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Displaying 281 - 285 of 661Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error
We developed a global, 30-m resolution dataset of percent tree cover by rescaling the 250-m MOderate-resolution Imaging Spectroradiometer (MODIS) Vegetation Continuous Fields (VCF) Tree Cover layer using circa- 2000 and 2005 Landsat images, incorporating the MODIS Cropland Layer to improve accuracy in agricultural areas. Resulting Landsat-based estimates maintained consistency with the MODIS VCF in both epochs (RMSE =8.6% in 2000 and 11.9% in 2005), but showed improved accuracy in agricultural areas and increased discrimination of small forest patches.
Evaluating the use of publicly available remotely sensed land cover data for areal interpolation
Areal interpolation is used to transfer attribute data between geographically incongruous zonal systems. Remotely sensed land cover data are widely used in intelligent areal interpolation methods to solve this problem. This article examines the usefulness of different publicly available remotely sensed land cover data sets as ancillary data used in conjunction with different areal interpolation methods.
Optical and radar data integration for land use and land cover mapping in the Brazilian Amazon
This study aims to evaluate different methods of integrating optical and multipolarized radar data for land use and land cover (LULC) mapping in an agricultural frontier region in the Central Brazilian Amazon, which requires continuous monitoring due to the increasing human intervention. The evaluation is performed using different sets of fused and combined data.
Land cover and impervious surface extraction using parametric and non-parametric algorithms from the open-source software R: an application to sustainable urban planning in Sicily
Detailed urban land-cover maps are essential information for sustainable planning. Land-cover maps assist planners in designing strategies for the optimisation of urban ecosystem services and climate change adaptation. In this study, the statistical software R was applied to land cover analysis for the Catania metropolitan area in Sicily, Italy. Six land cover classes were extracted from high-resolution orthophotos. Five different classification algorithms were compared. Texture and contextual layers were tested in different combinations as ancillary data.
Validating the geometric accuracy of high spatial resolution multispectral satellite data
Uses of high spatial resolution data obtained from satellite-based sensors include creating land cover maps, deriving large-scale quantitative assessments such as vegetation indices, and visually assessing an area for qualitative information only assessable from large-scale digital data. One of the more popular uses of high spatial resolution data is to use the image as a base map for on-screen digitizing spatially dependent vector products.