scholarly journals Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview

2020 ◽  
Vol 10 (12) ◽  
pp. 4207 ◽  
Author(s):  
Anju Asokan ◽  
J. Anitha ◽  
Monica Ciobanu ◽  
Andrei Gabor ◽  
Antoanela Naaji ◽  
...  
Keyword(s):  
Image Processing ◽  
Satellite Images ◽  
Satellite Image ◽  
Historical Maps ◽  
Satellite Imaging ◽  
Image Processing Techniques ◽  
Innovative Solutions ◽  
Satellite Image Processing ◽  
Processing Techniques ◽  
Selection Of

Historical maps classification has become an important application in today’s scenario of everchanging land boundaries. Historical map changes include the change in boundaries of cities/states, vegetation regions, water bodies and so forth. Change detection in these regions are mainly carried out via satellite images. Hence, an extensive knowledge on satellite image processing is necessary for historical map classification applications. An exhaustive analysis on the merits and demerits of many satellite image processing methods are discussed in this paper. Though several computational methods are available, different methods perform differently for the various satellite image processing applications. Wrong selection of methods will lead to inferior results for a specific application. This work highlights the methods and the suitable satellite imaging methods associated with these applications. Several comparative analyses are also performed in this work to show the suitability of several methods. This work will help support the selection of innovative solutions for the different problems associated with satellite image processing applications.

scholarly journals Photogrammetry and image processing techniques for beach monitoring

2020 ◽  
pp. 175
Author(s):  
Elena Sánchez-García ◽  
Ángel Balaguer-Beser ◽  
Josep Eliseu Pardo-Pascual
Keyword(s):  
Image Processing ◽  
Satellite Images ◽  
Morphological Changes ◽  
Satellite Image ◽  
Public Information ◽  
Quality Data ◽  
Satellite Image Processing ◽  
Processing Techniques ◽  
Incident Waves ◽  
Derived Data

<p>The land-water boundary varies according to the sea level and the shape of a beach profile that is continuously modelled by incident waves. Attempting to model the response of a landscape as geomorphologically volatile as beaches requires multiple precise measurements to recognize responses to the actions of various geomorphic agents. It is therefore essential to have monitoring systems capable of systematically recording the shoreline accurately and effectively. New methods and tools are required to efficiently capture, characterize, and analyze information – and so obtain geomorphologically significant indicators. This is the aim of the doctoral thesis, focusing on the development of tools and procedures for coastal monitoring using satellite images and terrestrial photographs. The work brings satellite image processing and photogrammetric solutions to scientists, engineers, and coastal managers by providing results that demonstrate the usefulness of these viable and lowcost techniques. Existing and freely accessible public information (satellite images, video-derived data, or crowdsourced photographs) can be converted into high quality data for monitoring morphological changes on beaches and thus help achieve a sustainable management of coastal resources.</p>

scholarly journals Deep Learning in Satellite Imaging: A Survey

2021 ◽  
pp. 45-51
Author(s):  
Ibrahim Goni ◽  
Asabe S. Ahmadu ◽  
Yusuf M. Malgwi
Keyword(s):  
Deep Learning ◽  
Satellite Images ◽  
Satellite Image ◽  
Histogram Equalization ◽  
Research Directions ◽  
Satellite Imaging ◽  
Image Processing Techniques ◽  
Image Capturing ◽  
Satellite Image Analysis ◽  
Processing Techniques

In recent time deep learning has been extensively applied in satellite image analysis, the aim of this work was to conduct a thorough review on the application of deep learning in satellite imaging, moreover we have also provide a detail description regarding the principles of satellite image capturing, in addition to the mathematical models of image processing techniques used in satellite images such as image denoising, image filtering, image segmentation and histogram equalization. We have also discuss some of the aspect of deep learning but not in deep. Finally we have pave away for further research directions both in satellite imaging and deep learning.

scholarly journals A WEB-BASED VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS

2018 ◽  
Vol XLII-5 ◽  
pp. 9-13
Author(s):  
K. M. Buddhiraju ◽  
L. N. Eeti ◽  
K. K. Tiwari
Keyword(s):  
Image Processing ◽  
System Architecture ◽  
Satellite Images ◽  
Satellite Image ◽  
Virtual Laboratory ◽  
Web Based ◽  
Continuous Increase ◽  
Image Processing And Analysis ◽  
The World ◽  
Satellite Image Processing

<p><strong>Abstract.</strong> With continuous increase in the utilization of satellite images in various engineering and science fields, it is imperative to equip students with additional educational aid in subject of satellite image processing and analysis. In this paper a web-based virtual laboratory, which is accessible via internet to anyone around the world with no cost or constraints, is presented. Features of the laboratory has been discussed in addition to details regarding system architecture and its implementation. Virtual laboratory is tested by students, whose responses are also presented in this paper. Future development of this laboratory is outlined in the end.</p>

scholarly journals UTILIZATION EOS PLATFORM AS CLOUD-BASED GIS TO ANALYZE VEGETATION GREENNESS IN CIREBON REGENCY, INDONESIA

2020 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Moh. Dede ◽  
Millary Agung Widiawaty
Keyword(s):  
Image Processing ◽  
Spatial Data ◽  
Urban Areas ◽  
Satellite Image ◽  
Google Earth ◽  
Vegetation Greenness ◽  
Satellite Image Processing ◽  
Google Earth Engine ◽  
Beta Version ◽  
Selection Of

Cloud-Based GIS development has been increasing rapidly since the need for big computing for online spatial data. Besides Google Earth Engine, there is actually another Cloud-Based GIS with similar features namely EOS Platform. This study aims to determine the EOS Platform utilization as a Cloud-Based GIS to Analyze Vegetation Greenness in Cirebon Regency, Indonesia. The selection of research location based on the various phenomenon of development in the Cirebon Regency. Vegetation greenness analysis using the NDVI algorithm which available on EOS Processing and Landsat series images are obtained from Land Viewer. Changes in vegetation greenness were analyzed descriptively from NDVI values in two periods at each pixel in the same location. The results of the analysis with the EOS Platform show a decreasing vegetation greenness in the western and peri-urban areas caused by LULC changes. From this analysis, it is proven that EOS Platform can be used for effective and efficient satellite image processing. Even so, some EOS Platform products with BETA version status still show some obstacles related to integration between products.

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