Share Email Print
cover

Proceedings Paper • new

People in pixels: developing remote sensing-based geodemographic estimation through volunteered geographic information and crowdsourcing
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Pixel-based remote sensing (RS) is widely used for social science research in particular for geodemographic interpolation data studies i.e. population distribution, poverty mapping, etc. Basically, RS research needs adequate amount of ground-truth data either for developing, validating, or improving the accuracy of the RS model. The oldfashioned ground-truth collecting from the field is time-cost consuming notably if the area is large heterogeneity. Development of crowd-sourcing methods for geoinformation science (GIS) and RS is getting attention and become more popular, known as volunteered geographic information (VGI). VGI may offer time-cost efficiency technology for ground-truth collecting data. We use mobile phone-based survey123 for ArcGIS to collect the ground-truth data. These ground-truth data used for improving the geo-demographic estimation map. Firstly, the geo-demographic map was developed by the traditional dasymetric method. Then, Support Vector Machine algorithm is used for improving the accuracy of traditional dasymetric map by using several predictor variables from remote sensing dataset. DKI Jakarta Province was chosen as a case study. We compare the geo-demographic estimation model with the existing data from Central Statistics Bureau of Republic of Indonesia. Using the combination of crowdsourcing, VGI dataset and several remote sensing-based predictor variables, a new method of geodemographic estimation was produced with higher R2 of 0.66 compared with the traditional dasymetric method with R2 of 0.09.

Paper Details

Date Published: 2 October 2019
PDF: 10 pages
Proc. SPIE 11157, Remote Sensing Technologies and Applications in Urban Environments IV, 111570A (2 October 2019); doi: 10.1117/12.2533230
Show Author Affiliations
Faris Zulkarnain, PT Infimap Geospasial Sistem (Indonesia)
Univ. of Indonesia (Indonesia)
Masita Dwi Mandini Manessa, PT Infimap Geospasial Sistem (Indonesia)
Univ. of Indonesia (Indonesia)
Weling Suseno, PT Infimap Geospasial Sistem (Indonesia)
. Ardiansyah, Univ. of Indonesia (Indonesia)
Rizki Bakhtiar, PT Infimap Geospasial Sistem (Indonesia)
Angga Niko Safaryanto, PT Infimap Geospasial Sistem (Indonesia)
Bernardus Wisnu Widjaja, Indonesian National Board for Disaster Management (Indonesia)
. Rokhmatuloh, Univ. of Indonesia (Indonesia)


Published in SPIE Proceedings Vol. 11157:
Remote Sensing Technologies and Applications in Urban Environments IV
Thilo Erbertseder; Nektarios Chrysoulakis; Ying Zhang; Frank Baier, Editor(s)

© SPIE. Terms of Use
Back to Top