THP.P19.5

COMPARISON OF MULTI-TEXTURE FEATURES EXTRACTS FROM GF-1 IMAGES TO MAP AGRICULTURAL PLASTIC GREENHOUSE THROUGH AN OBJECT-BASED APPROACH

Yuan Gao, Yaozhong Pan, Shoujia Ren, Chuanwu Zhao, Beijing Normal University, China
Session:
THP.P19: Agricultural Classification and Mapping II Poster
Track:
Land Applications
Location:
Poster Area 19
Presentation Time:
Thu, 20 Jul, 14:15 - 15:45 Pacific Time (UTC -8)
Session Chair:
Steven Reising, Colorado State University
Session Managers:
HUMAIRA SANAM and Ayoti Banerjee and Imara Mohamed Nazar and sunni kanta prasad kushwaha
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Session THP.P19
THP.P19.1: SYNERGISTIC USE OF SENTINEL-1 AND SENTINEL-2 IMAGES FOR IN-SEASON CROP TYPE CLASSIFICATION USING GOOGLE EARTH ENGINE AND MACHINE LEARNING
Sneha Sharma, Dongryeol Ryu, Sumesh K C, The University of Melbourne, Australia; Sun-Gu Lee, Seungtaek Jeong, Korea Aerospace Research Institute, South Korea
THP.P19.2: LONG IMAGE TIME SERIES FOR CROP EXTRACTION BASED ON THE AUTOMATICALLY GENERATED SAMPLES ALGORITHM
Nan Jia, Michigan State University, United States; Yinshuai Li, Shanghai Jiao Tong University, China; Andrés Viña, Michigan State University, United States; Jie Cheng, East China Normal University, China; Yue Dou, Universiteit Twente, Netherlands; Qian Song, Chinese Academy of Agricultural Sciences, China; Liuyue He, Wuhan University, China; Jianguo Liu, Michigan State University, United States
THP.P19.3: TIME SERIES-BASED ACTIVE LABELING FRAMEWORK FOR CURATING A MULTISPECTRAL SENTINEL-2 IMAGERY DATASET FOR CROP TYPE MAPPING
Vaneeza Mehmood, Ramesha Murtaza, Zuhair Zafar, National University of Sciences and Technology (NUST), Islamabad, Pakistan, Pakistan; Muhammad Shahzad, Technical University of Munich (TUM), Germany; Karsten Berns, Robotics Research Lab, Technical University of Kaiserslautern, Germany, Germany; Muhammad Moazam Fraz, National University of Sciences and Technology (NUST), Islamabad, Pakistan, Pakistan
THP.P19.4: POTENTIAL OF UAV-BASED PATTERN CLASSIFICATION WITH CONVOLUTIONAL NEURAL NETWORK ON MODERATE/LOW QUALITY UAV DATA
Linara Arslanova, Sören Hese, Friederike Metz, Christiane Schmullius, Friedrich-Schiller University of Jena, Germany; Christian Thau, Jena City Administration, Germany; Friedemann Scheibler, Planet Labs Germany GmbH, Germany; Kai Heckel, ESN EnergieSystemeNord GmbH, Germany; Marcel Fölsch, 365FarmNet GmbH, Germany; Marcel Urban, ESN EnergieSystemeNord GmbH, Germany; Michael Schultz, University of Tuebingen, Germany
THP.P19.5: COMPARISON OF MULTI-TEXTURE FEATURES EXTRACTS FROM GF-1 IMAGES TO MAP AGRICULTURAL PLASTIC GREENHOUSE THROUGH AN OBJECT-BASED APPROACH
Yuan Gao, Yaozhong Pan, Shoujia Ren, Chuanwu Zhao, Beijing Normal University, China
THP.P19.6: TWO DIMENSIONAL HISTOGRAM BASED ON RELATIVE ENTROPY THRESHOLDING FOR CROP SEGMENTATION USING UAV IMAGES
Gattu Priyanka, P Rajalakshmi, Indian Institute of Technology Hyderabad, India; Jana Kholova, International Crops Research Institute for Semi-Arid Tropics, Hyderabad, India
THP.P19.7: Rotation Adaptive Plot Extraction from UAV RGB Images
Jiaqi Guo, Changye Yang, Enyu Cai, Edward Delp, Purdue University, United States
THP.P19.8: CALIBRATION OF 3D MODELS OF MAIZE FIELDS USING UAV AND S2 IMAGES FOR SIMULATING THEIR VIS-NIR AND TIR OBSERVATION AND RADIATIVE BUDGET WITH DART
Paul Boitard, Benoit Coudert, Nicolas Lauret, Solen Queguiner, Claire Marais-Sicre, Jean-Philippe Gastellu-Etchegorry, CESBIO, France
THP.P19.9: EVALUATING YOLO MODELS FOR GRAPE MOTH DETECTION IN INSECT TRAPS
Ana Cláudia Teixeira, Gabriel Carneiro, Raul Morais, Joaquim J. Sousa, António Cunha, University of Trás-os-Montes and Alto Douro, 5000-801, Vila Real, Portugal, Portugal
Resources
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