DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA
The analysis of dynamical models for prediction and geosimulation using the information extracted from a geographical region processed from the data provided by multispectral remote sensing systems provides useful information for urban planning and resource management. However, several topics of int...
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doaj-e67ca139fbcc4c4488aa13c8168958ad2020-11-25T01:49:58ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502018-09-01IV-421321910.5194/isprs-annals-IV-4-213-2018DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATAI. E. Villalon-Turrubiates0Instituto Tecnológico y de Estudios Superiores de Occidente (ITESO), Universidad Jesuita de Guadalajara, Periférico Sur Manuel Gómez Morín 8585, 45604 Tlaquepaque Jalisco, MexicoThe analysis of dynamical models for prediction and geosimulation using the information extracted from a geographical region processed from the data provided by multispectral remote sensing systems provides useful information for urban planning and resource management. However, several topics of interest on this particular matter are still to be properly studied. Using the remote sensing data that has been extracted from multispectral images from a particular geographic region in discrete time, its dynamic study is performed in both, spatial resolution and time evolution, in order to obtain the dynamical model of the physical variables and the evolutionary information about the data. This provides a background for understanding the future trends in development of the dynamics inherent in the multispectral and high-resolution images. This proposition is performed via an intelligent computational paradigm based on the use of dynamical filtering techniques modified to enhance the quality of reconstruction of the data extracted from multispectral remote sensing images and using high-performance computational techniques to unify the available data scheme with its dynamic analysis and, therefore, provide a behavioral model of the sensed data.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4/213/2018/isprs-annals-IV-4-213-2018.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
I. E. Villalon-Turrubiates |
spellingShingle |
I. E. Villalon-Turrubiates DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
I. E. Villalon-Turrubiates |
author_sort |
I. E. Villalon-Turrubiates |
title |
DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA |
title_short |
DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA |
title_full |
DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA |
title_fullStr |
DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA |
title_full_unstemmed |
DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA |
title_sort |
dynamical prediction technique for geosimulation using multispectral remote sensing data |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2018-09-01 |
description |
The analysis of dynamical models for prediction and geosimulation using the information extracted from a geographical region processed from the data provided by multispectral remote sensing systems provides useful information for urban planning and resource management. However, several topics of interest on this particular matter are still to be properly studied. Using the remote sensing data that has been extracted from multispectral images from a particular geographic region in discrete time, its dynamic study is performed in both, spatial resolution and time evolution, in order to obtain the dynamical model of the physical variables and the evolutionary information about the data. This provides a background for understanding the future trends in development of the dynamics inherent in the multispectral and high-resolution images. This proposition is performed via an intelligent computational paradigm based on the use of dynamical filtering techniques modified to enhance the quality of reconstruction of the data extracted from multispectral remote sensing images and using high-performance computational techniques to unify the available data scheme with its dynamic analysis and, therefore, provide a behavioral model of the sensed data. |
url |
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4/213/2018/isprs-annals-IV-4-213-2018.pdf |
work_keys_str_mv |
AT ievillalonturrubiates dynamicalpredictiontechniqueforgeosimulationusingmultispectralremotesensingdata |
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1725003622096306176 |