The threshold determination methods of water body information extraction using GF-1 satellite image

AbstractApplications of Earth-observational remote sensing are rapidly increasing over urban areas. The latest regime shift from conventional urban development to smart-city development has triggered a rise in smart innovative technologies to complement spatial and temporal information in new urban design models. Remote sensing-based Earth-observations provide critical information to close the gaps between real and virtual models of urban developments. Remote sensing, itself, has rapidly evolved since the launch of the first Earth-observation satellite, Landsat, in 1972. Technological advancements over the years have gradually improved the ground resolution of satellite images, from 80 m in the 1970s to 0.3 m in the 2020s. Apart from the ground resolution, improvements have been made in many other aspects of satellite remote sensing. Also, the method and techniques of information extraction have advanced. However, to understand the latest developments and scope of information extraction, it is important to understand background information and major techniques of image processing. This chapter briefly describes the history of optical remote sensing, the basic operation of satellite image processing, advanced methods of object extraction for modern urban designs, various applications of remote sensing in urban or peri-urban settings, and future satellite missions and directions of urban remote sensing.

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Comparative Study of Water-Body Information Extraction Methods Based on Electronic Sensing Image

Advances in Mechanical and Electronic Engineering - Lecture Notes in Electrical Engineering ◽

10.1007/978-3-642-31528-2_52 ◽

2013 ◽

pp. 331-336 ◽

Cited By ~ 4

Author(s):

Xiumei Li ◽

Xianbin Liu ◽

Lina Liu ◽

Kun Xue

Keyword(s):

Comparative Study ◽

Information Extraction ◽

Water Body ◽

Extraction Methods ◽

Electronic Sensing

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Contenido y calidad de las imágenes de observación terrestre

Revista ECIPeru ◽

10.33017/reveciperu2012.0015/ ◽

2019 ◽

pp. 15-21

Keyword(s):

Remote Sensing ◽

Image Quality ◽

Information Extraction ◽

Satellite Images ◽

Satellite Image ◽

La Paz ◽

Sensing System ◽

Manual Intervention ◽

Shape Structure ◽

Important Amount

Contenido y calidad de las imágenes de observación terrestre Earth observation image information content and quality Avid Roman-Gonzalez, Natalia Indira Vargas-Cuentas TELECOM ParisTech, 46 rue Barrault, 75013 – Paris, Francia Escuela Militar de Ingeniería – EMI, La Paz, Bolivia DOI: https://doi.org/10.33017/RevECIPeru2012.0015/ Resumen En el presente artículo describiremos la extracción de información de imágenes satelitales y la importancia de la calidad de las imágenes satelitales. Indagaremos con más detalle en el ámbito de los artefactos y su influencia en la extracción de información de las imágenes satelitales. En un sistema de teledetección, si bien, las imágenes son muy importantes, pero lo más importante es la información que podemos extraer de ellas para interpretar y aplicar esta información en diferentes campos. En ese sentido, la calidad de imagen juega un papel importante. Si queremos obtener la mayor e importante cantidad de información de una imagen, es necesario que la imagen tenga una buena calidad. El principal objetivo de cualquier sistema de teledetección es el uso de la información que se puede extraer de las imágenes, esto incluye la detección, medición, identificación e interpretación de diferentes objetivos de interés. Los objetivos de interés en imágenes de teledetección pueden ser cualquier característica, objeto, textura, forma, estructura, espectro o cobertura superficial que están en la imagen. El proceso de un sistema de teledetección y análisis puede ser realizado manualmente o de manera automática, en realidad, hay muchos grupos de investigación que desarrollan diferentes herramientas para detectar, identificar, interpretar y extraer información de los objetivos de interés sin intervención manual de un intérprete humano. Descriptores: teledetección, imágenes satelitales, detección de artefactos, calidad de las imágenes. Abstract In this article we will describe the information extraction from satellite image, the importance of image quality in satellite image. In this paper we will study in more detail the artifacts and their influence on the information extraction from satellite images. In a remote sensing system, although, the images are very important, but more important is the information that we can extract from them to interpret and apply this information in different fields. In this sense, the image quality plays an important role. If we want to get the biggest and most important amount of information from the image, we need to have a good image quality. The main objective of any remote sensing system is the use of information that we can extract from the images, this includes detection, measurement, identification and interpretation of different targets. Targets in remote sensing images may be any feature, object, texture, shape, structure, spectrum or land covers which are in the image. Remote sensing process and analysis could be performed manually or automatically, actually, there are many research groups that develop different tools for detect, identify, extract information and interpret targets without manual intervention by a human interpreter. Keywords: remote sensing, satellite images, artifacts detection, image quality.

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A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach

Remote Sensing ◽

10.3390/rs12132118 ◽

2020 ◽

Vol 12 (13) ◽

pp. 2118

Author(s):

Bos Debusscher ◽

Lisa Landuyt ◽

Frieke Van Coillie

Keyword(s):

Water Body ◽

Satellite Image ◽

Mapping Unit ◽

Emergency Relief ◽

Temporal Behaviour ◽

Global Variation ◽

Object Based ◽

Spatio Temporal ◽

Radar Satellite ◽

Flood Dynamics

Insights into flood dynamics, rather than solely flood extent, are critical for effective flood disaster management, in particular in the context of emergency relief and damage assessment. Although flood dynamics provide insight in the spatio-temporal behaviour of a flood event, to date operational visualization tools are scarce or even non-existent. In this letter, we distil a flood dynamics map from a radar satellite image time series (SITS). For this, we have upscaled and refined an existing design that was originally developed on a small area, describing flood dynamics using an object-based approach and a graph-based representation. Two case studies are used to demonstrate the operational value of this method by visualizing flood dynamics which are not visible on regular flood extent maps. Delineated water bodies are grouped into graphs according to their spatial overlap on consecutive timesteps. Differences in area and backscatter are used to quantify the amount of variation, resulting in a global variation map and a temporal profile for each water body, visually describing the evolution of the backscatter and number of polygons that make up the water body. The process of upscaling led us to applying a different water delineation approach, a different way of ensuring the minimal mapping unit and an increased code efficiency. The framework delivers a new way of visualizing floods, which is straightforward and efficient. Produced global variation maps can be applied in a context of data assimilation and disaster impact management.

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Design of image processing technique in digital enhancement application

International Journal of Advances in Scientific Research ◽

10.7439/ijasr.v1i8.2463 ◽

2015 ◽

Vol 1 (8) ◽

pp. 340

Author(s):

Bhubneshwar Sharma ◽

Jyoti Dadwal

Keyword(s):

Image Processing ◽

Land Cover ◽

Information Extraction ◽

Digital Image ◽

Visual Analysis ◽

Satellite Image ◽

Image Data ◽

Image Processing Technique ◽

Geometric Distortion ◽

Satellite Image Processing

This paper describes the basic technological aspects of Digital Image Processing with special reference to satellite image processing. Basically, all satellite image-processing operations can be grouped into three categories: Image Rectification and Restoration, Enhancement and Information Extraction. The former deals with initial processing of raw image data to correct for geometric distortion, to calibrate the data radio metrically and to eliminate noise present in the data. The enhancement procedures are applied to image data in order to effectively display the data for subsequent visual interpretation. It involves techniques for increasing the visual distinction between features in a scene. The objective of the information extraction operations is to replace visual analysis of the image data with quantitative techniques for automating the identification of features in a scene. This involves the analysis of multispectral image data and the application of statistically based decision rules for determining the land cover identity of each pixel in an image. The intent of classification process is to categorize all pixels in a digital image into one of several land cover classes or themes. This classified data may be used to produce thematic maps of the land cover present in an image.

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