ACCESS NUMBER: M14AC00017 

STUDY TITLE: Testing the Use of Unmanned Aircraft Systems for Intertidal Surveys 

REPORT TITLE: Testing the Use of Unmanned Aircraft Systems for Intertidal Surveys 

CONTRACT NUMBER: M14AC00017, BOEM 2016-051

SPONSORING OCS REGION: Alaska 

APPLICABLE PLANNING AREA(S): Cook Inlet 

FISCAL YEAR(S) OF PROJECT FUNDING: 2014-2016 

COMPLETION DATE OF REPORT: May 24, 2016 

COSTS: $31,254 

PROJECT MANAGER(S): Brenda Konar, Katrin Iken 

LEAD AUTHOR OF REPORT: Brenda Konar 

AFFILIATION: University of Alaska Fairbanks 

ADDRESS: 905 N Koyukuk Dr. Fairbanks, Alaska 99775 

PRINCIPAL INVESTIGATOR(S): Brenda Konar and Katrin Iken 

KEY WORDS: Intertidal monitoring, Seagrass, Rocky, Unmanned Aircraft System, Unmanned 

Aerial Vehicle 

BACKGROUND: Intertidal monitoring is critical for supporting sustained ecosystem health and 

functioning because coastal systems are particularly vulnerable to environmental stressors and 

human impacts. Intertidal monitoring projects can be limited in their practicality because 

traditional labor-intensive methods, such as visual surveys and removal of biota, restrict the 

spatial extent for which data can be collected during low tide exposure periods. This spatial 

limitation can confound sampling intended to capture representative species occurrence and 

distribution, intertidal community structure, and variability in community composition. Ideally, 

intertidal survey methods should be completed quickly with broad special coverage while 

providing high enough taxonomic resolution to support accurate and detailed biological 

descriptions of large intertidal areas. 

OBJECTIVES: Use of a small Unmanned Aircraft System (sUAS) was tested in conjunction with 

an ongoing rocky and seagrass intertidal monitoring program in the Gulf of Alaska. A small 

Unmanned Aerial Vehicle (sUAS) with a camera was flown at low altitude to test if its images 

would allow for the analysis of percent cover of individual intertidal taxa or taxon groups. The 

efficacy of sUAS imagery was evaluated through comparison with data and images taken 

manually by ground observers. In addition, the sUAS imagery included large-scale (on the order 

of 100s of meters) coverage of a seagrass bed. Those images were used to assess variability in 

seagrass cover, which is difficult to achieve for a representative area doing ground surveys. 

DESCRIPTION: We paired intertidal surveys using a camera-equipped sUAS with ongoing 

traditional monitoring surveys at one rocky, macroalgal-dominated beach and one soft-bottom, 

seagrass intertidal site in Kachemak Bay, Alaska. At the rocky intertidal site, the sUAS was 

deployed at the mean higher high water (MHHW), the mean tidal level (MTL), and the mean 

lower low water (MLLW) level. At the seagrass site, the sUAS was deployed from a single 

starting point on the beach and flown in various directions across the seagrass bed. At the same 

time and location of each sUAS deployment, a field team conducted traditional biological ground 

surveys along a 50-m transect tape at the same depth stratum/location as the sUAS surveys. At 

the rocky intertidal site, the observer surveys included the visual estimation of percent cover of 

macroalgae, sessile invertebrates, and bare substrate in ten randomly-placed 1-m2 quadrats 

along the transect at each of the tidal strata. In addition, a photograph was taken of each 

quadrat and used for later comparisons with the sUAS images. At the seagrass site, percent 
cover of seagrass and other groups such as mussels, macroalgae, diatom mats, and open 

substrate was calculated from five randomly-placed 0.25-m

2

quadrats along a 50-m transect in 

the approximate center of the bed. A picture of each quadrats was taken to compare with five 

randomly selected sUAS image frames along the same transect. To attempt to assess the 

distribution and patchiness in seagrass cover over a larger spatial extent, the sUAS was flown 

along extended haphazard flight paths over the seagrass bed. 

