Exploring Invasive Plant Detection with Small Unmanned Aircraft Systems and Sensors Active
Spatial maps showing locations of invasive plants equip land managers with a valuable tool. Properly acquired aerial imagery provides vegetation mappers or machine learning software an efficient venue to map invasive plants, in contrast to the effort required for an on-the-ground census of plants. Small Unmanned Aircraft Systems (sUAS) can yield quick acquisition of aerial imagery over localized landscapes at low-altitudes (less than 400 feet above ground level) to offer high-resolution imagery for invasive plant mapping. However, questions arise regarding best practices for collecting imagery suitable for detecting invasive plants. What combination of sUAS and sensor parameters provides adequate imagery for detecting and mapping invasive plants? Is one sensor type better than another to detect invasive plants? Do seasonal periods (early, middle, late growing season) or environmental conditions (drought, prescribed burn) require adjustments in sUAS and sensor parameters? Does a set of collection standards adjust according to the invasive plant species being detected, and if so, how?
To investigate all possible variables would be daunting. However, this project explores the feasibility of collecting sUAS imagery with multi-spectral and natural-color sensors as a mode to detect and map invasive plants. Sensor types and their settings; sUAS types and their parameters including flight altitude for image resolution; and environmental conditions including time of season and land management are some of the facets being studied.
Proof of concepts and knowledge from these explorations are applied to future invasive plant detection projects and shared accordingly to aid other scientists in their research endeavors.
For information on sUAS and sensor assets at UMESC, visit https://www.usgs.gov/centers/umesc/science/small-unmanned-aircraft-system-assets?qt-science_center_objects=0#qt-science_center_objects
- Overview
Spatial maps showing locations of invasive plants equip land managers with a valuable tool. Properly acquired aerial imagery provides vegetation mappers or machine learning software an efficient venue to map invasive plants, in contrast to the effort required for an on-the-ground census of plants. Small Unmanned Aircraft Systems (sUAS) can yield quick acquisition of aerial imagery over localized landscapes at low-altitudes (less than 400 feet above ground level) to offer high-resolution imagery for invasive plant mapping. However, questions arise regarding best practices for collecting imagery suitable for detecting invasive plants. What combination of sUAS and sensor parameters provides adequate imagery for detecting and mapping invasive plants? Is one sensor type better than another to detect invasive plants? Do seasonal periods (early, middle, late growing season) or environmental conditions (drought, prescribed burn) require adjustments in sUAS and sensor parameters? Does a set of collection standards adjust according to the invasive plant species being detected, and if so, how?
To investigate all possible variables would be daunting. However, this project explores the feasibility of collecting sUAS imagery with multi-spectral and natural-color sensors as a mode to detect and map invasive plants. Sensor types and their settings; sUAS types and their parameters including flight altitude for image resolution; and environmental conditions including time of season and land management are some of the facets being studied.
Proof of concepts and knowledge from these explorations are applied to future invasive plant detection projects and shared accordingly to aid other scientists in their research endeavors.
For information on sUAS and sensor assets at UMESC, visit https://www.usgs.gov/centers/umesc/science/small-unmanned-aircraft-system-assets?qt-science_center_objects=0#qt-science_center_objects
Sources/Usage: Public Domain. View Media DetailsThe UMESC UAS team exploring invasive plant detection along a dike using a natural-color sensor on a 3DR Solo drone (Necedah National Wildlife Refuge, August 2019)