Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those requ...

The primary objective of this research is to predict and analyze the future urban growth of Dhaka City using the Landsat satellite images of 1989, 1999 and 2009. Dhaka City Corporation (DCC) and its surrounding impact areas have been selected as the study area. At the beginning, a fisher supervised classification method has been applied to prepare the base maps with five land cover classes. In ...

Super-resolution mapping (SRM) is a method to produce a fine spatial resolution land cover map from coarse spatial resolution remotely sensed imagery. A popular approach for SRM is a two-step algorithm, which first increases the spatial resolution of coarse fraction images by interpolation, and then determines class labels of fine resolution pixels using the maximum a posteriori (MAP) principle...

Tree cover maps are used for many purposes, such as vegetation mapping, habitat connectivity and fragmentation studies. Small remnant patches of native vegetation are recognised as ecologically important, yet they are underestimated in remote sensing products derived from Landsat. High spatial resolution sensors are capable of mapping small patches of trees, but their use in large-area mapping ...

land use maps are the most essential information in the hand of natural resources managers.in the present research, to prepare dahat abbas land use map, landsat etm+ (1386) data was used. the image was geometrically corrected with root mean square error of less than 0.47. for classification, artificial neural network, support vector machine and maximum likelihood methods were used.finally, thel...

A snow-cover mapping method accounting for forests (SnowFrac) is presented. SnowFrac uses spectral unmixing and endmember constraints to estimate the snow-cover fraction of a pixel. The unmixing is based on a linear spectral mixture model, which includes endmembers for snow, coniferous trees, branches of leafless deciduous trees and snow-free ground. Model input consists of a land-cover fractio...

New aerial cameras and new advanced geoprocessing tools improve the generation of urban land cover maps. Elevations can be derived from stereo pairs with high density, positional accuracy, and efficiency. The combination of multispectral high-resolution imagery and high-density elevations enable a unique method for the automatic generation of urban land cover maps. In the present paper, imagery...

The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM) system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD) to identify areas of change and no change. The system then automatically generates large amounts of training sa...

A statistic based algorithm for watermarking 2D vector maps is proposed. Instead of 2D coordinates, a one-dimensional distance sequence extracted from the original map is used as the cover data to achieve the shape-preserving ability. The statistical feature of the cover data is utilized for data embedding. Experiment results indicate the scheme’s better performance in invisibility, as well as ...

Long-term MODIS vegetation index records were used to extract regularly-repeating seasonal and interannual greenness cycles in Hawaiian ecosystems using harmonic analysis. With two vegetation indices, NDVI and EVI, the MODIS system provided an opportunity to combine the two measures and create a hybrid approach to the leaf phenology study in a diversity of Hawaiian ecosystems. Despite data nois...