{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T00:40:13Z","timestamp":1769733613605,"version":"3.49.0"},"reference-count":54,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T00:00:00Z","timestamp":1620259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100018527","name":"Key Research Program of Frontier Science, Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["ZDBS-LY-DQC016"],"award-info":[{"award-number":["ZDBS-LY-DQC016"]}],"id":[{"id":"10.13039\/501100018527","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61836013"],"award-info":[{"award-number":["61836013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19020103"],"award-info":[{"award-number":["XDA19020103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the remarkable development and progress of earth-observation techniques, remote sensing data keep growing rapidly and their volume has reached exabyte scale. However, it\u2019s still a big challenge to manage and process such huge amounts of remote sensing data with complex and diverse structures. This paper designs and realizes a distributed storage system for large-scale remote sensing data storage, access, and retrieval, called RSIMS (remote sensing images management system), which is composed of three sub-modules: RSIAPI, RSIMeta, RSIData. Structured text metadata of different remote sensing images are all stored in RSIMeta based on a set of uniform models, and then indexed by the distributed multi-level Hilbert grids for high spatiotemporal retrieval performance. Unstructured binary image files are stored in RSIData, which provides large scalable storage capacity and efficient GDAL (Geospatial Data Abstraction Library) compatible I\/O interfaces. Popular GIS software and tools (e.g., QGIS, ArcGIS, rasterio) can access data stored in RSIData directly. RSIAPI provides users a set of uniform interfaces for data access and retrieval, hiding the complex inner structures of RSIMS. The test results show that RSIMS can store and manage large amounts of remote sensing images from various sources with high and stable performance, and is easy to deploy and use.<\/jats:p>","DOI":"10.3390\/rs13091815","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T22:36:24Z","timestamp":1620426984000},"page":"1815","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["RSIMS: Large-Scale Heterogeneous Remote Sensing Images Management System"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9674-3690","authenticated-orcid":false,"given":"Xiaohua","family":"Zhou","sequence":"first","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuezhi","family":"Wang","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2144-1131","authenticated-orcid":false,"given":"Yuanchun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghui","family":"Lin","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7036-0800","authenticated-orcid":false,"given":"Jianghua","family":"Zhao","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianghai","family":"Meng","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,6]]},"reference":[{"key":"ref_1","unstructured":"(2021, April 23). Remote Sensing: Introduction and History, Available online: https:\/\/earthobservatory.nasa.gov\/features\/RemoteSensing."},{"key":"ref_2","unstructured":"(2021, February 01). Big Data. Available online: http:\/\/www.gartner.com\/it-glossary\/big-data."},{"key":"ref_3","unstructured":"(2021, February 01). DigitalGlobe Satellite and Product Overview, Available online: https:\/\/calval.cr.usgs.gov\/apps\/sites\/default\/files\/jacie\/DigitalGlobeOverview_JACIE_9_19_17.pdf."},{"key":"ref_4","unstructured":"Grawinkel, M., Nagel, L., Padua, F., Masker, M., Brinkmann, A., and Sorth, L. (2015, January 15\u201319). Analysis of the ECMWF storage landscape. Proceedings of the 13th USENIX Conference on File and Storage Technologies, Santa Clara, CA, USA."},{"key":"ref_5","first-page":"354","article-title":"Research on Application of Blockchain Technology in Field of Spatial Information Intelligent Perception","volume":"47","author":"Guo","year":"2020","journal-title":"Comput. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Fan, J., Yan, J., Ma, Y., and Wang, L. (2018). Big Data Integration in Remote Sensing across a Distributed Metadata-Based Spatial Infrastructure. Remote Sens., 10.","DOI":"10.3390\/rs10010007"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-Resolution Global Maps of 21st-Century Forest Cover Change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111702","DOI":"10.1016\/j.rse.2020.111702","article-title":"A remote sensing approach to mapping fire severity in south-eastern Australia using sentinel 2 and random forest","volume":"240","author":"Gibson","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"111402","DOI":"10.1016\/j.rse.2019.111402","article-title":"Remote sensing for agricultural applications: A meta-review","volume":"236","author":"Weiss","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Wang, F., Oral, S., Shipman, G., Drokin, O., Wang, T., and Huang, I. (2009). Understanding Lustre Filesystem Internals, Oak Ridge National Laboratory, National Center for Computational Sciences. Technical Paper.","DOI":"10.2172\/951297"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ghemawat, S., Gobioff, H., and Leung, S.