Annual Maps of Forests in Australia from Analyses of Microwave and Optical Images with FAO Forest Definition

遥感学报 Pub Date : 2021-08-23 DOI:10.34133/2021/9784657
Yuanwei Qin, Xiangming Xiao, J. Wigneron, P. Ciais, J. Canadell, M. Brandt, Xiaojun Li, L. Fan, Xiaocui Wu, Hao Tang, R. Dubayah, R. Doughty, Q. Chang, S. Crowell, Bo Zheng, K. Neal, J. Celis, B. Moore
{"title":"Annual Maps of Forests in Australia from Analyses of Microwave and Optical Images with FAO Forest Definition","authors":"Yuanwei Qin, Xiangming Xiao, J. Wigneron, P. Ciais, J. Canadell, M. Brandt, Xiaojun Li, L. Fan, Xiaocui Wu, Hao Tang, R. Dubayah, R. Doughty, Q. Chang, S. Crowell, Bo Zheng, K. Neal, J. Celis, B. Moore","doi":"10.34133/2021/9784657","DOIUrl":null,"url":null,"abstract":"The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10% and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.","PeriodicalId":38304,"journal":{"name":"遥感学报","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"遥感学报","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.34133/2021/9784657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10% and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
根据粮农组织森林定义的微波和光学图像分析绘制的澳大利亚年度森林地图
2010年,澳大利亚政府机构在联合国粮农组织(FAO)报告的森林总面积为1.49亿公顷,排名世界第六,这是基于树木高度为1.2米的森林定义。在这里,我们报告了一种新的森林覆盖数据产品,该产品使用粮农组织森林定义(观测时间或成熟时树木覆盖率为10%,树木高度为>5米),来自微波(相控阵型l波段合成孔径雷达,PALSAR)和光学(中分辨率成像光谱仪,MODIS)图像,并使用非常高的空间分辨率图像,来自冰、云和陆地高程卫星(ICESat)的光探测和测距(LiDAR)数据进行验证。并在现场进行实地调查。新的PALSAR/MODIS森林地图估计2010年澳大利亚有3200万公顷的森林。PALSAR/MODIS森林地图基于森林和非森林覆盖类型的高空间分辨率影像的目视解译数据,总体精度可达95%左右。与来自ICESat激光雷达条的冠层高度和冠层覆盖数据相比,PALSAR/MODIS森林图有73%的森林像元符合粮农组织森林定义,远高于其他四种广泛使用的森林图(36%至52%)。PALSAR/MODIS森林图与国家植被信息系统森林图在空间上也有一定的一致性。利用粮农组织森林资源评估报告中的数据,澳大利亚新的年度森林地图可以支持跨国比较。
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 去求助
来源期刊
遥感学报
遥感学报 Social Sciences-Geography, Planning and Development
CiteScore
3.60
自引率
0.00%
发文量
3200
期刊介绍:
期刊最新文献
Combining solar-induced chlorophyll fluorescence and optical vegetation indices to better understand plant phenological responses to global change Simulating potential tree height for beech-maple-birch forests in northeastern United States on Google Earth Engine Globe230k: A benchmark dense-pixel annotation dataset for global land cover mapping Urban renewal mapping: A case study in Beijing from 2000 to 2020 Improved fine-scale tropical forest cover mapping for Southeast Asia using Planet-NICFI and Sentinel-1 imagery
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1