Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems.

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales.

Provoking a Cultural Shift in Data Quality.

Ecological studies require quality data to describe the nature of ecological processes and to advance understanding of ecosystem change. Increasing access to big data has magnified both the burden and the complexity of ensuring quality data. The costs of errors in ecology include low use of data, increased time spent cleaning data, and poor reproducibility that can result in a misunderstanding of ecosystem processes and dynamics, all of which can erode the efficacy of and trust in ecological research.

Evaluation of the automated reference toolset as a method to select reference plots for oil and gas reclamation on Colorado Plateau rangelands.

Rangelands are typically characterized by low precipitation and low biomass which makes them susceptible to disturbance and difficult to reclaim. These characteristics become a management issue when considering the widespread and significant impact of oil and gas development on rangelands. Reclamation from this land use involves the complexities of dealing with multiple state and federal agencies, private landowners, and their sometimes conflicting rules.

Integrating drone imagery with existing rangeland monitoring programs.

The recent availability of small and low-cost sensor carrying unmanned aerial systems (UAS, commonly known as drones) coupled with advances in image processing software (i.e., structure from motion photogrammetry) has made drone-collected imagery a potentially valuable tool for rangeland inventory and monitoring.

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world.

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.

Rangeland and pasture monitoring: an approach to interpretation of high-resolution imagery focused on observer calibration for repeatability.

Collection of standardized assessment and monitoring data is critically important for supporting policy and management at local to continental scales. Remote sensing techniques, including image interpretation, have shown promise for collecting plant community composition and ground cover data efficiently. More work needs to be done, however, evaluating whether these techniques are sufficiently feasible, cost-effective, and repeatable to be applied in large programs.