State of Geographic Information Science (GIS), Spatial Analysis (SA) and Remote Sensing (RS) in India: A Machine Learning Perspective

2021 ◽  
pp. 29-41
Author(s):  
Shruti Sachdeva ◽  
Bijendra Kumar
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Spatial Analysis ◽  
Information Science ◽  
Geographic Information Science ◽  
Geographic Information ◽  
Gis Spatial Analysis

scholarly journals Visual analytics of movement: An overview of methods, tools and procedures

2012 ◽  
Vol 12 (1) ◽  
pp. 3-24 ◽  
Author(s):  
Natalia Andrienko ◽  
Gennady Andrienko
Keyword(s):  
Machine Learning ◽  
Visual Analytics ◽  
Data Analytics ◽  
Information Science ◽  
State Of The Art ◽  
Geographic Information Science ◽  
Geographic Information ◽  
Research Topic ◽  
Visual Methods ◽  
Movement Data

Analysis of movement is currently a hot research topic in visual analytics. A wide variety of methods and tools for analysis of movement data has been developed in recent years. They allow analysts to look at the data from different perspectives and fulfil diverse analytical tasks. Visual displays and interactive techniques are often combined with computational processing, which, in particular, enables analysis of a larger number of data than would be possible with purely visual methods. Visual analytics leverages methods and tools developed in other areas related to data analytics, particularly statistics, machine learning and geographic information science. We present an illustrated structured survey of the state of the art in visual analytics concerning the analysis of movement data. Besides reviewing the existing works, we demonstrate, using examples, how different visual analytics techniques can support our understanding of various aspects of movement.

scholarly journals Geographic Information System & Spatial Analysis

2019 ◽  
pp. 70-90
Author(s):  
Naser Ahmed Bipu
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Spatial Analysis ◽  
Information Science ◽  
Spatial Information ◽  
Geographic Information Science ◽  
Geographic Information ◽  
Gis Applications ◽  
Geographic Data ◽  
Transport Logistics

A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. GIS applications are tools that allow users to create interactive queries (user-created searches), analyze spatial information, edit data in maps, and present the results of all these operations. GIS (more commonly GIS science) sometimes refers to geographic information science (GIS science), the science underlying geographic concepts, applications, and systems. GIS can refer to a number of different technologies, processes, techniques and methods. It is attached to many operations and has many applications related to engineering, planning, management, transport/logistics, insurance, telecommunications, and business. For that reason, GIS and location intelligence applications can be the foundation for many location-enabled services that rely on analysis and visualization.

scholarly journals Revisiting the Role of Place in Geographic Information Science

2018 ◽  
Vol 7 (9) ◽  
pp. 364 ◽  
Author(s):  
Helena Merschdorf ◽  
Thomas Blaschke
Keyword(s):  
Information Science ◽  
Human Perception ◽  
Geographic Information Science ◽  
Geographic Information ◽  
Human Environment ◽  
Subjective Data ◽  
Main Research ◽  
The Social ◽  
The Individual

Although place-based investigations into human phenomena have been widely conducted in the social sciences over the last decades, this notion has only recently transgressed into Geographic Information Science (GIScience). Such a place-based GIS comprises research from computational place modeling on one end of the spectrum, to purely theoretical discussions on the other end. Central to all research that is concerned with place-based GIS is the notion of placing the individual at the center of the investigation, in order to assess human-environment relationships. This requires the formalization of place, which poses a number of challenges. The first challenge is unambiguously defining place, to subsequently be able to translate it into binary code, which computers and geographic information systems can handle. This formalization poses the next challenge, due to the inherent vagueness and subjectivity of human data. The last challenge is ensuring the transferability of results, requiring large samples of subjective data. In this paper, we re-examine the meaning of place in GIScience from a 2018 perspective, determine what is special about place, and how place is handled both in GIScience and in neighboring disciplines. We, therefore, adopt the view that space is a purely geographic notion, reflecting the dimensions of height, depth, and width in which all things occur and move, while place reflects the subjective human perception of segments of space based on context and experience. Our main research questions are whether place is or should be a significant (sub)topic in GIScience, whether it can be adequately addressed and handled with established GIScience methods, and, if not, which other disciplines must be considered to sufficiently account for place-based analyses. Our aim is to conflate findings from a vast and dynamic field in an attempt to position place-based GIS within the broader framework of GIScience.

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