A B S T R A C TThe rapid development of the environment and urban planning are increasingly demanding of management, celerity, and readiness in solving difficulties. Considering the development in the environment, companies invest in technologies and information modelling; when the State administration adopts these, it can contribute to the improvement of the operation of several aspects, reflecting the social and environmental quality of the regions of interest. Taking into account The rapid dissemination of communication and the advancement of technology, this work aimed to analyze the concepts that approach the considerations of Building Information Modelling-BIM and City Information Modeling-CIM for cities, presenting their functionalities and benefits. The methodological procedures that conditioned the organization of the data presented here were fundamentally a bibliographical survey to select the literature that would compose the theoretical basis of this research. The conception of BIM and its benefits to the academic community, the revolutionary arrival of CIM and the contribution of these forms of modelling to the formation of sustainable cities are analyzed and discussed. It is concluded that the modelling of BIM and CIM and its vast and integrated database can provide several benefits to the design, engineering, architecture and related areas, assisting in the management of projects, observing the area available for construction and the natural resources of the region. It is possible to create cities in the sustainable model, potentializing energy generation, water and soil use, population transition/seasonality and reducing unnecessary costs.
The Chapadinha microregion, located in the eastern part of the state of Maranhão, Brazil, maintains a large agricultural production, especially soybeans, causing beyond largesse of the economy, which promotes a degradation of large areas of native forests. The analysis of space - temporal with remote sensing images can be a tool for understanding the area and possible decision making of allocated mandates. The objective of this study is to analyze spatial and temporal variation of the micro-Chapadinha, Maranhão, Brazil by remote sensing technique called Normalized Difference Vegetation Index - NDVI for the years 2007, 2010 and 2014. It is used Lands at 5 images - TM and 8 - OLI orbits 220 / 62-63 months of 22/07/2007, 15/08/2010 and 25/07/2014and it being applied processing equations of radiometric radiance, reflectance and NDVI. The NDVI for micro-Chapadinha vegetation indicated a fall of the years 2007 to 2010 and at the same time, an increase in agricultural activity; low NDVI areas that are not exposed in 2007 were observed in 2010, one of the causes of this advent can be the event El Niño in the Northeast. In 2014, vegetation indices showed high in much of the micro-region; the response of this increase may be the reaction of trees was once under water stress the great rainfall that year. The municipalities of Brejo, Milagres of Maranhão and Buriti are the most affected by farming, they still come extending and have propensities to leave the micro limits. Remote sensing responded with great efficiency, but the complexity of the natural environment make it necessary that there interconnections with other indices therefore resulting in a more efficient monitoring and analysis.
The Sobradinho reservoir provides support for economic and social development for the area. However, is importance for the monitoring of water resources obtain mechanisms to monitor and analyze their interactions. The Remote sensing and geoprocessing are as important for supporting and assessing, however, some data can be seen with information that runs away from reality. In this context, this work aims to observe and analyze the SRTM images for the Sobradinho reservoir. The methodogy includes the vectorization of the Landsat 5 image and acquisition of the the SRTM arc second, with resolution of 30 meters. We concluded that there is a possibility of presence of areas rich in materials from macrophytes, algae and suspended sediments, reflecting no increase in project flood quota, also known as maximorum, including measures of approximately 2,0 meters. The sinks can also be seen as reasons for this image error. Overall, as SRTM arc second images are of great reliability for the study area.
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