Multiple UAV Flights across the Growing Season Can Characterize Fine Scale Phenological Heterogeneity within and among Vegetation Functional Groups

David J A Wood,Paul C Stoy,Todd M Preston,Scott Powell

doi:10.3390/rs14051290

David J A Wood, Paul C Stoy + Show 2 more

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https://doi.org/10.3390/rs14051290

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Abstract

Grasslands and shrublands exhibit pronounced spatial and temporal variability in structure and function with differences in phenology that can be difficult to observe. Unpiloted aerial vehicles (UAVs) can measure vegetation spectral patterns relatively cheaply and repeatably at fine spatial resolution. We tested the ability of UAVs to measure phenological variability within vegetation functional groups and to improve classification accuracy at two sites in Montana, U.S.A. We tested four flight frequencies during the growing season. Classification accuracy based on reference data increased by 5–10% between a single flight and scenarios including all conducted flights. Accuracy increased from 50.6% to 61.4% at the drier site, while at the more mesic/densely vegetated site, we found an increase of 59.0% to 64.4% between a single and multiple flights over the growing season. Peak green-up varied by 2–4 weeks within the scenes, and sparse vegetation classes had only a short detectable window of active phtosynthesis; therefore, a single flight could not capture all vegetation that was active across the growing season. The multi-temporal analyses identified differences in the seasonal timing of green-up and senescence within herbaceous and sagebrush classes. Multiple UAV measurements can identify the fine-scale phenological variability in complex mixed grass/shrub vegetation.

Highlights

The goal of this study is to examine tradeoffs in classification depth and accuracy between collecting data from individual versus multiple Unpiloted aerial vehicles (UAVs) flights during the growing season in rangelands
The single flight classifications based on the 12 June 2018, flight at Argenta and the
This study examined the ability of UAVs to identify fine-scale phenological heterogeneity, can be used to inform logistical decisions of future UAV studies, and illustrated options to effectively process data from multiple UAV flights

Summary

Introduction

Rangelands are widely distributed globally and contribute significant ecosystem services [1]. The grasslands, shrublands, and other ecosystems that make up rangelands are comprised of diverse plant species with divergent life-history strategies (e.g., annual vs perennial), structural differences (e.g., grass vs shrub), and photosynthetic pathways (e.g., C3 vs C4), which creates pronounced spatial variability in plant function and high biodiversity [2–4]. Interannual variability in climate, coupled with community and abiotic differences, can lead to large interannual variability in rangeland vegetation function [5–8]. Due to the collective variability and complexity of vegetation communities, understanding of the drivers of rangeland vegetation processes (e.g., carbon accumulation, reproduction, productivity, nutrient availability, etc.) across scales is needed to develop effective management strategies and predictive models of changes in a dynamic world [9,10]. Ground-based measurements provide crucial information for understanding these processes but are limited in scope. Linking in situ measurements with remotely sensed data can expand the geographic extent of observation, furthering the ability to prioritize management efforts and aid in answering key ecological questions [11–13]

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