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snippet: Machine learning detection of log decks and burn piles across Plumas County and the Dixie Fire perimeter using 2022 NAIP imagery. Confidence scores are classified into 10% bins (10-20% through 90-100%) for both deck and pile detections. Based on ~500 verified pile locations with approximately 75% accuracy. Detection focused on areas within 150m of road networks where pile operations typically occur. Covers approximately 5,050 square miles including Plumas National Forest. Original detection at 38.4m resolution.
summary: Machine learning detection of log decks and burn piles across Plumas County and the Dixie Fire perimeter using 2022 NAIP imagery. Confidence scores are classified into 10% bins (10-20% through 90-100%) for both deck and pile detections. Based on ~500 verified pile locations with approximately 75% accuracy. Detection focused on areas within 150m of road networks where pile operations typically occur. Covers approximately 5,050 square miles including Plumas National Forest. Original detection at 38.4m resolution.
extent: [[-121.547460628898,39.5333878726314],[-120.026043182434,40.5122219505599]]
accessInformation:
thumbnail: thumbnail/thumbnail.png
maxScale: 1.7976931348623157E308
typeKeywords: ["ArcGIS","ArcGIS Server","Data","Feature Access","Feature Service","providerSDS","Service"]
description:
licenseInfo:
catalogPath:
title: Deck_Pile_Detection_PC398_fs_deck_points
type: Feature Service
url:
tags: []
culture: en-US
portalUrl:
name: Deck_Pile_Detection_PC398_fs_deck_points
guid: E015BB8A-70B2-48C9-8D60-3A49F82ACBA5
minScale: 0
spatialReference: WGS_1984_Web_Mercator_Auxiliary_Sphere