ABSTRACT:In order to determine the absolute accuracy of SRMT model on Polish area the research work has been performed on the basis of reference terrain profiles measured by GPS technique. The flat and hilly terrains were examined in administrative borders of fourteen provinces. It was not reference data for mountainous terrains. For the analysis of accuracy of the SRTM model 332 terrain profiles and 29,308 points have been measured. The accuracy of SRTM model presented by RMSE was computed on the basic of the height differences between profiles and models homolog points. The analyses have been done in Modular GIS Environment Intergraph software. The absolute accuracy of SRTM model on Polish area RMSE Z = 2.9 m for flat regions and RMSE Z = 5.4 m for hilly regions were achieved. It was affirmed that this accuracy is depend on the resolution of grid points of DEM and terrain inclination. The statistic estimation showed systematic shift between SRTM data and reference profiles. The RMSE Z without systematic part was found to be 1.0 m for flat regions and 2.7 m for hilly regions of Polish area. The data of SRTM level DTED-1 could be used for DEM and contour lines generation on the topographic maps in scales smaller then 1:50,000 and for SRTM system calibration.

The growing demand for high-quality imaging data and the current technological limitations of imaging sensors require the development of techniques that combine data from different platforms in order to obtain comprehensive products for detailed studies of the environment. To meet the needs of modern remote sensing, the authors present an innovative methodology of combining multispectral aerial and satellite imagery. The methodology is based on the simulation of a new spectral band with a high spatial resolution which, when used in the pansharpening process, yields an enhanced image with a higher spectral quality compared to the original panchromatic band. This is important because spectral quality determines the further processing of the image, including segmentation and classification. The article presents a methodology of simulating new high-spatial-resolution images taking into account the spectral characteristics of the photographed types of land cover. The article focuses on natural objects such as forests, meadows, or bare soils. Aerial panchromatic and multispectral images acquired with a digital mapping camera (DMC) II 230 and satellite multispectral images acquired with the S2A sensor of the Sentinel-2 satellite were used in the study. Cloudless data with a minimal time shift were obtained. Spectral quality analysis of the generated enhanced images was performed using a method known as “consistency” or “Wald’s protocol first property”. The resulting spectral quality values clearly indicate less spectral distortion of the images enhanced by the new methodology compared to using a traditional approach to the pansharpening process.

AbstractArchival aerial photographs obtained in the 20th century play a special role in the process of upgrading the register of land and buildings. These photographs are the only resource presenting credible information on the coverage and use of land in a high degree of detail. In this article, particular attention is paid to the aspect of the spectral resolution of archival aerial photographs. Preliminary research was conducted into the assessment of the impact of simulations of new spectral bands with high spatial resolution for archival photographs upon the interpretation process of such data. The proposed simulation method of new bands is based on the integration of archival monochromatic aerial images with archival multispectral satellite imagery. Visual and quantitative comparative analysis of monochromatic imagery and of enhanced images obtained by application of the simulation process was performed. The results of this research unanimously confirmed the improved interpretation possibilities of archival aerial photographs, associated not only with the assignment of colours but also with the reconstruction of spectral information for the arable and afforested land photographed.

Textured three dimensional models are currently the one of the standard methods of representing the results of photogrammetric works. A realistic 3D model combines the geometrical relations between the structure's elements with realistic textures of each of its elements. Data used to create 3D models of structures can be derived from many different sources. The most commonly used tool for documentation purposes, is a digital camera and nowadays terrestrial laser scanning (TLS). Integration of data acquired from different sources allows modelling and visualization of 3D models historical structures. Additional aspect of data integration is possibility of complementing of missing points for example in point clouds. The paper shows the possibility of integrating data from terrestrial laser scanning with digital imagery and an analysis of the accuracy of the presented methods. The paper describes results obtained from raw data consisting of a point cloud measured using terrestrial laser scanning acquired from a Leica ScanStation2 and digital imagery taken using a Kodak DCS Pro 14N camera. The studied structure is the ruins of the Ilza castle in Poland.

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Post-WWII displacements in the Polish Carpathians resulted in widespread land abandonment. Most of the pre-war agricultural areas are now covered with secondary forests, which will soon reach the felling age. Mapping their exact cover is crucial to investigate succession–regeneration processes and to determine their role in the landscape, before making management decisions. Our goal was to map post-agricultural forests in the Polish Eastern Carpathians using archival remote sensing data, and to assess their connectivity with pre-displacement forests. We used German Flown Aerial Photography from 1944 to map agricultural lands and forests from before displacements, and Corona satellite images to map agricultural lands which converted into the forest as a result of this event. We classified archival images using Object-Based Image Analysis (OBIA) and compared the output with the current forest cover derived from Sentinel-2. Our results showed that mature (60–70 years old) post-agricultural forests comprise 27.6% of the total forest area, while younger post-agricultural forests comprise 9%. We also demonstrated that the secondary forests fill forest gaps more often than form isolated patches: 77.5% of patches are connected with the old-woods (forests that most likely have never been cleared for agriculture). Orthorectification and OBIA classification of German Flown Aerial Photographs and Corona satellite images made it possible to accurately determine the spatial extent of post-agricultural forest. This, in turn, paves the way for the implementation of site-specific forest management practices to support the regeneration of secondary forests and their biodiversity.

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