Affiliation:
1. School of Space Information, Space Engineering University, Beijing 101416, China
Abstract
As the world has become increasingly digitalized in recent years, high-dimensional data with geographical location coordinate attributes, mainly referring to latitude and longitude, have been accumulated and spread to many disciplines. It is challenging to analyze such data. The map-in-parallel-coordinates plot (MPCP) is an incorporate visual analysis method that can express, filter, and highlight high-dimensional geographical data to facilitate data exploration and comprehension. In this paper, the MPCP underwent a series of field trial studies to verify its applicability, adaptability, and high efficacy in the real-world. The results of the evaluation were positive, which provides reasonable proof and new insights into the benefits of using MPCP to visually analyze high-dimensional geographical datasets.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
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1. Visual Analysis of High-Dimensional Spatiotemporal Data;2023 2nd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM);2023-07-25