Remote Sensing Image Data Storage and Search Method Based on Pyramid Model in Cloud

Xia, Ying; Xuan-lun, Yang

doi:10.1007/978-3-642-31900-6_34

Cited by 3 publications

(1 citation statement)

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“…The concept of the PM is similar to an image pyramid (e.g., Figure 14 (left)), which represents a raster image on multiple resolutions by aggregation and resampling. Image pyramids were originally developed in the areas of computer vision, image processing, and signal processing [26,27], and are widely used to enhance the efficiency of multi-scale raster rendering in GIS [28][29][30]. In our approach, the construction of a PM is similar to that of the TM in the sense of developing a hierarchy; but the PM represents space across scales instead of time.…”

Section: The Conceptmentioning

confidence: 99%

Re-Arranging Space, Time and Scales in GIS: Alternative Models for Multi-Scale Spatio-Temporal Modeling and Analyses

Qiang

Weghe

2019

IJGI

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The representations of space and time are fundamental issues in GIScience. In prevalent GIS and analytical systems, time is modeled as a linear stream of real numbers and space is represented as flat layers with timestamps. Despite their dominance in GIS and information visualization, these representations are inefficient for visualizing data with complex temporal and spatial extents and the variation of data at multiple temporal and spatial scales. This article presents alternative representations that incorporate the scale dimension into time and space. The article first reviews a series of work about the triangular model (TM), which is a multi-scale temporal model. Then, it introduces the pyramid model (PM), which is the extension of the TM for spatial data, and demonstrates the utility of the PM in visualizing multi-scale spatial patterns of land cover data. Finally, it discusses the potential of integrating the TM and the PM into a unified framework for multi-scale spatio-temporal modeling. This article systematically documents the models with alternative arrangements of space and time and their applications in analyzing different types of data. Additionally, this article aims to inspire the re-thinking of organizations of space, time, and scales in the future development of GIS and analytical tools to handle the increasing quantity and complexity of spatio-temporal data.

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