Skidmore Andrew K, Coops Nicholas C, Neinavaz Elnaz, Ali Abebe, Schaepman Michael E, Paganini Marc, Kissling W Daniel, Vihervaara Petteri, Darvishzadeh Roshanak, Feilhauer Hannes, Fernandez Miguel, Fernández Néstor, Gorelick Noel, Geijzendorffer Ilse, Heiden Uta, Heurich Marco, Hobern Donald, Holzwarth Stefanie, Muller-Karger Frank E, Van De Kerchove Ruben, Lausch Angela, Leitão Pedro J, Lock Marcelle C, Mücher Caspar A, O'Connor Brian, Rocchini Duccio, Roeoesli Claudia, Turner Woody, Vis Jan Kees, Wang Tiejun, Wegmann Martin, Wingate Vladimir
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands.
Department of Earth and Environmental Science, Macquarie University, Sydney, New South Wales, Australia.
Nat Ecol Evol. 2021 Jul;5(7):896-906. doi: 10.1038/s41559-021-01451-x. Epub 2021 May 13.
Monitoring global biodiversity from space through remotely sensing geospatial patterns has high potential to add to our knowledge acquired by field observation. Although a framework of essential biodiversity variables (EBVs) is emerging for monitoring biodiversity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing biodiversity products that can further improve the monitoring of geospatial biodiversity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of biodiversity from satellites. Biodiversity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for example, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of biodiversity from local to global scales.
通过遥感地理空间模式从太空监测全球生物多样性，极有可能增加我们通过实地观测所获得的知识。尽管一个用于监测生物多样性的基本生物多样性变量（EBV）框架正在形成，但其与遥感产品的契合度欠佳，阻碍了实地观测之间的插值。本研究编制了一份全面且经过优先排序的遥感生物多样性产品清单，这些产品可进一步改进对地理空间生物多样性模式的监测，强化EBV框架及其适用性。通过专家评审过程表明，生态系统结构和生态系统功能EBV类别最具相关性、可行性、准确性和成熟度，可用于直接从卫星监测生物多样性，它们能够捕捉干扰的生物学效应以及栖息地结构。对于仍在开发中的、需要更高分辨率卫星遥感的生物多样性产品（例如，针对EBV类别物种特征），则给予较低优先级。某些EBV无法直接通过太空遥感测量，特别是EBV类别遗传组成。将遥感产品与EBV联系起来将加速产品生成，改善从地方到全球尺度的生物多样性状况报告。
