Production of orthophoto map using mobile photogrammetry and comparative assessment of cost and accuracy with satellite imagery for corridor mapping: a case study in Manesar, Haryana, India

ABSTRACT

The study aims to find a low-cost alternate technology to get imagery, using mobile platform, and produce digital orthophoto for corridor mapping, with a higher degree of accuracy and which can reduce the lag time of acquisition of data. The present study uses digital single-lens reflex cameras, mounted on a mobile vehicle, and acquisition of data in the video format rather than still photographs, as traditionally used in mobile mapping systems. The videos are used to create a set of images and orthophotos. A widespread ground control points were recorded in the study area, using the global navigation satellite system receiver, which measured the control points in real-time kinematic mode. Generation of digital orthophoto has been completed using the captured mobile imagery and ground control point. Furthermore, procurement of satellite imagery and aerial triangulation using ground control points have been done. While comparing the planimetric accuracy of orthophoto against satellite imagery using the ground control points, the achieved root mean square error value of produced orthophoto is 0.171 m in X axis and 0.205 m in Y axis. However, for Cartosat -1 satellite imagery, the RMSE value for X is 1.22 m and for Y is 1.98 m. This research proposes the alternate low-cost mobile mapping method to capture the imagery for orthophoto production. The cost of orthophoto production from mobile image was found 77% cheaper than the orthophoto cost from fresh/latest satellite imagery procurement, while the overall production was 70% cost-effective than the orthophoto maps made from archived imagery.

KEYWORDS:

• Mobile mapping
• corridor mapping orthophoto
• GNSS
• RTK (real-time kinematics)
• stereo satellite images
• panoramic imagery
• RMSE (root mean square Error)

Acknowledgements

MD, SMV and MJ are grateful to Amity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, NOIDA, UP, India, for all the support. AK is thankful to the Department of Geology, BHU, for the assistance.

Disclosure statement

No potential conflict of interest was reported by the authors.