Load the pdxTrees_parks data

Description

This function pulls the pdxTrees_parks dataset from the GitHub repository: https://github.com/mcconvil/pdxTrees. pdxTrees_parks is a data frame of all the trees in 174 parks in Portland, OR and was collected as part of the Urban Forestry Tree Inventory Project.

Usage

get_pdxTrees_parks(park = NULL)

Arguments

Value

Returns a data frame of 34 variables where each row is a tree:

UserID

ID

Inventory_Date

Date of data collection

Species

Species of the tree. All dead trees were listed as "unknown"

Common_Name

Common name of the tree

DBH

Diameter at breast height (4.5' above ground)

Condition

Trees were rated as good, fair, poor, or dead. These general ratings reflect whether or not a tree is likely to continue contributing to the urban forest (good and fair trees) or whether the tree is at or near the end of its life (poor and dead trees).

Tree_Height

Height from the ground to the live top of the tree. For dead trees, total height was measured.

Crown_Width_NS

North to South canopy width

Crown_Width_EW

East to West canopy width

Crown_Base_Height

Height from the ground to the lowest live canopy.

Collected_By

Whether data were collect by staff or volunteer

Park

Park where tree is located

Scientific_Name

Scientific name of the tree

Family

Family of the tree

Genus

Genus of the tree

Functional_Type

Categorical variable with groups: Broadleaf Deciduous (BD), Broadleaf Evergreen (BE), Coniferous Deciduous (CD), and Coniferous Evergreen (CE)

Mature_Size

Categorical variable with groups: Large (L), Medium (M), and Small (S). Categorization is based on the height, canopy width, and general form of the tree at maturity

Native

Whether or not the tree is native

Edible

Categorical variable of edible trees

Nuisance

Categorical variable indicating if it is a nuisance species

Structural_Value

Monetary value of replacing the tree and the benefits that it provides, based on methods from the Council of Tree and Landscape Appraisers

Carbon_Storage_lb

The amount of carbon (in lbs.) that is bound up in both the above-ground and below-ground parts of the tree

Carbon_Storage_value

The monetary value associated with tree effects on atmospheric carbon, $129.72/ton. This value is estimated based on the economic damages associated with increases in carbon or carbon dioxide emissions.

Carbon_Sequestration_lb

The amount of carbon (in lbs.) removed from the atmosphere by the tree, annually.

Carbon_Sequestration_value

The monetary value of carbon ($129.72/ton), estimated based on the economic damages associated with increases in carbon or carbon dioxide emissions.

Stormwater_ft

The amount (cubic feet) of avoided stormwater runoff because of rainfall interception by the tree on its leaves and other surfaces.

Stormwater_value

The monetary value of stormwater runoff that is avoided annually because of the rainfall interception by the tree ($0.008936/gallon), based on the economic damages associated with runoff and costs of stormwater control.

Pollution_Removal_oz

The amount (oz.) of air pollution that is removed from the atmosphere by trees.

Pollution_Removal_value

The monetary value associated with tree effects on atmospheric pollution, annually.

Total_Annual_Services

Sum of the annual benefits

Origin

Origin of the tree

Species_Factoid

Additional information about the tree

Longitude

Longitude

Latitude

Latitude

Source

https://www.portlandoregon.gov/parks/article/433143

Examples

 
# To grab all trees
 get_pdxTrees_parks() 

# To grab trees from one park
get_pdxTrees_parks(park = "Berkeley Park")

# To grab trees from multiple parks
get_pdxTrees_parks(park = c("Berkeley Park", "East Delta Park"))
 

Load the pdxTrees_streets data

Description

This function pulls the pdxTrees_streets dataset from the GitHub repository: https://github.com/mcconvil/pdxTrees. pdxTrees_streets is a data frame of all the street trees in the 96 neighborhoods of Portland, OR and was collected as part of the Urban Forestry Tree Inventory Project.

Usage

get_pdxTrees_streets(neighborhood = NULL)

Arguments

Value

Returns a data frame with 218602 rows and 23 variables:

UserID

ID

Inventory_Date

Date of data collection

Species

Species of the tree. All dead trees were listed as "unknown"

Common_Name

Common name of the tree

DBH

Diameter at breast height (4.5' above ground)

Condition

Trees were rated as good, fair, poor, or dead. These general ratings reflect whether or not a tree is likely to continue contributing to the urban forest (good and fair trees) or whether the tree is at or near the end of its life (poor and dead trees).

Site_Type

Where along the street the tree was located. There are 8 different site types and more info can be found here: http://gis-pdx.opendata.arcgis.com/datasets/street-trees

Site_Size

Categorical size of the site: Small, Medium, Large

Site_Width

How wide the site was in ft.

Wires

Whether or not the site had wires: High voltage, No High voltage (No HV), other

Site_Development

The condition of the site either being improved (ex. along a side walk or paved roadway ) or unimproved (a gravel road))

Address

The address where the tree is located

Neighborhood

The Portland neighborhood in which the tree is located

Collected_By

Who collected the data on this tree: staff or volunteer

Scientific

Scientific name of the tree

Family

Family of the tree

Genus

Genus of the tree

Functional_Type

Categorical variable with groups: Broadleaf Deciduous (BD), Broadleaf Evergreen (BE), Coniferous Deciduous (CD), and Coniferous Evergreen (CE)

Mature_Size

Categorical variable with groups: Large (L), Medium (M), and Small (S). Categorization is based on the height, canopy width, and general form of the tree at maturity

Edible

Categorical variable of edible trees

Notes

Note on the data collection

Longitude

Longitude

Latitude

Latitude

Source

https://www.portlandoregon.gov/parks/article/433143

Examples

 # To grab all trees
get_pdxTrees_streets() 

# To grab trees from one neighborhood
get_pdxTrees_streets(neighborhood = "Concordia")

# To grab trees from multiple neighborhoods 
get_pdxTrees_streets(neighborhood = c("Concordia","Eastmoreland","Sunnyside"))