We present a practical method for producing a high-resolution digital elevation map (DEM) from a set of spatially overlapping images. We start with the principle that multiple low-resolution DEMs can be combined to form a high-resolution DEM provided that (i) the sample DEMs are registered to the same coordinate system; (ii) the elevation estimates at each posting are partially independent; and...

Thin plate smoothing splines incorporating varying degrees of topographic dependence were used to interpolate 100 daily rainfall values, with the degree of data smoothing determined by minimizing the generalised cross validation. Analyses were performed on the square roots of the rainfall values. Model calibration was made difficult by short range correlation and the small size of the data set....

High resolution data have high relief displacement in hilly terrains. Development of Digital Elevation model helps to assess bio resources more accurately in such terrains. While estimating bio resources in the Himalayan hilly terrain using multispectral LISS-III data of 23 m spatial resolution, the need for orthorectifcation of satellite data was necessary to correct for spatial distances due ...

A typical way to build surface numerical models or Digital Elevation Models (DEMs) for Geographical Information Systems (GIS) is by processing the stereo images obtained from, for example, aerial photography or SPOT satellite data. These GIS can perform many computations involving their geographic databases. The quality control of a geographic database, and in particular the topological and geo...

The TanDEM-X mission will derive a global digital elevation model (DEM) with satellite SAR interferometry. Two radar satellites (TerraSAR-X and TanDEM-X) will map the Earth in a resolution and accuracy with an absolute height error of 10m and a relative height error of 2m for 90% of the data. In order to fulfill the height requirements in general two global coverages are acquired and processed....

Comparison of 1719 differential GPS measurements with a 1 m LiDAR DEM covering West Seattle shows that DEM elevation errors range from –4.88 m to +3.32 m. The errors are spatially correlated with a semivariogram range of 125 m, an unclustered mean of –0.11 m, and an unclustered standard deviation of ±0.75 m. Although there are statistically significant correlations between elevation error and e...

This paper describes the implementation of three methods for fitting surfaces: linear, quintic and stochastic. It uses qualitative (visual) and quantitative (statistical) criteria to compare the three approaches. The digital terrain model is based on a triangular irregular network (TIN) structure and the comparison is performed using a mathematically defined function and real data obtained from...

Photogrammetric digital elevation models (DEMs) are often used to derive and monitor surfaces in inaccessible areas. They have been used to monitor the spatial and temporal change of glacier surfaces in order to assess glacier response to climate change. However, deriving photogrammetric DEMs of steep mountainous topography where the surface is often obscured by regions of deep shadow and snow ...

Background: New technologies for terrain reconstruction have increased the availability of topographic data at a broad range of resolutions and spatial extents. The existing digital elevation models (DEMs) can now be updated at a low cost in selected study areas with newer, often higher resolution data using unmanned aerial systems (UAS) or terrestrial sensors. However, differences in spatial c...