Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired From an Unmanned Aerial Vehicle (Uav)

Abstract

ABSTRACT:Wildlife aerial surveys require time and significant resources. Multispecies detection could reduce costs to a single census for species that coexist spatially. Traditional methods are demanding for observers in terms of concentration and are not adapted to multispecies censuses. The processing of multispectral aerial imagery acquired from an unmanned aerial vehicle (UAV) represents a potential solution for multispecies detection. The method used in this study is based on a multicriteria object-based image analysis applied on visible and thermal infrared imagery acquired from a UAV. This project aimed to detect American bison, fallow deer, gray wolves, and elks located in separate enclosures with a known number of individuals. Results showed that all bison and elks were detected without errors, while for deer and wolves, 0-2 individuals per flight line were mistaken with ground elements or undetected. This approach also detected simultaneously and separately the four targeted species even in the presence of other untargeted ones. These results confirm the potential of multispectral imagery acquired from UAV for wildlife census. Its operational application remains limited to small areas related to the current regulations and available technology. Standardization of the workflow will help to reduce time and expertise requirements for such technology.

An approach for using off-the-shelf object-based image analysis software to detect and count birds in large volumes of aerial imagery

“…In some cases, it may be possible to reduce commission error rates to the point where manual review of automated analysis results is not necessary, while in other cases, like ours, varying degrees of manual postanalysis effort may be required. Although animal contrast in thermal-infrared imagery has proven useful for automated detection of mammals (Conn et al 2014, Chrétien et al 2015, 2016, Seymour et al 2017, the very coarse pixel resolution of thermal cameras compared to RGB cameras generally renders them ineffective for aerial detection of comparatively smaller birds (Chabot and Francis 2016). It should be noted that any aerial image-based survey will only allow detection of subjects that are visible from overhead and miss subjects that are, for example, concealed under canopy or diving underwater.…”

“…Objects can then be analyzed in elaborate ways based on a large variety of spatial, spectral, and texture attributes. OBIA has notably been used to detect birds at sea (Groom et al 2007(Groom et al , 2013) and on inland waters (Groom et al 2011, Liu et al 2015, as well as terrestrial mammals in a nature park (Chrétien et al 2015(Chrétien et al , 2016. In recent years, commercial offthe-shelf OBIA software has become increasingly accessible, but there is a need to develop standardized and readily adaptable procedures for using the software to detect and count birds (Chabot and Francis 2016).…”

Computer-automated bird detection and counts in high-resolution aerial images: a review

“…), and captive bison ( Bison bison ), elk ( Cervus canadensis ), fallow deer ( Dama dama ), white‐tailed deer ( Odocoileus virginianus ), and gray wolves ( Canis lupus ) (Chrétien et al. , ). However, a major obstacle to using aerial thermal images to detect birds is the low‐resolution of the cameras that, at best, record 640 × 480‐pixel frames, combined with the generally smaller size of birds compared to mammals.…”

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

“…In this instance, the body temperature of the animals is used, as it differs considerably from the surrounding environment (especially at night, at dusk or dawn). Direct classification of FES animals have been conducted using satellite RS techniques such as RapidEye or Worldview-2 for a number of animal species such as deer, wildebeest or birds [320,449], and UAV technology is becoming more commonly applied in recording wild animal species [448]. However, the success of UAV and satellite technologies for recording wild animals within forest has been found to be very limited.…”

“…Low cost camera traps with high battery lifetimes and memory capacity integrate thermal and movement sensors as well as RGB-photo and video technology and can record animals in FES [326,327,334,446]. Thermal cameras and multi-sensor combinations with optical sensors and LiDAR on UAV-and airborne platforms have been used to record wild animal species such as the white-tailed deer [331,447,448]. In this instance, the body temperature of the animals is used, as it differs considerably from the surrounding environment (especially at night, at dusk or dawn).…”