Institute on the Environment, University of Minnesota, 325 Learning & Environmental Sciences, 1954 Buford Avenue, St. Paul, MN 55108, USA.
Natural Capital Project, Stanford University Woods Institute for the Environment, 371 Serra Mall, Stanford, CA 94305, USA.
Sci Total Environ. 2019 May 15;665:1053-1063. doi: 10.1016/j.scitotenv.2019.02.150. Epub 2019 Feb 12.
The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.
自然为人类提供的益处，即生态系统服务，在基础设施开发、农业管理、保护优先级制定和可持续采购等方面的评估中越来越受到重视和考虑。然而，这些评估往往受到数据的限制，而通过地球观测（EO）可以填补这一巨大的空白，地球观测可以在空间和时间范围以及分辨率上产生各种数据。尽管人们普遍认识到这一潜力，但实际上很少有生态系统服务研究使用地球观测。在这里，我们确定了在生态系统服务建模和评估中使用地球观测的挑战和机遇。一些挑战是技术性的，涉及数据意识、处理和获取。这些挑战需要在模型平台和数据管理方面进行系统投资。其他挑战更具有概念性，但仍然是系统性的；它们是现有生态系统服务模型结构的副产品，解决这些问题需要在适用于广泛模型和方法的解决方案和工具方面进行科学投资。我们还强调了利用地球观测进行生态系统服务评估的新方法，确定了有前途的新研究领域。只有解决所有这些类型的挑战，才能更广泛地将地球观测用于生态系统服务评估。这将需要来自私营和公共机构的非传统资金和合作机会，以促进数据探索、共享和归档。在这方面的投资将体现在全球范围内更好和更准确的生态系统服务评估上。
