Name: Potential Control Locations

Display Field:

Type: Raster Layer

Geometry Type: null

Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>FROM RESEARCH ABSTRACT:</SPAN></P><P><SPAN>During active fire incidents, decisions regarding where and how to safely and effectively deploy resources to meet management objectives are often made under rapidly evolving conditions, with limited time to assess management strategies or for development of backup plans if initial efforts prove unsuccessful. Under all but the most extreme fire weather conditions, topography and fuels are significant factors affecting potential fire spread and burn severity. We leverage these relationships to quantify the effects of topography, fuel characteristics, road networks and fire suppression effort on the perimeter locations of 238 large fires, and develop a predictive model of potential fire control locations spanning a range of fuel types, topographic features and natural and anthropogenic barriers to fire spread, on a 34 000 km2 landscape in southern Idaho and northern Nevada. The boosted logistic regression model correctly classified final fire perimeter locations on an independent dataset with 69% accuracy without consideration of weather conditions on individual fires. The resulting fire control probability surface has potential for reducing unnecessary exposure for fire responders, coordinating pre-fire planning for operational fire response, and as a network of locations to incorporate into spatial fire planning to better align fire operations with land management objectives.</SPAN></P></DIV></DIV></DIV>

Service Item Id: eff01002067241048a593963e92926b0

Copyright Text: Provided to WA DNR by Chris Dunn (OSU), stewarded by Kirk Davis (WA DNR - Wildfire Division) CITATION: O'Connor, Christopher D.; Calkin, David E.; Thompson, Matthew P. 2017. An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management. International Journal of Wildland Fire. 26: 587-597.

Default Visibility: true

MaxRecordCount: 0

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 9244648.868618

Max Scale: 0

Supports Advanced Queries: false

Supports Statistics: false

Has Labels: false

Can Modify Layer: false

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:

XMin: -1.4062441226158949E7
YMin: 5447631.739326074
XMax: -1.284256949828572E7
YMax: 6425455.330390155
Spatial Reference: 102100  (3857)

Drawing Info:

N/A

Advanced Query Capabilities:

Supports Statistics: false
Supports OrderBy: false
Supports Distinct: false
Supports Pagination: false
Supports TrueCurve: true
Supports Returning Query Extent: true
Supports Query With Distance: true
Supports Sql Expression: false
Supports Query With ResultType: false
Supports Returning Geometry Centroid: false
Supports Binning LOD: false
Supports Query With LOD Spatial Reference: false

HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeNone

Type ID Field: null

Fields: None


Supported Operations:   Query   Query Attachments   Query Analytic   Generate Renderer   Return Updates

  Iteminfo   Thumbnail   Metadata