Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests - preliminary results
暂无分享,去创建一个
Anna Zmarz | Stanislaw Pagacz | J. Witczuk | A. Zmarz | Maciej Cypel | J. Witczuk | Stanisław Pagacz | Maciej Cypel
[1] Hiroshi Takahashi,et al. Comparison of Drive Counts and Mark-Resight As Methods of Population Size Estimation of Highly Dense Sika Deer (Cervus nippon) Populations , 2016, PloS one.
[2] J. H. Knapen,et al. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems , 2017, 1701.01611.
[3] C. Bertolucci,et al. Seasonal variation of activity patterns in roe deer in a temperate forested area , 2013, Chronobiology international.
[4] Karen Anderson,et al. Lightweight unmanned aerial vehicles will revolutionize spatial ecology , 2013 .
[5] B. Jędrzejewska,et al. Effects of exploitation and protection on forest structure, ungulate density and wolf predation in Bialowieza Primeval Forest, Poland , 1994 .
[6] Jan Kałuziński,et al. Weight and body measurements of forest and field roe deer , 1982 .
[7] J. Červený,et al. Reproductive and morphometric characteristics of wild boar (Sus scrofa) in the Czech Republic , 2018 .
[8] Julie Linchant,et al. HOW MANY HIPPOS (HOMHIP): ALGORITHM FOR AUTOMATIC COUNTS OF ANIMALS WITH INFRA-RED THERMAL IMAGERY FROM UAV , 2015 .
[9] D. Bird,et al. Evaluation of an off-the-shelf Unmanned Aircraft System for Surveying Flocks of Geese , 2012 .
[10] N. Morellet,et al. Ungulate Management in Europe: Problems and Practices: The census and management of populations of ungulates in Europe , 2010 .
[11] D. McCullough,et al. Infrared Scanning Techniques for Big Game Censusing , 1968 .
[12] Brett T. McClintock,et al. Estimating multispecies abundance using automated detection systems: ice‐associated seals in the Bering Sea , 2014 .
[13] Reg Austin,et al. Unmanned Aircraft Systems: Uavs Design, Development and Deployment , 2010 .
[14] J. Smart,et al. Monitoring woodland deer populations in the UK: an imprecise science , 2004 .
[15] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[16] B. Sabol,et al. Technique using thermal infrared-imaging for estimating populations of gray bats , 1995 .
[17] A. C. Seymour,et al. Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery , 2017, Scientific Reports.
[18] Jarrod C Hodgson,et al. Precision wildlife monitoring using unmanned aerial vehicles , 2016, Scientific Reports.
[19] Jérôme Théau,et al. Visible and thermal infrared remote sensing for the detection of white‐tailed deer using an unmanned aerial system , 2016 .
[20] Izabela Karsznia,et al. UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica) , 2017 .
[21] Peter Christiansen,et al. Automated Detection and Recognition of Wildlife Using Thermal Cameras , 2014, Sensors.
[22] U. Franke,et al. Aerial ungulate surveys with a combination of infrared and high–resolution natural colour images , 2012 .
[23] Martin Israel. A UAV-BASED ROE DEER FAWN DETECTION SYSTEM , 2012 .
[24] S. Palmer,et al. Drive counts as a method of estimating ungulate density in forests: mission impossible? , 2011, Acta Theriologica.
[25] S. Wich,et al. Dawn of Drone Ecology: Low-Cost Autonomous Aerial Vehicles for Conservation , 2012 .
[26] E. Sharp,et al. USING THERMAL IMAGERY IN THE AERIAL SURVEY OF ANIMALS , 1998 .
[27] GEORGE PIERCE JONES,et al. An Assessment of Small Unmanned Aerial Vehicles for Wildlife Research , 2006 .
[28] S. Buckland. Introduction to distance sampling : estimating abundance of biological populations , 2001 .
[29] M. Heurich,et al. Long-term measurement of roe deer (Capreolus capreolus) (Mammalia: Cervidae) activity using two-axis accelerometers in GPS-collars , 2013 .
[30] Michael C. Hatfield,et al. Unmanned aircraft systems in wildlife research: current and future applications of a transformative technology , 2016 .
[31] Sandra Johnson,et al. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation , 2016, Sensors.
[32] S. Gomáriz,et al. Fine-scale bird monitoring from light unmanned aircraft systems , 2012 .
[33] Douglas J. Krause,et al. A small unmanned aerial system for estimating abundance and size of Antarctic predators , 2015, Polar Biology.
[34] Julie Linchant,et al. Are unmanned aircraft systems (UASs) the future of wildlife monitoring? A review of accomplishments and challenges , 2015 .
[36] Mark S. Boyce,et al. GPS Based Daily Activity Patterns in European Red Deer and North American Elk (Cervus elaphus): Indication for a Weak Circadian Clock in Ungulates , 2014, PloS one.
[37] M. Mulero-Pázmány,et al. Remotely Piloted Aircraft Systems as a Rhinoceros Anti-Poaching Tool in Africa , 2014, PloS one.
[38] Mark S. Udevitz,et al. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery , 2009, Int. J. Appl. Earth Obs. Geoinformation.
[39] Kevin W Eliceiri,et al. NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.