Annual Forest Monitoring as part of The Indonesia’s National Carbon Accounting System

Kustiyo and O. Rowintiarti and A. Tjahjaningsih and R. Dewanti and S.Furby and J. Wallace (2015) Annual Forest Monitoring as part of The Indonesia’s National Carbon Accounting System. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL (7). pp. 441-448.

[thumbnail of Journal_ KustiyoPusfatja_2015.pdf]
Preview
Text
Journal_ KustiyoPusfatja_2015.pdf

Download (1MB) | Preview

Abstract

Land use and forest change, in particular deforestation, have contributed the largest proportion of Indonesia’s estimated greenhouse gas emissions. Indonesia’s remaining forests store globally significant carbon stocks, as well as biodiversity values. In 2010, the Government of Indonesia entered into a REDD+ partnership. A spatially detailed monitoring and reporting system for forest change which is national and operating in Indonesia is required for participation in such programs, as well as for national policy reasons including Monitoring, Reporting, and Verification (MRV), carbon accounting, and land-use and policy information.

Indonesia’s National Carbon Accounting System (INCAS) has been designed to meet national and international policy requirements. The INCAS remote sensing program is producing spatially-detailed annual wall-to-wall monitoring of forest cover changes from time-series Landsat imagery for the whole of Indonesia from 2000 to the present day. Work on the program commenced in 2009, under the Indonesia-Australia Forest Carbon Partnership. A principal objective was to build an operational system in Indonesia through transfer of knowledge and experience, from Australia’s National Carbon Accounting System, and adaptation of this experience to Indonesia’s requirements and conditions. A semi-automated system of image pre-processing (ortho-rectification, calibration, cloud masking and mosaicing) and forest extent and change mapping (supervised classification of a ‘base’ year, semi-automated single-year classifications and classification within a multi-temporal probabilistic framework) was developed for Landsat 5 TM and Landsat 7 ETM+. Particular attention is paid to the accuracy of each step in the processing. With the advent of Landsat 8 data and parallel development of processing capability, capacity and international collaborations within the LAPAN Data Centre this processing is being increasingly automated. Research is continuing into improved processing methodology and integration of information from other data sources.

This paper presents technical elements of the INCAS remote sensing program and some results of the 2000 – 2012 mapping.

Item Type: Article
Uncontrolled Keywords: Multi-temporal, Landsat, Land Cover, Monitoring, Forestry, Change Detection
Subjects: Taksonomi LAPAN > Teknologi Penginderaan Jauh > Pengelolaan dan Pengembangan > Pengoperasian Satelit
Divisions: LAPAN > Deputi Penginderaan Jauh > Pusat Pemanfaatan Penginderaan jauh
Depositing User: Administrator Repository
Date Deposited: 09 Feb 2021 03:16
Last Modified: 20 Jul 2022 08:02
URI: https://karya.brin.go.id/id/eprint/11128

Actions (login required)

View Item
View Item