데이터셋 상세
캐나다
Topographic humidity index from LiDAR
__The link: * Access the data directory* is available in the section*Dataset description sheets; Additional information*__. As part of the provincial LiDAR sensor data acquisition project, a topographic humidity index or *Topographic Wetness Index* (TWI) was produced from the digital terrain model derived from aerial LiDAR (*Light Detection and Ranging*). The matrix layers thus produced provide information on the potential for water accumulation on the territory as a function of the slope and accumulation at a given pixel.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
연관 데이터
Tumbarumba Wet Eucalypt Terrestrial LiDAR, 2022
공공데이터포털
This terrestrial LiDAR dataset captures detailed vegetation structural information at the Tumbarumba Wet Eucalypt site in the Bago State Forest, New South Wales, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.
Cumberland Plain Terrestrial LiDAR, 2022
공공데이터포털
This terrestrial LiDAR dataset captures detailed vegetation structural information at the Cumblerland Plain Woodland SuperSite in Western Sydney, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.
Fletcherview Tropical Rangeland Terrestrial LiDAR, 2022
공공데이터포털
This terrestrial LiDAR dataset captures detailed vegetation structural information at the Fletcherview Tropical Rangeland SuperSite, located 50km west of Townsville, Queensland, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.
Topographic Wetness Index derived from 1" SRTM DEM-H
공공데이터포털
Topographic Wetness Index (TWI) is calculated as log_e(specific catchment area / slope) and estimates the relative wetness within a catchment. The TWI product was derived from the partial contributing area product (CA_MFD_PARTIAL), which was computed from the Hydrologically enforced Digital Elevation Model (DEM-H; ANZCW0703014615), and from the percent slope product, which was computed from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016). Both DEM-S and DEM-H are based on the 1 arcsecond resolution SRTM data acquired by NASA in February 2000. Note that the partial contributing area product does not always represent contributing areas larger than about 25 km2 because it was processed on overlapping tiles, not complete catchments. This only impacts TWI values in river channels and does not affect values on the land around the river channels. Since the index is not intended for use in river channels this limitation has no impact on the utility of TWI for spatial modelling. The TWI data are available in gridded format at 1 arcsecond and 3 arcsecond resolutions. The 3 arcsecond resolution TWI product was generated from the 1 arcsecond TWI product and masked by the 3” water and ocean mask datasets.
Litchfield Savanna Terrestrial LiDAR, 2021
공공데이터포털
This terrestrial LiDAR dataset captures detailed vegetation structural information at the Litchfield Savanna SuperSite in NT, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.