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In recent years, climate change on a global scale has been attracting attention as a serious problem. Its impacts, such as frequent occurrence of abnormal weather, rising sea levels, and changes in ecosystems, extend to all areas of industry and life. In order to accurately analyze and predict such climate change, "visualization and analysis of spatial information" is essential.
GISBox, a SaaS-based geospatial platform that combines geographic information systems (GIS) and climate data, is attracting attention.
What is GISBox? A next-generation GIS platform specialized for utilizing climate data
GISBox is a lightweight, high-performance GIS tool that runs on a cloud base, allowing anyone to easily handle satellite images and time-series geospatial data. Unlike conventional specialized GIS software, it combines high operability and flexible scalability, and is supported by a wide range of users, from research institutions to local governments and private companies.
In particular, in research on climate change, the following uses are being promoted:
Visualization of land surface changes through differential analysis of time-series satellite images
Spatial correlation analysis with climate variables such as temperature, precipitation, and snowfall
Monitoring the progress of deforestation, drought, and desertification
Disaster risk assessment through collaboration with real-time weather data
Why choose GISBox for analyzing climate change trends
Cloud-based processing power
Large-volume satellite images and continuous observation data can be smoothly analyzed and visualized on the cloud. It does not depend on the specifications of the local machine.
High compatibility with open data
Equipped with an API function that allows you to easily import and collaborate with climate-related open data from NASA, NOAA, JAXA, etc.
Easy-to-understand dashboard and report output function
Analysis results can be intuitively displayed in graphs, heat maps, animations, etc. It is easy to use in administrative documents and research reports.
Trend prediction through AI collaboration
AI learns changes in weather patterns and can predict future geographical risks. It is also useful for planning sustainability strategies.
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Actual use cases: Urban heat island countermeasures and disaster response planning
GISBox has been introduced in a wide range of situations, such as planning mitigation measures for urban heat island effects, early detection of river flood risks, and weather forecast-based sowing time optimization in the agricultural field.
In particular, there are an increasing number of cases in which local governments overlay past climate data with future predictions and use it in planning infrastructure development and evacuation shelter design.
Summary
In order to respond to climate change, "time-space visualization" and "founded prediction" are essential.
GISBox makes it possible for anyone to handle geographical and chronological climate data, which was previously difficult, and is a tool that will take climate change countermeasures one step further. Why not try using GISBox now to protect the future of the global environment?