Next Article in Journal
Signal Classification of Submerged Aquatic Vegetation Based on the Hemispherical–Conical Reflectance Factor Spectrum Shape in the Yellow and Red Regions
Previous Article in Journal
Image-Based Coral Reef Classification and Thematic Mapping
Previous Article in Special Issue
Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2013, 5(4), 1842-1855; doi:10.3390/rs5041842

A Sample-Based Forest Monitoring Strategy Using Landsat, AVHRR and MODIS Data to Estimate Gross Forest Cover Loss in Malaysia between 1990 and 2005

1
Geographic Information Science Center of Excellence, South Dakota State University, 1021 Medary Ave., Wecota Hall, Box 506B, Brookings, SD 57007, USA
2
SUNY College of Environmental Science and Forestry, 1 Forestry Drive, Syracuse, NY 13210, USA
3
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
*
Author to whom correspondence should be addressed.
Received: 1 December 2012 / Revised: 1 April 2013 / Accepted: 9 April 2013 / Published: 15 April 2013
(This article belongs to the Special Issue Advances in Remote Sensing of Forestry)
View Full-Text   |   Download PDF [347 KB, uploaded 19 June 2014]   |  

Abstract

Insular Southeast Asia is a hotspot of humid tropical forest cover loss. A sample-based monitoring approach quantifying forest cover loss from Landsat imagery was implemented to estimate gross forest cover loss for two eras, 1990–2000 and 2000–2005. For each time interval, a probability sample of 18.5 km × 18.5 km blocks was selected, and pairs of Landsat images acquired per sample block were interpreted to quantify forest cover area and gross forest cover loss. Stratified random sampling was implemented for 2000–2005 with MODIS-derived forest cover loss used to define the strata. A probability proportional to x (πpx) design was implemented for 1990–2000 with AVHRR-derived forest cover loss used as the x variable to increase the likelihood of including forest loss area in the sample. The estimated annual gross forest cover loss for Malaysia was 0.43 Mha/yr (SE = 0.04) during 1990–2000 and 0.64 Mha/yr (SE = 0.055) during 2000–2005. Our use of the πpx sampling design represents a first practical trial of this design for sampling satellite imagery. Although the design performed adequately in this study, a thorough comparative investigation of the πpx design relative to other sampling strategies is needed before general design recommendations can be put forth. View Full-Text
Keywords: Landsat; MODIS; AVHRR; Indonesia; probability proportional to x sampling; stratified sampling Landsat; MODIS; AVHRR; Indonesia; probability proportional to x sampling; stratified sampling
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Giree, N.; Stehman, S.V.; Potapov, P.; Hansen, M.C. A Sample-Based Forest Monitoring Strategy Using Landsat, AVHRR and MODIS Data to Estimate Gross Forest Cover Loss in Malaysia between 1990 and 2005. Remote Sens. 2013, 5, 1842-1855.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top