Automatic Generation of Orthorectified High Resolution Satellite Imagery

a Case Study for Saudi Arabia

authored by

Christian Heipke, Muhamad Alrajhi

Abstract

The Ministry of Municipal and Rural Affairs (MOMRA) is responsible for the production, maintenance and delivery of accurate geospatial data for all urban and rural settlements in the Kingdom of Saudi Arabia. The fast urbanization requires up-to-date information, which is a major challenge. High resolution satellite imagery presents a novel and promising data resource for geospatial data update. It is well-known that a satellite image, if georeferenced using the vendor-provided rational polynomial coefficients (RPC), often displays X- and Y-coordinate biases of several pixels. Ground control points (GCP) are typically required to achieve an accuracy at pixel level. The collection of the 3D coordinates of GCP and their corresponding image coordinates is a time consuming and cost intensive manual process. The primary objective of this research is to use image matching between existing orthophotos and the satellite images, georeferenced with RPC instead of GCP, in order to automate and speed up the orthorectification process. Based on a series of practical experiments using imagery from GeoEye and IKONOS, the potential of automated matching between aerial and satellite images using the well known Speeded-Up Robust Features (SURF) algorithm for the described task is investigated. The matched points serve as a basis for transforming the satellite orthophoto to the aerial orthophoto using a 2D affine transformation. This research has led to the development of a simple and efficient tool for satellite imagery with a ground sampling distance of 50 cm to 1 m to be used for updating geospatial information that meets MOMRA accuracy standards for 1:10,000 scale mapping. The process completely eliminates the need for GCP. About 12 to 15 satellite images are routinely being processed on a workstation in a single day. The implementation of this tool at MOM-RA greatly enhances its ability to quickly respond to urgent needs for updated geospatial data.

Organisation(s)

Institute of Photogrammetry and GeoInformation (IPI)

External Organisation(s)

Ministry of Municipal and Rural Affairs (MOMRA)

Type

Article

Journal

Photogrammetrie, Fernerkundung, Geoinformation

Volume

2016

Pages

5-15

No. of pages

11

ISSN

1432-8364

Publication date

02.2016

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Geography, Planning and Development, Instrumentation, Earth and Planetary Sciences (miscellaneous)

Sustainable Development Goals

SDG 11 - Sustainable Cities and Communities

Electronic version(s)

https://doi.org/10.1127/pfg/2016/0285 (Access: Closed)