Mateo Gašparović

Gimbal Influence on the Stability of Exterior Orientation Parameters of UAV Acquired Images

In this paper, results from the analysis of the gimbal impact on the determination of the camera exterior orientation parameters of an Unmanned Aerial Vehicle (UAV) are presented and interpreted. Additionally, a new approach and methodology for testing the influence of gimbals on the exterior orientation parameters of UAV acquired images is presented. The main motive of this study is to examine the possibility of obtaining better geometry and favorable spatial bundles of rays of images in UAV photogrammetric surveying. The subject is a 3-axis brushless gimbal based on a controller board (Storm32). Only two gimbal axes are taken into consideration: roll and pitch axes. Testing was done in a flight simulation, and in indoor and outdoor flight mode, to analyze the Inertial Measurement Unit (IMU) and photogrammetric data. Within these tests the change of the exterior orientation parameters without the use of a gimbal is determined, as well as the potential accuracy of the stabilization with the use of a gimbal. The results show that using a gimbal has huge potential. Significantly, smaller discrepancies between data are noticed when a gimbal is used in flight simulation mode, even four times smaller than in other test modes. In this test the potential accuracy of a low budget gimbal for application in real conditions is determined.

Geospatial monitoring of green infrastructure – case study Zagreb, Croatia

This paper presents current research done under the GEMINI (Geospatial monitoring of green infrastructure using terrestrial, airborne and satellite imagery) project. GEMINI is a scientific project of the Faculty of Geodesy, University of Zagreb and Croatian Forest Research Institute funded by the Croatian science foundation. The project aims to explore new knowledge about the green infrastructure (GI) monitoring. The study area of the research is the capital of Croatia, the city of Zagreb. One of the main goals of the project is to explore the possibilities of data integration of all available remote sensing platforms: satellite, aerial and UAV (Unmanned Aerial Vehicles) imagery, terrestrial imagery and ground truth data. UAV-based remote sensing offers great possibilities to acquire field data for monitoring of GI within the urban areas in a fast and easy way. The main objective of this research is to establish an innovative, multidimensional system for monitoring of urban green infrastructure. It will integrate the latest means of data collection (multispectral satellite imagery improved and calibrated with high resolution terrestrial and airborne multispectral sources), advanced spatial analysis with the aim to improve decision support system for better management of urban GI. This project will improve the current state of the inventory and monitoring of the urban GI to support decision making and preservation of GI benefits, through the establishment of comprehensive procedures for integration of different sources of imagery at different resolution scales: satellite, terrestrial and airborne. This research will focus on novel methods for GI monitoring on the integration of different multispectral imagery sensors. It will require a highly multidisciplinary approach, leading to improvements in methods and procedures for automatic and semi-automatic processing of a large number of geospatial imagery data in the field of urban forest management with expected impact in forestry, arboriculture, urban and geospatial science.