Landscape‐scale extent, height, biomass, and carbon estimation of Mozambique's mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data

Abstract

[1] Mangroves are salt tolerant plants that grow within the intertidal zone along tropical and subtropical coasts. They are important barriers for mitigating coastal disturbances, provide habitat for over 1300 animal species and are one of the most productive ecosystems. Mozambique's mangroves extend along 2700 km and cover one of the largest areas in Africa. The purpose of this study was to determine the countrywide mean tree height spatial distribution and biomass of Mozambique's mangrove forests using Landsat ETM+ and Shuttle Radar Topography Mission (SRTM) data. The SRTM data were calibrated using the Landsat derived land-cover map and height calibration equations. Stand-specific canopy height-biomass allometric equations developed from field measurements and published height-biomass equations were used to calculate aboveground biomass of the mangrove forests on a landscape scale. The results showed that mangrove forests covered a total of 2909 km 2 in Mozambique, a 27% smaller area than previously estimated. The SRTM calibration indicated that average tree heights changed with geographical settings. Even though the coast of Mozambique spans across 16 degrees latitude, we did not find a relationship between latitude and biomass. These results confirm that geological setting has a greater influence than latitude alone on mangrove production. The total mangrove dry aboveground biomass in Mozambique was 23.6 million tons and the total carbon was 11.8 million tons.

Impactos Da Elevação Do Nível Médio Do Mar Sobre O Ecossistema Manguezal: A Contribuição Do Sensoriamento Remoto E Modelos Computacionais

“…Outra possível resposta é a migração do manguezal para áreas adjacentes, quando a elevação do nível do mar propicia o aumento da entrada de água salgada em rios e estuários (SOARES 2009). Contudo, o processo de migração depende das formas de uso e ocupação do solo em áreas marginais ao manguezal, principalmente as de origem antrópica, que podem atuar como barreiras à colonização de novas áreas (MCLEOD e SALM, 2006;FARACO, ANGRETO-FILHO;LANA, 2010).…”

“…Baseados em dois conjuntos de dados: composição de espécies e diferentes formas de uso e ocupação em áreas de ocorrência de manguezal. Fonte: KUENSER et al (2011) ções do manguezal com os sistemas físico-climáticos adjacentes, como nos casos das estimativas de carbono, áreas foliar, biomassa, identificação de espécies e altura do dossel (RASOLOFOHARINORO et al, 1998;KOVACS, WANG e FLORES-VERDUGO, 2005;FATOYINBO et al, 2008;HUANG, ZHANG e WANG, 2009) .…”

Measurement of Forest Above-Ground Biomass Using Active and Passive Remote Sensing at Large (Subnational to Global) Scales

“…For example, the European Commission SIBE-RIA project aimed to map approximately 1 million km 2 of the Siberian landmass using data from the ERS-1/2 and the JERS-1 SAR. A limitation of using the JERS-1 SAR data was that saturation of the L-band HH response occurred at 40 , accuracies of over 80 % were achieved for over 100 ERS frames [67].…”

“…Total biomass estimates varied between 1.2 and 1.7 Tg depending upon the allometric equations used (residual RMS of 17.3 and 18.6; correlation coefficient, r, of 0.67 and 0.9). For Mozambique, [40] calibrated SRTM elevation data using a Landsat-derived land cover map and height calibration equations. Field measurements and published allometric equations were then applied to map the spatial distribution of biomass within the mangrove forest.…”

New perspectives on an iconic landscape from comparative international long‐term ecological research

“…These studies will also generate regional maps of shortand long-term changes in land use to determine the differentiated vulnerability of mangrove forests in the Americas to land use change and disturbance. The proof of concept in the application of such remote sensing techniques began in the FCE mangrove ecotone region (Simard et al 2006, Zhang et al 2008, and now has allowed v www.esajournals.org further expansion in other mangrove dominated coastal regions around the world (Fatoyinbo et al 2008, Simard et al 2012, Lagomasino et al 2015. Notably, these studies integrate social science analytical frameworks with the remote sensing data to go beyond identifying the types or proximate sources of change (e.g., mangrove conversion to shrimp ponds, agriculture, urban uses) to evaluating the causal drivers of that change (e.g., population growth, local/global markets for fisheries or agricultural commodities, policies, land tenure, etc.…”