By understanding of different technologies of remote sensing is possible to choose proper data for updating of topographic maps. Described is use of remote sensing for weather forecast and observation of floods. Between 17th and 19th of September 2010 was in Slovenia heavy rain. The rain was well predicted in quantity and in location but was so intensive that floods appear in different areas of the country. With radar imagery is possible to get good overview of situation in a wider natural environment but is not possible to detect floods in urban areas. With the article we want to open discussion about usefulness of remote sensing data and fast mapping for different users in consideration of development Slovenian space technology.
B.06 Other
COBISS.SI-ID: 2303844What kind of status of topographic databases exists is also an important question to answer in CRP. Financing of topographic data in Slovenia has significantly decreased over the previous decade. As a result, the present status is far from acceptable or expected. The current status of the topographic data, as well as its quality and usability for potential users is discussed in this article. The overview starts with basic source data, aerial surveys, photographs and orthophotos. The quality of orthophotos largely depends on the DTM quality. Topographic data is nowadays organised in thematic datasets (geographical names, building cadastre, etc.) or joined in datasets of different levels of accuracy and details. The status in Slovenia is compared to those in some neighbouring and other comparable countries.
B.06 Other
COBISS.SI-ID: 5463905LIDAR is fast developing technology in remote sensing and very good potential for topographic map updating. The thesis is composed of two parts. In the first part we developed a new method for lidar DTM generation. In the second part we used vertical lidar profiles for model-based prediction of the percentages of individual tree species in the forest and to predict different light properties of the forest In steep forested relief, the existing algorithms for computing DTM from the lidar data have problems to distinguish between the ground returns and the vegetation returns, because on the steep slopes the local cloud neighborhood has properties similar to the vegetation. In the first part of the thesis we introduced a new method of DTM computation from the lidar data, called REIN, which is especially adapted to the steep forested topography. In the second part of the thesis we used vertical vegetation profiles, computed from the small-footprint discrete lidar data, to predict the percentages of individual tree species in the forest and to predict different light properties of the forest.
D.09 Tutoring for postgraduate students
COBISS.SI-ID: 5489249