<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>mtc-m21d.sid.inpe.br 808</site>
		<holdercode>{isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}</holdercode>
		<identifier>8JMKD3MGP3W34T/4AC7P4L</identifier>
		<repository>sid.inpe.br/mtc-m21d/2023/12.11.11.54</repository>
		<lastupdate>2023:12.11.11.54.48 urlib.net/www/2021/06.04.03.40 simone</lastupdate>
		<metadatarepository>sid.inpe.br/mtc-m21d/2023/12.11.11.54.48</metadatarepository>
		<metadatalastupdate>2024:01.02.17.16.55 urlib.net/www/2021/06.04.03.40 administrator {D 2023}</metadatalastupdate>
		<secondarykey>INPE--PRE/</secondarykey>
		<citationkey>QinXTDDLLSAWM:2023:AnFoEv</citationkey>
		<title>Annual Forest and Evergreen Forest Cover Mapping and Assessment in the Brazilian Amazon</title>
		<year>2023</year>
		<secondarytype>PRE CI</secondarytype>
		<author>Qin, Yuanwei,</author>
		<author>Xiao, xiangming,</author>
		<author>Tang, Hao,</author>
		<author>Dubayah, Ralph,</author>
		<author>Doughty, Russell,</author>
		<author>Liu, Diyou,</author>
		<author>Liu, Fang,</author>
		<author>Shimabukuro, Yosio Edemir,</author>
		<author>Arai, Egidio,</author>
		<author>Wang, Xinxin,</author>
		<author>Moore, Berrien,</author>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid></resumeid>
		<resumeid>8JMKD3MGP5W/3C9JJCQ</resumeid>
		<resumeid>8JMKD3MGP5W/3C9JGUP</resumeid>
		<group></group>
		<group></group>
		<group></group>
		<group></group>
		<group></group>
		<group></group>
		<group></group>
		<group>DIOTG-CGCT-INPE-MCTI-GOV-BR</group>
		<group>DIOTG-CGCT-INPE-MCTI-GOV-BR</group>
		<affiliation>University of Oklahoma Norman Campus</affiliation>
		<affiliation>University of Oklahoma</affiliation>
		<affiliation>National University of Singapore</affiliation>
		<affiliation>University of Maryland College Park</affiliation>
		<affiliation>California Institute of Technology</affiliation>
		<affiliation>China Agricultural University(CAU)</affiliation>
		<affiliation>University of Oklahoma</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Fudan University</affiliation>
		<affiliation>University of Oklahoma</affiliation>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress>yosio.shimabukuro@inpe.br</electronicmailaddress>
		<electronicmailaddress>egidio.arai@inpe.br</electronicmailaddress>
		<conferencename>AGU FAll Meeting</conferencename>
		<conferencelocation>San Francisco, CA</conferencelocation>
		<date>11-15 Dec. 2023</date>
		<publisher>AGU</publisher>
		<booktitle>Proceedings</booktitle>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<versiontype>publisher</versiontype>
		<abstract>Many forest cover maps have been generated by using optical and/or microwave images, but these forest cover maps have large area and spatial discrepancies. To date, few studies have assessed forest cover maps in terms of two biophysical parameters used in forest definition: (1) canopy height and (2) canopy coverage. We generated annual forest cover maps from 2007 to 2010 and evergreen forest cover maps from 2000 to 2021 in the Brazilian Amazon using the images from the Phased Array type L-band Synthetic Aperture Radar and the time series images from the Moderate Resolution Imaging Spectroradiometer, using the forest definition of the Food and Agriculture Organization (FAO) of the United Nations (> 5-m tree height and > 10% canopy coverage) as the reference. We used the canopy height and canopy coverage datasets from the Geoscience Laser Altimeter System during 2003-2007 to assess annual forest cover maps from 2007 to 2010 and annual evergreen forest cover maps from 2003 to 2007, and the results show high accuracy of these forest cover and evergreen forest cover maps in the Brazilian Amazon. These annual forest cover maps and annual evergreen forest cover maps provide data support for the analyses of the causes, process, and consequences of forest cover changes in the Brazilian Amazon.</abstract>
		<area>SRE</area>
		<language>en</language>
		<usergroup>simone</usergroup>
		<visibility>shown</visibility>
		<documentstage>not transferred</documentstage>
		<nexthigherunit>8JMKD3MGPCW/46KUATE</nexthigherunit>
		<hostcollection>urlib.net/www/2021/06.04.03.40</hostcollection>
		<username>simone</username>
		<agreement>agreement.html .htaccess .htaccess2</agreement>
		<lasthostcollection>urlib.net/www/2021/06.04.03.40</lasthostcollection>
	</metadata>
</metadatalist>