Use of satellite remote sensing for coastal conservation in the Eastern African Coast: advantages and shortcomings

Ferreira, Maria Adelaide; Andrade, Francisco; Mendes, Ricardo Manuel Nogueira; Paula, José

doi:10.5721/eujrs20124526

Cited by 14 publications

(3 citation statements)

References 15 publications

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“…The applicability of Landsat data for mapping the distribution and ecological characteristics of mangroves at global [20], national [24,[38][39][40] and-despite its moderate, 30 m spatial resolutionlocalised [27,41,42] scales is well proven. With an archive stretching back to the 1970s [43], Landsat data are also ideal for analysing and monitoring the dynamics of wetlands and their surrounding ecosystems [44][45][46][47].…”

Section: Remote Sensing Methodsmentioning

confidence: 99%

Mangrove Carbon Stocks and Ecosystem Cover Dynamics in Southwest Madagascar and the Implications for Local Management

Benson

Glass

Jones

et al. 2017

Forests

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Abstract:Of the numerous ecosystem services mangroves provide, carbon storage is gaining particular attention for its potential role in climate change mitigation strategies. Madagascar contains 2% of the world's mangroves, over 20% of which is estimated to have been deforested through charcoal production, timber extraction and agricultural development. This study presents a carbon stock assessment of the mangroves in Helodrano Fagnemotse in southwest Madagascar alongside an analysis of mangrove land-cover change from 2002 to 2014. Similar to other mangrove ecosystems in East Africa, higher stature, closed-canopy mangroves in southwest Madagascar were estimated to contain 454.92 (±26.58) Mg·C·ha −1 . Although the mangrove extent in this area is relatively small (1500 ha), these mangroves are of critical importance to local communities and anthropogenic pressures on coastal resources in the area are increasing. This was evident in both field observations and remote sensing analysis, which indicated an overall net loss of 3.18% between 2002 and 2014. Further dynamics analysis highlighted widespread transitions of dense, higher stature mangroves to more sparse mangrove areas indicating extensive degradation. Harnessing the value that the carbon stored within these mangroves holds on the voluntary carbon market could generate revenue to support and incentivise locally-led sustainable mangrove management, improve livelihoods and alleviate anthropogenic pressures.

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Section: Remote Sensing Methodsmentioning

confidence: 99%

Mangrove Carbon Stocks and Ecosystem Cover Dynamics in Southwest Madagascar and the Implications for Local Management

Benson

Glass

Jones

et al. 2017

Forests

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“…Techniques for mapping mangrove extent are clearly varied. In many cases, approaches exclusively using optical remote sensing [9,30] to map mangroves are insufficient due to persistent cloud cover in the tropics, the primary location of mangrove forests. Cloud-free optical imagery for mangrove mapping on an annual or subannual basis can be difficult to obtain [31].…”

Section: Introductionmentioning

confidence: 99%

Integrating SAR, Optical, and Machine Learning for Enhanced Coastal Mangrove Monitoring in Guyana

Chan-Bagot,

Herndon,

Puzzi Nicolau

et al. 2024

Remote Sensing

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Mangrove forests are a biodiverse ecosystem known for a wide variety of crucial ecological services, including carbon sequestration, coastal erosion control, and prevention of saltwater intrusion. Given the ecological importance of mangrove forests, a comprehensive and up-to-date mangrove extent mapping at broad geographic scales is needed to define mangrove forest changes, assess their implications, and support restoration activities and decision making. The main objective of this study is to evaluate mangrove classifications derived from a combination of Landsat-8 OLI, Sentinel-2, and Sentinel-1 observations using a random forest (RF) machine learning (ML) algorithm to identify the best approach for monitoring Guyana’s mangrove forests on an annual basis. Algorithm accuracy was tested using high-resolution planet imagery in Collect Earth Online. Results varied widely across the different combinations of input data (overall accuracy, 88–95%; producer’s accuracy for mangroves, 50–87%; user’s accuracy for mangroves, 13–69%). The combined optical–radar classification demonstrated the best performance with an overall accuracy of 95%. Area estimates of mangrove extent ranged from 908.4 to 3645.0 hectares. A ground-based validation exercise confirmed the extent of several large, previously undocumented areas of mangrove forest loss. The results establish that a data fusion approach combining optical and radar data performs marginally better than optical-only approaches to mangrove classification. This ML approach, which leverages free and open data and a cloud-based analytics platform, can be applied to mapping other areas of mangrove forests in Guyana. This approach can also support the operational monitoring of mangrove restoration areas managed by Guyana’s National Agricultural and Research Extension Institute (NAREI).

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“…Optical satellite imagery is being employed more and more to map mangroves efficiently because of mangrove species' unique multispectral signature, improving upon previous manual and field based methods or interpretation of aerial photography [10,11]. Owing to its long-term record of consistent moderate resolution imagery with varied spectral bands, the Landsat sensor in particular can be used for accurate change analyses, particularly in mangroves [2,10].…”

Section: Introductionmentioning

confidence: 99%

The Mangroves of the Zambezi Delta: Increase in Extent Observed via Satellite from 1994 to 2013

et al. 2015

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Abstract:Mangroves are recognized for their valued ecosystem services provision while having the highest carbon density among forested ecosystems. Yet they are increasingly threatened by deforestation, conversion to agriculture and development, reducing the benefits they provide for local livelihoods, coastal protection and climate change mitigation. Accordingly, accurate estimates of mangrove area and change are fundamental for developing strategies for sustainable use, conservation and Reducing Emissions from Deforestation and Degradation (REDD+). The Zambezi River Delta in Mozambique contains one of the largest mangrove forests in Africa, and deforestation has been reported to be substantial, however these estimates vary widely. We used Landsat imagery from 1994, 2000 and 2013, to estimate a total current mangrove area of 37,034 ha, which is a net increase of 3723 ha over 19 years. The land cover change assessment was also used to provide perspective on ecosystem carbon stocks, showing that the Zambezi Delta mangrove ecosystem acts as a large carbon sink. Our findings reinforce the importance of conducting land cover change assessments using coherent data and analytical models, coupled with field validation. Broader application of our approach could help quantify the rates of natural change from erosion and land aggradation contrasted with anthropogenic causes.

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Use of satellite remote sensing for coastal conservation in the Eastern African Coast: advantages and shortcomings

Cited by 14 publications

References 15 publications

Mangrove Carbon Stocks and Ecosystem Cover Dynamics in Southwest Madagascar and the Implications for Local Management

Mangrove Carbon Stocks and Ecosystem Cover Dynamics in Southwest Madagascar and the Implications for Local Management

Integrating SAR, Optical, and Machine Learning for Enhanced Coastal Mangrove Monitoring in Guyana

The Mangroves of the Zambezi Delta: Increase in Extent Observed via Satellite from 1994 to 2013

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