Applying Cloud-Based Computing and Emerging Remote Sensing Technologies to Inform Land Management Decisions

Monica Vermillion, Josh Enterkine, Lucas Spaete, Nancy Glenn

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Who: Boise State University and Mountain Home Air Force Base

What: Creating a species level classification map through the use of Google Earth Engine (GEE), a cloud-based computing platform, to map invasive species

When: In-situ data collected in Summer 2018, a continuation of data collected in Summer 2016. Classification was created in Fall 2018. Unmanned aerial vehicles (UAV) flights in August 2018.

Where: Mountain Home Air Force Base (MHAFB) in southwest Idaho, ecosystem is in the Great Basin Range (GBR)

Why: The introduction of exotic species like cheatgrass ( Bromus tectorum ) has drastically altered the fire cycle of the Northern Great Basin (NGB) from 50 – 100 year burn intervals to 10 year intervals (1). Factors such as soil, elevation, temperature, and precipitation can affect the resilience of a sagebrush steppe ecosystem to invasive species. Remote sensing techniques allow large scale analysis of invasive encroachment and assessment of conservation efforts and land management.

Original languageAmerican English
Title of host publicationASPRS Annual Conference and International Lidar Mapping Forum 2019
StatePublished - 1 Jan 2019

EGS Disciplines

  • Earth Sciences
  • Geophysics and Seismology

Fingerprint

Dive into the research topics of 'Applying Cloud-Based Computing and Emerging Remote Sensing Technologies to Inform Land Management Decisions'. Together they form a unique fingerprint.

Cite this