Generation and comprehensive validation of 30 m conterminous United States Landsat percent tree cover and forest cover loss annual products

IF 5.7 Q1 ENVIRONMENTAL SCIENCES
Alexey Egorov , David P. Roy , Luigi Boschetti
{"title":"Generation and comprehensive validation of 30 m conterminous United States Landsat percent tree cover and forest cover loss annual products","authors":"Alexey Egorov ,&nbsp;David P. Roy ,&nbsp;Luigi Boschetti","doi":"10.1016/j.srs.2023.100084","DOIUrl":null,"url":null,"abstract":"<div><p>This study describes the generation and comprehensive validation of 30 m Landsat-based annual percent tree cover and forest cover loss products for the conterminous United States (CONUS). The products define (i) forest status with respect to three thematic classes: stable forest, stable non-forest, forest cover loss, (ii) percent tree cover (PTC, 0–100%), (iii) percent tree cover decrease (ΔPTC), and (iv) the Landsat acquisition dates bounding mapped forest cover loss occurrence. Forest was defined, based on the U.S. federal government forested land definition, as 30 m pixels with mapped PTC &gt;10%. Annual products were derived using temporally overlapping 9-year periods (mapping within each central 5-year period) of USGS Landsat Analysis Ready Data (ARD) with reconciliation of the results between periods. The products for 2013 are presented and were validated rigorously by comparison with 1910 30 m independent reference data interpreted from bi-temporal &lt;1 m resolution aerial imagery selected using a Stage 3 CONUS stratified random sampling design. The stable forest, stable non-forest, and forest cover loss results were validated using standard accuracy metrics derived from the confusion matrix. The overall accuracy was high (0.92), and class-specific user's accuracy (UA) and producer's accuracy (PA) metrics were also high for the stable forest (UA = 0.94, PA = 0.84) and stable non-forest (UA = 0.90, PA = 0.97) classes. The forest cover loss class had similarly high UA (0.89) but significantly lower PA (0.61) indicating non-negligible omission errors. All standard errors were &lt;5%. The total area of stable forest over CONUS for year 2013 was estimated as 3,049,380 ± 114,392 km<sup>2</sup> and the total area of forest cover loss was estimated as 31,382 ± 4751 km<sup>2</sup>, with 95% confidence interval. The PTC and ΔPTC products were validated by linear regression with the reference data, indicating good PTC precision reflected by a high coefficient of determination (R<sup>2</sup> = 0.79), and accuracy with a regression slope close to unity (0.86) and small intercept (3.48). The regression between mapped ΔPTC and the reference data had a high coefficient of determination (R<sup>2</sup> = 0.74) but a regression slope further away from unity (0.78) and small intercept (1.68) consistent with the forest cover loss omission errors revealed by the confusion matrix. State-level comparison of the stable forest mapped area with forest land area statistics published by the U.S. federal government for the 48 CONUS states indicated reasonable correspondence (R<sup>2</sup> = 0.97) but with a 1.15 regression line slope indicating relative over estimation of the mapped stable forest area, likely related to forest land reporting differences.</p></div>","PeriodicalId":101147,"journal":{"name":"Science of Remote Sensing","volume":"7 ","pages":"Article 100084"},"PeriodicalIF":5.7000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666017223000093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 2

