Terra and Aqua, 2 satellites launched by the NASA-centered international Earth Observing System project, house MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Moderate resolution remote sensing allows the quantifying of land surface type and extent, which can be used to monitor changes in land cover and land use for extended periods of time. In this paper, we propose applying a p...

Digital Elevation Models (DEMs) and land cover products are primary inputs for hydrologic models of surface runoff that affects infiltration, erosion, and evapotranspiration. DEM and land cover play important role in determining the runoff characteristics of specific catchment areas. Recently, at local level, a number of data sources have been used to derive land cover products for high resolut...

Statewide land-cover change detection analysis provides a useful tool for conservation planning and environmental monitoring and addresses issues of habitat fragmentation and urban sprawl. Furthermore, land-cover data offer a historical and recent perspective on landscape dynamics. To this end, the first alliance level land-cover map of Kansas (Kansas Vegetation Map) recently completed by the K...

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engageme...

CORINE Land Cover is an Europeanwide land cover and land use classification which is based in most countries on visual interpretation of satellite images. The new CORINE2000 classification of Finland is based automated interpretation of satellite images and data integration with existing digital map data. Satellite images are used in estimation of continuous variables describing vegetation type...

Objects on the surface of earth describe unique patterns in time and this is exploited in the proposed land cover classification method enumerated in this paper. The applicability of various distance measures to reasonably find similarity or dissimilarity between time series vegetation index patterns for land cover classification is demonstrated. These distance metrics have inherent advantages ...

This paper, proposed a classification approach that utilizes the high recognition ability of Hidden Markov Models (HMM s) to perform high accuracy of classification by exploiting the spatial inter pixels dependencies ( i.e. the context ) as well as the spectral information. Applying unsupervised classification to remote sensing images can provide benefits in converting the raw image data into u...

This study promotes the use of a multiclassifier system (MCS) fed with high-resolution remote sensing data coupled with contextual and textural data in the domain of land cover and land use classification. The gain of this approach is shown by a favorable comparison of our BAGFS classifier (a mixture of bagging and feature subset classifier) over two single classifier techniques (5-NN and C4.5 ...

A stochastic, spatially explicit method for assessing the impact of land cover classification error on distributed hydrologic modeling is presented. One-hundred land cover realizations were created by systematically altering the North American Landscape Characterization land cover data according to the dataset’s misclassification matrix. The matrix indicates the probability of errors of omissio...

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodi...