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Estimating animal population size with very high-resolution satellite imagery.

التفاصيل البيبلوغرافية
العنوان: Estimating animal population size with very high-resolution satellite imagery.
المؤلفون: Zhao P; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou, 570228, China.; CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.; National Marine Data & Information Service, Tianjin, 300171, China., Liu S; National Marine Data & Information Service, Tianjin, 300171, China., Zhou Y; CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China.; Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China.; CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China., Lynch T; CSIRO Oceans and Atmosphere Flagship, Hobart, 7001, Australia., Lu W; National Marine Data & Information Service, Tianjin, 300171, China., Zhang T; CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China.; Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China.; CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China., Yang H; CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China.; Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China.; CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
المصدر: Conservation biology : the journal of the Society for Conservation Biology [Conserv Biol] 2021 Feb; Vol. 35 (1), pp. 316-324. Date of Electronic Publication: 2020 Nov 04.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Blackwell Publishing, Inc. on behalf of the Society for Conservation Biology Country of Publication: United States NLM ID: 9882301 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1523-1739 (Electronic) Linking ISSN: 08888892 NLM ISO Abbreviation: Conserv Biol Subsets: MEDLINE
أسماء مطبوعة: Publication: Malden, MA : Blackwell Publishing, Inc. on behalf of the Society for Conservation Biology
Original Publication: Boston, Mass. : Blackwell Scientific Publications,
مواضيع طبية MeSH: Conservation of Natural Resources* , Satellite Imagery*, Animals ; Animals, Wild ; China ; Population Density
مستخلص: 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.
(© 2020 Society for Conservation Biology.)
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فهرسة مساهمة: Keywords: distribución poblacional; manejo de fauna; population distribution; population size; remote sensing; tamaño poblacional; teledetección; wildlife management; 关键词: 种群规模; 种群分布; 遥感; 野生动物管理
Local Abstract: [Publisher, Spanish; Castilian] Estimación del Tamaño de las Poblaciones Animales Mediante Imágenes Satelitales de Muy Alta Resolución Resumen Los sensores satelitales de muy alta resolución (VHR) pueden utilizarse para estimar el tamaño de las poblaciones animales, un factor muy importante para el manejo de fauna, y para adquirir las distribuciones espaciales de los animales de una manera económica, sencilla y precisa. Desarrollamos un método para la estimación satelital del tamaño poblacional que incluye fotogrametría no invasiva, a partir de la cual se calcula el área ortogonal promedio del animal, y un método de interpretación de imágenes que estima el tamaño poblacional con base en la proporción del área poblacional observada de un animal con respecto al área individual promedio. Como demostración conceptual, usamos este método para estimar el tamaño poblacional del cisne trompetista (Cygnus cygnus) dentro de una reserva natural nacional en China. Para reducir los errores, subdividimos la reserva en regiones de interés con base en las ubicaciones de los cisnes y el brillo del fondo. Las estimaciones a partir de los pixeles satelitales fueron comparadas con los conteos manuales realizados a lo largo de dos años en tres ubicaciones y en tres tipos de cobertura de suelo. Nuestros resultados mostraron a 1124 cisnes ocupando una reserva natural nacional el 15 de febrero de 2013 y el error porcentual promedio fue de 3.15% (SE 1.37). Estos resultados demostraron que nuestro método produjo datos sólidos para la estimación del tamaño poblacional que eran indistinguibles de los datos obtenidos mediante el conteo manual. Nuestro método puede usarse de manera generalizada para estimar el tamaño poblacional de especies gregarias y visibles que exhiben un contraste alto en relación con su entorno y puede orientar las estimaciones de poblaciones con fondos complejos. [Publisher, Chinese] 甚高分辨率 (VHR) 卫星传感器可以经济、便捷和准确的方式获得对野生动物管理至关重要的种群规模和空间分布信息。我们提出了一种使用卫星估算动物种群的方法, 该方法包括计算动物平均正射面积的非侵入式摄影方法, 以及从观测动物种群面积与平均个体面积比例估算动物种群规模的影像解译方法, 作为概念验证, 我们使用该方法估算了中国一个国家级自然保护区中大天鹅 (Cygnus cygnus) 的种群规模. 为了减少误差, 根据大天鹅分布和背景亮度该保护区被划分为多个感兴趣区域。我们对2期影像中3个地点和3种土地覆盖类型的卫星影像估算结果与目视计数进行了比较。结果表明 2013 年2月15日该国家级自然保护区内共有 1124 只大天鹅, 该方法的平均百分误差为 3.16% (SE 1.37) 。上述结果表明该方法为目视计数无法区分的动物提供可靠的种群规模数据。该方法总体上可用于估算可见的、聚集分布并与环境呈现高度反差的动物种群规模, 并为估算复杂背景下动物种群规模提供了思路.
تواريخ الأحداث: Date Created: 20200826 Date Completed: 20210426 Latest Revision: 20210426
رمز التحديث: 20240628
DOI: 10.1111/cobi.13613
PMID: 32839996
قاعدة البيانات: MEDLINE
الوصف
تدمد:1523-1739
DOI:10.1111/cobi.13613