetation Index, EVI) were normalized to the reference period (dry season mean over a historical time series). The Hurricane Disturbance Vegetation Anomaly (HDVA) was used to estimate the extent, severity, and temporal patterns of ecological changes with Sentinel-2 and MODIS data and used vicarious validation with microsatellite interpretation (Planet). HDVA values were classed to convey qualitative labels useful for local scientists: (1) Catastrophic, (2) Severe, (3) Moderate, (4) Mild, and (5) No Loss. Sentinel-2 had a limited reference period (2015–2017) compared to MODIS (2000–2017), yet the HDVA patterns were similar. Mangrove and wetlands (>265,000 ha) sustained widespread damages, with a staggering 78% showing damage, largely severe to catastrophic (0–0.81 HDVA; >207,000 ha). The damaged area is 24 times greater than impacts from Irma as documented elsewhere. Caguanes National Park (>8400 ha, excluding marine zones) experienced concentrated, severe mangrove and wetland damages (nearly 4000 ha). The phenological declines from Irma’s impacts took up to 17 months to fully actualize, a much longer period than previously suggested. In contrast, dry forests saw rapid green flushes post-hurricane. With the increase of high-intensity storm events and other threats to ecosystems, the HDVA methods outlined here can be used to assess intense to low-level damages. Full article
(This article belongs to the Special Issue Remote Sensing in Mangroves III)
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Article
Global Mangrove Watch: Monthly Alerts of Mangrove Loss for Africa
by
Pete Bunting
,
Lammert Hilarides
,
Ake Rosenqvist
,
Richard M. Lucas
,
Edmond Kuto
,
Yakhya Gueye
and
Laye Ndiaye
Remote Sens. 2023, 15(8), 2050; https://doi.org/10.3390/rs15082050 - 12 Apr 2023
Viewed by 842
Abstract
Current mangrove mapping efforts, such as the Global Mangrove Watch (GMW), have focused on providing one-off or annual maps of mangrove forests, while such maps may be most useful for reporting regional, national and sub-national extent of mangrove forests, they may be of [...] Read more.
Current mangrove mapping efforts, such as the Global Mangrove Watch (GMW), have focused on providing one-off or annual maps of mangrove forests, while such maps may be most useful for reporting regional, national and sub-national extent of mangrove forests, they may be of more limited use for the day-to-day management of mangroves and for supporting the Global Mangrove Alliance (GMA) goal of halting global mangrove loss. To this end, a prototype change mangrove loss alert system has been developed to identify mangrove losses on a monthly basis. Implemented on the Microsoft Planetary Computer, the Global Mangrove Watch v3.0 mangrove baseline extent map for 2018 was refined and used to define the mangrove extent mask under which potential losses would be identified. The study period was from 2018 to 2022 due to the availability of Sentinel-2 imagery used for the study. The mangrove loss alert system is based on optimised normalised difference vegetation index (NDVI) thresholds used to identify mangrove losses and a temporal scoring system to filter false positives. The mangrove loss alert system was found to have an estimated overall accuracy of 92.1%, with the alert commission and omission estimated to be 10.4% and 20.6%, respectively. Africa was selected for the mangrove loss alert system prototype, where significant losses were identified in the study period, with 90% of the mangrove loss alerts identified in Nigeria, Guinea-Bissau, Madagascar, Mozambique and Guinea. The primary drivers of these losses ranged from economic activities that dominated West Africa and Northern East Africa (mainly agricultural conversion and infrastructure development) to climatic in Southern East Africa (primarily storm frequency and intensity). The production of the monthly mangrove loss alerts for Africa will be continued as part of the wider Global Mangrove Watch project, and the spatial coverage is expected to be expanded to other regions over the coming months and years. The mangrove loss alerts will be published on the Global Mangrove Watch online portal and updated monthly. Full article
(This article belongs to the Special Issue Remote Sensing in Mangroves III)
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