Competitiveness factors : a study of the real estate market in China

The execution of 'macro-adjustment' policies by the central government to cool down the overheated real estate market in the past few years has created an unfavourable operating environment for real estate developers in Mainland China. Developers need to rethink their business model and create a new form of competitive advantage in order to survive. Despite this, research into the factors that influence the competitiveness of the real estate market in China has been limited. Therefore, a survey of 58 real estate actitioners, experts and academics in China was conducted to probe opinion on the factors that influence competitiveness in real estate firms in China. Survey results suggest that the developer's financial competency, market coverage and management competencies are vital to its competitiveness. Findings also highlight the importance of industry ecognition/award, share in different types of property sales/development projects, profit after tax, growth rate of their securities price, and diversification of R&D in reflecting the competitiveness of real estate developers in China. The findings provide an insight into the factors that influence competitiveness in China's real estate market and also assist practitioners to formulate competitiveness improvement strategies.

Methods in general model localization

The aim of this study was to evaluate and test methods which could improve local estimates of a general model fitted to a large area. In the first three studies, the intention was to divide the study area into sub-areas that were as homogeneous as possible according to the residuals of the general model, and in the fourth study, the localization was based on the local neighbourhood. According to spatial autocorrelation (SA), points closer together in space are more likely to be similar than those that are farther apart. Local indicators of SA (LISAs) test the similarity of data clusters. A LISA was calculated for every observation in the dataset, and together with the spatial position and residual of the global model, the data were segmented using two different methods: classification and regression trees (CART) and the multiresolution segmentation algorithm (MS) of the eCognition software. The general model was then re-fitted (localized) to the formed sub-areas. In kriging, the SA is modelled with a variogram, and the spatial correlation is a function of the distance (and direction) between the observation and the point of calculation. A general trend is corrected with the residual information of the neighbourhood, whose size is controlled by the number of the nearest neighbours. Nearness is measured as Euclidian distance. With all methods, the root mean square errors (RMSEs) were lower, but with the methods that segmented the study area, the deviance in single localized RMSEs was wide. Therefore, an element capable of controlling the division or localization should be included in the segmentation-localization process. Kriging, on the other hand, provided stable estimates when the number of neighbours was sufficient (over 30), thus offering the best potential for further studies. Even CART could be combined with kriging or non-parametric methods, such as most similar neighbours (MSN).

Análise comparada da segmentação e classificação orientada por objectos de uma imagem de alta resolução WORLDVIEW-2

Dissertação de Mestrado em Gestão do Território, Especialização em Detecção Remota e Sistemas de Informação Geográfica

Participação popular versus movimentos comunitarios : o caso de Vila Velha (ES), de 1983 a 1992

Análise qualitativa do processo de participação popular ocorrido em Vila Velha (ES) de 1983 a 1992) baseada em entrevistas realizadas com os quatro Prefeitos Municipais desse periodo. bem como com os quatro diretores mais antiqos do Conselho Comunitário entidade federativa representante dos movimentos comunitários do municipio. Os critérios uti1izados na análise foram a disseminação das in formações a cerca da gestão municipal, o tipo de relação estabelecida entre esses gestores e os movimentos comunitários, a razão entre as propostas planejadas coletivamente e as propostas imp1ementadas pela administracão municipal, e os obietivos explicitos e implicitos do Prefeito ao implementar o processo participativo. A reflexão apresentada tenta desmistificar os processos participativos encaminhados no municipio tendo em vista que a prática ao longo dos dez anos estudados mais desmobilizou do que ampliou a participar.;:~o da sociedade, a pesar de reconhecer a contribuir.;:~o de cada um dos qestores do per iodo p·3ra. o avanr.;:o da orqanizaç~o dess a sociedade.

Classificação de áreas de favelas a partir de imagens IKONOS: Viabilidade de uso de uma abordagem orientada a objeto

The growth of large cities is usually accelerated and disorganized, which causes social, economical and infrastructural conflicts and frequently, occupation in illegal areas. For a better administration of these areas, the public manager needs information about their location. This information can be obtained through land utilization and land cover maps, where orbital images of remote sensing are used as one of the most traditional sources of data. In this context, the present work tested the applicability of the object-based classification to categorize two slum areas, taking into account the structure of the streets, size of the huts, distance between the houses, among other parameters. These area combinations of physical aspects were analyzed using the image IKONOS II and the software eCognition. Slum areas tend to be, to the contrary of the planned areas, disarranged, with narrow streets, small houses built with a variety of materials and without definition of blocks. The results of land cover classification for slum areas are encouraging because they are accurate and little ambiguous in the classification process. Thus, it would allow its utilization by urban managers.

Geoprocessamento aplicado ao mapeamento do índice de vulnerabilidade DRASTIC, no Sistema Aquífero Guarani em Ribeirão Bonito - SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação do método de classificação baseada no objeto em imagens de alta resolução espacial aplicado para o monitoramento de faixa de dutos: estudo de caso no entorno da refinaria de Capuava em Mauá - SP