-T. (2003, January 19\u201322). The Google file system. Proceedings of the 19th ACM Symposium on Operating Systems Principles, Bolton Landing, NY, USA.","DOI":"10.1145\/945445.945450"},{"key":"ref_12","first-page":"463","article-title":"Earth observation data processing in distributed systems","volume":"34","author":"Dana","year":"2010","journal-title":"Informatica"},{"key":"ref_13","first-page":"9","article-title":"The distributed file system about moose fs and application","volume":"5","author":"Qiao","year":"2009","journal-title":"Inspur"},{"key":"ref_14","unstructured":"Weil, S.A., Brandt, S.A., Miller, E.L., Long, D.D.E., and Maltzahn, C. (2006, January 6\u20138). Ceph: A scalable, high-performance distributed file system. Proceedings of the 7th Symposium on Operating Systems Design and Implementation, Seattle, WA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, H., Ghodsi, A., Zaharia, M., Shenker, S., and Stoica, I. (2014, January 3\u20135). Tachyon: Reliable, memory speed storage for cluster computing frameworks. Proceedings of the ACM Symposium on Cloud Computing, Seattle, WA, USA.","DOI":"10.1145\/2670979.2670985"},{"key":"ref_16","unstructured":"Beaver, D., Kumar, S., Li, H.C., Sobel, J., and Vajgel, P. (2010, January 4\u20136). Finding a needle in Haystack: Facebook\u2019s photo storage. Proceedings of the Usenix Conference on Operating Systems Design & Implementation, Vancouver, ON, Canada."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2126","DOI":"10.1109\/TPDS.2013.272","article-title":"Task-tree based large-scale mosaicking for massive remote sensed imageries with dynamic DAG scheduling","volume":"25","author":"Ma","year":"2014","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_18","unstructured":"Kou, W., Yang, X., Liang, C., Xie, C., and Gan, S. (2016, January 14\u201317). HDFS enabled storage and management of remote sensing data. Proceedings of the 2016 2nd IEEE International Conference on Computer and Communications (ICCC 2016), Chengdu, China."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.1016\/j.future.2013.05.002","article-title":"Rapid processing of remote sensing images based on cloud computing","volume":"29","author":"Wang","year":"2013","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_20","first-page":"637","article-title":"Cloud Hadoop Map Reduce for Remote Sensing Image Analysis","volume":"4","author":"Almeer","year":"2014","journal-title":"J. Emerg. Trends Comput. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_22","unstructured":"(2021, February 01). Earth on AWS. Available online: https:\/\/aws.amazon.com\/earth."},{"key":"ref_23","unstructured":"(2021, February 01). R-tree. Available online: https:\/\/en.wikipedia.org\/wiki\/R-tree."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Peano, G. (1990). Sur une courbe, qui remplit toute une aire plane. Arbeiten zur Analysis und zur Mathematischen Logik, Springer.","DOI":"10.1007\/978-3-7091-9537-6"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"March, V., and Yong, M.T. (2006, January 9\u201311). Multi-Attribute Range Queries on Read-Only DHT. Proceedings of the 15th International Conference on Computer Communications and Networks (ICCCN), Arlington, VA, USA.","DOI":"10.1109\/ICCCN.2006.286312"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s10109-013-0191-6","article-title":"Indexing and querying moving objects with uncertain speed and direction in spatiotemporal databases","volume":"16","author":"Huang","year":"2014","journal-title":"J. Geogr. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2629333","article-title":"Towards a painless index for spatial objects","volume":"39","author":"Zhang","year":"2014","journal-title":"ACM Trans. Database Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.jcp.2014.10.022","article-title":"A mesh partitioning algorithm for preserving spatial locality in arbitrary geometries","volume":"281","author":"Nivarti","year":"2015","journal-title":"J. Comput. Phys."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.envsoft.2015.10.002","article-title":"A GPU-accelerated smoothed particle hydrodynamics (SPH) model for the shallow water equations","volume":"75","author":"Xia","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1007\/s11760-013-0565-8","article-title":"Space-filling curves applied to compression of ultraspectral images","volume":"9","author":"Herrero","year":"2015","journal-title":"Signal Image Video Process."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1109\/TPDS.2014.2322362","article-title":"A parallel file system with application-aware data layout policies for massive remote sensing image processing in digital earth","volume":"26","author":"Wang","year":"2015","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/BF01199431","article-title":"\u00dcber die stetige Abbildung einer Linie auf ein Fl\u00e4chenst\u00fcck","volume":"38","author":"Hilbert","year":"1891","journal-title":"Mathematische Annalen"},{"key":"ref_33","unstructured":"Weisstein, E.W. (2021, April 05). Sierpi\u0144ski Curve. Available online: https:\/\/en.wikipedia.org\/wiki\/MathWorld."