Keynote Speakers/主讲嘉宾

Keynote Speakers/主讲嘉宾

Prof. Quazi K. Hassan

University of Calgary, Canada

Title: Modeling of flood-induced damages using satellite data in Bangladesh

Abstract: Bangladesh is one of the flood prone countries in the world due to its geographic location. In this talk, I would like to talk about two specific cases. The first one is about the delineation of the impact of the 2017 flash flood (that initiated on 27 March 2017) boro (dry season) rice using multi-temporal satellite data acquired by Landsat-8 OLI and MODIS sensors that occurred in northeastern region of Bangladesh. The second one is the assessment of the flood extent and crop damage using RADARSAT SAR satellite data during the extremely unusual flooding event occurred in the southwestern region of Bangladesh in the year 2000. Both of the case studies demonstrate the usefulness of using satellite dat in flood management; and these may play a critical role in developing strategies for flood management and disaster mitigation activities to aid the process of ensuring food security for the country.


Prof. David Bassir

French University of Technology, France

Title: Geologic optimal 3D mapping: Advantages of VTOL drones for LIDAR and drone photogrammetry technics

Author: David BASSIR1,2, Mudit KAPOOR3, Yue HAO4,5

Abstract: Three-dimensional geologic mapping have been applied for several applications, such as oil and gas, as well as mineral resource exploration. Local application to geology remains new [1,3], due to the sensitivity and details of the mapping. As it requires surface analysis, HD image processing and recently integration of new generation of hybrid Unmanned Aerial Vehicles (UAV). Among the development of the autonomous control technology in recent decades [4], hybrid UAV, that combines Fixed-Wing and Vertical-Taking-Off-and-Landing are taking an important role from military to civil applications. With the integration of drones, engineering have the choice now between photogrammetry (technics of measurements from photographs to output map, drawing, or 3D model) and LIDAR (method based on the measurement of the distance to a target by illuminating it with laser light and measuring the reflection with a sensor) [5,6]. Both technics provide a remarkable 3D model comparable to the terrestrial sample methods. However, the efficiency and the optimal results will depend on the exact needs. Having an accurate mapping and data can reduce the land-use pressures and can be also important in urban settings or expanding suburban areas, As there are thousands of data locations to consider, analysis, and compiled to build accurate 3D geological maps and models at large scales. In this work, we first, present the advantages and disadvantages of each technics to create geologic mapping and how hybrid Vertical-Taking-Off-and-Landing drone can optimize the output of the 3D geologic model.

Details about the  Keynote Presentation: Click

Dr. Nada M. Alhakkak

Baghdad College for Economic Science University, Iraq

Title: Mining Big Data from Remote Sensing

Abstract: The term Big Data refers to a huge amount of data generated from any IOT device or application; i.e. remote sensing. Big Data mining is extracting information and patterns for knowledge and better decision ability. Traditional analysis tools do not work professionally with streams of big data; those are collected from remote sensing devices. Massive online analysis MOA is an efficient big data mining tool that includes different classification and clustering techniques; it’s scalable and extensible with java platform. I would like to talk about the big data mining tools in general and constraint on MOA.