42 ISPRS: Earth Observing Data and Tools for Health Studies

Wednesday, 28 August 2013
11:00 AM - 12:15 PM
Monroe

JAPAN'S EFFORTS OF USING SATELLITE REMOTE SENSING FOR THE PREDICTION OF INFECTIOUS DISEASES

Paper number: 42-2
Program: Sessions
Time: 11:25 AM – 11:50 AM

Authors

  • Tamotsu Igarashi Presenting Author
    Remote Sensing Technology Center of Japan (RESTEC), Tokyo, N/A
  • Shinichi Sobue
    Remote Sensing Technology Center of Japan (RESTEC), Tokyo, N/A
  • Aya Yamamoto
    Remote Sensing Technology Center of Japan (RESTEC), Tokyo, N/A
  • Kazuhide Yamamoto
    Japan Aerospace Exploration Agency (JAXA), Ibaraki, N/A
  • Kei Oyoshi
    Japan Aerospace Exploration Agency (JAXA), Ibaraki, N/A
  • Toru Fukuda
    Japan Aerospace Exploration Agency (JAXA), Ibaraki, N/A

Abstract

Introduction. Time-series geospatial data of the Earth is useful for the identification of risk factors of disease, and for developing prediction models. JAXA is a space agency and provider of multi-sensor data from TRMM and GCOM-W in operation and ALOS-2, GCOM-C, DPR, EarthCARE in development and the Earth surface observation optical sensors in the near future.

Material and Method. The JAXA and Nagasaki University cooperative study is a project to develop tools for the reduction and prevention of infectious diseases, started in 2012. The diseases of study are malaria and cholera around Lake Victoria. Mapping of the lagoon and calm and clear water pool on the lakeshore are important as this is habitat for mosquito. For the mapping of water pool and aquatic plants, satellite-borne sensor data were explored.

Results. For the calibration and validation of satellite remote sensing data, a field router has been set on the site. Using these ground truth data, satellite data will be evaluated in the comparative study and correction.

Discussion. There should be discussions to find significant correlations among satellite remote sensing data on the Earth environment and the epidemiologic research data, of which changes may be driven by natural material cycle and anthropogenic factors. Consequently, observation data and statistical or physical models of the epidemic process should be clarified based on the holistic data analysis.