Details
| Original language | English |
|---|---|
| Pages (from-to) | 5-15 |
| Number of pages | 11 |
| Journal | Photogrammetrie, Fernerkundung, Geoinformation |
| Volume | 2016 |
| Issue number | 1 |
| Publication status | Published - Feb 2016 |
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.
Keywords
- High resolution, Image matching, Orthophotos, Satellite imagery
ASJC Scopus subject areas
- Social Sciences(all)
- Geography, Planning and Development
- Physics and Astronomy(all)
- Instrumentation
- Earth and Planetary Sciences(all)
- Earth and Planetary Sciences (miscellaneous)
Sustainable Development Goals
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In: Photogrammetrie, Fernerkundung, Geoinformation, Vol. 2016, No. 1, 02.2016, p. 5-15.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Automatic Generation of Orthorectified High Resolution Satellite Imagery
T2 - a Case Study for Saudi Arabia
AU - Heipke, Christian
AU - Alrajhi, Muhamad
PY - 2016/2
Y1 - 2016/2
N2 - 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.
AB - 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.
KW - High resolution
KW - Image matching
KW - Orthophotos
KW - Satellite imagery
UR - http://www.scopus.com/inward/record.url?scp=84971671375&partnerID=8YFLogxK
U2 - 10.1127/pfg/2016/0285
DO - 10.1127/pfg/2016/0285
M3 - Article
AN - SCOPUS:84971671375
VL - 2016
SP - 5
EP - 15
JO - Photogrammetrie, Fernerkundung, Geoinformation
JF - Photogrammetrie, Fernerkundung, Geoinformation
SN - 1432-8364
IS - 1
ER -