DOI: 10.7280/d1fd5c
title: Monitoring marine bound debris using UAS on the US-Mexico Border

description: The Tijuana river estuary suffers from overwhelming solid-waste
 contamination such as marine bound plastics, tires, and sediment. Funded
 by the US EPA's Border 2020 program (SOLTA-C-19-008), this project
 intends to establish a framework for bi-national monitoring of
 trans-boundary, marine bound trash (TBMBT) using light-weight unmanned
 aerial systems (UASs), also known as drones. The developed framework is
 intended to benefit 1) border authorities through the establishment of a
 low-cost, minimally invasive, operational standard to monitor TBMBT in
 coastal ecosystems and optimize upstream trash capture interventions, 2)
 natural habitat in the Tijuana River Valley (TRV) and TRE through the
 identification of trash hotspots to guide clean-up operations, and 3)
 visitors and residents of the TRV and TRE through the long term benefits
 of reduced trash volumes from optimized interventions. Three surveys were
 carried out between 2020 and 2021 collecting data on trash locations using
 drones and ground-based smartphones. Drone imagery was processed
 to extract locations of trash using image classification algorithms, while
 ground-based data was used to complement the data collected from drones
 and to validate the accuracy of the drone generated data.
description: UAS monitoring occured at two sites, Border Field State Park on
 the US side of the Los Laureles Canyon watershed (LLCW), and the Milenio
 2000 neighborhood on the Mexico side of the LLCW. Across the duration of
 the project three surveys were conducted: Jan/Feb 2020, Novemebr 2020, and
 Jan/Feb 2021. Each survey required one day of field work.
 UAS/image monitoring was used as tools to detect trash
 accumulation. To assist with those goals a fixed-wing AeroVironment
 Quantix UAS was deployed at border field state park due to its extended
 flight range capabilities and its dual RGB/NIR camera setup. At the
 sediment basins locations in Border Field State PArk, and in the Milenio
 2000 neighborhood, a Phantom 4 quadcopter was deployed able to navigate
 accurately at low altitude between the canyon walls. Flights occured
 between the hours of 10:00 am – 2:00 pm to reduce impact from shadows in
 the collected imagery. Flight dates were conditional on agreeable weather
 conditions, in consideration of bird nesting sseason, as well as in
 coordination with land managers (State Parks, California Border Patrol,
 and Mexico Aviacion Civil). For US flights, survey dates occured on
 weekends when FAA airspace at the Tijuana river valley is in class G
 (unrestricted to UAS deployment). UAS flights were executed at low
 altitude, approximately 150 ft above ground level, capturing images with a
 ground resolution of approximately 1.2 cm/pixel irrespective of the
 imaging sensor used. A fine image resolution was targeted to capture macro
 and mega trash, which have defined diameters of 2-10 cm, and &gt;10 cm
 respectively. Ground data collection campaigns of trash
 locations and conditions were carried out concurrently with the UAS
 surveys on the same survey days. Ground survey methods of trash debris
 developed by the Bay Area Stormwater Management Agencies Association
 (BASMAA, 2017) and the Stormwater Monitoring Coalition (San Francisco
 RWQCB, 2004) were adapted and implemented for this project. Surveys were
 carried out using a digital survey sheet developed using Esri’s Survey123
 online platform (ESRI, Redlands, CA) that can be accessed at:
 https://arcg.is/Tuyf5. During each survey, the survey sheet was accessed
 in the field using GPS enabled tablets or smartphones and allowed
 collecting visual qualitative data of trash such as photographs,
 categorization of trash type, and ratios of trash types within larger
 patches in accordance with the reference methods. Measurements of trash
 were also performed using tape measures whenever possible (e.g. length and
 width of trash patch). Field data collection was organized in conjunction
 with local land managers across the LLCW. <b>UAS
 DATA Processing:</b> Individual UAS images were
 photogrammetrically processed using Metashape Pro (Agisoft LLC, St.
 Petersburg, Russia), a popular commercial Structure from Motion (SfM)
 photogrammetry software package with low entry costs relative to competing
 commercial software. Using SfM photogrammetry, the individual UAS images
 were geometrically corrected and stitched together into orthometric images
 (orthophotos) with uniform scale across the whole scene. Separate
 orthophotos were generated for each survey and for each survey location.
 Ground control points were not available at the survey sites and due to
 budget limitations SfM processing was carried out without the use of
 ground control. We estimate 3-5 m horizontal accuracy of the derived
 orthophotos (equivalent to the UAV on-board GPS receiver).
 The focus of this project is to detect trash from UAS imagery,
 and here we tested various image classification algorithms from the field
 of computer vision. Image classification algorithms have proven to be
 capable of segmenting aerial imagery into features and landcover classes,
 and here we tested automatic unsupervised classification as well as
 semi-automatic supervised classification strategies.
 <b>SHARED DATA:</b> 
 Orthophotos of each UAS survey (raster tif format).
 Ground based data of identified trash locations (vector
 shapefile format). Classification results from
 supervised object-oriented classifier (raster tif format).