Identification of the Direct and Indirect Drivers of Deforestation and Forest Degradation in Cambodia
Identification of the drivers and their agents of deforestation and forest degradation is important for effective implementation of the REDD+ activities. Here, we identified the direct and indirect drivers through the analysis of local perceptions. The mi
- PDF / 32,404,200 Bytes
- 438 Pages / 439.37 x 666.142 pts Page_size
- 17 Downloads / 258 Views
Van-Nam Huynh · Tomoe Entani · Chawalit Jeenanunta · Masahiro Inuiguchi · Pisal Yenradee (Eds.)
Integrated Uncertainty in Knowledge Modelling and Decision Making 8th International Symposium, IUKM 2020 Phuket, Thailand, November 11–13, 2020 Proceedings
123
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
12482
More information about this series at http://www.springer.com/series/1244
Van-Nam Huynh Tomoe Entani Chawalit Jeenanunta Masahiro Inuiguchi Pisal Yenradee (Eds.) •
•
•
•
Integrated Uncertainty in Knowledge Modelling and Decision Making 8th International Symposium, IUKM 2020 Phuket, Thailand, November 11–13, 2020 Proceedings
123
Editors Van-Nam Huynh Japan Advanced Institute of Science and Technology Nomi, Ishikawa, Japan Chawalit Jeenanunta Sirindhorn International Institute of Technology Thammasat University Pathum Thani, Thailand
Tomoe Entani University of Hyogo Kobe, Japan Masahiro Inuiguchi Graduate School of Engineering Science Osaka University Toyonaka, Osaka, Japan
Pisal Yenradee Sirindhorn International Institute of Technology Thammasat University Pathum Thani, Thailand
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-62508-5 ISBN 978-3-030-62509-2 (eBook) https://doi.org/10.1007/978-3-030-62509-2 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham,