Comparison Between Block-Encoding and Quadtree Compression Methods for Raster Maps

2018 ◽  
pp. 258-263
Author(s):  
Phyo Phyo Wai ◽  
Su Su Hlaing ◽  
Khin Lay Mon ◽  
Mie Mie Tin ◽  
Mie Mie Khin
Keyword(s):  
Raster Maps

Valuation mapping of hazards of the crisis natural and economic situations

2017 ◽  
Vol 929 (11) ◽  
pp. 40-49
Author(s):  
N.E. Krasnoshtanova ◽  
A.K. Cherkashin
Keyword(s):  
Spatial Data ◽  
Heterogeneous Information ◽  
Secondary Use ◽  
Raster Maps ◽  
Irkutsk Region ◽  
Homogeneous Network ◽  
Surrounding Areas ◽  
Integral Assessment ◽  
Multidimensional Statistics

An innovative technique for the secondary use of cartographic information for creating assessment hazard maps of crisis natural and economic situations and an integral assessment of the sustainability economic development and the quality of live is presented. Valuation mapping was carried for the Slyudyansky district of the Irkutsk region. A database has been created for homogeneous network of plots, which contains heterogeneous information about the nature and socio-economic environment of the district. Spatial data were processed using multidimensional statistics on the base of reliability theory models. An account of the environmental correction for each plots is an important aspect of the proposed technique of assessing and creating through maps. This makes it possible to reduce the evaluation function to an invariant form common to all locations and it is used in through way to create assessment maps for natural and socio-economic objects. As a result, a series of raster maps of through thematic content was made. The map of integral hazard of emergence of economic crisis situation displays the lowest hazard values for the territories of settlements and their surrounding areas, as well as areas along roads and railways. Additionally it allocates undeveloped valley of taiga rivers, advanced for economic use, primarily for recreational purposes.

scholarly journals Evaluating the Performance of Three Popular Web Mapping Libraries: A Case Study Using Argentina’s Life Quality Index

2020 ◽  
Vol 9 (10) ◽  
pp. 563
Author(s):  
Alejandro Zunino ◽  
Guillermo Velázquez ◽  
Juan Pablo Celemín ◽  
Cristian Mateos ◽  
Matías Hirsch ◽  
...  
Keyword(s):  
Life Quality ◽  
Web Technologies ◽  
Web Mapping ◽  
Network Bandwidth ◽  
Web Map ◽  
Raster Maps ◽  
Dynamic Web ◽  
Network Usage ◽  
Overall Performance

Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.

scholarly journals Use of Airborne Hyperspectral Imagery to Map Soil Properties in Tilled Agricultural Fields

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
W. Dean Hively ◽  
Gregory W. McCarty ◽  
James B. Reeves ◽  
Megan W. Lang ◽  
Robert A. Oesterling ◽  
...  
Keyword(s):  
Soil Properties ◽  
Data Extraction ◽  
Agricultural Fields ◽  
Moisture Regime ◽  
Imaging Spectrometer ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Raster Maps ◽  
Low Pass ◽  
Airborne Imaging

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm,∼10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n=315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted withR2>0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a3×3low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

scholarly journals Fire propagation visualization in real time

2018 ◽  
Vol 18 (03) ◽  
pp. e27
Author(s):  
Monica Denham ◽  
Sigfrido Waidelich ◽  
Karina Laneri
Keyword(s):  
Real Time ◽  
Stochastic Simulations ◽  
Computational Tool ◽  
Graphic Processing Units ◽  
Ignition Point ◽  
Fire Propagation ◽  
Raster Maps ◽  
Real Time Computing ◽  
Computing Simulation ◽  
Critical Direction

Our motivation comes from the need of a tailored computational tool for simulation and prediction of forest fire propagation, to be used by firefighters in Patagonia, Argentina. Based on previous works on Graphic Processing Units (GPU) for fitting and simulating fires in our region, we developed a visualization interface for real time computing, simulation and prediction of fire propagation. We have the possibility of changing the ensemble of raster maps layers to change the region in which fire will propagate.The visualization platform runs on GPUs and the user can rotate and zoom the landscape to select the optimal view of fire propagation. Opacity of different layers can be regulated by the user, allowing to see fire propagation at the same time that underlying vegetation, wind direction and intensity. The ignition point can also be selected by the user, and firebreaks can be plotted while simulation is going on.After the performance of a high number of stochastic simulations in parallel in GPUs, the application shows a map of the final fire surface colored according to the probability that a given cell burns. In this way the user can visually identify the most critical direction for fire propagation, a useful information to stop fire optimizing resources, which is specially important when they are scarce like is the case of our Patagonia region.

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