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Application of Image Processing and Data in Remote Sensing
Published in Ankur Dumka, Alaknanda Ashok, Parag Verma, Poonam Verma, Advanced Digital Image Processing and Its Applications in Big Data, 2020
Ankur Dumka, Alaknanda Ashok, Parag Verma, Poonam Verma
ENVI is image analysis software which is used for image processing and analysis in order to extract the meaningful information from images. It can be deployed in desktop, cloud, or mobile devices and can be customized as per requirements using APIs. MATLAB is short form for matrix laboratory which consists of software used in the field of digital image processing. PCI Geomatica is used for remote sensing desktop software package used for processing of earth observation data. It can be used for loading of satellite and aerial imaginary data with advanced analysis features. IDRISI is a GIS analytical tool used for GIS-based application for finding remote sensing data. Some of the open source software packages that are available for remote sensing applications are ILWIS, Opticks, GRASS, OSSIN, Multispec, etc.
Aggregation of uncertain information and its implementation in geographic information systems and spatial databases
Published in Soňa Molčíková, Viera Hurčíková, Vladislava Zelizňaková, Peter Blišťan, Advances and Trends in Geodesy, Cartography and Geoinformatics, 2018
R. Ďuračiová, M. Muňko, J. Caha
For raster data, some principles of fuzzy set theory as well as basic aggregation operators are implemented in some GIS. Such GIS environments are GRASS GIS, ArcGIS, IDRISI, etc. For example, tools such as Fuzzy Membership and Fuzzy Overlay are implemented in ArcGIS. However, no GIS software environment supports all above mentioned fuzzy aggregation operators. If we need to apply an aggregation operator that is not implemented in ArcGIS, we can use tools such as Cell Statistics or Raster Calculator (tools for map algebra realisation) to define it.
A Comparison of Wetland Mapping Using SPOT Satellite Imagery and National Wetland Inventory Data for a Watershed in Northern Michigan
Published in Carl C. Trettin, Martin F. Jurgensen, David F. Grigal, Margaret R. Gale, John K. Jeglum, Northern Forested Wetlands, 2018
Trae A. Forgette, John A. Shuey
The computer platform used for classifying the images was a desktop PC, with a 486 DX processor, running at a clock speed of 33 MHz, and operating in the DOS environment. Software used for image processing, classification, and statistical comparison was IDRISI (The IDRISI Project, Clark University). This software was selected because it is a powerful, yet inexpensive raster (grid-based) analysis package.
Assessing the impacts of land use/land cover and climate change on surface runoff of a humid tropical river basin in Western Ghats, India
Published in International Journal of River Basin Management, 2023
Rakesh Kumar Sinha, T. I. Eldho, Ghosh Subimal
IDRISI is a GIS software and image processing tool along with a constellation of vertical applications which was developed by CLARK LAB (https://clarklabs.org/terrset/). The land change modeller (LCM) has been used for the future LULC projection which is incorporated in the IDRISI model. LCM module gives quantitative analysis of category-wise LULC changes in terms of losses and gains with respect to each LULC class. The quantitative conversion of LULC categories and a better understanding of spatiotemporal changes are described by the Markov transition matrix and the physical structure using a mathematical process with cellular automata (CA) (Wolfram, 1998). Space and time are separate in this physical system. The empirical possibility of change between initial land use maps (t − 1) and a final image (t) represented by the evidence likelihood technique. To project the future images, the predictive capabilities of all LULC change drivers were tested and suitability maps were developed indicating the suitability of each changing cell of LULC map to another use.