DeepAI AI Chat
Log In Sign Up

An improved tile-based scalable distributed management model of massive high-resolution satellite images

by   Yosra Hajjaji, et al.

The amount of remote sensing (RS) data has increased at an unexpected scale, due to the rapid progress of earth-observation and the growth of satellite RS and sensor technologies. Traditional relational databases attend their limit to meet the needs of high-resolution and large-scale RS Big Data management. As a result, massive RS data management is currently one of the most imperative topics. To address this problem, this paper describes a distributed architecture for big RS data storage based on a unified metadata file, pyramid model, and Hilbert curve for data composition and indexing using NoSQL databases (i.e, Apache Hbase). In this paper, a Hadoop-based framework in AzureInsight cloud platform is designed to manage massive RS data in a parallel and distributed way. Experimental results prove that our method has the potential to overcome the weakness of traditional methods. The proposed model is suitable for massive high-resolution image data management.


Tensor Representation and Manifold Learning Methods for Remote Sensing Images

One of the main purposes of earth observation is to extract interested i...

Raptor Zonal Statistics: Fully Distributed Zonal Statistics of Big Raster + Vector Data [Pre-Print]

Recent advancements in remote sensing technology have resulted in petaby...

A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval

Remote sensing (RS) images are usually stored in compressed format to re...

Classification of LULC Change Detection using Remotely Sensed Data for Coimbatore City, Tamilnadu, India

Maps are used to describe far-off places . It is an aid for navigation a...

Urban Change Detection by Fully Convolutional Siamese Concatenate Network with Attention

Change detection (CD) is an important problem in remote sensing, especia...

In-Season Crop Progress in Unsurveyed Regions using Networks Trained on Synthetic Data

Many commodity crops have growth stages during which they are particular...

AI Security for Geoscience and Remote Sensing: Challenges and Future Trends

Recent advances in artificial intelligence (AI) have significantly inten...