Simulating rainfall, water evaporation and groundwater flow in three-dimensional satellite images with cellular automata

Abstract Remote sensing has been used in numerous environmental simulations with the aim of solving and improving many different kinds of problems, e.g., meteorology applications, soil quality studies, water resource exploration, and environmental protection. Besides, cellular automata have been widely used in the field of remote sensing for simulating natural phenomena over two-dimensional satellite images. However, simulations on Digital Elevation Models (DEM), or three-dimensional (3D) satellite images, are scarce. This paper presents a study of modeling and simulation of the weather phenomena of rainfall, water evaporation and groundwater flow in 3D satellite images through a new algorithm, developed by the authors, named RACA (RAinfall with Cellular Automata). The purpose of RACA is to obtain, from the simulation, numerical and 3D results related to the total cumulative flow and maximum level of water that allow us to make decisions on important issues such as analyzing how climate change will affect the water level in a particular area, estimating the future water supply of a population, establishing future construction projects and urban planning away from locations with high probability of flooding, or preventing the destruction of property and human life from future natural disasters in urban areas with probability of flooding.

[1]  Parvatham Venkatachalam,et al.  Neural Network Based Cellular Automata Model for Dynamic Spatial Modeling in GIS , 2009, ICCSA.

[2]  Jarkko Kari,et al.  Theory of cellular automata: A survey , 2005, Theor. Comput. Sci..

[3]  J. Bear Dynamics of Fluids in Porous Media , 1975 .

[4]  Yunjie Zhang,et al.  Image Classification Method Based on Cellular Automata Transforms , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[5]  Francesco Dottori,et al.  Developments of a flood inundation model based on the cellular automata approach: Testing different methods to improve model performance , 2011 .

[6]  H. Balzter,et al.  Cellular automata models for vegetation dynamics , 1998 .

[7]  E. C. Barrett,et al.  Introduction to Environmental Remote Sensing. , 1978 .

[8]  Marcelo J. Vénere,et al.  Cellular automata algorithm for simulation of surface flows in large plains , 2007, Simul. Model. Pract. Theory.

[9]  Bastien Chopard,et al.  A Cellular Automata Model for Species Competition and Evolution , 2006, ACRI.

[10]  Anthony Gar-On Yeh,et al.  Neural-network-based cellular automata for simulating multiple land use changes using GIS , 2002, Int. J. Geogr. Inf. Sci..

[11]  Guido Visconti,et al.  Cellular automata algorithms for drainage network extraction and rainfall data assimilation , 2007 .

[12]  James Zijun Wang,et al.  Contextual and Hierarchical Classification of Satellite Images Based on Cellular Automata , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Ioannis G. Karafyllidis,et al.  A model for predicting forest fire spreading using cellular automata , 1997 .

[14]  R. Colwell,et al.  Climate and infectious disease: use of remote sensing for detection of Vibrio cholerae by indirect measurement. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Witold Dzwinel A Cellular Automata Model of Population Infected by Periodic Plague , 2004, ACRI.

[16]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[17]  Saturnino Leguizamón Dicyt,et al.  MODELING LAND FEATURES DYNAMICS BY USING CELLULAR AUTOMATA TECHNIQUES , 2006 .

[18]  Ian Masser,et al.  Cellular Automata Based Temporal Process Understanding of Urban Growth , 2002, ACRI.

[19]  S. D. Gregorio,et al.  A Cellular Automata model for soil erosion by water , 2001 .

[20]  José Alí Moreno,et al.  Cellular Automata and Its Application to the Modeling of Vehicular Traffic in the City of Caracas , 2006, ACRI.

[21]  Rocco Rongo,et al.  An Evolutionary Approach for Modelling Lava Flows Through Cellular Automata , 2004, ACRI.

[22]  Nuria Gómez Blas,et al.  SELF-ORGANIZING MAP AND CELLULAR AUTOMATA COMBINED TECHNIQUE FOR ADVANCED MESH GENERATION IN URBAN AND ARCHITECTURAL DESIGN , 2007 .

[23]  E. Chuvieco Fundamentals of Satellite Remote Sensing , 2009 .

[24]  L. Matteo,et al.  Studio idrogeologico e climatico del bacino del lago di Montedoglio (F. Tevere, Arezzo - Italia Centrale) , 2006 .

[25]  P. Kanongchaiyos,et al.  3D cloud animation using CA based method , 2009, 2009 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS).

[26]  Maria Vittoria Avolio,et al.  Development and Calibration of a Preliminary Cellular Automata Model for Snow Avalanches , 2010, ACRI.

[27]  Jean François Santucci,et al.  Modelling and simulation of ecological propagation processes: application to fire spread , 2005, Environ. Model. Softw..

[28]  Luis Iribarne,et al.  Characterization of Texture in Images by Using a Cellular Automata Approach , 2010, WSKS.

[29]  Sarah Theiss,et al.  Physical Principles Of Remote Sensing , 2016 .