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TreeValueMatrix

Tree Value Matrix is a field tool for arborists, ecologists, environmentalists, and other users that need to evaluate the value of a tree based on several relevant qualities

Tree Value Matrix is a field tool for arborists, ecologists, environmentalists, and other users that need to evaluate the value of a tree based on several relevant qualities

TreeValueMatrix

by EcoAddendum
TreeValueMatrix
TreeValueMatrix
TreeValueMatrix

What is it about?

Tree Value Matrix is a field tool for arborists, ecologists, environmentalists, and other users that need to evaluate the value of a tree based on several relevant qualities. Users can select a tree based on its name or family or use the search bar to find a tree by its common or scientific name. The app currently supports sites in Southeastern Piedmont, USA. Once the tree species has been selected, the user can answer a series of questions about the tree’s diameter breast height (dbh), overall condition, and contribution to its surrounding area. These properties are used to evaluate and assign the tree a qualitative value. The trees can be valued as: Excellent, High, Moderate, or Low.

TreeValueMatrix

App Details

Version
2.0.3
Rating
NA
Size
82Mb
Genre
Utilities Reference
Last updated
March 31, 2020
Release date
March 31, 2020
More info

App Screenshots

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App Store Description

Tree Value Matrix is a field tool for arborists, ecologists, environmentalists, and other users that need to evaluate the value of a tree based on several relevant qualities. Users can select a tree based on its name or family or use the search bar to find a tree by its common or scientific name. The app currently supports sites in Southeastern Piedmont, USA. Once the tree species has been selected, the user can answer a series of questions about the tree’s diameter breast height (dbh), overall condition, and contribution to its surrounding area. These properties are used to evaluate and assign the tree a qualitative value. The trees can be valued as: Excellent, High, Moderate, or Low.

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