STUDY RESULTS: Observer percent cover surveys on the ground consistently achieved a 

higher resolution of taxonomic categories compared with sUAS images. Most of these 

differences resulted from the much higher taxonomic resolution possible for macroalgae by the 

observers in both the rocky intertidal and seagrass systems. In most cases, percent cover of 

individual categories and overall community composition were very similar once the observer 

data were aggregated at the coarser taxonomic resolution level of the sUAS images in the rocky 

intertidal. However, we still detected notable differences in community structure at the coarse 

taxonomic resolution at the MHHW. As at the MHHW, we found significant differences in 

percent cover for some individual species at the MTL and MLLW, although the community-wide 

structures were highly similar. While the sUAS did not consistently provide sufficient resolution 

on the genus or order level for all species, our results show promise for the sUAS imaging 

approach in detecting larger spatial scale (regional) differences in community structure on the 

coarse taxonomic resolution level. Similar to the rocky intertidal system, the higher resolution of 

macroalgae in the observer data versus the sUAS images in the seagrass system was related 

to the limited resolution of sUAS imagery for these delicate algal species. The ground camera 

imagery also proved a more reliable tool in detecting macroalgal species in the seagrass system 

than the sUAS camera. Seagrass cover itself was not significantly different between sUAS

images and observer data; a promising case for using sUASs in monitoring programs where the 

goal is to assess seagrass cover over large spatial scales. We successfully used sUAS images 

to create distribution maps of seagrass cover over a much larger scale than is feasible to cover 

by observers on the ground. The maps demonstrate that the size of a seagrass bed can be 

reliably determined by sUAS because the transition from seagrass cover to no cover was clearly 

recognizable. The sUAS images were also useful to gain an understanding of the small-scale

variability and patchiness of seagrass cover, even in the densest region of the bed. 

SIGNIFICANT CONCLUSIONS: The low resolution of the sUAS imagery created problems in 

reliably identifying many taxa to species. It is possible this shortfall could be remedied by using 

higher resolution cameras and a compatible sUAS system. Lower flight altitudes would help with 

image resolution; however, this could be challenging if a beach contains large boulders or other 

obstacles to flight altitude. Ultimately, the value of using sUASs over the more traditional 

monitoring method of observer surveys remains dependent on the goals of a monitoring 

program. Questions that can be addressed by a lower taxonomic resolution than observers 

produce could benefit greatly from the sUAS approach, mostly because of the larger spatial 

extent that can be covered during a single low tide period. Our approach of assessing largescale distribution patterns of seagrass demonstrated that the coarse taxonomic resolution of 

sUAS images was sufficient to yield highly valuable results. Other coarse taxonomic uses could 

include focusing on key taxa such as rockweed (Fucus sp.) in rocky intertidal areas or similar 

surveys. While we obtained mixed results for the applicability of sUASs in the rocky intertidal 

and seagrass bed in our study, we have shown that sUASs can be valuable tools for specific 

monitoring questions and, with further development, they are likely to be an important tool for

monitoring and ocean observing in the future. More testing of their use in various systems and 

the optimization of camera resolution to flight height will lay the groundwork for more routine 

applications.
STUDY PRODUCT(S): 

Konar B and K Iken. Submitted to Deep Sea Research II (special issue: Gulf of Alaska). The 

use of unmanned aerial vehicle imagery in intertidal monitoring.

Iken K, B Konar and S Vanderwaal. 2016. Testing the use of unmanned aircraft systems in

intertidal surveys. Oral presentation at the Coastal Marine Institute Annual Review in 

Anchorage, Alaska. January 29, 2016.

Konar B and K Iken. 2016. Recommendations for the use of unmanned aircraft systems in 

intertidal surveys. Poster at the Alaska Marine Science Symposium in Anchorage,

Alaska. 

Konar B. 2015. The use of unmanned aircraft systems for marine application in Kachemak Bay. 

Oral presentation at the Kachemak Bay Science meeting in Homer, Alaska. March 5-7 

2015.

Iken K, B Konar, S Vanderwaal and M Rogers. 2015. Testing the use of unmanned aircraft 

systems for intertidal surveys-proof of concept. Oral presentation at the Coastal Marine 

Institute Annual Review in Anchorage, Alaska. January 23, 2015.

Konar B, K Iken, M Rogers and S Vanderwaal. 2015. Testing the use of unmanned aircraft 

systems for intertidal surveys – proof of concept. Poster presentation at the Alaska 

Marine Science Symposium in Anchorage, Alaska. January 19-23, 2015.