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LANDFIRE Session: Full Speed Ahead: Increasing Frequency and Reducing Latency of National-Scale Maps

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Pecora 2022

Under the big data paradigm, many national mapping programs are feeling the pressure to increase frequency and reduce latency of national-scale map products. Conterminous United States (CONUS)-scale land cover programs are especially challenged given the efficiencies required to produce classified maps at this scale, let alone annual products using rulesets or imagery representing near current conditions. Data users have high expectations of accurate near-real time data that they can use to update their near-real time models and processes. But that’s the goal and the game is on! New satellite and aerial platforms, computing technologies, and models are helping to speed things up and increase accuracy, aided by cloud computing, state of the art compositing and change detection algorithms, artificial intelligence, machine learning, new sensors and space-aerial-ground lidar. In this special session, representatives from LANDFIRE, NLCD and LCMAP will showcase processes and technology that are being applied to get mapped products out the door faster and better.

Presentation Abstracts

NLCD: Balancing accuracy and methodology innovation with increasing production frequency
Jon Dewitz - USGS

Mapping Disturbance for the Conterminous United States in Less than Six Months: Exploring Improvements in Processing Power, Image Compositing, and Improved Change Detection Algorithms
Brian Tolk - KBR contractor to USGS EROS Center
Abstract | Presentation

A Random Forest-Based Commission Error Filter for LANDFIRE Disturbance Mapping
Sanath Sathyachandran Kumar ASRC Federal Data Solutions, contractor to USGS EROS Center
Abstract | Presentation

The LANDFIRE image-based annual prototype: Detailed annual updates to vegetation maps for the United States using machine learning
Daryn Dockter - LANDFIRE Vegetation Specialist, KBR Contractor to USGS EROS
Abstract | Presentation

Painting the landscape by number: The use of image segmentation to improve geospatial vegetation classification
Joshua J. Picotte - ASRC Federal Data Solutions, contractor to the USGS EROS Center
Abstract | Presentation

Annual Monitoring of Land Cover Change: The Benefits and Challenges of Lowering Latency
Jesslyn Brown - USGS


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