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Northeast_Forest_Recreation_Hotspots (Map Service)


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Current Version: 10.81

Service Description:

Key Layers:

  1. Hiking Hotspots (Strava & iNaturalist):

    • Shows areas with high hiking activity based on usage data from both Strava and iNaturalist.

  2. Biking Hotspots (Strava):

    • Maps biking hotspots using Strava data, identifying popular biking routes and trails.

  3. Hiking with Soil Suitability:

    • This layer multiplies hiking use counts by soil suitability scores to highlight areas where high hiking activity coincides with soils that may be less capable of sustaining intense recreational use. The analysis reveals areas of environmental vulnerability where soil degradation risks are higher.

  4. Biking with Soil Suitability:

    • Similar to the hiking layer, this map integrates biking counts with soil suitability, identifying regions where intensive biking occurs on soils that may be more susceptible to erosion, compaction, or other forms of degradation. This analysis informs land management decisions about which trails may require maintenance, rerouting, or other conservation measures.

Use Case:
These hotspot maps are valuable for land managers, conservationists, and recreation planners seeking to balance recreational access with environmental sustainability. By identifying areas of high recreational use and overlaying them with soil suitability data, the maps help prioritize regions for trail maintenance, restoration efforts, and conservation actions. Additionally, the dataset supports efforts to monitor and mitigate the impacts of outdoor recreation on forest ecosystems, providing a tool for strategic planning in parks and protected areas.

Spatial Extent:
The dataset covers forested areas in the northeastern U.S., including Maine (ME), New York (NY), New Hampshire (NH), Rhode Island (RI), Connecticut (CT), Vermont (VT), and Massachusetts (MA).

Data Sources:

Analysis Method:
The kernel density layers were created using Kernel Density Estimation (KDE), with population expander fields set to the number of recreational uses in 2022. Soil suitability scores were applied to assess the potential impact of recreation on vulnerable soils.



Map Name: Primary

Legend

All Layers and Tables

Layers: Tables: Description:

Key Layers:

  1. Hiking Hotspots (Strava & iNaturalist):

    • Shows areas with high hiking activity based on usage data from both Strava and iNaturalist.

  2. Biking Hotspots (Strava):

    • Maps biking hotspots using Strava data, identifying popular biking routes and trails.

  3. Hiking with Soil Suitability:

    • This layer multiplies hiking use counts by soil suitability scores to highlight areas where high hiking activity coincides with soils that may be less capable of sustaining intense recreational use. The analysis reveals areas of environmental vulnerability where soil degradation risks are higher.

  4. Biking with Soil Suitability:

    • Similar to the hiking layer, this map integrates biking counts with soil suitability, identifying regions where intensive biking occurs on soils that may be more susceptible to erosion, compaction, or other forms of degradation. This analysis informs land management decisions about which trails may require maintenance, rerouting, or other conservation measures.

Use Case:
These hotspot maps are valuable for land managers, conservationists, and recreation planners seeking to balance recreational access with environmental sustainability. By identifying areas of high recreational use and overlaying them with soil suitability data, the maps help prioritize regions for trail maintenance, restoration efforts, and conservation actions. Additionally, the dataset supports efforts to monitor and mitigate the impacts of outdoor recreation on forest ecosystems, providing a tool for strategic planning in parks and protected areas.

Spatial Extent:
The dataset covers forested areas in the northeastern U.S., including Maine (ME), New York (NY), New Hampshire (NH), Rhode Island (RI), Connecticut (CT), Vermont (VT), and Massachusetts (MA).

Data Sources:

Analysis Method:
The kernel density layers were created using Kernel Density Estimation (KDE), with population expander fields set to the number of recreational uses in 2022. Soil suitability scores were applied to assess the potential impact of recreation on vulnerable soils.



Copyright Text: Forest Ecosystem Monitoring Cooperative. (2024). https://www.uvm.edu/femc. OpenStreetMap contributors. (2021). OpenStreetMap Data. Retrieved from https://www.openstreetmap.org Strava Metro. (2022). Strava Hiking and Biking Use Data. Retrieved from https://metro.strava.com/ USDA NRCS. (2023). Web Soil Survey. Retrieved from https://websoilsurvey.sc.egov.usda.gov/ Multi-Resolution Land Characteristics (MRLC) Consortium. (2021). National Land Cover Database 2021. Retrieved from https://www.mrlc.gov/data/nlcd-2021-land-cover-conus iNaturalist 2022 observations. iNaturalist (2022). Retrieved from https://www.inaturalist.org/

Spatial Reference:
4326

Single Fused Map Cache: true

Capabilities: Map,TilesOnly,Tilemap

Tile Info:
Initial Extent:
Full Extent:
Min Scale: 9244649.0
Max Scale: 5980.0

Min LOD: 5
Max LOD: 15

Units: esriDecimalDegrees

Supported Image Format Types: Mixed

Export Tiles Allowed: true
Max Export Tiles Count: 100000

Document Info: