Mapping spatial distribution and biomass of coastal wetland vegetation in Indonesian Papua by combining active and passive remotely sensed data

Article history: Received 30 July 2015 Received in revised form 13 April 2016 Accepted 30 April 2016 Available online xxxx There is ongoing interest to develop remote sensingmethods formapping andmonitoring the spatial distribution and biomass ofmangroves. In this study,we develop a suite ofmethods to evaluate the combination of Landsat-8, ALOS PALSAR, and SRTM data for mapping spatial distribution of mangrove composition, canopy height, and aboveground biomass in the wide intertidal zones and coastal plains of Mimika district, Papua, Indonesia. Image segmentation followed by visual interpretation of composite PALSAR images was used to delineate mangrove areas, whereas a flexible statistical rule based classification of spectral signatures from Landsat-8 images was used to classify mangrove associations. The overall accuracy of land cover classification was 94.38% with a kappa coefficient of 0.94 when validated with field inventory data and Google Earth images. Mangrove height and aboveground biomass were mapped using the SRTM DEM, which were calibrated with field-measured data via quantile regressionmodels. Therewas a strong correlation between the SRTMDEMand the 0.98 quantile of field canopy heights (H.98), which was used to represent the tallest trees in each of 196 10 m radius subplots (r=0.84 and R=0.804).Model performancewas evaluated through 10,000bootstrapped simulations, producing a mean absolute error (MAE) of 3.0 m for canopy height estimation over 30 m pixels of SRTM data. Quantile regression revealed a relatively strong non-linear relationship between the SRTM derived canopy height model and aboveground biomass measured in 0.5 hamangrove inventory plots (n= 33, R = 0.46). The model results produced estimates of mean standing biomass of 237.52 ± 98.2 Mg/ha in short canopy (Avicennia/Sonneratia) stands to 353.52 ± 98.43 Mg/ha in mature tall canopy (Rhizophora) dominated forest. The model estimates of mangrove biomass were within 90% confidence intervals of area-weighted biomass derived from field measurements. When validated at the landscape scale, the difference between modeled and measured aboveground mangrove biomass was 3.48% with MAE of 105.75 Mg/ha. These results indicate that the approaches developed here are reliable for mapping and monitoring mangrove composition, height, and biomass over large areas of Indonesia. © 2016 Elsevier Inc. All rights reserved.