MIERUNE JCT #01

『FOSS4G × オープンデータで2023年の猛暑を可視化してみる』

amedas, landsat, remote sensing, NetCDF, cdo (climate data operators), QGIS

Transcript

1. FOSS4G 2023 2023.08.30 @ShinagawaJP
2. SaaS & SNS & JCT
3. HydroSHEDS
4. Yahoo! API 2021 5
6. 1909 1967
7. 1909 1967
16. • • https://amu.rd.naro.go.jp/ • ( , , ) • 1km • NetCDF • QGIS QGIS3.14 • CDO Climate Data Operators • OPeNDAP, Excel , Python • OPeNDAP Data Access Form DL Python wget
17. • NetCDF • CDO • selmonth,8 8 • timmin • timmax • timpctl,50 timmin.nc timmax.nc • NetCDF QGIS
18. • • • • • • , , 1 , • 2002/12/31 • 2003/01/01 10 • 2008 09
22. • Landsat 8-9 OLI/TIRS Collection 2 Level 1 • USGS Earth Explorer https://earthexplorer.usgs.gov/ • GeoTiff • • Band 4/5 Green/Red / • Band 10/11 TIR (Thermal Infrared) • 30m Band 10/11 100m
23. • 2023 8 4 11 Band4/5/10 DL • QGIS gdal_calc.py Band10 TOA Radiance TOA Reflectance Band4/5 NDVI • NetCDF QGIS
24. • • Landsat 8/9 8 1 • JAXA GCOM-C 1 2 250m • •
25. WBGT
26. WBGT ( ) (WBGT) 35 31 31 35 28 31 28 31 25 28 24 28 21 25 24 21 • https://www.wbgt.env.go.jp/wbgt.php
28. • • https://www.wbgt.env.go.jp/data_service.php • CSV • 3 • , , • 2023 4 1 1 • , , , • • https://www.jma.go.jp/jma/kishou/know/amedas/ame_master.pdf • PDF