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

Abstract

ABSTRACT. Computer-automated image analysis techniques can save time and resources for detecting and counting birds in aerial imagery. Sophisticated object-based image analysis (OBIA) software is now widely available and has proven effective for various challenging detection tasks, but there is a need to develop accessible and readily adaptable procedures that can be implemented in an operational context. We developed a systematic, repeatable approach using commercial off-the-shelf OBIA software, and tested its effectiveness and efficiency to detect and count Lesser Snow Geese (Chen caerulescens caerulescens) in large numbers of images of breeding colonies across the Canadian Arctic that present a variety of landscapes, numerous confounding features, and varying illumination conditions and exposure levels. Coarse-scale review of analysis results was necessary to remove conspicuous clusters of commission errors, thus rendering the technique semiautomated. It was effective for imagery with spatial resolutions of 4-5 cm, producing overall accurate estimates of goose numbers compared to manual counts (R2 = 0.998, regression coefficient = 0.974) in 41 test images drawn from several breeding colonies. The total automated count (19,920) across all test images exceeded the manual count (19,836) by just 0.4%. We estimate the typical time required to review images for errors to be only 5-10% of that required to count birds manually. This could reduce the person-time required to analyze aerial photos of the major Arctic colonies of Snow Geese from several months to several days. Our approach could be adapted to many other bird detection tasks in aerial imagery by anyone possessing at least basic skills in image analysis and geographic information systems.

Surveying Wild Animals from Satellites, Manned Aircraft and Unmanned Aerial Systems (UASs): A Review

“…Aerial surveys of wild animals fall into two main categories: (a) Real-time surveys, in which the wild animals are counted in situ by trained observers, i.e., no imaging sensors are used during the surveys [2,17,[37][38][39]41], and (b) photographic surveys, in which wild animals are counted from still RGB images or video [36,42,[70][71][72][73]. Infrared thermography has also been tested for surveying wild animals with a significant temperature difference from the background environment, such as the Pacific walrus (Odobenus rosmarus) [63,74,75], and red deer (Cervus elaphus), fallow deer (Dama dama), roe deer (Capreolus capreolus), wild boar (Sus scrofa), foxes, wolves and badgers [76].…”

“…Manned helicopter or fixed-wing vehicles have a relatively long endurance time and have been used for regular and geographically comprehensive animal monitoring by directly observing animals from the air [17,23,37,39,41] or reviewing centimeter-scale resolution imagery [42,[70][71][72][73]. Stoner et al [41] assessed the effectiveness of protection strategies in Tanzania based on a decade (1988-1998) of aerial survey data collected for 23 types of large herbivores, including buffalos (Syncerus caffer), elands (Taurotragus oryx), elephants (Loxodonta africana), and giraffes (Giraffa camelopardalis).…”

“…With the development of digital imaging and computer technologies, still images or videos captured from manned aerial aircraft have been used to count animals [36,71]. The separation of animal counting and aerial flight missions provides the photography-based method with several benefits over the real-time survey method, including allowing aircraft to fly at a higher altitude (high-resolution or telephoto cameras are required), revisiting the imagery or video after flights, and developing automatic counting algorithms [71][72][73]. Furthermore, aerial imagery can be collected with RGB cameras and infrared thermography at significantly higher spatial resolutions of up to 2.5 cm [23].…”

“…Furthermore, aerial imagery can be collected with RGB cameras and infrared thermography at significantly higher spatial resolutions of up to 2.5 cm [23]. Therefore, aerial imagery allows one to directly discern more small (<0.6 m) animals, such as birds [70][71][72][73], sea turtles, and fish [42]; large animals that are difficult to distinguish from the background at the species level, such as roe deer (Capreolus pygargus) and red deer (Cervus elaphus) [36]; and some animals in varying habitats and at night, such as Pacific walruses (Odobenus rosmarus) [74], and and red deer (Cervus elaphus), fallow deer (Dama dama), roe deer (Capreolus capreolus), wild boar (Sus scrofa), foxes, wolves and badgers [76]. Table 4 summarizes the animal species surveyed using manned aircraft.…”

“…However, manual reviews of remote sensing imagery by inspectors or the direct observation of animals from aircraft are time consuming and subjective [1,2]. With the resolution improvement of remote sensing imagery and advancements in computer technologies, researchers have developed various automatic and semiautomated counting algorithms for detecting and counting wild animals in remote sensing imagery [3,[71][72][73]. Although automatic and semiautomated counting algorithms have remarkable advantages in terms of dataset processing speed, most such studies have focused on only a few remote sensing images (usually covering only a few square kilometers) in relatively homogenous environments [23,32].…”