Do podatkov Sentinel je, odvisno od misije in vrste podatkov, mogoče dostopati prek običajnih dostopnih točk ESE in EUMETSAT-a2 ali prek platform DIAS3 (Data and Information Access Services'), ki ...zagotavljajo (delno) zrcaljenje podatkov, tematskih platform TEP4 (Thematic Exploitation Platforms) ali regionalnih podatkovnih storitev5 (Copernicus Collaborative Ground Segment), kot tudi drugih uveljavl2 2 podatkovnih centrov6 ali spletišč za hitro prikazovanje in iskanje satelitskih podatkov po obširnih ? bazah podatkov teh centrov (med temi želimo posebej izpostaviti platformo Sentinel Hub, ki jo zelo uspešno upravlja slovensko podjetje Sinergise) (ESA Sentinel Data Access, 2021; ESA Earth Online, TS 2021). Medagencijski Odbor za satelite za opazovanje Zemlje (Committee on Earth Observation Satellites, CEOS) spodbuja pripravo in distribucijo tako imenovanih ,podatkov, pripravljenih za analizo' (Analysis Ready g Data, ARD), s čimer želi podpreti hitro, zanesljivo in avtomatizirano uporabo podatkov Sentinel ter ^ omogočiti interoperabilnost tako med različnimi obdobji zajema satelitskih podatkov kot z drugimi zbirkami satelitskih podatkov, na primer s podatki Landsat (CEOS, 2020). Doseganje ustrezne primerljivosti in boljše konsistentnosti satelitskih podatkov ter s tem boljše povezljivosti in združljivosti podatkov je zahtevna naloga, zato pri njej sodelujejo vsi pomembnejši proizvajalci podatkov, tj. vesoljske agencije (NASA, ESA, JAXA itd.) ter glavni centri za dostavo in dostop do podatkov (ponudniki storitev v oblaku, regionalna podatkovna vozlišča). ESIN portal Copernicus Open Access Hub (https://scihub.copernicus.eu/, prej znan kot Sentinels Scientific Data Hub) zagotavlja brezplačen in odprt dostop do uporabniških izdelkov Sentinel-1, Sentinel-2, Sentinel-3 in Sentinel-5P Prenos posnetkov s tega spletišča v naš arhiv smo realizirali prek vmesnika API Hub, ki
Such a diverse and sensitive eco-region as Karst needs to be managed with special attention and consideration of its natural and cultural resources. Land cover is an important indicator, which ...enables the analysis of their condition and development monitoring. Advanced satellite images classification represents an accurate and cost-effective alternative to the classical techniques of land cover mapping. The methods used to produce a reliable land cover map are presented in this paper. The complexity of the area requires a combination of various data such as Landsat satellite images, digital elevation model, digital orthophotos as well as existing topographic and thematic maps. The maximum likelihood algorithm was used as the main classifier and the accuracy of results was further improved by fuzzy classification, altitude and inclination filtering and auxiliary data integration.
The aim of this article is to investigate methods for the automatic extraction of the infrared (IR) textures for the roofs and facades of existing building models. We focus on the correction of the ...measured exterior orientation parameters of the IR camera mounted on a mobile platform. The developed method is based on point-to-point matching of the features extracted from IR images with a wire-frame building model. Firstly, the extraction of different feature types is studied on a sample IR image; Forstner and intersection points are chosen for a representation of the image features. Secondly, the three-dimensional (3D) building model is projected into each frame of the IR video sequence using orientation parameters; only coarse exterior orientation parameters are known. Then the automatic co-registration of a 3D building model projection into the image sequence with image features is carried out. The matching of a model and extracted features is applied iteratively, and exterior orientation parameters are adjusted with least square adjustment The method is tested on a dataset of a dense urban area. Finally, an evaluation of the developed method is presented with five quality parameters, i.e. efficiency of the method, completeness and correctness of matching and extraction.
