Lidar snow depth thresholding (Plantae)

Knowledge graph centered on Lidar snow depth thresholding (Plantae) with 54 nodes and 155 connections. Top connected: Delphinium, Spruce, Delphinium barbeyi, snowpack persistence, groundwater storage dynamics.

Method synopsis

Method to convert continuous lidar-measured snow depth to binary snow presence/absence using a fixed depth threshold. Standard approach for creating training data from airborne lidar surveys.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — High-Resolution Snow-Covered Area Mapping in Forested Mountain Ecosystems Using PlanetScope Imagery (2022), Remote Sensing. Implementations in other papers (listed below) may differ.

1. Generate benchmark snow cover masks
   Applied snow depth threshold of greater than or equal to 10 cm to lidar-derived snow depth measurements to create binary snow cover masks for model training and validation.
   Quantities: 10 cm threshold for snow presence determinationDuration: Single processing stepConditions: Applied to all lidar-derived snow depth data
   Equipment: Airborne Snow Observatory snow depth products

Typical Equipment

• NASA Airborne Snow Observatory lidar

Output Measurements

• binary snow cover masks

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used