Brazilian Mangrove Status: Three Decades of Satellite Data Analysis
1
Solved—Solutions in Geoinformation, Belém 66075-750, Brazil
2
Geoscience Institute, Federal University of Pará, Belém 66075-110, Brazil
3
Regional Center of the Amazon, National Institute for Space Research (INPE), São Paulo 12227-010, Brazil
4
Global Land Analysis and Discovery (GLAD) laboratory, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
5
Instituto Tecnológico Vale (ITV), Belém 66055-090, Brazil
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(7), 808; https://doi.org/10.3390/rs11070808
Received: 25 January 2019 / Revised: 12 March 2019 / Accepted: 22 March 2019 / Published: 4 April 2019
(This article belongs to the Special Issue Remote Sensing of Mangroves)
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.
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Keywords:
mangroves; machine learning; Google Earth Engine; spectral indices; Brazil; Landsat
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Diniz, C.; Cortinhas, L.; Nerino, G.; Rodrigues, J.; Sadeck, L.; Adami, M.; Souza-Filho, P.W.M. Brazilian Mangrove Status: Three Decades of Satellite Data Analysis. Remote Sens. 2019, 11, 808. https://doi.org/10.3390/rs11070808
AMA Style
Diniz C, Cortinhas L, Nerino G, Rodrigues J, Sadeck L, Adami M, Souza-Filho PWM. Brazilian Mangrove Status: Three Decades of Satellite Data Analysis. Remote Sensing. 2019; 11(7):808. https://doi.org/10.3390/rs11070808
Chicago/Turabian StyleDiniz, Cesar; Cortinhas, Luiz; Nerino, Gilberto; Rodrigues, Jhonatan; Sadeck, Luís; Adami, Marcos; Souza-Filho, Pedro W.M. 2019. "Brazilian Mangrove Status: Three Decades of Satellite Data Analysis" Remote Sens. 11, no. 7: 808. https://doi.org/10.3390/rs11070808
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