Abstract
The purpose of this study was to verify the applicability of unmanned aerial vehicles (UAVs) to update cadastral records in areas affected by landslides. Its authors intended to compare the accuracy of coordinates determined using different UAV data processing methods for points which form the framework of a cadastral database, and to find out whether products obtained as a result of such UAV data processing are sufficient to define the extent of changes in the cadastral objects. To achieve this, an experiment was designed to take place at the site of a landslide. The entire photogrammetry mission was planned to cover an area of more than 70 ha. Given the steep grade of the site, the UAV was flown over each line at a different, individually preset altitude, such as to ensure consistent mean shooting distance (height above ground level), and thus, appropriate ground sample distance (GSD; pixel size). The results were analyzed in four variants, differing from each other in terms of the number of control points used and the method of their measurement. This allowed identification of the factors that affect surveying accuracy and the indication of the cadastral data updatable based on an UAV photogrammetric survey.
Highlights
In recent years, the use of unmanned aerial vehicles (UAVs) steadily grew in many countries, including Poland, primarily as a result of rapid developments in the field of unmanned flight and drone-borne sensors for geospatial data collection
As UAV photogrammetry became immensely popular, it is unsurprising that attempts were made to apply it to the maintenance of a cadastre
The research described in this article proved that an orthophoto map and a digital surface model (DSM) developed with due care based on UAV-acquired data may be used to update cadastral data, including those with respect to areas affected by landslides
Summary
The use of unmanned aerial vehicles (UAVs) steadily grew in many countries, including Poland, primarily as a result of rapid developments in the field of unmanned flight and drone-borne sensors for geospatial data collection. Wachholz de Souza et al [8] described an object-based image analysis (OBIA) procedure for UAV images, designed to map and extract information about skips in sugarcane planting rows. In Reference [11], high-resolution thermal imagery acquired by an unmanned aerial vehicle was used to map plant water stress and its spatial variability. This technology can be applied widely in engineering [12,13] and environmental protection. An interesting application is presented in Reference [14], which describes the integration of an off-the-shelf laser-based methane detector into a multi-rotor UAV, and demonstrates its efficacy in generating an aerial methane concentration map of a landfill. In order to perform plant protection operations, an automatic spraying system based on unmanned aerial vehicles (UAVs) was designed in China [15]
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