Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques

Phinn, Stuart R.; Stanford, Michael; Scarth, Peter; Murray, Alan T.; Shyy, P. T.

doi:10.1080/01431160110114998

Cited by 276 publications

(175 citation statements)

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“…No final foi alcançada uma exactidão global ajustada de 83%. Para a mesma área, Phinn et al (2002) compararam a tradicional classificação de imagens (TM), a interpretação de fotografias aéreas e análise linear de mistura espectral (TM) e chegaram à conclusão que as imagens fraccionárias do VIS garantiam uma melhor classificação que os métodos pixel-a-pixel e a agregação de classes obtidas por foto-interpretação. Na Tailândia foi utilizado um classificador não supervisionado (ISODATA) para classificar dados TM da Área Metropolitana de Banguecoque em sete classes (Madhavan et al, 2001).…”

Section: As Classificações De Uso E Ocupação Do Solo E O Modelo Visunclassified

Classificação de uso do solo urbano através da análise linear de mistura espectral com imagens de satélite

Rocha¹,

Tenedório²,

Estanqueiro³

et al. 2012

FIT

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Resumo -Os ambientes urbanos são heterogéneos, sendo útil simplificá-los em combinações de materiais básicos de uso e ocupação do solo a fim de permitir estudos quantitativos. O modelo VIS proposto por Ridd em 1995 é um modelo conceptual que permite simplificar ambientes urbanos através da combinação de três componentes básicos: vegetação (V), superfície impermeável (I) e solo (S). A maioria dos usos urbanos pode ser interpretada à luz de combinações destes três componentes básicos. A análise da composição do VIS permite revelar que a maioria das características urbanas tem a sua própria composição original destes três factores, a qual é difícil de observar através dos métodos de classificação de imagens de saté-lite que operam ao nível do pixel. Este trabalho examina as características das classes de uso e ocupação do solo urbano na Grande Área Metropolitana de Lisboa (GAML) utilizando técnicas de classificação baseadas no sub-pixel, nomeadamente a Análise de Mistura Espectral (AME), desenvolvendo um modelo conceptual para caracterizar os padrões de ocupação, sendo explorada e testada a aplicabilidade da AME para medir a composição física da morfologia urbana, através de imagens multiespectrais Landsat 7 ETM+ e SPOT 5 HRVIR, avaliando, ao mesmo tempo, o efeito que as diferenças de resolução espacial podem ter nos resultados obtidos. Palavras-chave:Detecção remota, Análise de Mistura Espectral, uso do solo urbano.Abstract -URBAN LAND USE CLASSIFICATION THROUGH SATELLITE IMAGES SPEC-TRAL MIXTURE LINEAR ANALYSIS. Urban environments are heterogeneous by nature. Hence, to allow quantitative studies it's necessary to simplify them in combinations of basic land use/cover materials. The Ridd's VIS model (1995) is a conceptual representation that allows simplifying urban environments through the combination of three basic components: vegetation (V), impervious surface (I) and soil (S). The majority of urban uses can be interpreted as a combination of those three basic components. The VIS analysis allows to disclose that the mainstream of urban features has it's own VIS signature, which is difficult to detect through pixel-by-pixel based classifiers. This work examines the land use/cover characteristics of the Great Lisbon Metropolitan Area (GAML) using sub-pixel classification techniques, mainly linear spectral unmixing (LSU), developing a conceptual model to characterize the occupation standards. The LSU ability to measure the physical composition of urban morphology is also explored and tested. In this paper we use Landsat 7 ETM+ multispectral images and SPOT 5 HRVIR, evaluating at the same time the land use/cover signatures evolution and the effect of spatial resolution differences on the same signatures measurements.

