Forest production predicted from satellite image analysis for the Southeast Asia region

Abstract

BackgroundThe objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010. These CASA model results have been designed to be spatially detailed enough to support carbon cycle assessments in different wooded land cover classes, e.g., open woodlands, wetlands, and forest areas.ResultsThe country with the highest average forest net primary production (NPP greater than 950 g C m-2 yr-1) over the period was the Philippines, followed by Malaysia and Indonesia. Myanmar and Vietnam had the lowest average forest NPP among the region’s countries at less than 815 g C m-2 yr-1. Case studies from throughout the Southeast Asia region for the maximum harvested wood products amount that could be sustainably extracted per year were generated using the CASA model NPP predictions.ConclusionsThe method of using CASA model’s estimated annual change in forest carbon on a yearly basis can conservatively define the upper limit for the amount of harvested wood products that can be removed and still avoid degradation (net loss) of the total wood carbon stock over that same time period.

Mapping Human Impact on Net Primary Productivity Using MODIS Data for Better Policy Making

“…In Indonesia, for example, the main driving forces of forest loss in provincial areas are poorly controlled infrastructure development, mining, and conversion to crop plantations (Potter et al 2013). Although these activities are legal, they should be shifted from high productivity areas to lower productivity areas, as depicted in Fig.…”

“…In this study, we classify NPP based on Natural Breaks (Jenks optimization) applied in ArcMap. A study by Potter et al (2013) used this approach to divide NPP into low, moderate and high production forest categories in tropical forest of Southeast Asia. The method minimized the average deviation of each class, while maximizing each class's deviation from the means of the other groups (Jenks 1967).…”

“…Net Primary Productivity (NPP) is the amount of biomass produced by green vegetation, which provides the chemical energy driving most biotic processes on earth (Krausmann et al 2008;Potter et al 2013). Meanwhile, Human Appropriation of Net Primary Production (HANPP) is an indicator used for measuring human impact on NPP, including (1) the human impact of land use changes (NPP LC ) (land conversion) and (2) the harvesting and destruction of forests (NPP h ) (Haberl et al 2011).…”

Evaluation of modelled net primary production using MODIS and landsat satellite data fusion

“…The CASA model was also capable of predicting annually summed NPP with an R 2 = 0.90 on a global scale using the NOAA Advanced Very High Resolution Radiometer (AVHRR) VI and regressing against over 1900 observed NPP data points [ 22 ]. The model has been used successfully in measuring the global effects of deforestation on NPP [ 21 , 26 ], particularly in tropical Amazonian and Asian carbon fluxes [ 23 , 27 , 41 ].…”

Forest biomass change estimated from height change in interferometric SAR height models

“…In addition, it has been demonstrated that loggings, i.e. clear-cutting and forest degradation, can be detected as temporal changes in surface height [ 31 ],[ 32 ]. The latter studies detected the logging-induced decreases from the 90 m SRTM C-band DSM to a recent and higher resolution X-band DSM.…”