ジョンソン ブライアン

The current (2014) and future (2025) land cover maps were generated and analyzed for flood modelling. High resolution digital elevation model from LiDAR data was used to generate detailed terrain for accurate flood simulation. Findings from this study will be shared to the local governments to help make their land-use planning climate-sensitive.

In this study, we investigated trends in the use of remote sensing (RS) to address some major global environmental issues to see if it is being increasingly or decreasingly used to address each issue. We considered several land, water, air, and integrated Earth system issues. Of the 12 environmental issues we considered, there was an increasing...

The goal of this research is to develop a method for quantitative and objective assessment of the effect of satellite Earth observations on environmental policy. For this purpose, as an initial case study, the protection of the ozone layer is taken up to analyze the different phases and processes where satellite observations might have had an...

This presentation discusses the impact of Earth Observation (EO) on the deforestation-/forest degradation-related science and policy.

In this study we tested the impacts of three fast pansharpening methods – Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Additive Wavelet Transform (AWT) – on the classification of sugarcane in a Landsat 8 image (bands 1-7), and proposed an ensemble pansharpening approach that combines the pixel-level information from the IHS and BT...

A data base used for automated mapping of urban land cover (trees, grass, soil, concrete, asphalt, buildings, etc.) in satellite or aerial imagery. Published in the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Urban+Land+Cover), the largest machine learning data base worldwide. Researchers can use the data set to learn...

This study evaluated the effects of image pansharpening on Vegetation Indices (VIs) in an agricultural area of Thailand, and found that pansharpening was able to downscale single-date and multi-temporal VI data without introducing significant distortions. The downscaled (15m resolution) VI values can be used for estimating above-ground biomass...

During FY2013, PMO Knowledge Management undertook a study and pilot work to consider options for creating a visual map of where IGES is conducting its research activities which could serve as both an interactive outreach mechanism and an internal knowledge tool. This idea was also discussed with the Network and Outreach team who felt that this...

Data set for monitoring Japanese forest health using satellite imagery and machine learning techniques. Published in the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Wilt), the largest machine learning database worldwide. Researchers can use the data set to learn, develop, and improve methods for forest monitoring using...