Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, USA.
Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Naturales y Matemáticas, Guayaquil, Ecuador.
Sci Data. 2021 Nov 26;8(1):304. doi: 10.1038/s41597-021-01081-9.
Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth's surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.
遥感卫星影像具有通过获取地球表面信息来监测和理解动态环境现象的潜力。然而，由于数据限制等原因，海洋生态系统的研究强度不如陆地生态系统。海表温度 (SST) 和叶绿素-a (Chlo-a) 数据可以提供沿海地区高时空分辨率的环境条件定量信息。我们以沿海地区专属经济区作为研究区域，编制了 2003 年至 2020 年全球范围内 SST 和 Chlo-a 的月和年统计数据。这个即用型数据集旨在减少沿海地区的本地、区域、大陆和全球各级研究的计算时间和成本。该数据集可能对生态学、海洋学、生物地理学、渔业和全球变化等领域的研究人员有兴趣。数据库的目标应用包括生物多样性和海洋微生物的环境监测以及环境异常。
