Title :
Monitoring forest succession with multitemporal Landsat images: factors of uncertainty
Author :
Song, Conghe ; Woodcock, Curtis E.
Author_Institution :
Dept. of Geogr., North Carolina Univ., Chapel Hill, NC, USA
Abstract :
This study evaluates uncertainty factors in using multitemporal Landsat images for subtle change detection, including atmosphere, topography, phenology, and sun and view angles. The study is based on monitoring forest succession with a set of multiple Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images spanning 15 years over the H.J. Andrews Experimental Forest in the Western Cascades of Oregon. The algorithms for removing atmospheric effects from remotely sensed images evaluated include a new version of the dark object subtraction (DOS3) method, the dense dark vegetation (DDV) method, the path radiance (PARA) approach, and the 6S radiative transfer codes. We found that the DOS3 approach undercorrects the image, and the recently developed DDV and PARA approaches can produce surface reflectance values closely matching those produced by 6S using in situ measurements of atmospheric aerosol optical depth. Atmospheric effects reduce normalized difference vegetation index (NDVI) and greenness, and increase brightness and wetness. Topography modifies brightness and greenness, but has minimal effects on NDVI and wetness, and it interacts with sun angle. Forest stands at late successional stages are more sensitive to topography than younger stands. Though the study areas are covered predominantly by evergreen needleleaf forests, phenological effect is significant. Sun angle effects are confounded with phenology, and reflectance values for stands at different successional stages are related to sun angles nonlinearly. Though Landsat has a small field of view angle, the view angle effects from overlapping Landsat scenes for a mountainous forested landscape may not be ignored when monitoring forest succession with multitemporal images.
Keywords :
forestry; geophysical signal processing; image processing; topography (Earth); vegetation mapping; 6S radiative transfer codes; DDV method; DOS3 method; Landsat Thematic Mapper/Enhanced Thematic Mapper Plus images; NDVI; Oregon; PARA approach; Western Cascades; atmosphere; atmospheric aerosol optical depth; atmospheric effects; brightness; change detection; dark object subtraction; dense dark vegetation; evergreen needleleaf forests; forest succession; greenness; mountainous forested landscape; multitemporal Landsat images; normalized difference vegetation index; path radiance approach; phenology; remotely sensed images; sun angle; surface reflectance; topography; uncertainty; view angles; wetness; Atmosphere; Brightness; Monitoring; Reflectivity; Remote sensing; Satellites; Sun; Surfaces; Uncertainty; Vegetation mapping;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2003.818367