Abstract: In this paper, we describe intelligent methods and technologies for environmental risks assessment using geospatial data. The risk assessment process is based on fusion of data acquired from different sources: models, in-situ observations and remote sensing instruments. The ensemble approach is used for data processing. Several real-world applications are described to demonstrate efficiency of the proposed approach, namely numeral weather prediction (NWP), land biodiversity assessment, vegetation state assessment, fire monitoring and flood mapping. These applications are being implemented within international projects within the UN-SPIDER Regional Support Office (RSO) in Ukraine.

Keywords: intelligent methods, risk assessment, remote sensing from space, satellite data processing, environmental monitoring, vegetation state assessment, fire monitoring, UN-SPIDER.

ACM Classification Keywords: D.2.12 Software Engineering Interoperability; Information Systems; H.1.1 Models and Principles Systems and Information Theory; H.3.5 Information Storage and Retrieval Online Information Services; I.4.8 Image Processing and Computer Vision Scene Analysis - Sensor Fusion.

Link:

ENVIRONMENTAL RISK ASSESSMENT USING GEOSPATIAL DATA AND INTELLIGENT METHODS

Nataliia Kussul, Sergii Skakun, Oleksii Kravchenko

http://foibg.com/ijitk/ijitk-vol05/ijitk05-2-p04.pdf