TY - JOUR
T1 - Ecological fingerprinting of ecosystem succession
T2 - Estimating secondary tropical dry forest structure and diversity using imaging spectroscopy
AU - Kalacska, M.
AU - Sanchez-Azofeifa, G. A.
AU - Rivard, B.
AU - Caelli, T.
AU - White, H. Peter
AU - Calvo-Alvarado, J. C.
PY - 2007/5/15
Y1 - 2007/5/15
N2 - We evaluated the use of EO-1 Hyperion hyperspectral satellite imagery for mapping structure and floristic diversity in a Neotropical tropical dry forest as a way of assessing a region's ecological fingerprint. Analysis of satellite imagery provides a means to spatially appraise the dynamics of the structure and diversity of the forest. We derived optimal models for mapping canopy height, live aboveground biomass, Shannon diversity, basal area and the Holdridge Complexity Index from a dry season image. None of the evaluated models adequately estimated stem or species density. Due to the dynamic nature of the leaf phenology we found that for the application of remote sensing in Neotropical dry forests, the spectro-temporal domain (changes in the spectral signatures over time-season) must be taken into account when choosing imagery. The analyses and results presented here provide a means for rapid spatial assessment of structure and diversity characteristics from the microscale site level to an entire region.
AB - We evaluated the use of EO-1 Hyperion hyperspectral satellite imagery for mapping structure and floristic diversity in a Neotropical tropical dry forest as a way of assessing a region's ecological fingerprint. Analysis of satellite imagery provides a means to spatially appraise the dynamics of the structure and diversity of the forest. We derived optimal models for mapping canopy height, live aboveground biomass, Shannon diversity, basal area and the Holdridge Complexity Index from a dry season image. None of the evaluated models adequately estimated stem or species density. Due to the dynamic nature of the leaf phenology we found that for the application of remote sensing in Neotropical dry forests, the spectro-temporal domain (changes in the spectral signatures over time-season) must be taken into account when choosing imagery. The analyses and results presented here provide a means for rapid spatial assessment of structure and diversity characteristics from the microscale site level to an entire region.
KW - Biomass
KW - Costa Rica
KW - Holdridge Complexity Index
KW - Hyperion
KW - Hyperspectral remote sensing
KW - Neural network
KW - Structure
KW - Tropical dry forest
KW - Wavelet decomposition
UR - http://www.scopus.com/inward/record.url?scp=34047253781&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2006.11.007
DO - 10.1016/j.rse.2006.11.007
M3 - Article
SN - 0034-4257
VL - 108
SP - 82
EP - 96
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
IS - 1
ER -