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Section: As Classificações De Uso E Ocupação Do Solo E O Modelo Visunclassified

Classificação de uso do solo urbano através da análise linear de mistura espectral com imagens de satélite

Rocha¹,

Tenedório²,

Estanqueiro³

et al. 2012

FIT

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“…It displays the results in terms of proportions of pure land cover types, called endmembers [33]. One basic assumption of SMA models is that the spectrum for each pixel is a linear or nonlinear combination of endmember spectra according to the complexity of scattering of light on land cover types [34].…”

Section: The Spectral Mixture Analysis (Sma)mentioning

confidence: 99%

“…One basic assumption of SMA models is that the spectrum for each pixel is a linear or nonlinear combination of endmember spectra according to the complexity of scattering of light on land cover types [34]. For this study, a linear SMA model was used due to its proven effectiveness in urban applications [18,33]. All linear SMA procedures were undertaken in the ENVI environment.…”

Section: The Spectral Mixture Analysis (Sma)mentioning

confidence: 99%

Urban Land Cover Change in Ecologically Fragile Environments: The Case of the Galapagos Islands

Benítez

Mena

Zurita-Arthos

2018

Land

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Abstract:The Galapagos Islands are a unique sanctuary for wildlife and have gone through a fluctuating process of urbanization in the three main inhabited islands. Despite being colonized since the 1800s, it is during the last 25 years that a dramatic increase in population has been observed. Analyzing impervious surface change over this period in an ecologically fragile environment is a challenging task, thus two methods that have been widely employed in studying urban environments were compared in this study: sub-pixel using spectral mixture analyses (SMA) and object-based classification. The SMA linear model, applied over moderate spatial resolution imagery, does not produce accurate results for urban composition mapping showing significant spectral confusion between classes. Instead, the object-based classification using spectral indices proved to be more effective for detecting impervious surfaces over heterogeneous urban environments in inhabited islands. The accuracy assessment showed a correlation between estimated and true impervious surface abundance fraction higher than first expected (R 2 = 67.7%) for the object-based classification, considering the limitations of pixel size (Landsat imagery) in small heterogeneous urban landscapes. Hence, this methodology was applied to all three urban centers for further analysis. Through this assessment, the average annual growth rate in urban areas was calculated as 3.3% from 1992 to 2017. The foreseen applications and local implications for land planning and management are especially important for the Galapagos Islands. There is a need for planning systems and processes that involve all stakeholders, in order to support pre-existing conservation initiatives and sustainable development policies.

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“…This issue is discussed in more detail in the next section (Section 4.3). Linear spectral mixture analysis is also commonly used to map urban areas according to the V-I-S concept (see Section 4.1), where vegetation, impervious surface and soil, which commonly occur within meters of each other, are considered as three endmembers in an unmixing model [105][106][107]. However, these endmembers may comprise several surface materials that cannot be differentiated due to limited spectral information available from multispectral sensors.…”

Section: Multispectral Approachesmentioning

confidence: 99%

Can the Future EnMAP Mission Contribute to Urban Applications? A Literature Survey

et al. 2011

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With urban populations and their footprints growing globally, the need to assess the dynamics of the urban environment increases. Remote sensing is one approach that can analyze these developments quantitatively with respect to spatially and temporally large scale changes. With the 2015 launch of the spaceborne EnMAP mission, a new hyperspectral sensor with high signal-to-noise ratio at medium spatial resolution, and a 21 day global revisit capability will become available. This paper presents the results of a literature survey on existing applications and image analysis techniques in the context of urban remote sensing in order to identify and outline potential contributions of the future EnMAP mission. Regarding urban applications, four frequently addressed topics have been identified: urban development and planning, urban growth assessment, risk and vulnerability assessment and urban climate. The requirements of four application fields and associated image processing techniques used to retrieve desired parameters and create geo-information products have been reviewed. As a result, we identified promising research directions enabling the use of EnMAP for urban studies. First and foremost, research is required to analyze the spectral information content of an EnMAP pixel used to support material-based land cover mapping approaches. This information can subsequently be used to improve urban indicators, such as imperviousness. Second, we identified the global monitoring of urban areas as a promising field of investigation taking advantage of EnMAP's spatial coverage and revisit capability.Remote Sens. 2011, 3 1818However, owing to the limitations of EnMAPs spatial resolution for urban applications, research should also focus on hyperspectral resolution enhancement to enable retrieving material information on sub-pixel level.

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Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques

Cited by 276 publications

References 0 publications

Classificação de uso do solo urbano através da análise linear de mistura espectral com imagens de satélite

Classificação de uso do solo urbano através da análise linear de mistura espectral com imagens de satélite

Urban Land Cover Change in Ecologically Fragile Environments: The Case of the Galapagos Islands

Can the Future EnMAP Mission Contribute to Urban Applications? A Literature Survey

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