Doyno Petkov

Remote sensing measurements in creating thematic spectral library

In Earth observations the reference spectra of well-described objects are required for better object-oriented interpretation of remotely sensed data from laboratory, field, airborne, and satellite sensors. For this purpose measurements of spectra using laboratory and field spectrometers are performed. The acquired spectra are used in creating a thematic spectral library. The used spectral instruments work in the wavelengths (0.4 to 2.5 microns) covering the spectral ranges from the visible /VIS/ to the shortwave infrared /SWIR/. Two different spectrometers are used to measure spectra included in the library: (1) Thematically oriented multichannel spectrometer covering the spectral range 0.4 to 0.9 microns and (2) high resolution NIRQuest spectrometer covering the range from 0.9 to 2.5 microns, both models of Ocean Optics Inc. Spectrometric measurements of representative samples of minerals, rocks, related soils, vegetation, and their natural mixtures are made in laboratory and field conditions. In some cases, samples were purified, so that the unique spectral characteristics of the studied objects could be related to their typical structure. The relations between the spectra and the structures are important for interpreting remotely sensed data acquired in the field or from an air- or space-borne platform. In some cases for making easy wide use of the spectra in the library the obtained spectra have to resample to selected broadband multispectral sensors for example those based on the satellites Landsat and Sentinel. The obtained spectral data with the metadata and additional information are planned for including in files for better interpretation of images with different spatial resolution.

Multisensor Earth observation systems: data fusion

Advancements in modern technologies, such as remote sensing systems and instruments have led to rapid developments in the field of Earth observation /EO/. As a result, enormous volumes of EO data with various spatial and spectral resolutions are obtained. However, the expected enhancements in the classification accuracy still have not been reached, due to the complexity of the remote sensing measurements and the big volume of data that need to be processed. The last leads to the necessity of development and improvement of methods and techniques for data obtaining and analysis. The methods include the validation multi-sensor systems, the processing technique of big data, and the object identification and classification methods for improving information quality through data fusion. To achieve correct information with highest accuracy in data analyzing and interpreting, researchers have to apply these methods and to create technologies for obtaining and integrating data from different Earth Observation Systems /EOS/. For gathering and using all of the information a local and regional EOS of Systems needs to be established. By creating such local EOS of Systems more extensive information could be collected, analyzed and retrieved. In this paper a local system is presented, focusing on the description of the ground component. The main sensors embedded in the system are spectrometers. The working range of the multi-sensor system is VIS-NIR-SWIR. Thus, by applying the data fusion methods, combining images and spectral information, a more accurate thematic interpretation is achieved. Example illustrating the benefits of a multisensor system data fusing is presented and discussed.

Optical hyperspectral measurements of rocks and soils in Central Srednogorie, Bulgaria

Remote sensing is the technique of acquiring, processing, and interpreting images and multi channels spectral data, acquired from optical imager sensors mounted on aircraft and satellite platforms recording the interaction between investigated objects and electromagnetic energy. Remote sensing application in Earth observation begins with the design and development of equipment for carrying out research of the monitored objects remotely and without disturbing their integrity. Ground-truth data in Earth observation of the environment and in the remote sensing investigations are very important. In this work remote sensing images are used for mineral exploration in different applications for mapping geology and recognizing soils and rocks by their spectral signatures. We are used Landsat, ASTER and Sentinel satellites images used to interpret both structures, soils and rocks. For data verification hyperspectral systems USB 2000 and NIRQUEST 512.2 of Ocean Optics Inc. are used in laboratory and field spectrometric measurements. They provide to define finest spectral characteristics of soil minerals and rocks for their identification. The obtained spectral data are compared with similar data from different instruments for Earth observation included in the spectral libraries. They correspond to the shape of the spectral signature in the same spectral range obtained with other spectrometers. These promising results encourage us to plan the next campaigns for the field spectroscopy measurements in different regions of Bulgaria.

Unmixing techniques for better segmentation of urban zones, roads, and open pit mines

In this paper the linear unmixing method has been applied in classification of manmade objects, namely urbanized zones, roads etc. The idea is to exploit to larger extent the possibilities offered by multispectral imagers having mid spatial resolution in this case TM/ETM+ instruments. In this research unmixing is used to find consistent regression dependencies between multispectral data and those gathered in-situ and airborne-based sensors. The correct identification of the mixed pixels is key element for the subsequent segmentation forming the shape of the artificial feature is determined much more reliable. This especially holds true for objects with relatively narrow structure for example two-lane roads for which the spatial resolution is larger that the object itself. We have combined ground spectrometry of asphalt, Landsat images of RoI, and in-situ measured asphalt in order to determine the narrow roads. The reflectance of paving stones made from granite is highest compared to another ones which is true for open and stone pits. The potential for mapping is not limited to the mid-spatial Landsat data, but also may be used if the data has higher spatial resolution (as fine as 0.5 m). In this research the spectral and directional reflection properties of asphalt and concrete surfaces compared to those of paving stone made from different rocks have been measured. The in-situ measurements, which plays key role have been obtained using the Thematically Oriented Multichannel Spectrometer (TOMS) - designed in STIL-BAS.

Data Acquisition Field Network in Support of Remote Sensing Investigations

Integrated use of data collected during remote sensing experiments and data from in-situ measurements reveal more features of the land cover objects under study. This features incorporated into existing GIS databases leads to better understanding, representing, managing, and integrating many aspects of the Earth as a complex system. The in-situ gathered data such as, ground control points by GPS, current meteorological conditions, soil moisture, etc., provides additional information that is crucial in improving GIS effectiveness in decision support. To improve and facilitate the process of collection and storage of in-situ data a distributed mobile, wireless, field network was developed. The main components of the system are the autonomous, battery-powered micro controller devices wirelessly communicating with a central one. In this paper short description of the technical parameters and communication protocols between devices, hubs and the control center is outlined. From topological point of view two types of networks can be implemented -simple, used in small areas (usually less than 10 km2) and full, covering areas up to 50 km2. Both networks has flexible structure, offered by a variable number of commands that could be easily adapted to meet the requirements of dissimilar measuring devices thus increasing the number of target applications -from land use to disaster monitoring. A prototype of the system successfully performed well on test polygons in North Bulgaria.

Interconnection architectures for transputer-based parallel image processing

Abstract Image processing has been undergoing rapid development for more than thirty years /1/, /2/. The tasks in this field are characterized by high computational complexity. Enabling image processing algorithms to run in real time requires large computational power. Modern display systems support more than 256 colors (8-bits) per pixel and typical images have a spatial resolution of 512×512 pixels or larger for each image. Supporting high resolution displays and imagery requires the use of visualization systems with high performance computational capabilities. The transputer is a contemporary state-of-the-art parallel computer environment that offers high computational performance at a relatively low price (i.e. high performance/price ratio) for building such systems. Our other goal is to prototype the use of transputers as a flexible image processing enginer for remote sensing applications.