Brazilian Mangrove Status: Three Decades of Satellite Data Analysis

Since the 1980s, mangrove cover mapping has become a common scientific task. However, the systematic and continuous identification of vegetation cover, whether on a global or regional scale, demands large storage and processing capacities. This manuscript presents a Google Earth Engine (GEE)-managed...

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Main Authors: Cesar Diniz, Luiz Cortinhas, Gilberto Nerino, Jhonatan Rodrigues, Luís Sadeck, Marcos Adami, Pedro Walfir M. Souza-Filho
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/11/7/808
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spelling doaj-796c95b075424226ac25ba7754f4f5f12020-11-24T21:50:23ZengMDPI AGRemote Sensing2072-42922019-04-0111780810.3390/rs11070808rs11070808Brazilian Mangrove Status: Three Decades of Satellite Data AnalysisCesar Diniz0Luiz Cortinhas1Gilberto Nerino2Jhonatan Rodrigues3Luís Sadeck4Marcos Adami5Pedro Walfir M. Souza-Filho6Solved—Solutions in Geoinformation, Belém 66075-750, BrazilSolved—Solutions in Geoinformation, Belém 66075-750, BrazilSolved—Solutions in Geoinformation, Belém 66075-750, BrazilSolved—Solutions in Geoinformation, Belém 66075-750, BrazilSolved—Solutions in Geoinformation, Belém 66075-750, BrazilGeoscience Institute, Federal University of Pará, Belém 66075-110, BrazilGeoscience Institute, Federal University of Pará, Belém 66075-110, BrazilSince the 1980s, mangrove cover mapping has become a common scientific task. However, the systematic and continuous identification of vegetation cover, whether on a global or regional scale, demands large storage and processing capacities. This manuscript presents a Google Earth Engine (GEE)-managed pipeline to compute the annual status of Brazilian mangroves from 1985 to 2018, along with a new spectral index, the Modular Mangrove Recognition Index (MMRI), which has been specifically designed to better discriminate mangrove forests from the surrounding vegetation. If compared separately, the periods from 1985 to 1998 and 1999 to 2018 show distinct mangrove area trends. The first period, from 1985 to 1998, shows an upward trend, which seems to be related more to the uneven distribution of Landsat data than to a regeneration of Brazilian mangroves. In the second period, from 1999 to 2018, a trend of mangrove area loss was registered, reaching up to 2% of the mangrove forest. On a regional scale, ~85% of Brazil’s mangrove cover is in the states of Maranhão, Pará, Amapá and Bahia. In terms of persistence, ~75% of the Brazilian mangroves remained unchanged for two decades or more.https://www.mdpi.com/2072-4292/11/7/808mangrovesmachine learningGoogle Earth Enginespectral indicesBrazilLandsat
collection DOAJ
language English
format Article
sources DOAJ
author Cesar Diniz
Luiz Cortinhas
Gilberto Nerino
Jhonatan Rodrigues
Luís Sadeck
Marcos Adami
Pedro Walfir M. Souza-Filho
spellingShingle Cesar Diniz
Luiz Cortinhas
Gilberto Nerino
Jhonatan Rodrigues
Luís Sadeck
Marcos Adami
Pedro Walfir M. Souza-Filho
Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
Remote Sensing
mangroves
machine learning
Google Earth Engine
spectral indices
Brazil
Landsat
author_facet Cesar Diniz
Luiz Cortinhas
Gilberto Nerino
Jhonatan Rodrigues
Luís Sadeck
Marcos Adami
Pedro Walfir M. Souza-Filho
author_sort Cesar Diniz
title Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
title_short Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
title_full Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
title_fullStr Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
title_full_unstemmed Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
title_sort brazilian mangrove status: three decades of satellite data analysis
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2019-04-01
description Since the 1980s, mangrove cover mapping has become a common scientific task. However, the systematic and continuous identification of vegetation cover, whether on a global or regional scale, demands large storage and processing capacities. This manuscript presents a Google Earth Engine (GEE)-managed pipeline to compute the annual status of Brazilian mangroves from 1985 to 2018, along with a new spectral index, the Modular Mangrove Recognition Index (MMRI), which has been specifically designed to better discriminate mangrove forests from the surrounding vegetation. If compared separately, the periods from 1985 to 1998 and 1999 to 2018 show distinct mangrove area trends. The first period, from 1985 to 1998, shows an upward trend, which seems to be related more to the uneven distribution of Landsat data than to a regeneration of Brazilian mangroves. In the second period, from 1999 to 2018, a trend of mangrove area loss was registered, reaching up to 2% of the mangrove forest. On a regional scale, ~85% of Brazil’s mangrove cover is in the states of Maranhão, Pará, Amapá and Bahia. In terms of persistence, ~75% of the Brazilian mangroves remained unchanged for two decades or more.
topic mangroves
machine learning
Google Earth Engine
spectral indices
Brazil
Landsat
url https://www.mdpi.com/2072-4292/11/7/808
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