In 2005, Hurricane Katrina’s diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, field data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts.

Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.

<p>Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.</p><p> </p>

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-04-17T16:12:32Z No. of bitstreams: 1 Arquivototal.pdf: 5868651 bytes, checksum: e5d4ddb02a065600f83257ded96722d7 (MD5) / Made available in DSpace on 2018-04-17T16:12:32Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 5868651 bytes, checksum: e5d4ddb02a065600f83257ded96722d7 (MD5) Previous issue date: 2015-03-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The practices of soil usage and occupation generate severe deterioration processes and in semiarid areas may result in desertification. In Paraiba, one of the areas representing this process is the one named “Cariris Velhos”. Through a multitemporal analysis, aided by statistical techniques and geotechnologies, it was possible to carry out some analysis and to diagnose the desertification state. Descriptive analysis, non-parametric test and multivariate statistics techniques were used. The precipitation was used and revealed three important patterns that explain about 70% of data variability, exposing how the rainfall occurred in the years of the images, making visible the rainy occurred, drought and transitioning periods. It was possible to confirm the edaphoclimatic frailty existent and the strong correlation with the climate anomalies (El Niño and La Niña) caused by meteorological systems. The second aspect to be analyzed was the vegetation coverage, defined in different strata and surface temperature. Three timed clippings were selected to compose these aspects: images from the 80’s (1989, 1985), from the 90’s (1990 and 1995) and of the 2000 years (2004,2005 and 2007). The images processing was done with part of algorithm SEBAL which were determined SAVI, IAF and Surface Temperature. SAVI and IAF were obtained, however, owing few studies with IAF for semiarid was decided to used. The results have shown that the vegetation strata diminished gradually, from a moderate stage to a severe one, with coefficient of variation (56%, 78,75% e 84%) unrepresentative, proving the diversity of landscapes. A significant amount of municipalities, on the last clipping, already presented, in its majority, more than 50% of values of the pixels presented in the classes of exposed soil, that is, with accentuated deterioration, proving strong evidence of desertification. With the deforestation, the surface temperature increased significantly configuring a higher number of pixels presented in classes superior to 30ºC. This factor, allied to the rainfall, hampers the development and spreading of species, since seed dispersal is by anemochory, diminishing the biodiversity of the caatinga. Concerning the agricultural, economic and social aspects, three profiles were revealed for each clipping, showing the most important indicators on each one. With this, it was observed that between 1980 and 1995, the population was more dependent of the land, in a way that when there was a worsening in the physical plan, a diminishing in the rainfall, the production also diminished, directly affecting social and economically the population. Between 2000 and 2010, the governmental incentives contribute to an improvement of these aspects so that they did not contribute, not directly, for the process of desertification, configuring a smaller impact (weight) on the analysis. In this case, the deterioration is originated from the agricultural aspect, being an example the incentive to the goatrearing and wood extraction to the plaster polo of Pernambuco in some municipalities of the “Cariris Velhos” region. / As práticas de uso e ocupação do solo geram processos de degradação intensa e em regiões semiáridas podem culminar na desertificação. Na Paraíba, uma das áreas representativas desse processo é a delimitação denominada de Cariris Velhos. Através de uma análise multitemporal, com o auxílio de algumas técnicas estatísticas e das geotecnologias, foi possível realizar algumas análises e diagnosticar o quadro da desertificação. Foram utilizadas análises descritivas, teste não paramétrico e a técnica da estatística multivariada: análise fatorial em componentes principais. Utilizou-se a precipitação pluviométrica que revelou três padrões importantes que explicaram cerca de 70% da variabilidade dos dados cada, expondo a forma como a chuva ocorreu para os anos das imagens, tornando visíveis períodos chuvosos, secos e de transição. Pôde-se comprovar a fragilidade edafoclimática existente e a forte relação com as anomalias climáticas (El Niño e La Niña) provocadas por sistemas meteorológicos. O segundo aspecto a ser analisado foi a cobertura vegetal, definida em diferentes estratos, e a temperatura da superfície. Foram selecionados três recortes temporais para compor esses aspectos: imagens da década de 80 (1989, 1985), da década de 90 (1990 e1995) e dos anos 2000 (2004, 2005 e 2007). O processamento das imagens foi feito com parte do algoritmo SEBAL onde foram determinados o SAVI, o IAF e a Temperatura da Superfície. Foram gerados o SAVI e IAF, entretanto, devido a poucos trabalhos realizados com o IAF para o semiárido considerou-se utilizá-lo. Os resultados mostraram que os estratos de vegetação diminuíram gradativamente, passando para um estágio moderado para muito grave, com coeficientes de variação (56%, 78,75% e 84%) pouco representativos, comprovando a diversidade de paisagens. Boa parte dos municípios, no último recorte, já apresentava, em sua maioria, mais de 50% dos valores dos pixels presentes nas classes de solo exposto, isto é, com degradação acentuada, comprovando forte evidencia de desertificação. Com o desmatamento, a temperatura da superfície aumentou significativamente passando a configurar um maior número de pixels presentes em classes superiores aos 30ºC. Este fator, aliado ao quadro de chuvas, dificulta o desenvolvimento e a propagação de espécies, uma vez que a dispersão das sementes se dá por anemocoria, o que diminui a biodiversidade da caatinga. Em relação aos aspectos agropecuários, econômicos e socais, foram revelados três perfis, para cada recorte, mostrando os indicadores mais importantes em cada um. Com isso, observou-se que entre 1980 e 1995, a população dependia mais da terra, de forma que uma piora no quadro físico, na diminuição no quadro de chuvas, diminuía a produção, refletindo diretamente no econômico e no social e deste modo na população. Entre 2000 e 2010, os incentivos governamentais contribuíram para a melhora desses aspectos de forma que eles passaram a não contribuir, diretamente, para o processo de desertificação, configurando um menor impacto (peso) na análise. Neste caso, a degradação é mais proveniente do aspecto agropecuário, tendo como exemplo o incentivo a caprinocultura e a extração da madeira para o polo gesseiro de Pernambuco, em alguns municípios dos Cariris Velhos.

