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Validation of a large area land cover product using purpose-acquired airborne video

机译:使用目的明确的机载视频验证大面积土地覆盖产品

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Large area land cover products generated from remotely sensed data are difficult to validate in a timely and cost effective manner. As a result, preexisting data are often used for validation. Temporal, spatial, and attribute differences between the land cover product and pre-existing validation data can result in inconclusive depictions of map accuracy. This approach may therefore misrepresent the true accuracy of the land cover product, as well as the accuracy of the validation data, which is not assumed to be without error. Hence, purpose-acquired validation data is preferred; however, logistical constraints often preclude its use - especially for large area land cover products. Airborne digital video provides a cost-effective tool for collecting purpose-acquired validation data over large areas. An operational trial was conducted, involving the collection of airborne video for the validation of a 31,000 km(2) sub-sample of the Canadian large area Earth Observation for Sustainable Development of Forests (EOSD) land cover map (Vancouver Island, British Columbia, Canada). In this trial, one form of agreement between the EOSD product and the airborne video data was defined as a match between the mode land cover class of a 3 by 3 pixel neighbourhood surrounding the sample pixel and the primary or secondary choice of land cover for the interpreted video. This scenario produced the highest level of overall accuracy at 77% for level 4 of classification hierarchy (13 classes). The coniferous treed class, which represented 71% of Vancouver Island, had an estimated user's accuracy of 86%. Purpose acquired video was found to be a useful and cost-effective data source for validation of the EOSD land cover product. The impact of using multiple interpreters was also tested and documented. Improvements to the sampling and response designs that emerged from this trial will benefit a full-scale accuracy assessment of the EOSD product and also provides insights for other regional and global land cover mapping programs. (c) 2006 Elsevier Inc. All rights reserved.
机译:由遥感数据生成的大面积土地覆盖产品很难及时,经济地进行验证。结果,通常使用预先存在的数据进行验证。土地覆被产品与预先存在的验证数据之间的时间,空间和属性差异可能导致对地图准确性的不确定性描述。因此,这种方法可能会错误地代表土地覆被产品的真实准确性以及验证数据的准确性,而这并不是假定没有错误。因此,首选获得目的验证数据;但是,后勤方面的限制通常会阻止其使用-特别是对于大面积的土地覆盖产品。机载数字视频提供了一种经济高效的工具,可用于在大范围内收集目的明确的验证数据。进行了一项运营试验,涉及收集机载视频,以验证31,000 km(2)的加拿大大面积森林可持续发展地球观测(EOSD)土地覆盖图(不列颠哥伦比亚省温哥华岛,加拿大)。在该试验中,EOSD产品与机载视频数据之间的一种协议形式被定义为围绕采样像素的3 x 3像素邻域的模式土地覆盖类别与该土地的主要或次要选择之间的匹配解释视频。对于分类层次结构的第4级(13个类),此方案产生了最高的整体准确性,达到77%。针叶树类占温哥华岛的71%,估计用户的准确性为86%。发现专用视频是验证EOSD土地覆盖产品的有用且具有成本效益的数据源。还测试并记录了使用多个口译员的影响。该试验中出现的采样和响应设计改进将有助于对EOSD产品进行全面的准确性评估,并为其他区域和全球土地覆盖制图计划提供见解。 (c)2006 Elsevier Inc.保留所有权利。

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