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"123","DOI":"10.15514\/ISPRAS-2017-29(4)-8","article-title":"The Metric Travelling Salesman Problem: The Experiment on Pareto-optimal Algorithms","volume":"29","author":"Avdoshin","year":"2017","journal-title":"Proc. ISP RAS"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2947668","article-title":"Parallel memory-efficient adaptive mesh refinement on structured triangular meshes with billions of grid cells","volume":"43","author":"Meister","year":"2016","journal-title":"ACM Trans. Math. Software"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1023\/A:1025196714293","article-title":"Analysis of Multi-Dimensional Space-Filling Curves","volume":"7","author":"Mokbel","year":"2003","journal-title":"GeoInformatica"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/69.908985","article-title":"Analysis of the Clustering Properties of Hilbert Space-filling Curve","volume":"13","author":"Moon","year":"2001","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Jagadish, H.V. (1990, January 23\u201325). Linear clustering of objects with multiple attributes. Proceedings of the 1990 ACM SIGMOD International Conference on Management of data, Atlantic City, NJ, USA.","DOI":"10.1145\/93597.98742"},{"key":"ref_39","unstructured":"ANZLIC (1995). ANZLIC Working Group on Metadata: Core Metadata Elements, Australia and New Zealand Land Information Council."},{"key":"ref_40","unstructured":"FGDC (1998). FGDC-STD-001-1998\u2014Content Standard for Digital Geographic Metadata, Federal Geographic Data Committee."},{"key":"ref_41","unstructured":"Moellering, H., Aalders, H., and Crane, A. (2005). World Spatial Metadata Standards, Elsevier Ltd."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Brodeur, J., Coetzee, S., Danko, D., Garcia, S., and Hjelmager, J. (2019). Geographic information metadata\u2014an outlook from the international standardization perspective. ISPRS Int. J. Geo. Inf., 8.","DOI":"10.3390\/ijgi8060280"},{"key":"ref_43","unstructured":"ISO\/TC 211 (2003). ISO19115:2003. Geographic Information\u2014Metadata, International Organization for Standardization."},{"key":"ref_44","unstructured":"ISO\/TC 211 (2009). ISO19115-2:2009. Geographic Information\u2014Metadata\u2014Part 2: Extensions for Imagery and Gridded Data, International Organization for Standardization."},{"key":"ref_45","unstructured":"ISO\/TC 211 (2019). ISO19115-2:2019. Geographic Information\u2014Metadata\u2014Part 2: Extensions for Acquisition and Processing, International Organization for Standardization."},{"key":"ref_46","unstructured":"(2021, April 07). Unified Metadata Model (UMM), Available online: https:\/\/earthdata.nasa.gov\/eosdis\/science-system-description\/eosdis-components\/cmr\/umm."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"van der Veen, J.S., Sipke, J., van der Waaij, B., and Meijer, R.J. (2012, January 24\u201329). Sensor data storage performance: SQL or NoSQL, physical or virtual. Proceedings of the 5th IEEE International Conference on Cloud Computing, Honololu, HI, USA.","DOI":"10.1109\/CLOUD.2012.18"},{"key":"ref_48","unstructured":"Makris, A., Tserpes, K., Spiliopoulos, G., and Anagnostopoulos, D. (2019, January 26). Performance Evaluation of MongoDB and PostgreSQL for Spatio-temporal Data. Proceedings of the EDBT\/ICDT 2019 Joint Conference on CEUR-WS.org, Lisbon, Portugal."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Weil, S.A., Brandt, S.A., Miller, E.L., and Maltzahn, C. (2006, January 11\u201317). CRUSH: Controlled, Scalable, Decentralized Placement of Replicated Data. Proceedings of the 2006 ACM\/IEEE Conference on Supercomputing, Tampa, FL, USA.","DOI":"10.1109\/SC.2006.19"},{"key":"ref_50","unstructured":"(2021, February 01). Coverity Scan: GDAL. Available online: https:\/\/scan.coverity.com\/projects\/gdal."},{"key":"ref_51","unstructured":"(2021, February 01). Raster Data Model. Available online: https:\/\/gdal.org\/user\/raster_data_model.html."},{"key":"ref_52","unstructured":"(2021, February 01). Vector Data Model. Available online: https:\/\/gdal.org\/user\/vector_data_model.html."},{"key":"ref_53","unstructured":"(2021, April 07). Introduction to Librados. Available online: https:\/\/docs.ceph.com\/en\/latest\/rados\/api\/librados-intro."},{"key":"ref_54","unstructured":"(2021, April 07). 2nd Index Internals. Available online: https:\/\/docs.mongodb.com\/manual\/core\/geospatial-indexes."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1815\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:57:45Z","timestamp":1760162265000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1815"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,6]]},"references-count":54,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091815"],"URL":"https:\/\/doi.org\/10.3390\/rs13091815","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,6]]}}}