数字图像处理翻译

Good practices for estimating area and assessing accuracy of land change
估计面积和评估土地变化的准确度良好做法
The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are critical to ensure the integrity of land change information. We provide practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data. The good practice recommendations address the three major components: sampling design, response design and analysis. The primary good practice recommendations for assessing accuracy and estimating area are: (i) implement a probability sampling design that is chosen to achieve the priority objectives of accuracy and area estimation while also satisfying practical constraints such as cost and available sources of reference data; (ii) implement a response design protocol that is based on reference data sources that provide sufficient spatial and temporal representation to accurately label each unit in the sample (i.e., the “reference classification” will be considerably more accurate than the map classification being evaluated); (iii) implement an analysis that is consistent with the sampling design and response design protocols; (iv) summarize the accuracy assessment by reporting the estimated error matrix in terms of proportion of area and estimates of overall accuracy, user's accuracy (or commission error), and producer's accuracy (or omission error); (v) estimate area of classes (e.g., types of change such as wetland loss or types of persistence such as stable forest) based on the reference classification of the sample units; (vi) quantify uncertainty by reporting confidence intervals for accuracy and area parameters; (vii) evaluate variability and potential error in the reference classification; and (viii) document deviations from good practice that may substantially affect the results. An example application is provided to illustrate the recommended process.
遥感科学与应用社区已经开发出越来越可靠，一致的和强大的方法用于捕捉动态的土地，以满足各种信息需求。统计学健全和透明的方式进行评估的准确性和估计的变化范围是至关重要的，以确保土地变化信息的完整性。我们从业者提供了一套“良好做法”的建议设计和实施的变化图的精度评估，并根据参考样本数据估计区域。良好做法的建议解决三个主要部分组成：采样设计，响应的设计和分析。主要的良好做法的建议，评估的准确性和估算面积为：（i）执行该选择来实现的精度和面积估算的优先目标，同时也能满足实际情况的限

制，如参考数据成本和可用资源的概率抽样设计; （ii）实施响应设计协议，它是基于提供足够的空间和时间表示样品中准确地标记每个单元参考的数据源（例如，根据“参照分类”，将显着大于地图分类被评估更准确??） ; （三）实施分析与抽样设计和响应的设计方案保持一致; （四）通过报告在面积和总体精度，用户精度（或委托误差），以及生产者的准确度（或不作为的错误）估计的比例计算估计误差矩阵总结了精度评估; （五）估计的类（例如，改变类型，如湿地的损失或类型的持久性，如稳定的森林）的基础上的样本单位的参考分类区; （六）通过报告置信区间的精度和面积参数量化的不确定性; （ⅶ）评估变异性和在参考分类的潜在错误;及（viii）良好做法文件的偏差，可能会大大影响结果。一个示例应用程序被提供来说明所建议的过程。