Remote Sensing Big Data: Theory, Methods and Applications

Peng Liu,Qian Du,Liping Di,Lizhe Wang

doi:10.3390/rs10050711

Abstract

Nowadays, our ability to acquire remote sensing data has been improved to an unprecedented level.[...]

Highlights

Nowadays, our ability to acquire remote sensing data has been improved to an unprecedented level
The theory and methods can not change the wold if they are not connected with concrete applications. This special issue included three papers of applications based on remote sensing big data: flood response decision [7], land-cover change detection [8] and coastal land use [9]
In [9], the study presents a model named ARCLUSSM (Association Rules-based Coastal Land use Spatial Sequence Model) to mine the sequential pattern of land use with interesting associations in the sea–land direction of the coastal zone. It is a good application of remote sensing big data, which focuses on land use in the sea–land direction and the sequential relationship between land-use types

Summary

Introduction

Our ability to acquire remote sensing data has been improved to an unprecedented level. Journal of Applied Remote Sensing launched the special issue on Management and Analytics of Remotely Sensed Big Data in 2015. The International Journal of Digital Earth is calling for papers for the special issue on Social Sensing and Big Data Computing for Disaster Management in 2018. No matter whether it is government projects, commercial applications or academic research, when characterizing big data, it is popular to refer to the 3Vs, i.e., remarkable growth in Volume, Velocity and Variety of data [1]. It is important for us to consider these more concrete and particular characteristics of remote sensing big data when using remote sensing to extract information and understand geo-processes. With these issues in mind, it is to present the current state-of-the-art theoretical, methodological, and applicational research on remote sensing big data

Overview of Contributions

Conclusions