Lossy compression is becoming increasingly used in remote sensing, although its effect on the processing results has yet not been fully investigated. This paper presents the effects ofJPEG2000 lossy ...compression on the classification of very high-resolution WorldView-2 imagery. For the first time, the k-nearest neighbor and support vector machine methods of the object based classification were used. The results explore the impact of compression on the images, segmentation and resulting classification. The study proves that in general lossy compression does not adversely affect the classification of images; moreover, in some cases classification of compressed images yields better results than classification of the original image. Classification accuracy of the support vector machine method indicates that compression ratios of up to 30:1 can be used without any loss of classification accuracy. The best result of the k-nearest neighbor method was obtained with the highest compression ratio (100:1). The support vector machine is recommended for further research. In addition to the classification method, image segmentation also plays an important role in the accuracy of the results.
This article presents a review and comparison of the detection capability of water facilities or water surfaces with different systems of remote sensing: optical and radar satellite sensors, as well ...as optical sensors on aircraft. The capabilities of water detection are estimatedfrom several aspects: differences in the spatial and spectral resolution of imagery, the complexity of imagery pre-processing requirements, and the method of analysis and interpretation feasibilities for the type and purpose of mapping. Particular attention is paid to evaluating the applicability of remote sensing data in light of the detection efficiency of water areas in heterogeneously structured environments.
Remote sensing has developed various methods and technologies for contactless and cost-effective mapping of large area land cover/land use maps and other thematic maps. The key factor for the ...availability and reliability of these maps for use in Earth sciences is the development of effective procedures for satellite data analysis and classification. The most appropriate approach for classifying low and medium resolution satellite images (pixel size is coarser than, or at best similar to, the size of geographical objects) is pixel-based classification in which an individual pixel is classified into the closest class based on its spectral similarity. With increasing spatial resolution, pixel-based classification methods became less effective, since the relationship between the pixel size and the dimension of the observed objects on the Earth's surface has changed significantly. Therefore object-oriented classification has become increasingly popular over the past decade. This combines segmentation (which is a fundamental phase of the approach) and contextual classification. Segmentation divides the image into homogeneous pixel groups (segments), which are -during the semantic classification process - arranged into classes based on their spectral, geometric, textural and other features during. The intent of this paper is to present the theoretical argumentation and methodology of object-based image analysis of remote sensing data, provide an overview of the field and point out certain restrictions as regards the current operational solutions.
Remote sensing has developed various methods and technologies for contactless and cost-effective mapping of large area land cover/land use maps and other thematic maps. The key factor for the ...availability and reliability of these maps for use in Earth sciences is the development of effective procedures for satellite data analysis and classification. The most appropriate approach for classifying low and medium resolution satellite images (pixel size is coarser than, or at best similar to, the size of geographical objects) is pixel-based classification in which an individual pixel is classified into the closest class based on its spectral similarity. With increasing spatial resolution, pixel-based classification methods became less effective, since the relationship between the pixel size and the dimension of the observed objects on the Earth's surface has changed significantly. Therefore object-oriented classification has become increasingly popular over the past decade. This combines segmentation (which is a fundamental phase of the approach) and contextual classification. Segmentation divides the image into homogeneous pixel groups (segments), which are - during the semantic classification process - arranged into classes based on their spectral, geometric, textural and other features during. The intent of this paper is to present the theoretical argumentation and methodology of object-based image analysis of remote sensing data, provide an overview of the field and point out certain restrictions as regards the current operational solutions.
In the recent years radar interferometry (InSAR) has become an important tool in various studies. It can be used to produce accurate digital elevation models and observe small surface displacements. ...Differential interferometry (DInSAR) can detect movements in the radar look direction that are in the order of wavelength used, i.e. less than one centimetre with ERS data. In the presented study DInSAR has been used to observe surface movements in western Slovenia. Three ERS radar images have been supplemented with an external digital elevation model to produce three differential interferograms that temporally covered the Posočje earthquake, which happened on April 12, 1998. For the area around Bovec a land subsidence of approximately 0.5 cm has been observed; the largest movements detected exceeded 2 cm. DInSAR has been compared to the permanent scatterers interferometry (PSInSAR). Both methods are complementary and both have individual advantages and disadvantages.
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