This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈ 1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations.

No abstract

V tem članku se osredotočamo na implementacijo naprednega geografskega informacijskega sistema, ki omogoča samodejno ocenjevanje večletnih profilov gibanja nadmorskih višin gladine jezer. Implementacija predlaganega sistema temelji na integraciji platforme Open Access Hub, ki omogoča dostop do odprtih podatkov Copernicus. Pri tem se osredotočamo na multispektralne optične slike para satelitov Sentinel 2, ki omogočajo izvedbo meritev s petdnevno časovno in desetmetrsko prostorsko ločljivostjo. Ključni gradniki predlaganega sistema so podsistem za samodejen zajem podatkov ter njihovo predobdelavo, vključno s tehnikami podatkovnega razšumljanja, obrezovanje slik in njihovo prostorsko poravnavo, digitalni model reliefa oziroma točkovna definicija nadmorskih višin okoliškega terena, algoritem za razpoznavo in filtriranje oblačnih slik, komponenta za razpoznavo pokrivnosti površja, izračun vodnega indeksa in segmentacijo gladine jezer ter sistem za preslikavo razpoznanih mej gladine jezer v nadmorske višine. Z rezultati demonstriramo, da predlagan pristop omogoča dovolj visoko natančnost za praktično uporabo.

Acts of fraud have become much more prevalent in the financial industry with the rise of technology and the continued economic growth in modern society. Fraudsters are evolving their approaches continuously to exploit the vulnerabilities of the current prevention measures in place, many of whom are targeting the financial sector. To overcome and investigate financial frauds, this paper presents STALITA, which is an innovative platform for the analysis of bank transactions. STALITA enables graph-based data analysis using a powerful Neo4j graph database and the Cypher query language. Additionally, a diversity of other supporting tools, such as support for heterogeneous data sources, force-based graph visualisation, pivot tables, and time charts, enable in-depth investigation of the available data. In the Results section, we present the usability of the platform through real-world case scenarios.