Journal für Ornithologie · 2019 · 20 citations · 11 references
Earth ObservationEnvironmental MonitoringEngineeringOceanographyTerrestrial SensingEarth ScienceSocial SciencesUnderwater ImagingDigital SurveysBiogeographyDrone SurveyingAerial SurveysSatellite ImagingBiodiversitySurveyingGeographyBird MonitoringDigital Survey TechniquesDigital SurveyEarth Observation DataVisual Aerial SurveysLand Cover MapDigital Video SurveysDigital PhotogrammetryRemote Sensing
The increasing demand for robust marine bird abundance and distribution assessments coupled with technological advances has led to the development of digital survey techniques for birds. Although digital surveys for bird monitoring are becoming a standard method in some countries, their strengths and weaknesses and comparability with traditional visual surveys remain insufficiently documented and understood. Aiming to improve existing knowledge on digital video monitoring techniques, we conducted one parallel digital video survey with 2-cm ground resolution and a 544-m swath flown at 549 m and an aerial visual survey flown at 76 m over the southern Baltic Sea in March 2015. We assessed bird sighting rates, identification rates, observed densities, and model-based abundance estimates. The digital survey covered a larger area through direct registrations, provided higher numbers of bird sightings and identified species, and higher spatial accuracy than the visual survey. Overall species identification rates were similar between the survey methods; however, there were marked differences among bird taxonomic groups: more individuals were identified to species level in the digital survey dataset for the majority of taxonomic groups, except for grebes and auks. These advantages supplement other previously identified benefits of digital aerial surveys, such as the elimination of bird disturbance due to high flight altitude, reduced observer bias, and availability of raw data for quality assurance. Furthermore, higher numbers of direct bird sightings at a higher spatial resolution during digital surveys ensure better statistical analyses, including distribution modelling, of more species for the same survey effort.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 352.8K citations · Full text
Simon N. Wood · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2010 · 7.2K citations · Full text
Aerial surveys of seabirds: the advent of digital methods
S. T. Buckland, M. Louise Burt, Eric A. Rexstad et al. · Journal of Applied Ecology · 2012 · 125 citations · Full text
Earth Observation, Ocean Monitoring, Environmental Monitoring +13