Intelligence analysis and application for satellite imagery of big data

Jinfang ZHANG; Xiaohui HU; Hui ZHANG; Rui WANG; Haichang LI

doi:10.11959/j.issn.2096-0271.2016053

您当前的位置：

首页 >

文章列表页 >

Intelligence analysis and application for satellite imagery of big data

research | 更新时间：2024-06-03

- Intelligence analysis and application for satellite imagery of big data
- Big data research Vol. 2, Issue 5, Pages: 2016053(2016)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2016053
  CLC： TP75
- Online First：2016-09，
  
  Published：20 September 2016
- 稿件说明：
移动端阅览
Jinfang ZHANG, Xiaohui HU, Hui ZHANG, et al. Intelligence analysis and application for satellite imagery of big data[J]. Big data research, 2016, 2(5): 2016053.
DOI：

Jinfang ZHANG, Xiaohui HU, Hui ZHANG, et al. Intelligence analysis and application for satellite imagery of big data[J]. Big data research, 2016, 2(5): 2016053. DOI： 10.11959/j.issn.2096-0271.2016053.

摘要

卫星遥感技术的发展使得影像获取能力大大提高，深度学习方法使信息的自动提取上了一个新的台阶，而云计算为卫星影像的大数据处理提供了强大的计算能力支持。这3项技术激活了科研领域对卫星影像潜在商业价值、军事价值的预期，很多科研机构加入这个实力竞争中，也吸纳了大量的风险投资。总结了基于卫星影像大数据的潜在价值分析与应用，并提出了下一步可能的技术突破途径和未来的发展方向。

Abstract

Imaging capability has been greatly improved along with the development of remote sensing technology

the image information extraction based on deep learning raises to a new level

and cloud computing makes it possible of processing satellite imagery of big data.These three technologies activated the research on the expected potential commercial and military value

many research institutions joined the strength competition

and attracted a large number of venture capital.The potential value analysis and application based on satellite imagery of big data were summarized

and the next possible technological breakthroughs and the future direction of development were presented.

关键词

Keywords

references

SEVER T L , IRWIN D E . Landscape archaeology:remote-sensing investigation of the ancient maya in the peten rainforest of northern guatemala [J ] . Ancient Mesoamerica , 2003 , 14 ( 1 ): 113 - 122 .

STEVEN M D , CLARK J A . Applications of remote sensing in agriculture [J ] . 1990 , 13 ( 1989 ): 69 - 75 .

LIAGHAT S , BALASUNDRAM S . A review:the role of remote sensing in precision agriculture [J ] . American Journal of Agricultural and Biological Sciences , 2010 , 5 ( 1 ): 553 - 564 .

BECKERRESHEF I , JUSTICE C , DOORN B , et al . NASA contribution to the group on earth observation (GEO) global agricultural monitoring system of systems [J ] . The Earth Obs , 2009 ( 21 ): 24 - 29 .

COUNCIL N R . Contributions of land remote sensing for decisions about food security and human health:workshop report [R ] . 2007 .

BROWN M E , GRACE K , SHIVELY G , et al . Using satellite remote sensing and household survey data to assess human health and nutrition response to environmental change [J ] . Population and Environment , 2014 , 36 ( 1 ): 48 - 72 .

MARTINUZZIA S , GOULDA W A , GONZALEZA O M R . Land development,land use,and urban sprawl in Puerto Rico integrating remote sensing and population census data [J ] . Landscape and Urban Planning , 2007 , 79 ( 3 ): 288 - 297 .

NETZBAND M , STEFANOV W , REDMAN C . Applied remote sensing for urban planning,governance and sustainability [M ] . Berlin Heidelberg:Springer-Verlag , 2007 .

DENG X , HUANG J , ROZELLE S , et al . Growth,population and industrialization,and urban land expansion of china [J ] . Journal of Urban Economics , 2008 , 63 ( 1 ): 96 - 115 .

GAMBA P , HEROLD M . Global mapping of human settlement:experiences,datasets,and prospects [M ] . Florida:CRC Press , 2009 .

BHATTA B . Analysis of urban growth and sprawl from remote sensing data [M ] . Berlin Heidelberg:Springer-Verlag , 2010 .

CROWTHER T W , GLICK H B , COVEY K R . Mapping tree density at a global scale [J ] . Nature , 2015 , 525 ( 7568 ): 201 - 205 .

HALL O . Remote sensing in social science research [J ] . The Open Remote Sensing Journal , 2010 , 3 ( 1 ): 1 - 16 .

BASU S . Deepsat-a learning framework for satellite imagery [J ] .Computer Science,2015. Computer Science , 2015 .

HARALICK R M , SHANMUGAM K , DINSTEIN I . Textural features for image classification [J ] . IEEE Transactions on Systems,Man and Cybernetics , 1973 , SMC-3 ( 6 ): 610 - 621 .

SOH L K , TSATSOULIS C . Texture analysis of sar sea ice imagery using gray level co-occurrence matrices [J ] . IEEE Transactions on Geoscience and Remote Sensing , 1999 , 37 ( 2 ): 780 - 795 .

CLAUSI D A . An analysis of co-occurrence texture statistics as a function of grey level quantization [J ] . Canadian Journal of Remote Sensing , 2002 , 28 ( 1 ): 45 - 62 .

BOUREAU Y L , PONCE J , LECUN Y . A theoretical analysis of feature pooling in visual recognition [C ] // International Conference on Machine Learning,July 11-14,2010,Qingdao,China .[S.l.:s.n ] , 2010 : 459 - 459 .

CERUTI C , BASSIS S , ROZZA A , et al . Danco:an intrinsic dimensionality estimator exploiting angle and norm concentration [J ] . Pattern Recognition , 2014 , 47 ( 8 ): 2569 - 2581 .

ZHU Z , WOODCOCK C E . Continuous change detection and classification of land cover using all available landsat data [J ] . Remote Sensing of Environment , 2013 , 144 ( 1 ): 152 - 171 .

Views

1509

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A scalable parallel sorting algorithm by regular sampling for big data

Gansu smart tourism system based on big data

Big data and computing models

Analysis and research on the strategy and problems of “Channel Computing Resources from the East to the West”

Trusted sharing of cross-domain intelligence based on data objects

Related Author

Ying WANG

Zhiguang CHEN

Yutong LU

Liang GUO

Yi YANG

Bingfeng QIN

Jianwen CAO

Min LI

Related Institution

School of Information Science and Engineering, Lanzhou University

Key Laboratory of Tourism Information Fusion Processing and Data Ownership Protection, Ministry of Culture and Tourism, Lanzhou University

Technology Information Department, Gansu Provincial Department of Culture and Tourism

School of Computer and Artificial Intelligence, Lanzhou Polytechnical College

Key Laboratory of Artificial Intelligence and Computing Power Technology

Postal code：100079
Tel：（010）53879208、53859533 Email：bdr@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
Total Visits：273427 Visits Today：333

⁰