Tim Bailey

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Supporting forest climate adaptation planning with point cloud analytics for nontraditional geospatial users
Tim Bailey

In fire adapted forests, three dimensional structural characteristics are critical factors in drought and fire resilience. Public point cloud repositories such as the USGS 3DEP program, Opentopography.org, and in the future the Earth Archive, are critical data infrastructure for climate adaptation planning. As we collectively face escalating climate hazards, the value in deploying operational geospatial tools for managing risk grows. Historical forest management in the Western United States has resulted in declining resilience. To stabilize above ground carbon pools and secure critical ecosystem services, the State of California and the US Forest Service have committed to treating 400,000 hectares of forest per year through 2030. These typically involve strategic mechanical thinning coupled with application of beneficial low to moderate intensity fire. These programs are often planned and implemented through shared stewardship agreements between government agencies and implementation partners from nongovernmental organizations, First Nations governments, and local jurisdictions. Large government land managers and industrial forest operators have typically used commercial enterprise geospatial software for data driven decision support. Software licensing restrictions create arbitrary barriers between partners. The proliferation of nontraditional climate planners and the need for long term reproducible data science products have created an important opportunity for the FOSS4G community. The California Forest Lidar Collaborative has been providing technical support and training to a diverse user community to apply point cloud analytics to a broad range of forestry problems. This program has facilitated the adoption of data science pipelines using Python, R, PDAL, GDAL, GRASS, and QGIS. This results in transparent environmental compliance processes, democratization of climate adaptation planning, reproducible forest data science workflows and increased diffusion of best-in-class geospatial tools.

Environmental Sustainability
Microsoft AI for Earth