There has been rapid change in the landcover/landuse in the Mekong delta, Viet Nam. The landcover/landuse has changed very fast due to intense population pressure, agriculture/aquaculture farming and timber collection in the coastal areas of the delta. The changing landuse pattern in the coastal areas of the delta is threatened to be flooded by sea level rise; sea level is expected to rise 33 cm until 2050; 45 cm until 2070 and 1 m until 2100. The coastline along the eastern Mekong delta has never been static, but the loss of mangrove forests along the coast has intensified coastline change. The objective of the present study is to map the changes in landcover/landuse along the eastern coast of the Mekong delta; and to detect the changes in position of the eastern coastline over the time period from 1989 to 2002.To detect changes in landuse, two satellite images of the same season, acquired by the TM sensor of Landsat 5 and the ETM+ sensor of Landsat 7 were used. The TM image was acquired on January 16, 1989 and ETM+ image was acquired on February 13, 2002. The landcover/landuse classes selected for the study are water, forest, open vegetation, soil and shrimp farms. Image differencing and post classification comparison are used to detect the changes between two time periods. Image to image correction technique is used to align satellite images. Maximum likelihood supervised classification technique is used to classify images. The result of the classification consists of five classes for 1989 and 2002, respectively. Overall accuracies of 87.5% and 86.8%, with kappa values of 0.85 and 0.84 are obtained for landuse 1989 and landuse 2002, respectively. The overall accuracy for the change map is 82% with kappa value 0.80. Post classification comparison is carried out in this study based on the supervised classification results. According to the results obtained from the post classification comparison, a significant decrease of 48% in forest and a significant increase of 74% in open vegetation and 21% in shrimp farms area observed over the entire study area. The coastline obtained by the combination of histogram thresholding and band ratio showed an overall advancement towards the South China Sea. The results showed that new land patches emerged along the eastern coast. The amount of new land patches appeared along the coast of the Mekong delta is approximately 2% of the entire study area.

Indiana University-Purdue University Indianapolis (IUPUI) / Over the past two decades, northern parts of the United States have experienced extreme heat conditions. Some of the notable heat wave impacts have occurred in Chicago in 1995 with over 600 reported deaths and in Philadelphia in 1993 with over 180 reported deaths. The distribution of extreme heat events in Indianapolis has varied since the year 2000. The Urban Heat Island effect has caused the temperatures to rise unusually high during the summer months. Although the number of reported deaths in Indianapolis is smaller when compared to Chicago and Philadelphia, the heat wave in the year 2010 affected primarily the vulnerable population comprised of the elderly and the lower socio-economic groups. Studying the spatial distribution of high temperatures in the vulnerable areas helps determine not only the extent of the heat affected areas, but also to devise strategies and methods to plan, mitigate, and tackle extreme heat. In addition, examining spatial patterns of vulnerability can aid in development of a heat warning system to alert the populations at risk during extreme heat events. This study focuses on the qualitative and quantitative methods used to measure extreme heat events. Land surface temperatures obtained from the Landsat TM images provide useful means by which the spatial distribution of temperatures can be studied in relation to the temporal changes and socioeconomic vulnerability. The percentile method used, helps to determine the vulnerable areas and their extents. The maximum temperatures measured using LST conversion of the original digital number values of the Landsat TM images is reliable in terms of identifying the heat-affected regions.