The concept of remote sensing is very closely related with sciences, in particularly with the study of Geography and Geology. However, what if remote sensing could be applied to social sciences?
Centre for Southeast Asian Social Studies (CESASS) UGM organised a workshop with the theme “Geographical Information System Application on Social Sciences”, with Prof. Magaly Koch, Ph. D from Center for Remote Sensing, Boston University, United States which was held in the Ruang Indonesia, CESSAS UGM (6/11/2017). This workshop is part of the World Class Professor (WCP) program from the Ministry of Research, Technology and Higher Education of the Republic of Indonesia which was hosted by the consortium of CESASS UGM, Center for Costal Rehabilitation and Disaster Mitigation Studies Universitas Diponegoro and Center for Tsunami and Disaster Mitigation Universitas Syiah Kuala. Prof. Magaly herself is a visiting professor in the Center for Costal Rehabilitation and Disaster Mitigation Studies Universitas Diponegoro.
The workshop took place from 8:30-15:00 WIB with the goal to provide an understanding of the technicality of remote sensing and Geographical Information System (GIS) for social scientist. Remote sensing can be utilised to help social scientist to layout their regional planning where the results can be used to build facilities needed. The participant whom participated came from diverse background. Initially it was directed towards social scientist, however scholars from a scientific background input were brought upon the workshop. In addition, despite the limited number of participant allowed, the composition of participants varied from different universities in Yogyakarta.
In the workshop, Prof. Magaly invited the students to use the QGIS in analysing the area of California digitally. They were then taught to categories images from Landsat to create soil mapping. Through such practice, it is hoped to provide knowledge about soil classification, on how to obtain soil images, and to equip the steps in analysing along with classifying soil images. (MLK/Dipka)