Search Results for "memory"
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Showing 7 open source projects for "memory"
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SAGA - System for Automated Geoscientific Analyses - is a Geographic Information System (GIS) software with immense capabilities for geodata processing and analysis. SAGA is programmed in the object oriented C++ language and supports the implementation of new functions with a very effective Application Programming Interface (API). Functions are organised as modules in framework independent Module Libraries and can be accessed via SAGA’s Graphical User Interface (GUI) or various scripting...
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GeoTools, the Java GIS toolkit
Toolkit for working with and mapping geospatial data
GeoTools is an open source (LGPL) Java code library which provides standards compliant methods for the manipulation of geospatial data. GeoTools is an Open Source Geospatial Foundation project. The GeoTools library data structures are based on Open Geospatial Consortium (OGC) specifications. -
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viewpix
A Landsat 8 scene viewer
Viewpix allows the user to load all eleven bands of a Landsat 8 Level 1 data set into memory concurrently. You can scroll and view each band at full resolution. Change bands instantly with a single key press. Band 8 is 15 meters resolution, all other bands are 30m resolution. A 30m resolution gray scale scene is generated by Viewpix and is presented as band 12. Each Landsat 8 scene is roughly 190 X 180 kilometers. -
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BioSARN
BioSARN is an environmental niche model refinement tool
...This is a Java™ Desktop MicroSoft Windows Application with a simple GUI. Preferably BioSARN should be used with 64-bit Java and a substantial RAM as the application reads input files into memory to minimize compute times. -
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libral is a C library for in-memory rasters. It also includes code to render GDAL raster and vector data onto a GDK pixbuf.
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2D, 3D object indexes (Quadtree, Octree, Quadtree with object radius indexation), fast geometry find functions, template classes with embedded 2D, 3D indexation and fast search features.
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Volumetric is a 3-D image processing tool. It reads point cloud data, expands it to a volumetric space with highly effective memory usage, and filter out necessary points.
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