Translating bumblebee dialect…
This is a map of vegetation canopy height suitable for tree detection and crown segmentation, derived from high-density airborne LiDAR scans collected in August - September 2015 and 2019. Classified LiDAR point clouds from both datasets were re-projected to a common coordinate system (EPSG:32613, WGS84 UTM Zone 13N). A 0.33m canopy height model was constructed for each dataset by triangulating ground returns and subtracting the elevation of the ground surface. A pitfree algorithm (Khosravipour et al. 2014) was then used to reconstruct canopy geometry. All point cloud processing was done using the R package lidR version 2.1. The two canopy height models from the 2015 and 2019 LiDAR datasets were mosaiced to produce a continous dataset, with the 2019 data taking priority where there was coverage (approximately 80% of the domain). Buildings and topographic artifacts were removed by setting canopy heights to zero within 1m of building footprints in the Microsoft Bing dataset, and in areas with a negative NDVI in NAIP 4-band aerial imagery. References: Khosravipour, A., Skidmore, A. K., Isenburg, M., Wang, T., & Hussin, Y. A. (2014). Generating pit-free canopy height models from airborne lidar. Photogrammetric Engineering & Remote Sensing, 80(9), 863-872.
Knowledge graph centered on One-third meter resolution vegetation canopy heigh with 3 nodes and 3 connections. Top connected: Forest inventory plot sampling, Upper East River Beaver Pond.
Items connected by shared entities, co-authorship, citations, or semantic similarity.