Title of article :
A comparison of forest cover maps in Mainland Southeast Asia from multiple sources: PALSAR, MERIS, MODIS and FRA
Author/Authors :
Dong، نويسنده , , Jinwei and Xiao، نويسنده , , Xiangming and Sheldon، نويسنده , , Sage and Biradar، نويسنده , , Chandrashekhar and Duong، نويسنده , , Nguyen Dinh and Hazarika، نويسنده , , Manzul Kumar and Yasuoka، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
The uncertainty in tracking tropical forest extent and changes substantially affects our assessment of the consequences of forest change on the global carbon cycle, biodiversity and ecosystem services. Recently cloud-free imagery useful for tropical forest mapping from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) has become available. We used PALSAR 50-m orthorectified mosaic imagery in 2009 and a decision tree method to conduct land cover classification and generate a 2009 forest map, which was evaluated using 2106 field photos from the Global Geo-referenced Field Photo Library (http://www.eomf.ou.edu/photos). The resulting land cover classification had a high overall accuracy of 93.3% and a Kappa Coefficient of 0.9. The PALSAR-based forest map was then compared with three existing forest cover products at three scales (regional, national, and continental): the Food and Agriculture Organization of the United Nations (FAO) Forest Resources Assessments (FRA) 2010, Global Land Cover Map with MERIS (GlobCover) 2009, and the MODIS Terra + Aqua Land Cover Type product (MCD12Q1) 2009. The intercomparison results show that these four forest datasets differ. The PALSAR-based forest area estimate is within the range (6.1–9.0 × 105 km2) of the other three products and closest to the FAO FRA 2010 estimate. The spatial disagreements of the PALSAR-based forest, MCD12Q1 forest and GlobCover forest are evident; however, the PALSAR-based forest map provides more details (50-m spatial resolution) and high accuracy (the Producerʹs and the Userʹs Accuracies were 88% and 95%, respectively) and PALSAR can be used to evaluate MCD12Q1 2009 and GlobCover 2009 forest maps. Given the higher spatial resolution, PALSAR-based forest products could further improve the modeling accuracy of carbon cycle in tropical forests.
Keywords :
FRA , Forest mapping , Southeast Asia , MCD12Q1 , GLOBCOVER , PALSAR
Journal title :
Remote Sensing of Environment
Journal title :
Remote Sensing of Environment