MOP.P5.5

IN-DEPTH MINING SPATIAL PATTERN OF INVASIVE ALIEN SPECIES BY DEEP LEARNING FROM PHENOLOGICAL-BASED DRONE IMAGES

Hao-Yuan Hung, National Chung-Hsing University, Taiwan; Chin-Rou Hsu, National Taiwan University, Taiwan; Bao-Hua Shao, Nan-Tou Division Office, Forest Bureau, Taiwan; Nan-Chang Lo, Experimental Forest Management Office, National Chung-Hsing University, Taiwan; Kai-Yi Huang, National Chung-Hsing University, Taiwan
Session:
MOP.P5: Classification and Clustering I Poster
Track:
Data Analysis
Location:
Poster Area 5
Presentation Time:
Mon, 17 Jul, 14:15 - 15:45 Pacific Time (UTC -7)
Session Chair:
Yeji Kim, Korea Aerospace Research Institute
Session Managers:
Al Adil Al Hinai and Ivan Arias and Shubham Awasthi and Ayoti Banerjee
Presentation
Discussion
Resources
No resources available.
Session MOP.P5
MOP.P5.1: LIGHTWEIGHT LANDSLIDE DETECTION METHOD BASED ON DEPTH SEPARABLE CONVOLUTION AND DOUBLE SELF-ATTENTION MECHANISM
Weibin Li, Yuhui Kong, Rongfang Wang, Xidian University, China; Chunlei Huo, Chinese Academy of Sciences, China; Jiawei Chen, Yi Niu, Xidian University, China
MOP.P5.2: SUSCEPTIBILITY EVALUATION OF RAIN-INDUCED LANDSLIDES BASED ON MULTI-SOURCE DATA: A CASE STUDY OF XINGGUO COUNTY, CHINA
Hongze Dong, Xinye Tang, University of Electronic Science and Technology of China, China; Mingcang Zhu, Department of Natural Resources of Sichuan Province, China; Guoqing Zhou, Guilin University of Technology, China; Zezhong Zheng, University of Electronic Science and Technology of China, China; Xuefeng Yang, China Railway Eryuan Engineering Group Co., LTD, China
MOP.P5.3: EXPLAINABLE MACHINE LEARNING MODEL FOR PARAMETER INFLUENCE ASSESSMENT OF LANDSLIDES USING XGBOOST-SHAP
Vishal Mishra, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India, India; Anuj Tiwari, University of Illinois, United States; Chandra Has Singh, Kamal Jain, Indian Institute of Technology Roorkee, India
MOP.P5.4: A STUDY ON THRESHOLDING METHODS OF DAMAGED AREA DETECTION BY WILDFIRES FOR NEWLY LAUNCHING MICROSATELLITES
Yeji Kim, Korea Aerospace Research Institute, South Korea; Ahram Song, Kyungpook National University, South Korea; Hongtak Lee, Hyun Ok Kim, Sun Gu Lee, Korea Aerospace Research Institute, South Korea
MOP.P5.5: IN-DEPTH MINING SPATIAL PATTERN OF INVASIVE ALIEN SPECIES BY DEEP LEARNING FROM PHENOLOGICAL-BASED DRONE IMAGES
Hao-Yuan Hung, National Chung-Hsing University, Taiwan; Chin-Rou Hsu, National Taiwan University, Taiwan; Bao-Hua Shao, Nan-Tou Division Office, Forest Bureau, Taiwan; Nan-Chang Lo, Experimental Forest Management Office, National Chung-Hsing University, Taiwan; Kai-Yi Huang, National Chung-Hsing University, Taiwan
MOP.P5.6: IMPROVING LAND COVER CLASSIFICATION IN SUBARCTIC WETLANDS USING MULTI-SOURCE REMOTELY SENSED DATA
Baoxin Hu, Yongjie Xia, York University, Canada; Glen Brown, Ontario Ministry of Northern Development, Mines, Natural Resources & Forestry, Canada; Jianguo Wang, York University, Canada
MOP.P5.7: EFFECTS OF URBANIZATION ON URBAN ECOSYSTEM SERVICES (UESS) - A GEOSPATIAL APPROACH
Deeksha Nayak, Anoop Kumar Shukla, Rama Devi Nandineni, Manipal Academy of Higher Education, India
MOP.P5.8: RADIOMETRIC AND GEOMETRIC APPROACH FOR MAJOR WOODY PARTS SEGMENTATION IN FOREST LIDAR POINT CLOUDS
Jinyuan Shao, Yi-Ting Cheng, Yerassyl Koshan, Raja Manish, Ayman Habib, Songlin Fei, Purdue University, United States
MOP.P5.9: AN IMBALANCED SIGNAL MODULATION CLASSIFICATION AND EVALUATION METHOD BASED ON SYNTHETIC MINORITY OVER-SAMPLING TECHNIQUE
Xuebo Liu, Yiran Wang, Jing Bai, Haoran Li, Xu Wang, School of Artificial Intelligence, Xidian University, Xi’an 710071, China, China
MOP.P5.10: SENTINEL-1 BASED CUSUM CAPABILITIES AS A FOREST / NON-FOREST MASK IN TROPICAL AREAS
Bertrand Ygorra, National Institute for Research in Digital Science and Technology, France; Frédéric Frappart, Jean-Pierre Wigneron, National Research Institute for Agriculture, Food and Environment, France; Thibault Catry, Benjamin Pillot, Espace-DeV, France; Serge Riazanoff, VisioTerra, France
Resources
No resources available.