<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Wataru Ohira</style></author><author><style face="normal" font="default" size="100%">Satoshi Kaneko</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an Automated Settlement Mapping System using High-Resolution Satellite Images and Deep Learning</style></title><secondary-title><style face="normal" font="default" size="100%">The 60th Annual Meeting for the Japanese Society of Tropical Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2019</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Okinawa, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We developed an automated system of building with the use of high-resolution satellite images and deep learning, comprising a geospatial data management system, an image data processing system, and a quality control system. The system development has achieved the component of the geospatial data management and image data processing, and performed building mapping of some large extents, while the development of quality control systems is ongoing. Because we developed the system with open-source and web-based software, anyone can participate in the preparation of training data just only with a computer and the Internet. The system is expected to be a platform for the large-scale mapping of buildings and other ground objects with international collaborations of local partners. The building maps developed by this system are expected to be a basis of analyzing demography with possible risks and impacts of communicable diseases.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yuki Akiyama</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Sirinya Sirikanjanaanan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of micro population data for each building: Case study in Tokyo and Bangkok</style></title><secondary-title><style face="normal" font="default" size="100%">2019 First International Conference on Smart Technology &amp; Urban Development (STUD)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building</style></keyword><keyword><style  face="normal" font="default" size="100%">census</style></keyword><keyword><style  face="normal" font="default" size="100%">disaggregation</style></keyword><keyword><style  face="normal" font="default" size="100%">micro geodata</style></keyword><keyword><style  face="normal" font="default" size="100%">population</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9018851</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In order to carry out sustainable development and management of cities, it is necessary to design and implement appropriate city planning and traffic planning. Indispensable information for designing them is the population distribution. However, population data with high spatial resolution, such as building units, are rarely maintained in cities in developing countries. Therefore, this study examined the development of methods for estimating the number of residents per building in Tokyo and Bangkok using detailed building maps and population census in subdistrict units. In addition, using these methods, we tried to develop micro population data (MPD) across Tokyo and Bangkok. Moreover, the reliability of MPD was verified by comparing it with population census with higher resolution than subdistrict unit in Tokyo. As a result, it has become possible to develop MPDs that are strongly correlated with the population census of various aggregation units and have small errors.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yohei Koga</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deep Domain Adaptation for Single-Shot Vehicle Detector in Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/abstract/document/8519129</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Uttam Dwivedi</style></author><author><style face="normal" font="default" size="100%">Zhiling Guo</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Mohamed Batran</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Population Distribution Map and Automated Human Settlement Map Using High Resolution Remote Sensing Images</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/abstract/document/8517827</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>