Title of article :
Delineation of secondary succession mechanisms for tropical dry forests using LiDAR
Author/Authors :
Castillo-Nٌْez، نويسنده , , Mauricio and Sلnchez-Azofeifa، نويسنده , , G. Arturo and Croitoru، نويسنده , , Arie and Rivard، نويسنده , , Benoit and Calvo-Alvarado، نويسنده , , Julio and Dubayah، نويسنده , , Ralph O.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Pages :
15
From page :
2217
To page :
2231
Abstract :
Research suggests that secondary forest structure and composition subsequent to human disturbance could be related to wind or vertebrate dependent seed dispersal mechanisms. This paper examines the capability of a waveform LiDAR system (LVIS: LiDAR Vegetation Imaging System) to detect the location of wind-dispersed or vertebrate-dispersed forest patches in a mosaic of a secondary Tropical Dry Forest in the Santa Rosa National Park, Guanacaste, Costa Rica. Canopy-height estimations derived from LVIS data were used to identify and locate two types of dispersal-dependent arrangements of canopy heights: flat-topped (windborne seed dispersed) or dome-shaped (vertebrate-dispersed) fragments. Following identification, a Ripleyʹs K indicator was used to compare the locations for each confirmed canopy type to those reported in existing maps. Results indicated that dome-shaped patches tended to be arranged in clusters at the middle of former pastures (far from older forests), and that flat-topped patches tended to be located adjacent to older forests, forming extensions from the old growth patches and at the downwind side of the slope. Such characteristics agree with the theoretical observation of the spatial configuration of vertebrate- and wind-dispersed fragments reported in the study site. Our findings demonstrate that processes controlling forest regeneration in the TDF can be successfully identified through LiDAR data.
Keywords :
Tropical dry forests , LIDAR , Secondary forests , Canopy digital model
Journal title :
Remote Sensing of Environment
Serial Year :
2011
Journal title :
Remote Sensing of Environment
Record number :
1630923
Link To Document :
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