James R. Kellner, David B. Clark, and Michelle A. Hofton. 2009. Canopy height and ground elevation in a mixed-land-use lowland Neotropical rain forest landscape. Ecology 90:3274.


Data Paper

Ecological Archives E090-233-D1.

Copyright


Authors
Data Files
Abstract
Metadata


Author(s)

James R. Kellner
Department of Plant Biology
The University of Georgia
Athens, GA 30602 USA, and
Department of Global Ecology
Carnegie Institution for Science
Stanford, CA 94305 USA
E-mail: jkellner@stanford.edu

David B. Clark
Department of Biology
University of Missouri, St. Louis
St. Louis, MO 63121 USA, and
La Selva Biological Station

Puerto Viejo de Sarapiquí, Costa Rica
E-mail: dbclark@sloth.ots.ac.cr

Michelle A. Hofton
Department of Geography
University of Maryland
College Park, MD 20742 USA
E-mail: mhofton@umd.edu


Data Files

AllTiles.zip -- a 1.7 Gb file containing 511 comma-delimited ASCII text files. Each file represents a 500 × 500 m contiguous area and is named tilexxx.txt, where xxx is replaced by the respective tile number from 001–511. To download selected data tiles, rather than the entire data set, please click here to go to a page listing all 511 files with links. Tile locations are shown graphically in Fig. 3, and can be indexed in a GIS using the shapefile (see section V.C.2), or in text format in Table 1.

LandUseHistoryShapefile.zip -- land use history for La Selva Biological Station

500mTilesShapefile.zip -- mapped locations of 511 LiDAR data tiles.

RFunction.txt -- an R function to read the LiDAR data.


Abstract

We obtained spatially extensive canopy height measurements using airborne remote sensing to characterize the structure and dynamics of a tropical rain forest landscape. Light detection and ranging (LiDAR) is a remote-sensing technology that acquires measurements of canopy height and ground elevation. By recording the return time of laser pulses emitted by aircraft-mounted sensors, LiDAR systems quantify the structure and geometry of individual trees and canopy height and enable estimation of the vertical and horizontal distribution of biomass using millions of accurate height measurements. This data set contains 127,849,839 records from 128 square kilometers of tropical wet forest in the Atlantic lowlands of Costa Rica (mean sampling density is 1.99 observations/m2). The study area includes all 16 square kilometers of mixed-land-use forest at the La Selva Biological Station and the lower flanks of Braulio Carrillo National Park. It contains a mosaic of historical and contemporary land use that is representative of contemporary tropical forest landscapes. Field studies demonstrated that LiDAR measurements were precise and accurate throughout the topographic and structural conditions at the site. Each record includes: easting and northing mapped coordinates (UTM Zone 16 North), height above ground (m), interpolated ground elevation (m), and six remote-sensing descriptors (point classification, the return number, the number of returns for the given pulse, intensity, scan angle, and the time of emission of the laser pulse). The data can be applied to a wide range of questions in basic and applied science, and are a valuable resource from a well-studied tropical rain forest for teaching and education. They also provide a quantitative baseline against which future conditions can be assessed.

Key words: biomass; carbon; Costa Rica; forest structure; landscape; La Selva Biological Station; LiDAR; light detection and ranging; Neotropics; remote sensing; sustainability.


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