‘Uncertainty audit’ for ecosystem accounting: Satellite-based ecosystem extent is biased without design-based area estimation and accuracy assessment

IF 6.1 2区 环境科学与生态学 Q1 ECOLOGY
Zander S. Venter, Bálint Czúcz, Erik Stange, Megan S. Nowell, Trond Simensen, Bart Immerzeel, David N. Barton
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引用次数: 0

Abstract

There are currently no guidelines in the System of Environmental-Economic Accounting Ecosystem Accounting (SEEA EA) for quantifying and disclosing uncertainty. However, without quantifying uncertainty, it is unclear whether or not accounting tables contain biased (erroneous) area estimates which do not reflect real land cover changes. We use Oslo municipality in Norway as a case study to illustrate best practices in quantifying unbiased area estimates using design-based statistical methods. As input for ecosystem extent accounts, we compared a custom Sentinel-2 land cover map with a globally available one called Dynamic World for 2015, 2018 and 2021. The design-based area estimation involved (i) generating a stratified probability sample of locations using the satellite-based maps to define strata, (ii) assigning ecosystem type labels to the samples using photointerpretation according to a response design protocol, and (iii) applying a stratified area estimator to produce 95% confidence intervals around opening, closing and change stocks in the extent accounting table. We found that pixel counting practices, currently adopted by the SEEA EA community, led to biased extent accounts, particularly for ecosystem conversions, with biases averaging 195% of the true change value derived from design-based methods. We found that the uncertainty inherent in state-of-the-art satellite-based maps exceeded the ability to detect real change in extent for some ecosystem types including water and bare/artificial surfaces. In general, uncertainty in extent accounts is higher for ecosystem type conversion classes compared to stable classes, and higher for 3-yr compared to 6-yr accounting periods. Custom, locally calibrated satellite-based maps of ecosystem extent changes were more accurate (81% overall accuracy) than globally available Dynamic World maps (75%). We suggest that rigorous accuracy assessment in SEEA EA will ensure that ecosystem extent (and consequently condition and service) accounts are credible. A standard for auditing uncertainty in ecosystem accounts is needed.

生态系统核算的 "不确定性审计":如果不进行基于设计的面积估算和精度评估,基于卫星的生态系统范围就会出现偏差
目前,环境经济核算体系生态系统核算 (SEEA EA) 中没有量化和披露不确定性的指导原则。然而,如果不对不确定性进行量化,就不清楚核算表是否包含有偏差(错误)的面积估算,而这些估算并不反映真实的土地覆被变化。我们以挪威奥斯陆市为案例,说明使用基于设计的统计方法量化无偏见面积估算的最佳实践。作为生态系统范围账户的输入,我们将定制的哨兵-2 土地覆被图与全球可用的 2015 年、2018 年和 2021 年动态世界地图进行了比较。基于设计的面积估算包括:(i) 使用卫星地图生成分层概率位置样本,以定义分层;(ii) 根据响应设计规程,使用照片解释法为样本分配生态系统类型标签;(iii) 应用分层面积估算器,围绕范围核算表中的开放、关闭和变化存量得出 95% 的置信区间。我们发现,SEEA EA 社区目前采用的像素计数方法会导致范围核算出现偏差,尤其是在生态系统转换方面,偏差平均为基于设计方法得出的真实变化值的 195%。我们发现,最先进的卫星地图中固有的不确定性超出了检测某些生态系统类型(包括水和裸露/人工表面)范围真实变化的能力。一般来说,生态系统类型转换类的范围核算不确定性高于稳定类,3 年核算期的不确定性高于 6 年核算期。与全球可用的 "动态世界 "地图(75%)相比,定制的、经过本地校准的基于卫星的生态系统范围变化地图更为准确(总体准确率为 81%)。我们建议在 SEEA EA 中进行严格的准确性评估,以确保生态系统范围(以及随之而来的状况和服务)账户的可信度。需要一个标准来审核生态系统账户中的不确定性。
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来源期刊
Ecosystem Services
Ecosystem Services ECOLOGYENVIRONMENTAL SCIENCES&-ENVIRONMENTAL SCIENCES
CiteScore
14.90
自引率
7.90%
发文量
109
期刊介绍: Ecosystem Services is an international, interdisciplinary journal that is associated with the Ecosystem Services Partnership (ESP). The journal is dedicated to exploring the science, policy, and practice related to ecosystem services, which are the various ways in which ecosystems contribute to human well-being, both directly and indirectly. Ecosystem Services contributes to the broader goal of ensuring that the benefits of ecosystems are recognized, valued, and sustainably managed for the well-being of current and future generations. The journal serves as a platform for scholars, practitioners, policymakers, and other stakeholders to share their findings and insights, fostering collaboration and innovation in the field of ecosystem services.
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