Currently, the possibilities offered by measurement techniques allow development of both cities in the form of 3D models as well as models of small and large architecture objects. Depending on the needs, the scale of an examined object or the intended use of the final product, geodesy finds readymade measurement methods. If one wants to work out a 3D model of a building object in detail, the most accurate way is to use laser scanning technology. However, there are situations in which limitations resulting from the terrain layout or the structure of the building preclude to obtain full information about its shape. In such situations, the solution is to integrate data from various measurement devices. If creating a full 3D model of large buildings, the best choice to complete data, especially the roof of the object, is to use an unmanned aerial platform, because the resolution of images made on a low altitude is good enough to obtain a satisfactory effect in the form of a point cloud. The research used integration of data obtained at low altitude from two unmanned aerial vehicles, Fly-Tech DJI S1000 and DJI Phantom 3 Advanced – using various types of missions – with data recorded with the Leica ScanStation P40 terrestrial laser scanner. The data was integrated by giving them a common coordinate system – in this case the 2000 system, for the grid points measured in the field with the GNSS technique, and the use of Cyclone, Metashape and Pix4D software for this purpose. Combined point clouds were used for 3D modelling of the sacred object with Bentley CAD software. The accuracy with which data integration was performed and errors resulting from the use of various measurement techniques were determined. The result of the study is a 3D model of the Church of Our Lady of Consolation, located in Krakow at the Sportowe estate.

3D maps are becoming more and more popular due not only to their accessibility and clarity of reception, but above all, they provide comprehensive spatial information. Three-dimensional cartographic studies meet the accuracy requirements set for traditional 2D stu-dies, and additionally, they naturally connect the place where the phenomenon occurs with its spatial location. Due to the scale of the objects and difficulties in obtaining comprehensive data using only one source, a frequent procedure is to integrate measurement, cartographic, photo-grammetric information and databases in order to generate a comprehensive study in the form of a 3D map. This paper presents the method of acquiring and processing, as well as, integrating data from TLS and UAVs. Clouds of points representing places and objects are the starting point for the implementation of 3D models of buildings and technical objects, as well as for the con-struction of the Digital Terrain Model. However, in order to supplement the spatial information about the object, the geodetic database of the record of the utilities network was integrated with the model. The procedure performed with the use of common georeferencing, based on the global coordinate system, allowed for the generation of a comprehensive basemap in a three-dimensional form.

With the rapid development of remote sensing technology, our ability to obtain remote sensing data has been improved to an unprecedented level. We have entered an era of big data. Remote sensing data clear showing the characteristics of Big Data such as hyper spectral, high spatial resolution, and high time resolution, thus, resulting in a significant increase in the volume, variety, velocity and veracity of data.This paper proposes a feature supporting, salable, and efficient data cube for timeseries analysis application, and used the spatial feature data and remote sensing data for comparative study of the water cover and vegetation change. In this system, the feature data cube building and distributed executor engine are critical in supporting large spatiotemporal RS data analysis with spatial features. The feature translation ensures that the geographic object can be combined with satellite data to build a feature data cube for analysis. Constructing a distributed executed engine based on dask ensures the efficient analysis of large-scale RS data. This work could provide a convenient and efficient multidimensional data services for many remote sens-ing applications.