Mangrove vulnerability modelling in parts of Western Niger Delta, Nigeria using satellite images, GIS techniques and Spatial Multi-Criteria Analysis (SMCA)

2010 ◽  
Vol 178 (1-4) ◽  
pp. 39-51 ◽  
Author(s):  
Omo O. Omo-Irabor ◽  
Samuel B. Olobaniyi ◽  
Joe Akunna ◽  
Valentijn Venus ◽  
Joseph M. Maina ◽  
...  
Keyword(s):  
Niger Delta ◽  
Satellite Images ◽  
Gis Techniques ◽  
Multi Criteria Analysis

THE ASSESSMENT OF LOTIC ECOSYSTEMS DEGRADATION USING MULTI-CRITERIA ANALYSIS AND GIS TECHNIQUES

2019 ◽  
Vol 14 (2) ◽  
pp. 255-268
Author(s):  
Cristiana Maria CIOCĂNEA ◽  
◽  
Petru Ciprian CORPADE ◽  
Diana Andreea ONOSE ◽  
Gabriel Ovidiu VÂNĂU ◽  
...  
Keyword(s):  
Lotic Ecosystems ◽  
Gis Techniques ◽  
Multi Criteria Analysis

scholarly journals Hydrological problems of flash floods and the encroachment of wastewater affecting the urban areas in Greater Cairo, Egypt, using remote sensing and GIS techniques

2020 ◽  
Vol 44 (1) ◽  
Author(s):  
Hanaa A. Megahed ◽  
Mohammed A. El Bastawesy
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Satellite Images ◽  
Flash Flood ◽  
Flow Direction ◽  
Flash Floods ◽  
Mitigation Measures ◽  
Water Volume ◽  
Gis Techniques ◽  
Greater Cairo

Abstract Background This paper discusses the hydrological problems assessment of flash floods and the encroachment of wastewater in selected urban areas of Greater Cairo using remote sensing and geographic information system (GIS) techniques. The integration of hydrogeological and geomorphological analyses with the fieldwork of drainage basins (Wadi Degla) hosting these urban areas endeavors to provide the optimum mitigation measures that can be feasibly taken to achieve sustainability of the urban areas and water resources available. Results Landsat 5 and Sentinel-2 satellite images were obtained shortly before and after flash flood events and were downloaded and analyzed to define the active channels, urban interference, storage areas, and the natural depressions response. The quantitative flash flood estimates include total GSMap meteorological data sets, parameters of rainfall depths from remote sensing data, active channel area from satellite images, and storage areas that flooded. In GIS, digital elevation model was used to estimate the hydrographic parameters: flow direction within the catchment, flow accumulation, time zone of the catchment, and estimating of the water volume in the largely inundated depressions. Conclusions Based on the results obtained from the study of available satellite images, it has been shown that there are two significant hydrological problems, including the lack of flash flood mitigation measures for urban areas, as the wastewater depressions and sanitary facilities are dotting in the downstream areas.

scholarly journals Urban Growth Assessment of Chennai District by Remote Sensing and Gis Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 5119-5125
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Satellite Images ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Gis Techniques ◽  
Land Cover Map ◽  
Landsat Satellite

Urban growth of Chennai district is exponential and heading towards extreme urbanisation. Hence this necessitates the study of urban growth in Chennai district. The recent advancement in Remote sensing and GIS has an excellent ability to derive various data from the satellite images obtained .This helps us to map, monitor and picturise various aspects of development with respect to their demands. The basic principle of remote sensing is followed as the methodology. By following the methodology correctly and by proper processing of the data acquired from the satellite images, the exact requirements of information can be obtained. The Change in the urban growth of the Chennai district for three decades from 1989 to 2019 have been found by using remote sensing and GIS techniques. The satellite images of various years are obtained from Landsat satellite from the USGS Earth Explorer .The Land use characteristics of Chennai district of each year can be obtained by preparing the land use land cover map of Chennai district by the use of landsat satellite images. The two software namely ArcGIS and ERDAS Imagine are used to create the Land use land cover map. From the Land use land cover map of Chennai district, the change detection and statistical analysis of three decades are done and these analysis clearly shows that the urban growth of Chennai district is constantly increasing and there is a huge decrease in other natural features such as vegetation, water body and barren land. By performing urban trend analysis the urban growth of Chennai district for the upcoming years are predicted to prove the urban agglomeration in Chennai district.

scholarly journals Coastal disaster mitigation through shoreline changes analysis in Pariaman city

2020 ◽  
Vol 156 ◽  
pp. 01007
Author(s):  
Azria Paldi Donal ◽  
Andriani
Keyword(s):  
Coastal Erosion ◽  
Satellite Images ◽  
Coastal Areas ◽  
Disaster Mitigation ◽  
Coastal Change ◽  
Construction Costs ◽  
Shoreline Changes ◽  
Gis Techniques ◽  
Coastal Changes ◽  
Good Research

Disasters caused losses and damage to the coastal areas of Pariaman City. The construction costs for development in coastal areas are relatively expensive. Early good research must be done to monitor shoreline changes and reduce losses and damage in the coastal areas of Pariaman City. The method used to monitor shoreline changes using satellite images with GIS techniques. The coastal change analyzes is studied including coastal erosion and sedimentation. In this study, disaster mitigation and impacts reduction caused by coastal changes are the final purposes. The losses and damage due to coastal changes were monitored during a certain time. The results of this study are aimed to make a solution for disaster mitigation in coastal areas caused by the shoreline changes in Pariaman City.

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

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