The metropolitan region of São Paulo is the most populous of the country, this happens because of its great importance in the national economy and the job opportunities that are offered to the population. These factors result in intense population growth and urban expansion, reaching some non-habitable places of the metropolis, as areas of pipelines, which are very important for the transportation of natural gas, oil and its derivatives. Before the population growth of the region, these sites were unoccupied, do not presenting problems for the population. However, with the disorderly occupation is generated great anthropogenic pressure on the pipeline stitches, causing risks to people who are around them. Therefore it is extremely important to monitor the strip of pipelines through products and techniques of remote sensing and geoprocessing, enabling, through high spatial resolution images, identification of objects or phenomena that occur on Earth's surface that can alter the functioning and safety of pipelines. Therefore, this study aims to monitor a stretch of the area of the pipeline mesh GASPAL/OSVAT and Capuava Refinery (RECAP), located on the outskirts of the metropolitan area of São Paulo in the city of Mauá, who suffer great human pressure, proving thus the techniques of remote sensing and geographic information system (GIS) as effective tools for monitoring phenomena occurred in urban areas of great complexity. The monitoring was done by object-based classification applied in orbital images Ikonos II and RapidEye, of high spatial resolution and, image processing, detection of objects, segmentation, classification and editing were developed through the eCognition and ArcGis softwares. To determine the statistical accuracy of the mapping of the land cover of the stretch of pipeline in Maua, the results were analyzed by error matrix... (Complete abstract click electronic access below)

Spatial distribution and morphometric analysis of thermokarst lakes and other water bodies : Case study from the sporadic permafrost region, Tavvavuoma, Sweden

Projected air and ground temperatures are expected to be higher in Arctic and sub-Arcticlatitudes and with temperatures already close to the limit where permafrost can exist,resistance against degradation is low. With thawing permafrost, the landscape is modifiedwith depression in which thermokarst lakes emerge. In permafrost soils a considerableamount of soil organic carbon is stored, with the potential of altering climate even furtherif expansion and formation of new thermokarst lakes emerge, as decay releasesgreenhouse gases (C02 and CH4) to the atmosphere. Analyzing the spatial distribution andmorphometry over time of thermokarst lakes and other water bodies, is of importance inaccurately predict carbon budget and feedback mechanisms, as well as to assess futurelandscape layout and these features interaction. Different types of high-spatial resolutionaerial and satellite imageries from 1963, 1975, 2003, 2010 and 2015, were used in bothpre- and post-classification change detection analyses. Using object oriented segmentationin eCognition combined with manual adjustments, resulted in digitalized water bodies>28m2 from which direction of change and morphometric values were extracted. Thequantity of thermokarst lakes and other water bodies was in 1963 n=92, with succeedingyears as a trend decreased in numbers, until 2010-2015 when eleven water bodies wereadded in 2015 (n=74 to n=85). In 1963-2003, area of these water bodies decreased with50 651m2 (189 446-138 795m2) and continued to decrease in 2003-2015 ending at 129337m2. Limnicity decreased from 19.9% in 1963 to 14.6% in 2003 (-5.3%). In 2010 and2015 13.7-13.6%. The late increase in water bodies differs from an earlier hypothesis thatsporadic permafrost regions experience decrease in both area and quantity of thermokarstlakes and water bodies. During 1963-2015, land gain has been in dominance of the ratiobetween the two competing processes of expansion and drainage. In 1963-1975, 55/45%,followed by 90/10% in 1975-2003. After major drainage events, land loss increased to62/38% in 2010-2015. Drainage and infilling rates, calculated for 15 shorelines werevaried across both landscape and parts of shorelines, with in average 0.17/0.15/0.14m/yr.Except for 1963-1975 when rate of change in average was in opposite direction (-0.09m/yr.), likely due to evident expansion of a large thermokarst lake. Using a squaregrid, distribution of water bodies was determined, with an indistinct cluster located in NEand central parts. Especially for water bodies <250m2, which is the dominant area classthroughout 1963-2015 ranging from n=39-51. With a heterogeneous composition of bothsmall and large thermokarst lakes, and with both expansion and drainage altering thelandscape in Tavvavuoma, both positive and negative climate feedback mechanisms are inplay - given that sporadic permafrost still exist.

Apports de la texture multibande dans la classification orientée-objets d'images multisources (optique et radar).

Résumé : La texture dispose d’un bon potentiel discriminant qui complète celui des paramètres radiométriques dans le processus de classification d’image. L’indice Compact Texture Unit (CTU) multibande, récemment mis au point par Safia et He (2014), permet d’extraire la texture sur plusieurs bandes à la fois, donc de tirer parti d’un surcroît d’informations ignorées jusqu’ici dans les analyses texturales traditionnelles : l’interdépendance entre les bandes. Toutefois, ce nouvel outil n’a pas encore été testé sur des images multisources, usage qui peut se révéler d’un grand intérêt quand on considère par exemple toute la richesse texturale que le radar peut apporter en supplément à l’optique, par combinaison de données. Cette étude permet donc de compléter la validation initiée par Safia (2014) en appliquant le CTU sur un couple d’images optique-radar. L’analyse texturale de ce jeu de données a permis de générer une image en « texture couleur ». Ces bandes texturales créées sont à nouveau combinées avec les bandes initiales de l’optique, avant d’être intégrées dans un processus de classification de l’occupation du sol sous eCognition. Le même procédé de classification (mais sans CTU) est appliqué respectivement sur : la donnée Optique, puis le Radar, et enfin la combinaison Optique-Radar. Par ailleurs le CTU généré sur l’Optique uniquement (monosource) est comparé à celui dérivant du couple Optique-Radar (multisources). L’analyse du pouvoir séparateur de ces différentes bandes à partir d’histogrammes, ainsi que l’outil matrice de confusion, permet de confronter la performance de ces différents cas de figure et paramètres utilisés. Ces éléments de comparaison présentent le CTU, et notamment le CTU multisources, comme le critère le plus discriminant ; sa présence rajoute de la variabilité dans l’image permettant ainsi une segmentation plus nette, une classification à la fois plus détaillée et plus performante. En effet, la précision passe de 0.5 avec l’image Optique à 0.74 pour l’image CTU, alors que la confusion diminue en passant de 0.30 (dans l’Optique) à 0.02 (dans le CTU).