A STUDY ON THE SAR DATA OBSERVATION TIME FOR THE CLASSIFICATION OF PLANTING CONDITION OF PADDY FIELDS

被引:0
|
作者
Kimura, A. [1 ]
Kondo, A. [1 ]
Mochizuki, K. [1 ]
机构
[1] PASCO CORP, PASCO Res Inst, Meguro Ku, 2-8-10 Higashiyama, Tokyo 1530043, Japan
来源
XXIII ISPRS CONGRESS, COMMISSION VIII | 2016年 / 41卷 / B8期
关键词
Paddy; TerraSAR-X; Classification; Observation time; Backscattering; Polarization;
D O I
10.5194/isprsarchives-XLI-B8-927-2016
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
In recent years, cultivation methods of rice have been diversified due to the low cost of rice-growing techniques. For example, there is direct sowing of seed rice in paddy field in addition to the practice of usual paddy field to flooding at the time of planting. The yield of the usual paddy field and the direct sowing is different even though the same varieties are grown in the same area. It is necessary to grasp by performing classification for the usual paddy field or direct sowing for the management of agricultural crops. The main objective of this study was to select the observation time for the classification of paddy fields' planting conditions by utilizing Synthetic Aperture Radar TerraSAR-X satellite. The planting conditions included the usual planting of rice, the direct sowing of rice and the soybean. We selected the observation time by the statistical distance of the microwave backscattering in each paddy field for maximizing the planting condition classification. In addition, the satellite data observation timing considered the processing time of the analysis and the acquisition costs. The acquisition was performed 4 periods from 2 periods in the rice growing season and the planting phase. In the current study, we were able to classify the usual planting of rice, the direct sowing of rice and the soybean by TerraSAR-X data for the later planting of rice during mid-May and initial growth of rice in early June.
引用
收藏
页码:927 / 930
页数:4
相关论文
共 50 条
  • [21] Observation of Japanese rice paddy fields using multi wavelength and full polarimetric SAR - Remote sensing sensor on next generation satellite
    Ishitsuka, N
    Saito, G
    Ouchi, K
    Uratsuka, S
    SPACE ACTIVITIES AND COOPERATION CONTRIBUTING TO ALL PACIFIC BASIN COUNTRIES, 2004, 117 : 565 - 575
  • [22] Deep learning-based models for temporal satellite data processing: Classification of paddy transplanted fields
    Rawat, Anuvi
    Kumar, Anil
    Upadhyay, Priyadarshi
    Kumar, Shashi
    ECOLOGICAL INFORMATICS, 2021, 61
  • [23] Estimating soil moisture in rainfed paddy fields using ERS-2 C-band SAR data
    Ugsang, DM
    Honda, K
    Eiumnoh, A
    Tokunaga, M
    PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON RETRIEVAL OF BIO- AND GEOPHYSICAL PARAMETERS FROM SAR DATA FOR LAND APPLICATIONS, 2002, 475 : 403 - 408
  • [24] Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data
    Jing-jing Shi
    Jing-feng Huang
    Feng Zhang
    Journal of Zhejiang University SCIENCE B, 2013, 14 : 934 - 946
  • [25] Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data
    Shi, Jing-jing
    Huang, Jing-feng
    Zhang, Feng
    JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE B, 2013, 14 (10): : 934 - 946
  • [26] Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data
    Jing-jing SHI
    Jing-feng HUANG
    Feng ZHANG
    Journal of Zhejiang University-Science B(Biomedicine & Biotechnology), 2013, 14 (10) : 934 - 946
  • [27] Fine classification and phenological analysis of rice paddy based on multi-temporal general compact polarimetric SAR data
    Guo, Xianyu
    Yin, Junjun
    Li, Kun
    Yang, Jian
    FRONTIERS IN PLANT SCIENCE, 2024, 15
  • [28] Semi-supervised Classification of Paddy Fields from Dual Polarized Synthetic Aperture Radar (SAR) images using Deep Learning
    Chatterjee, Ankita
    Mukherjee, Jayanta
    Aikat, Subhas
    Misra, Arundhati
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2021, 42 (05) : 1867 - 1892
  • [29] Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data
    Xiao, X
    Boles, S
    Frolking, S
    Salas, W
    Moore, B
    Li, C
    He, L
    Zhao, R
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (15) : 3009 - 3022
  • [30] SEMI-SUPERVISED LAND COVER CLASSIFICATION USING PI-SAR2 OBSERVATION DATA
    Arima, Yuya
    Kojima, Shoichiro
    Uemoto, Jyunpei
    Konno, Tomohiko
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 2755 - 2758