DOI: 10.5061/dryad.m905qfv25
title: Identification of Wright fishhook cactus using drone and remote sensing technology

description: Obtaining accurate population estimates of plants has been an integral
 part of the listing, recovery, and delisting of species under the U.S.
 Endangered Species Act (ESA) of 1973 and for monitoring vegetation in
 response to livestock grazing management. However, obtaining such
 estimates for many plant species remains a daunting and labor-intensive
 task. The use of small unmanned aircraft systems (sUAS or drones) may
 provide an effective alternative to ground surveys for rare and endangered
 plants. The objective of our study was to evaluate the effectiveness of
 using sUAS (DJI Phantom 4 Pro with a 20 MP camera) to survey for Wright
 fishhook cactus (Sclerocactus wrightiae L.D.Benson), a small (1-8 cm
 diameter) endangered plant species endemic to Utah, located in southwest
 USA desert grazing lands. This species functions in enhancing soil
 stability, providing nectar for pollinating insect species, and increasing
 biodiversity in hot arid environments. We used georectified images
 overlaid with grid plots in ArcGIS Pro to 1) assess the effectiveness of
 very high resolution remotely sensed imagery for detecting and counting
 individual cacti and then compared these with ground surveys and 2)
 determine the optimal altitude (10 m, 15 m, or 20 m) and associated
 resolution for identifying individual cactus plants. Our results
 demonstrated that the lowest altitude flights (10 m) provided the best
 detection rates (from 26.6% at 20m to 67% at 10m; p&lt;0.001) and
 counts (p&lt;0.001). We generated population estimates based on the
 inclusion of error terms in the analysis. We suggest that sUAS can be
 effectively used to locate cactus within grazing land areas, but should be
 coupled with ground surveys for higher accuracy and reliability. We
 suggest that sUAS surveys can be effectively conducted for locating cactus
 populations within the flowering period and for documenting known
 populations outside of the flowering period. While sUAS remote sensing did
 not provide a complete census of Wright fishhook cactus plants, likely due
 to its small, obscure, thorny, low-growing structure, nonetheless this
 tool can be effective in early plant population detection, monitoring
 populations in response to grazing activities, and preventing potential
 soil/plant disturbance resulting from ground-based surveys.
description: We conducted survey flights and collected images using drone
 technology. Specially, we utilized a DJI Phantom 4 Pro (SZ DJI Technology
 Co. Ltd. Shenzhen, China) with a standard DJI RGB camera (Table 1).
 NIR/RGB images were obtained using a Sony Qx1 camera transported by a 3DR
 Solo RTF quadcopter. Each flight was programmed using the Pix4D capture
 application (Pix4D S.A. Lausanne, Switzerland) on an iPad:6th Gen (Apple,
 Cupertino, California). Flight images were stitched into an orthomosaic
 using Pix4D (Pix4D S.A. Lausanne, Switzerland). Images were georectified
 using GPS coordinate locations of distinct cactus plants in each image as
 ground control. Images were loaded into ArcGIS Pro where orthomasics were
 georectified using GPS coordinate locations of distinct cactus plants in
 each image as ground control. On the ground sample
 plots were censured by foot for cacti immediately following the three
 flights. Each cactus location was marked using the same GPS, and the
 following attributes were recorded: location (UTM), diameter (cm), number
 of stems, and any damage or disturbance to the plant.
 Cactus counts between the different survey altitudes and ground
 censuses were compared using two techniques: 1) a validation data matrix
 adapted from Rominger and Meyer (2019) and 2) mixed effects modeling
 (glmer and lmer). In all analyses, 14 flights were used for analysis at
 each flight altitude. One of the original 15 flights was not included due
 to distortion caused by high winds at the time of the flight. Generalized
 and linear mixed-effects regression (glmer and lmer) were conducted in R
 (R Core Team 2018) using packages lme4 (Bates et al.), lmerTest
 (Kuznetsova et al., 2017), MuMIn (Barton) to analyze cactus detection
 rates (%) and cactus counts (#) relative to flight altitude.