| Presentation | 2023-05-23 NDVI prediction with SAR data using time series features Raiki Kudo, Seiseke Fukuda, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The Normalized Difference Vegetation Index (NDVI) is used to determine the growth of crops, the condition of cultivated land and forests, and land use. NDVI is obtained from multispectral images acquired by optical satellites. However, accurate values cannot be obtained when light is blocked by clouds. Research on estimating NDVI using data from Synthetic Aperture Radar (SAR) satellites, which use microwaves that penetrate clouds, is therefore attracting attention. In this study, we focused on the time-series changes of vegetation and improved the accuracy of NDVI estimation by using the time-series changes of SAR images with short time scales and the characteristics of the time-series changes of vegetation over a year. Experiments using satellite data confirmed the effectiveness of the proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Synthetic Aperture Radar / NDVI / Time Series / Random Forest |
| Paper # | SANE2023-7 |
| Date of Issue | 2023-05-16 (SANE) |
| Conference Information | |
| Committee | SANE |
|---|---|
| Conference Date | 2023/5/23(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Information Technology R & D Center, MITSUBISHI Electric Corp. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Radar, EW and generals |
| Chair | Toshifumi Moriyama(Nagasaki Univ.) |
| Vice Chair | Makoto Tanaka(Tokai Univ.) / Takeshi Amishima(Meiji Univ.) |
| Secretary | Makoto Tanaka(ENRI) / Takeshi Amishima(Mitsubishi Electric) |
| Assistant | Shang Fang(Univ. of Electro-Comm) |
| Paper Information | |
| Registration To | Technical Committee on Space, Aeronautical and Navigational Electronics |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | NDVI prediction with SAR data using time series features |
| Sub Title (in English) | |
| Keyword(1) | Synthetic Aperture Radar |
| Keyword(2) | NDVI |
| Keyword(3) | Time Series |
| Keyword(4) | Random Forest |
| 1st Author's Name | Raiki Kudo |
| 1st Author's Affiliation | The University of Tokyo(UTokyo) |
| 2nd Author's Name | Seiseke Fukuda |
| 2nd Author's Affiliation | Japan Aerospace Exploration Agency(JAXA) |
| Date | 2023-05-23 |
| Paper # | SANE2023-7 |
| Volume (vol) | vol.123 |
| Number (no) | SANE-46 |
| Page | pp.pp.36-41(SANE), |
| #Pages | 6 |
| Date of Issue | 2023-05-16 (SANE) |