Image Tagging

Camera trapping produces high volumes of raw image data, to which additional information needs to be added to make it useful for analysis. This is done by image tagging, which is the process of adding descriptive tags to the metadata of images using the software Digikam. While the cameras automatically embed basic details such as timestamp, temperature, and location, the crucial step of manually recording the species captured in each image is performed by the women. This process transforms the data from a chaotic collection into a structured dataset that can be readily filtered, sorted, and analysed.

While this helps filter and categorize species data from the vast number of images, it is also a crucial first step in more advanced analyses to understand habitat use, population size, inter‑species interactions, and spatio-temporal niche segregation across the winter landscape.

After the retrieval of the winter camera traps, the team painstakingly processes thousands of photographs, assigning species tags to each file. Their efforts have revealed a rich assemblage of wildlife: alongside the iconic snow leopard, the cameras have captured wolves, red foxes, stone martens, ibex, blue sheep, mountain weasels, and birds such as chukars and Himalayan snowcocks. To date, the women have tagged close to 100,000 images from their own winter surveys in the Spiti Valley. Their contribution extends far beyond the local area—they have also tagged more than one million images collected across the Greater Himalayan and Trans‑Himalayan regions of Himachal Pradesh and Jammu & Kashmir as part of larger collaborative projects. This extensive, meticulously curated image library now serves as a valuable resource for researchers studying high‑altitude ecosystems and the species that depend on them.