Suppr超能文献

美国本土2016年国家土地覆盖数据库(NLCD)的专题精度评估

Thematic Accuracy Assessment of the NLCD 2016 land cover for the conterminous United States.

作者信息

Wickham James, Stehman Stephen V, Sorenson Daniel G, Gass Leila, Dewitz Jon A

机构信息

Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27111, USA.

College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA.

出版信息

Remote Sens Environ. 2021 May;257. doi: 10.1016/j.rse.2021.112357.

Abstract

The National Land Cover Database (NLCD) is an operational land cover monitoring program providing updated land cover and related information for the United States at five-year intervals. NLCD2016 extends temporal coverage to 15 years (2001 - 2016). We collected land cover reference data for the 2011 and 2016 nominal dates to report land cover accuracy for the NLCD2016 database 2011 and 2016 land cover components at Level II and Level I and for Level I 2011 - 2016 land cover change using two definitions of agreement. For both the 2011 and 2016 land cover components, single-date Level II overall accuracies (OA) were 72% (standard error of ± 0.9%) when agreement was defined as match between the map label and primary reference label only and 86% (± 0.7%) when agreement also included the alternate reference label. The corresponding level I OA for both dates were 79% (± 0.9%) and 91% (± 1.0%). The 2011 - 2016 user's and producer's accuracies (UA and PA) were ~75% for forest loss and PA for water loss, grassland loss, and grass gain were > 70% when agreement included a match between the map label and either the primary or alternate reference label. Depending on agreement definition and level of the classification hierarchy, OA for the 2011 land cover component of the NLCD2016 database was about 4% to 7% higher than OA for the 2011 land cover component of the NLCD2011 database, suggesting that the changes in mapping methodologies initiated for production of the NLCD2016 database have led to improved product quality. Additionally, we used the reference dataset collected for assessment of the NLCD2011 database to assess the 2001 and 2006 land cover components of the NLCD2016 database. OA for the 2001 and 2006 land cover components was 1% - 5% lower than OA for the 2011 and 2016 land cover components of the NLCD2016 database. Higher OA for 2011 and 2016 land cover components of the NLCD2016 database relative to OA for its 2001 and 2006 components may be attributable to differences in reference data quality.

摘要

国家土地覆盖数据库(NLCD)是一项业务性土地覆盖监测计划,每五年为美国提供更新的土地覆盖及相关信息。NLCD2016将时间覆盖范围扩展至15年(2001 - 2016年)。我们收集了2011年和2016年标称日期的土地覆盖参考数据,以报告NLCD2016数据库2011年和2016年土地覆盖组成部分在二级和一级水平的土地覆盖精度,以及2011 - 2016年一级水平土地覆盖变化情况,采用了两种一致性定义。对于2011年和2016年的土地覆盖组成部分,当一致性仅定义为地图标签与主要参考标签匹配时,单日期二级总体精度(OA)为72%(标准误差±0.9%);当一致性还包括替代参考标签时,总体精度为86%(±0.7%)。两个日期相应的一级总体精度分别为79%(±0.9%)和91%(±1.0%)。当一致性包括地图标签与主要或替代参考标签匹配时,2011 - 2016年森林损失的用户精度和生产者精度(UA和PA)约为75%,水域损失、草地损失和草地增加的生产者精度大于70%。根据一致性定义和分类层次级别,NLCD2016数据库2011年土地覆盖组成部分的总体精度比NLCD2011数据库2011年土地覆盖组成部分的总体精度高约4%至7%,这表明为生成NLCD2016数据库而启动的制图方法变化导致了产品质量的提高。此外,我们使用为评估NLCD2011数据库而收集的参考数据集来评估NLCD2016数据库2001年和2006年的土地覆盖组成部分。NLCD2016数据库2001年和2006年土地覆盖组成部分的总体精度比NLCD2016数据库2011年和2016年土地覆盖组成部分的总体精度低1% - 5%。NLCD2016数据库2011年和2016年土地覆盖组成部分的总体精度相对于其2001年和2006年组成部分的总体精度更高,这可能归因于参考数据质量的差异。

相似文献

引用本文的文献

6
Where forest may not return in the western United States.美国西部的森林可能无法恢复。
Ecol Indic. 2023 Feb;146:109756. doi: 10.1016/j.ecolind.2022.109756.

本文引用的文献

4
Global land change from 1982 to 2016.全球 1982 年至 2016 年土地变化情况。
Nature. 2018 Aug;560(7720):639-643. doi: 10.1038/s41586-018-0411-9. Epub 2018 Aug 8.
6
Developing a science of land change: challenges and methodological issues.发展土地变化科学:挑战与方法问题
Proc Natl Acad Sci U S A. 2004 Sep 28;101(39):13976-81. doi: 10.1073/pnas.0401545101. Epub 2004 Sep 21.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验