{'fraction_non_alphanumeric': 0.02122186495176849, 'fraction_numerical': 0.012218649517684888, 'mean_word_length': 5.351020408163265, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Estimating animal population size with very high‐resolution satellite imagery

Very high‐resolution (VHR) satellite sensors can be used to estimate the size of animal populations, a critical factor in wildlife management, and acquire animal spatial distributions in an economical, easy, and precise way. We developed a method for satellite population size estimation that includes a noninvasive photogrammetry, from which the animal's average orthographic area is calculated, and an imagery interpretation method that estimates population size based on the ratio of an observed animal population area to the average individual area. As a proof of concept, we used this method to estimate the population size of Whooper Swans (Cygnus cygnus) in a national nature reserve in China. To reduce errors, the reserve was subdivided into regions of interest based on locations of Whooper Swan and background brightness. Estimates from the satellite pixels were compared with manual counts made over 2 years, at 3 locations, and in 3 land‐cover types. Our results showed 1124 Whooper Swans occupied a national nature reserve on 15 February 2013, and the average percent error was 3.16% (SE = 1.37). These results demonstrate that our method produced robust data for population size estimation that were indistinguishable from manual count data. Our method may be used generally to estimate population sizes of visible and gregarious animals that exhibit high contrast relative to their environments and may inform estimations of populations in complex backgrounds.