<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>mtc-m16c.sid.inpe.br 804</site>
		<identifier>8JMKD3MGPDW34P/4ADCA38</identifier>
		<repository>sid.inpe.br/mtc-m16c/2023/12.18.16.13</repository>
		<lastupdate>2023:12.18.16.13.42 sid.inpe.br/mtc-m18@80/2008/03.17.15.17 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/mtc-m16c/2023/12.18.16.13.43</metadatarepository>
		<metadatalastupdate>2024:01.15.20.39.08 sid.inpe.br/bibdigital@80/2006/04.07.15.50 administrator</metadatalastupdate>
		<issn>2179-4847</issn>
		<citationkey>BragaArAnDuCaDa:2023:StCaJa</citationkey>
		<title>Quantifying selective logging intensity through airborne LiDAR data in an Amazon rainforest: study case at Jamari National Forest</title>
		<format>On-line.</format>
		<year>2023</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>2</numberoffiles>
		<size>7845 KiB</size>
		<author>Braga, Daniel,</author>
		<author>Aragão, Luiz Eduardo Oliveira e Cruz de,</author>
		<author>Anderson, Liana O.,</author>
		<author>Dutra, Débora J.,</author>
		<author>Cabral, Beatriz Figueiredo,</author>
		<author>Dalagnol, Ricardo,</author>
		<group></group>
		<group>DIOTG-CGCT-INPE-MCTI-GOV-BR</group>
		<affiliation>Universidade Federal de Santa Catarina (UFSC)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)</affiliation>
		<affiliation>Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)</affiliation>
		<affiliation>Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)</affiliation>
		<affiliation>University of California</affiliation>
		<electronicmailaddress>danielalvezbraga@gmail.com</electronicmailaddress>
		<electronicmailaddress>luiz.aragao@inpe.br</electronicmailaddress>
		<electronicmailaddress>liana.anderson@gmail.com</electronicmailaddress>
		<electronicmailaddress>ddutra.ambiental@gmail.com</electronicmailaddress>
		<electronicmailaddress>beatriz.figueiredocabal@gmail.com</electronicmailaddress>
		<electronicmailaddress>ricds@hotmail.com</electronicmailaddress>
		<editor>Vinhas, Lubia (INPE),</editor>
		<editor>Feitosa, Flavia F. (UFABC),</editor>
		<conferencename>Simpósio Brasileiro de Geoinformática, 24 (GEOINFO)</conferencename>
		<conferencelocation>On-line</conferencelocation>
		<date>04 a 06 dez. 2023</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<booktitle>Anais</booktitle>
		<tertiarytype>Full paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<abstract>Airborne LiDAR data represents one of the most accurate ways to estimate forest strucutre and carbon nowadays. This study aimed to estimate the intensity of selective logging activities in terms of density and volume of logged trees based on airborne LiDAR data in comparison to ground measurements on a forest concession area in the Brazilian Amazon, the Jamari National Forest. The results show a significant relationship between logging intensity and LiDAR intensity. This constituted an important step towards monitoring selective logging in the Amazon and areas under forest concession.</abstract>
		<area>SRE</area>
		<language>en</language>
		<targetfile>Braga_Quantifying.pdf</targetfile>
		<usergroup>simone</usergroup>
		<visibility>shown</visibility>
		<copyright>urlib.net/www/2012/11.12.15.19</copyright>
		<rightsholder>originalauthor yes</rightsholder>
		<mirrorrepository>dpi.inpe.br/banon-pc2@80/2006/07.04.20.21</mirrorrepository>
		<nexthigherunit>8JMKD3MGPCW/46KUATE</nexthigherunit>
		<nexthigherunit>8JMKD3MGPDW34P/4ADE2M8</nexthigherunit>
		<citingitemlist>sid.inpe.br/mtc-m16c/2023/12.19.01.40 3</citingitemlist>
		<hostcollection>sid.inpe.br/mtc-m18@80/2008/03.17.15.17</hostcollection>
		<username>simone</username>
		<lasthostcollection>sid.inpe.br/mtc-m18@80/2008/03.17.15.17</lasthostcollection>
		<url>http://mtc-m16c.sid.inpe.br/rep-/sid.inpe.br/mtc-m16c/2023/12.18.16.13</url>
	</metadata>
</metadatalist>