Replication of Spatio-temporal Land Use Patterns at Three Levels of Aggregation by an Urban Cellular Automata

Author(s):  
Charles Dietzel ◽  
Keith C. Clarke
Author(s):  
Matt Grove

This chapter aims to summarize the results of recent research producing estimates of hominin range areas, population sizes, and land use patterns based on archaeological data. Estimates of such variables are essential to any geographic or demographic discussion of human evolution, yet at present no generally applicable quantitative method is available to link them to the often abundant data of the archaeological record. Such data offer a unique window onto the patterns of adaptation characterizing prehistoric human populations, and developing a generic method to describe trajectories of change will allow researchers to compare range areas, population sizes and land use patterns between different regions and periods from throughout the vast spatio-temporal range of human evolution. The discussion gives particular emphasis to estimating a trajectory of group size through time from shortly after 2 million years ago until approximately 14,000 years ago.


2020 ◽  
Vol 15 (02) ◽  
pp. 263-290
Author(s):  
Jean Jesus Ilsuk da Silva ◽  
Sony Cortese Caneparo

O município de Pontal do Paraná está localizado no litoral do estado do Paraná, na região sul do Brasil. Em 1995, foi aí instalado o Porto de Pontal Importação e Exportação LTDA e, em 2013, foi aprovada a licença ambiental para a construção de um complexo portuário neste município. Tal obra se apresenta como um desafio, devido ao potencial que o mesmo apresenta em produzir impactos ambientais e mudanças nos padrões de uso da terra.Essa pesquisa objetiva analisar as mudanças espaciais que podem ocorrer futuramente no uso da terra e na cobertura vegetal em Pontal do Paraná (2032), em virtude da instalação deste complexo. Foram utilizadas rotinas de sistemas de informações geográficas, inseridas no IDRISI TAIGA, da Clark University, dentre elas se destacam a  Cadeia de Markov e os Autômatos Celulares para a geração do cenário futuro. O resultado da modelagem preditiva (2032), em função da expansão portuária, foi um aumento nas áreas urbanas, fator que poderia impactar diretamente as áreas de Restingas, de Mangues e da Floresta Ombrófila Densa. O presente trabalho revelou que o uso da modelagem preditiva pode ser uma ferramenta bastante útil para a avaliação e interpretação de cenários futuros. Palavras-chave: Modelagem Preditiva; Ambiente Litorâneo; Dinâmica Espaço-Temporal.   ANALYSIS OF SPACE VARIATIONS IN THE MUNICIPALITY OF PONTAL DO PARANÁ (PARANÁ - BRAZIL), BETWEEN 1980 AND 2032 ARISING FROM THE PORT COMPLEX INSTALLATION Abstract The city of Pontal do Paraná is located on the coast of the state of Paraná, in the southern region of Brazil. In 1995, the Port of Pontal Importação e Exportação Company was installed there, and in 2013, the environmental license was approved for the installation of a port complex in this municipality. This Port presents itself as a challenge, due to its potential in producing environmental impacts and changes in land use patterns. This research aims to analyze the spatial changes that may occur in the future of land use and vegetation cover of Pontal do Paraná (2032), due to the installation of this complex. Routines of geographic information systems, inserted in the IDRISI TAIGA, of Clark University, among them, the Markov Chain and the Cellular Automatics were used to generate the future scenario. The result of predictive modeling (2032), caused by the port expansion, was an increase in urban areas, a factor that could directly impact the areas of restingas,  mangroves, and the atlantic rainforest. The present study revealed that the use of predictive modeling can be a very useful tool for the evaluation and interpretation of future scenarios. Keywords: Predictive Modeling; Coastal Environment; Spatio-Temporal Dynamics.   ANÁLISIS DE LAS VARIACIONES ESPACIALES EN EL MUNICIPIO DE PONTAL DO PARANÁ (PARANÁ - BRASIL), ENTRE LOS AÑOS 1980 Y 2032 RESULTANTE DE LA INSTALACIÓN DEL COMPLEJO PORTUARIO Resumen El municipio de Pontal do Paraná está ubicado en la costa del estado de Paraná, en la región sur de Brasil. En 1995, se instaló el Puerto de Importación y Exportación de Pontal Ltd. y, en 2013, se aprobó el permiso ambiental para la construcción de un complejo portuario en este municipio. Esta obra se presenta como un desafío, debido a la posibilidad  de producir impactos ambientales y cambios en los patrones de uso de la tierra. El objetivo de este estudio es analizar los cambios espaciales que puedan ocurrir en el futuro uso de la tierra y la vegetación en el Pontal do Paraná (2032), debido a la instalación de este complejo. Las rutinas se utilizan sistemas de información geográfica, insertado en el IDRISI TAIGA, Clark University, entre ellos se encuentran la Cadena de Markov y Autómatas Celulares para la generación de escenarios futuros. Los resultados de la modelización predictiva (2032), dependiendo de la expansión de lo puerto, fue un aumento en las zonas urbanas, un factor que podría tener un impacto directo sobre las áreas de Restinga, Manglares y Bosque Ombrophilous Denso. El presente estudio demostró que el uso de modelado predictivo puede ser una herramienta muy útil para la evaluación e interpretación de escenarios futuros. Palabras clave: Modelado Predictivo; Costero; Dinámica Espacio-Temporal.


Energies ◽  
2015 ◽  
Vol 8 (5) ◽  
pp. 3882-3902 ◽  
Author(s):  
Yuanyuan Yang ◽  
Shuwen Zhang ◽  
Jiuchun Yang ◽  
Xiaoshi Xing ◽  
Dongyan Wang

2021 ◽  
Vol 13 (17) ◽  
pp. 9525
Author(s):  
René Ulloa-Espíndola ◽  
Susana Martín-Fernández

Rapid urban growth has historically led to changes in land use patterns and the degradation of natural resources and the urban environment. Uncontrolled growth of urban areas in the city of Quito has continued to the present day since 1960s, aggravated by illegal or irregular new settlements. The main objective of this paper is to generate spatial predictions of these types of urban settlements and land use changes in 2023, 2028 and 2038, applying the Dinamica EGO cellular automata and multivariable software. The study area was the Machachi Valley between the south of the city of Quito and the rural localities of Alóag and Machachi. The results demonstrate the accuracy of the model and its applicability, thanks to the use of 15 social, physical and climate predictors and the validation process. The analysis of the land use changes throughout the study area shows that urban land use will undergo the greatest net increase. Growth in the south of Quito is predicted to increase by as much as 35% between 2018 and 2038 where new highly vulnerable urban settlements can appear. Native forests in the Andes and forest plantations are expected to decline in the study area due to their substitution by shrub vegetation or agriculture and livestock land use. The implementation of policies to control the land market and protect natural areas could help to mitigate the continuous deterioration of urban and forest areas.


1993 ◽  
Vol 14 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Jordan E. Kerber

Selecting an effective archaeological survey takes careful consideration given the interaction of several variables, such as the survey's goals, nature of the data base, and budget constraints. This article provides justification for a “siteless survey” using evidence from a project on Potowomut Neck in Rhode Island whose objective was not to locate sites but to examine the distribution and density of prehistoric remains to test an hypothesis related to land use patterns. The survey strategy, random walk, was chosen because it possessed the advantages of probabilistic testing, as well as the ease of locating sample units. The results were within the limits of statistical validity and were found unable to reject the hypothesis. “Siteless survey” may be successfully applied in similar contexts where the distribution and density of materials, as opposed to ambiguously defined sites, are sought as evidence of land use patterns, in particular, and human adaptation, in general.


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