Quantifying the physical composition of urban morphology throughout Wales based on the time series (1989-2011) analysis of Landsat TM/ETM+ images and supporting GIS data

Knowledge of impervious surface areas (ISA) and on their changes in magnitude, location, geometry and morphology over time is significant for a range of practical applications and research alike from local to global scales. Despite this, use of Earth Observation (EO) technology in mapping ISAs within some European Union (EU) countries, such as the United Kingdom (UK), is to some extent scarce. In the present study, a combination of methods is proposed for mapping ISA based on freely distributed EO imagery from Landsat TM/ETM+ sensors. The proposed technique combines a traditional classifier and a linear spectral mixture analysis (LSMA) with a series of Landsat TM/ETM+ images to extract ISA. Selected sites located in Wales, UK, are used for demonstrating the capability of the proposed method. The Welsh study areas provided a unique setting in detecting largely dispersed urban morphology within an urban-rural frontier context. In addition, an innovative method for detecting clouds and cloud shadow layers for the full area estimation of ISA is also presented herein. The removal and replacement of clouds and cloud shadows, with underlying materials is further explained. Aerial photography with a spatial resolution of 0.4 m, acquired over the summer period in 2005 was used for validation purposes. Validation of the derived products indicated an overall ISA detection accuracy in the order of ~97%. The latter was considered as very satisfactory and at least comparative, if not somehow better, to existing ISA products provided on a national level. The hybrid method for ISA extraction proposed here is important on a local scale in terms of moving forward into a biennial program for the Welsh Government. It offers a much less subjectively static and more objectively dynamic estimation of ISA cover in comparison to existing operational products already available, improving the current estimations of international urbanization and soil sealing. Findings of our study provide important assistance towards the development of relevant EO-based products not only inaugurate to Wales alone, but potentially allowing a cost-effective and consistent long term monitoring of ISA at different scales based on EO technology

Análise multitemporal do uso do solo da microbacia do Rio Sarandi no Sudoeste do estado do Paraná, Brasil utilizando imagens LANDSAT/TM

The evaluation of the changes a particular location undergoes over several years may be carried out with the analysis of images in different periods of time. The objective of this study was to carry out the multi-temporal analysis of the land use on the Sarandi River watershed that has predominance of family farms and high agricultural potential and is located in the Southwest mesoregion of the state of Paraná, Southern Brazil. To verify the changes of land use in the basin was necessary to apply the linear image enhancement technique to improve spectral information and facilitate images interpretation. The classification method used was supervised as the Bhattacharya classifier, on LANDSAT/TM satellite’s images, from 1985 to 2010. The data were processed by SPRING and the results showed along these 25 years a 0.40% decline in forest cover, with decrease in grazing areas in a ratio of 4.21% and around 6.64% for exposed soil and a increase of 10.52% in agriculture, 0.62% in urban area and 0.11% in water blade. The evaluation of the accuracy of the mappings generated was made using as reference the images LANDSA/TM, IK ranged between (97.2 98.7%) and EG medium was 98% which indicates the efficiency of the classifier.Este trabalho teve como objetivo realizar a análise multitemporal do uso do solo da microbacia do Rio Sarandi que possui predomínio de agricultura familiar e forte potencial agropecuário e está localizada na mesorregião Sudoeste do estado do Paraná, região Sul do Brasil. Para verificar as mudanças de uso do solo da bacia foi necessário aplicar a técnica de realce linear de imagem para melhorar visualmente a informação espectral e facilitar a interpretação das imagens. Fez-se o estudo com imagens do satélite LANDSAT/TM no período de 1985 a 2010, com a técnica de classificação supervisionada com o classificador Bhattacharya. Os dados foram processados no programa SPRING e com os resultados obtidos foi possível evidenciar que ao longo desses 25 anos houve uma diminuição na cobertura florestal de 0,40%, de 4,21% nas áreas de pastagens e de 6,64% para solo exposto e um aumento de 10,52% na agricultura, de 0,62% na área urbana e de 0,11% em lâmina de água. A avaliação da acurácia dos mapeamentos gerados foi feita usando como referência as imagens LANDSA/TM, o IK variou entre (97,2 e 98,7%) e o EG médio foi de 98% o que indica a eficiência do classificador