Research and education are conducted on methodologies to acquire, process, and utilize spatial information for disaster prevention and environmental protection. In particular, we focus on satellite remote sensing, 3-D digital photogrammetry, laser surveying, and geographic information systems for monitoring, modeling, planning, and management of the national land and the environment.

Academic Staff

Nobuhiro UNO

Nobuhiro UNOProfessor (Graduate School of Engineering)

Research Topics

In order for creating the safe, efficient and comfortable urban transport system, I have been studying the management and control schemes especially for road transport system into which IT is incorporated. My main research topics are an analysis of travel behavior under provision of dynamic information, a development of dynamic inflow control model for urban expressway and a microscopic analysis of traffic conflicts using video image data.


Room 205, Bldg. C1, Katsura Campus
TEL: +81-75-383-3299
FAX: +81-75-383-3299

Junichi SUSAKI

Junichi SUSAKIAssociate Professor (Graduate School of Engineering)

Research Topics

Sensors used in satellite remote sensing are classified into microwave sensors including Synthetic Aperture Radar (SAR) and optical sensors in the visible to thermal infrared bands. I'm interested in developing methodology to combine these different types of sensor data with respect to the advantages for the applications such as disaster mitigation and environmental change analysis.


Room 206, Bldg. C1, Katsura Campus
TEL: +81-75-383-3300
FAX: +81-75-383-3300


Yusuke KIMURAAssistant Professor (Graduate School of Engineering)

Research Topics

  • Methodology for planning and development of urban regeneration and public space utilizing infrastructures fulfilled thei r initial functions
  • Evaluation on the historic importance of urban infrastructures build after World War II


Room 204, Bldg. C1, Katsura Campus
TEL: +81-75-383-3301
FAX: +81-75-383-3301

Research Topics

Assessment of disaster damage and environmental changes by remote sensing

Satellite or airborne sensors can regularly observe temporal changes of the national land and the environment at global or regional scale. In this project, we are developing methodologies for observing the current state and changes of the Earth's surface using optical and radar sensors for disaster prevention and environmental protection.

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Fig1. Detection of liquefaction areas in Kanto region caused by the 2011 East Japan Earthquake. Liquefaction areas were detected using ALOS-PALSAR radar interferometry.

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Fig.2 Tracking changes of mangrove forests in Vietnam from 1990 to 2010. Multiple Landsat optical images were used

Estimation of Urban Density Using Polarimetric SAR (PolSAR) data

We are conducting researches about estimating building density using satellite-borne polarimetric synthetic aperture radar (PolSAR). In general, we need at least two images to estimate three-dimensional (3D) data and the related data, but the developed method can estimate it only from one PolSAR image by extracting the data related to structural distribution. The method is potential to be applied for mapping urban areas where statistics are insufficient for comparing the urban structures.

Fig.3 Urban density estimated using satellite images and generated using GIS data: (Left)  Urban density estimated using ALOS/PALSAR launched by JAXA, Japan, (middle) building-to-land ratio and (right) floor-to-land ratio generated using Zmap TownII, ZENRIN. The estimated urban density has a high correlation with building-to-land ratio

3D building modeling using airborne LiDAR and aerial images

We are developing knowledge-based algorithms for automatically generating three-dimensional (3D) building models in dense urban areas by using airborne light detection and ranging (LiDAR) data and aerial images. Automatic 3D building modeling using LiDAR is challenging in dense urban areas, in which houses are typically located close to each other and their heights are similar. This makes it difficult to separate point clouds into individual buildings. It was found that a combination of airborne LiDAR and aerial images can be an effective approach to resolve this issue.

Fig.4 Example of 3D building modeling in Higashiyama-Ward, Kyoto:(Upper left) Aerial image, (upper right) segmentation results, and (lower) modeling results for an area containing low-rise buildings. In the models, red denotes a flat-roof building, blue denotes a gable-roof building, green denotes a hip-roof building, pink denotes a slant-roof building, black denotes a flat big building and yellow denotes a flat model generated using finally unused points.

Laboratory Website