To protect the location of camera trap data containing sensitive, high-target species, many ecologists randomly obfuscate the latitude and longitude of the camera when publishing their data. For example, they may publish a random location within a 1km radius of the true camera location for each camera in their network. In this paper, we investigate the robustness of geo-obfuscation for maintaining camera trap location privacy, and show via a case study that a few simple, intuitive heuristics and publicly available satellite rasters can be used to reduce the area likely to contain the camera by 87% (assuming random obfuscation within 1km), demonstrating that geo-obfuscation may be less effective than previously believed.

With coyote attacks on humans in cities and suburbs making headlines – coyotes injured two people in Chicago earlier this month – officials could tap into a data repository to get a better handle on what's bringing the area's animals into such close proximity to humans. Called eMammal, the tool has been around for several years in one form or another and has helped researchers manage camera-trapping projects. It uses a data pipeline that takes images and metadata from the field through a cloud-based review processes and into SIdora, a Smithsonian Institution data repository. To date, eMammal has data on more than 1 million detections of wildlife worldwide, including in cities. Smithsonian researchers collaborated with others at the North Carolina Museum of Natural Sciences, Conservation International and the Wildlife Conservation Society to develop an open standard for camera trap metadata -- the Camera Trap Metadata Standard -- as part of the eMammal project. Camera traps are ruggedized cameras that researchers place in forests, jungles, grasslands, cities and elsewhere to capture images of mammals.

All around the world, conservationists and biologists have hard drives full of millions of camera trap photos. Going through these images can be laborious and time-consuming, but a new program--a partnership between Google and several conservation organizations--simplifies the process with the help of artificial intelligence. Wildlife Insights, an online portal with more than 4.5 million photos dating back to 1990, launched Tuesday. Anyone, anywhere can access the photos and pinpoint the location of wildlife. And the site also invites collaborators to drop their own camera trap images to map creatures around the world and grow the database.

A simple device, just a heat and movement sensor attached to digital camera, has revolutionised the way that conservationists learn about animals in the wild. Camera traps are a very simple solution to the task of working out when, where and how wildlife interacts with its environment. Monitoring populations without damaging habitats, these relatively simple devices have provided some astonishing finds including revealing species previously hidden in the untouched depths of the forest. Elusive new creatures aren't their only speciality, however, as in 2015, similar devices helped reveal that the critically endangered Javan rhinoceros was breeding and significantly adding to its tiny population. After identifying a likely area for a sighting, usually with the help of local guides, traps are placed at animal height on trees and posts and left to wait until wildlife walks by.

With respect to climate change, poaching, and encroachment on natural habitats, some animal populations have fared far worse than others. It's estimated that the populations of more than 4,000 species shrunk by 60% between 1970 and 2014, and a recent United Nations global assessment found that as many as 1 million species are at risk of extinction within the next decade. That's why Google has partnered with Conservation International and other organizations -- the Smithsonian's National Zoo and Conservation Biology Institute, North Carolina Museum of Natural Sciences, Map of Life, World Wide Fund for Nature, Wildlife Conservation Society, and Zoological Society of London, with support from Google's Earth Outreach program and the Gordon and Betty Moore Foundation and Lyda Hill Philanthropies. The goal is to help process one of the world's largest and most diverse databases of photographs taken from motion-activated cameras. As of today, the fruits of their labor is available through Google Cloud as a part of Wildlife Insights, an AI-enabled platform that streamlines conservation monitoring by expediting trap-camera photo analysis.