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Lidar Strategy Pacific Northwest Region

Explore the strategic framework for Lidar acquisition and utilization in the Pacific Northwest Region to inform NEPA. Learn about efficient procurement processes, standardized data analysis, and integration with existing vegetation mapping.

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Lidar Strategy Pacific Northwest Region

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  1. Lidar Strategy Pacific Northwest Region Using LiDAR to Inform NEPA April 23, 2015 BLM Office | Salem, OR Mark Riley Remote Sensing Coordinator US Forest Service, Region 6, Data Resources Management Portland, OR

  2. Lidar has evolved considerably in 50 years

  3. REGIONAL STRATEGY TEAM Pete Heinzen, Data Resources Management Brian Wing, Pacific Southwest Station Tom DeMeo, Natural Resources Leah Rathbun, NR Kim Mellen-McLean, NR Robyn Darbyshire, NR Josh Chapman, NR Dorothy Thomas, DRM Mike Simpson, Deschutes NF Mark Riley, DRM

  4. Lidar strategic framework • The Pacific Northwest Region has developed a strategic framework for acquiring, processing, and exploiting lidar effectively and efficiently. To create lidar continuity across the Region it is necessary to: • Explore new processing methods of lidar data • Identify new partnerships and leverage existing ones • Coordinate interdisciplinary efforts across the Region to assess existing natural resource conditions • Monitor outcomes of land management actions

  5. Lidar strategic framework • The R6 strategy provides recommendations for: • An efficient procurement processes • A protocol to prioritize lidar acquisition • A framework for modeling and analysis of lidar data to provide standardized outputs • Collecting in-situ field data to validate interpretation of lidar outputs Easier, more consistent tablet-based collection sUAS higher order field data collection

  6. Lidar strategic framework • Integrating lidar with Gradient Nearest Neighbor (GNN) existing vegetation mapping • An effective approach for lidar data discovery and distribution • Training of interdisciplinary specialists and managers Possible structural component or increase in classification accuracy http://lemma.forestry.oregonstate.edu/methods/species-maps

  7. Data discovery and distribution • New las tools (ArcGIS, Fugro, ERDAS) that will make point clouds less esoteric to a larger community • Huge files that are difficult to store and work with (las, derivatives, and other remotely sensed data sets) • Enterprise T: drive (ds.fs.fed.us\EFS) is a temporary, non-scalable solution • ArcGIS Pro and online • Image server options (remote rendering, remote processing) • OR archived at OSU and DOGAMI • OR and WA LiDAR archived on BLM and FS external hard drives in Portland

  8. Data discovery and distribution • Cloud-based archiving • Network Access Storage (NAS) • Intranet access • Near-term, low-cost solution (48TB/$7,000; 4TB/$8,700; 96TB/$10,150 at RAID0) • Scalable • Smaller NAS at field office 16TB, $2,500

  9. Mark Riley Remote Sensing Coordinator markriley@fs.fed.us USDA Forest Service Portland, OR

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