University of Hamburg, World Forestry, Leuschnerstr, 91, D-21031 Hamburg, Germany.
Carbon Balance Manag. 2011 Nov 8;6(1):10. doi: 10.1186/1750-0680-6-10.
Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources.
We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives.
CONCLUSIONS, BRIEF SUMMARY AND POTENTIAL IMPLICATIONS: Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.
愿意采用 REDD 机制的国家需要建立国家衡量、报告和核实(MRV)系统,提供有关森林碳储量和碳储量变化的信息。由于森林覆盖面积广泛,这些信息通常通过基于样本的调查获得。大多数运营采样方法利用地球观测数据和现场评估作为数据源。
我们比较了在 REDD 范围内提出的四种不同抽样设计方案(简单随机抽样、回归估计、分层抽样、带回归估计的两阶段抽样)的成本效益。其中三种设计方案提供了现场和地球观测数据的组合。在不同的遥感覆盖设置下,计算了每个现场样方的成本、遥感图像的成本、遥感和现场数据中量化属性之间的相关性、以及种群变异性和总调查成本的标准误差百分比。森林碳储量评估的成本效益取决于所选择的抽样设计。我们的结果表明,遥感图像的成本是抽样设计成本效益的决定性因素。样本总体的变异性会影响成本效益,但不会改变个别设计方案的成本效益模式。
结论、简要总结和潜在影响:我们的结果清楚地表明,在开发森林碳储量评估和选择遥感技术时,考虑成本效益非常重要。REDD 的 MRV 系统的开发需要基于一个合理的优化过程,该过程比较不同数据源和抽样设计的成本效益。这有助于减少与量化碳储量相关的不确定性,并增加采用 REDD 机制的经济效益。