Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps

Abstract

This study investigates how two existing pan-tropical above-ground biomass (AGB) maps (Saatchi 2011 can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5%) leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest OPEN ACCESSLand 2015, 4 657 and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively). The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%), upper dipterocarp (10.9%) and peat swamp forests (10.2%). Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.

Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

“…Predicted AGB values were compared with field AGB values using Pearson’s correlation, RMSE, MAE and %bias. The local scale AGB map that was built using field data and remote sensing texture variables was used to improve the efficacy of the 1-km Avitabile AGB mapped [ 17 ] by using the method of Langner et al [ 62 ]. Correlation coefficients between the two AGB maps were calculated over kernel windows of varying size (4×4 pixels).…”

Review: Diversity, structure, and community composition of Bornean heath forest with a focus on Brunei Darussalam

“…The tropical coastal heath forests of Borneo are distributed along the coastline on raised Pleistocene sea beaches with a podzolic profile (Whitmore 1984;Jusoh and Aziz 2014;Nugroho et al 2022). Lowland heath forests (< 1000 m above sea level) are found inland on sandstone plateaus and cuesta formations on the hillsides of Kalimantan, Sarawak, Sabah, and Brunei (Brunig 1964;Miyamoto et al 2003;Ashton 2014;Langner et al 2015). On mountains (> 1000 m above sea level), lower montane heath forests (lower montane kerangas; Ashton 2014) occur on sandstone ridges, on podozolized soils, and over ultrabasic rocks (Ashton 2014;Van der Ent et al 2015;Aiba and Kitayama 2020).…”

Investigating El Nino Southern Oscillation as the main driver of forest fire in Kalimantan

“…Figure 3 show Lowland Dipterocarp Forest and Upper Dipterocarp Forest are accounted as the widest area with 306 t/ha and 274 t/ha, respectively; the characteristic of this type of land is vulnerability to fire due to its drought-susceptibility even from small disturbance (Guhardja et al, 2000;Siegert et al, 2001;Cochrane, 2003;Goldammer, 2007) Figure 3. Borneo land cover classification of the year 2008 (Langner, et al, 2015) Borneo has an equatorial tropical climate, with often relatively light winds and only small annual temperature and humidity variations. The precipitation over Kalimantan is 3000 m every year with seasonal variation which means the rainfall is high and crucial in this region (Hamada, et al, 2002).…”