This study examined the use of satellite sensor imagery for chronosequential assessment of land use and ecosystem carbon stock in slash-and-burn (S/B) regions of Laos. The segmentation approach was useful because the boundaries of S/B patches are subject to change due to natural or anthropogenic factors. Polygon-based classification using six optical bands of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery showed that S/B patches could be discriminated with high accuracy (0.98). Normalized difference spectral indices, NDSI[i, j] = [Rj -Ri ]/[Rj +Ri ], using reflectances Rj and Ri at j and i nm wavelengths for S/B polygons during four consecutive years (1999-2002) showed that NDSI[2215, 830], NDSI[1650, 830] and NDSI[660, 830] ( = the normalized difference vegetation index, NDVI) values decreased significantly in S/B years compared to those under fallow conditions (by 0.21±0.04, 0.20±0.04 and 0.17±0.03, respectively). Only slight differences were found before and after the S/B year, regardless of fallow length or biomass estimated by the allometry method. Relating reflectance signatures directly to fallow biomass was unsuitable, but these NDSIs were also useful for distinguishing S/B patches. Land-use history, including the community age of fallow vegetation, can be traced on a pixel basis using a superimposed set of segmented classified images.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
Document Type: Research Article
National Institute for Agro-Environmental Sciences, Tsukuba, Japan
Michigan State University, East Lansing, MI 48823
INRA-CSE, Domaine Saint-Paul, 84914 Avignon Cedex 9, France
Forestry and Forest Products Research Institute, Tsukuba, Ibaraki 305-8687, Japan
Kyoto University, Kyoto 606-6502, Japan
National Agriculture and Forest Research Institute, Vientiane, Lao PDR
Publication date: 2007-01-01
More about this publication?