trp_seg

<p>Example data set containing optional treepoint positions sampled in the Maburg University Forest (MOF). The resolution is 10 cm. ETRS89 UTM32</p>

Support the analysis of drone derived imagery and point clouds as a cheap and easy to use alternative/complement to light detection and ranging data. It provides functionality to analyze poor quality digital aerial images as taken by low budget ready to fly drones. This includes supported machine learning based classification functions, comprehensive texture analysis, segmentation algorithms as well as forest relevant analyzes of metrics and measures on the derived products.

Chris Reudenbach

uavRst

Unmanned Aerial Vehicle Remote Sensing Tools

Hanna Meyer

Florian Detsch

Finn M<c3><b6>ller

Thomas Nauss

Lars Opgenoorth

Environmental Informatics Marburg 

trp_seg function

Format

Optional tree position raster map — trp_seg

Optional tree position raster map

trp_seg: Optional tree position raster map

Description

Arguments

Format