Zbigniew Łubniewski

Innovative Web-Based Geographic Information System for Municipal Areas and Coastal Zone Security and Threat Monitoring Using EO Satellite Data

The paper presents a novel design of a web-based Safe City & Coastal Zone GIS (SCCZ-GIS). The system integrates data acquired from different remote sensing and geospatial data sources for the purpose monitoring the security of the coastal zone, its inhabitants and critical infrastructure. The system utilizes several innovative technologies and solutions and is capable of direct co-operation with different remote sensing data sources and services, including satellite ground station and ESA Service Support Environment. The system runs in operational mode, and the results of the analysis are ready in quasi real time, that is, immediately after receiving a new scene of satellite imagery. The system may be accessed by authorized users either through a web-based client or mobile device application. The paper describes the architecture of the system and presents several case studies where the software is applied to processing of earth observation satellite and spatial analysis of coastal zone infrastructure.

Characterizing Surface and Air Temperature in the Baltic Sea Coastal Area Using Remote Sensing Techniques and Gis

Abstract Estimation of surface temperature using multispectral imagery retrieved from satellite sensors constitutes several problems in terms of accuracy, accessibility, quality and evaluation. In order to obtain accurate results, currently utilized methods rely on removing atmospheric fluctuations in separate spectral windows, applying atmospheric corrections or utilizing additional information related to atmosphere or surface characteristics like atmospheric water vapour content, surface effective emissivity correction or transmittance correction. Obtaining accurate results of estimation is particularly critical for regions with fairly non-uniform distribution of surface effective emissivity and surface characteristics such as coastal zone areas. The paper presents the relationship between retrieved land surface temperature, air temperature, sea surface temperature and vegetation indices (VI) calculated based on remote observations in the coastal zone area. An indirect comparison method between remotely estimated surface temperature and air temperature using LST/VI feature space characteristics in an operational Geographic Information System is also presented.

3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning

Abstract The technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation, i.e. 3D surfaces composed of edges and facets, is preferred with respect to the terrain or seabed surface relief as well as various objects shape. In the paper, the authors propose a new approach to 3D shape reconstruction from both multibeam and LiDAR measurements. It is based on a multiple-step and to some extent adaptive process, in which the chosen set and sequence of particular stages may depend on a current type and characteristic features of the processed data. The processing scheme includes: 1) pre-processing which may include noise reduction, rasterization and pre-classification, 2) detection and separation of objects for dedicated processing (e.g. steep walls, masts), and 3) surface reconstruction in 3D by point cloud triangulation and with the aid of several dedicated procedures. The benefits of using the proposed methods, including algorithms for detecting various features and improving the regularity of the data structure, are presented and discussed. Several different shape reconstruction algorithms were tested in combination with the proposed data processing methods and the strengths and weaknesses of each algorithm were highlighted.

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

Abstract Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR), using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdansk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255°C with correlation coefficient R equal to 0.828 and Bias = 0.557°C. For comparison, using the PBIM method, it was obtained RMSE = 2.832°C, R = 0.775 and Bias = 0.997°C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53°C on average, in the case of applying the proposed method than in the case of using the PBIM method.

Using EO satellite data in Safe City and Coastal Zone web-GIS

The paper presents a novel design of a web-based Safe City & Coastal Zone GIS (SCCZ-GIS) which integrates data acquired from different remote sensing and geospatial data sources for monitoring the security of the coastal zone, its inhabitants and Critical Infrastructure. The system utilizes several innovative technologies and directly co-operates with different remote sensing data sources and services, like a satellite ground station or ESA Service Support Environment. The results of analysis are ready in quasi real time, e.g., immediately after receiving the new scene of satellite imagery. Also, the system is accessible for authorized users by a client application oriented either to a browser-based personal computer platform, or to mobile devices.