Abstract

This study describes the generation and comprehensive validation of 30 m Landsat-based annual percent tree cover and forest cover loss products for the conterminous United States (CONUS). The products define (i) forest status with respect to three thematic classes: stable forest, stable non-forest, forest cover loss, (ii) percent tree cover (PTC, 0–100%), (iii) percent tree cover decrease (ΔPTC), and (iv) the Landsat acquisition dates bounding mapped forest cover loss occurrence. Forest was defined, based on the U.S. federal government forested land definition, as 30 m pixels with mapped PTC >10%. Annual products were derived using temporally overlapping 9-year periods (mapping within each central 5-year period) of USGS Landsat Analysis Ready Data (ARD) with reconciliation of the results between periods. The products for 2013 are presented and were validated rigorously by comparison with 1910 30 m independent reference data interpreted from bi-temporal <1 m resolution aerial imagery selected using a Stage 3 CONUS stratified random sampling design. The stable forest, stable non-forest, and forest cover loss results were validated using standard accuracy metrics derived from the confusion matrix. The overall accuracy was high (0.92), and class-specific user's accuracy (UA) and producer's accuracy (PA) metrics were also high for the stable forest (UA = 0.94, PA = 0.84) and stable non-forest (UA = 0.90, PA = 0.97) classes. The forest cover loss class had similarly high UA (0.89) but significantly lower PA (0.61) indicating non-negligible omission errors. All standard errors were <5%. The total area of stable forest over CONUS for year 2013 was estimated as 3,049,380 ± 114,392 km2 and the total area of forest cover loss was estimated as 31,382 ± 4751 km2, with 95% confidence interval. The PTC and ΔPTC products were validated by linear regression with the reference data, indicating good PTC precision reflected by a high coefficient of determination (R2 = 0.79), and accuracy with a regression slope close to unity (0.86) and small intercept (3.48). The regression between mapped ΔPTC and the reference data had a high coefficient of determination (R2 = 0.74) but a regression slope further away from unity (0.78) and small intercept (1.68) consistent with the forest cover loss omission errors revealed by the confusion matrix. State-level comparison of the stable forest mapped area with forest land area statistics published by the U.S. federal government for the 48 CONUS states indicated reasonable correspondence (R2 = 0.97) but with a 1.15 regression line slope indicating relative over estimation of the mapped stable forest area, likely related to forest land reporting differences.

生成和综合验证30 m连续美国陆地卫星百分比树木覆盖和森林覆盖损失年产品
本研究描述了美国(CONUS)基于陆地卫星的30m年树木覆盖率和森林覆盖损失百分比产品的生成和综合验证。这些产品定义了(i)三个主题类别的森林状况:稳定森林、稳定非森林、森林覆盖损失,(ii)树木覆盖率百分比(PTC,0-100%),(iii)树木覆盖减少百分比(ΔPTC),以及(iv)陆地卫星获取日期,该日期界定了绘制的森林覆盖损失发生情况。根据美国联邦政府的林地定义,森林被定义为30米像素,地图PTC>;10%。年度产品是使用美国地质调查局陆地卫星分析就绪数据(ARD)的时间重叠的9年期(每个中心5年期内的映射)得出的,并对各期之间的结果进行对账。给出了2013年的产品,并通过与1910年的30m独立参考数据进行比较进行了严格验证;使用第3阶段CONUS分层随机抽样设计选择的1m分辨率航空图像。稳定森林、稳定非森林和森林覆盖损失的结果使用从混淆矩阵得出的标准精度指标进行了验证。总体准确度较高(0.92),稳定森林(UA=0.94,PA=0.84)和稳定非森林(UA 0.90,PA=0.97)类别的特定类别用户准确度(UA)和生产者准确度(PA)指标也较高。森林覆盖损失类别具有类似的高UA(0.89),但显著较低的PA(0.61),表明不可忽略的遗漏误差。所有标准误差均<;5%。2013年CONUS的稳定森林总面积估计为3049380±114392 km2,森林覆盖损失总面积预计为31382±4751 km2,置信区间为95%。PTC和ΔPTC产物通过与参考数据的线性回归进行了验证,表明高的确定系数(R2=0.79)反映了良好的PTC精度,ΔPTC与参考数据之间的回归具有较高的决定系数(R2=0.74),但回归斜率进一步远离单位(0.78)和小截距(1.68),这与混淆矩阵揭示的森林覆盖损失遗漏误差一致。美国联邦政府公布的48个州的稳定森林地图面积与林地面积统计数据在州一级的比较表明了合理的一致性(R2=0.97),但1.15的回归线斜率表明了对地图稳定森林面积的相对高估,这可能与林地报告差异有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
12.20
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信