scholarly journals Archiving and Managing Remote Sensing Data using State of the Art Storage Technologies

Author(s):  
B. Lakshmi ◽  
C. Chandrasekhara Reddy ◽  
S. V. S. R. K. Kishore

Integrated Multi-mission Ground Segment for Earth Observation Satellites (IMGEOS) was established with an objective to eliminate human interaction to the maximum extent. All emergency data products will be delivered within an hour of acquisition through FTP delivery. All other standard data products will be delivered through FTP within a day. The IMGEOS activity was envisaged to reengineer the entire chain of operations at the ground segment facilities of NRSC at Shadnagar and Balanagar campuses to adopt an integrated multi-mission approach. To achieve this, the Information Technology Infrastructure was consolidated by implementing virtualized tiered storage and network computing infrastructure in a newly built Data Centre at Shadnagar Campus. One important activity that influences all other activities in the integrated multi-mission approach is the design of appropriate storage and network architecture for realizing all the envisaged operations in a highly streamlined, reliable and secure environment. Storage was consolidated based on the major factors like accessibility, long term data protection, availability, manageability and scalability. The broad operational activities are reception of satellite data, quick look, generation of browse, production of standard and valueadded data products, production chain management, data quality evaluation, quality control and product dissemination. For each of these activities, there are numerous other detailed sub-activities and pre-requisite tasks that need to be implemented to support the above operations. <br><br> The IMGEOS architecture has taken care of choosing the right technology for the given data sizes, their movement and long-term lossless retention policies. Operational costs of the solution are kept to the minimum possible. Scalability of the solution is also ensured. The main function of the storage is to receive and store the acquired satellite data, facilitate high speed availability of the data for further processing at Data Processing servers and help to generate data products at a rate of about 1000 products per day. It also archives all the acquired data on tape storage for long-term retention and utilization. Data sizes per satellite pass range from hundreds of megabytes to tens of gigabytes <br><br> The images acquired from remote sensing satellites are valuable assets of NRSC and are used as input for further generation of different types of user data products through multiple Data Processing systems. Hence, it is required to collect and store the data within a shared, high speed repository concurrently accessible by multiple systems. After the raw imagery is stored on a high-speed repository, the images must be processed in order for them to be useful for value-added processing or for imagery analysts. The raw image file has to be copied on to data processing servers for further processing. Given the large file sizes, it is impractical to transfer these files to processing servers via a local area network. Even at gigabit Ethernet rates (up to 60 MB/s), a 5 GB file will take at least 83 seconds. For this reason, it is useful to employ a shared file system which allows every processing system to directly access the same pool where raw images were stored. Concurrent access by multiple systems is ensured for processing and generation of data products. With the above reasons, it was chosen to have high speed disk arrays for acquisition and processing purposes and tape based storage systems for long-term huge data (Peta Bytes) archival in a virtualized multitier storage architecture. <br><br> This paper explains the architecture involved in a virtualized tiered storage environment being used for acquisition, processing and archiving the remote sensing data. It also explains the data management aspects involved in ensuring data availability and archiving Peta bytes sized, remote sensing data acquired over the past 40 years.

2018 ◽  
Vol 8 (2) ◽  
pp. 74-79
Author(s):  
A.A. Emel'yanov ◽  
◽  
V.V. Malyshev ◽  
V.H.N. Nguyen ◽  
A.V. Starkov ◽  
...  

Author(s):  
Lyudmila Shagarova ◽  
Mira Muratova ◽  
Aray Yermenbay

Free access to moderate resolution remote sensing data enable the worldwide users for their studies of many key geophysical parameters of the Earth’s system, solving various tasks on regular monitoring of natural phenomena, including tasks on ecological space monitoring. This requires multilevel processing of satellite data. The processing results are given for the Aral Sea. This endorheic salt lake is located in Central Asia on the border of Kazakhstan and Uzbekistan. Aral was chosen as an example not by chance as because before shallowing, it was the fourth-largest lake in the world. During the process of drying, the lake was divided into three parts. Currently, the eastern part of the lake has completely disappeared. To the Aral Sea is happening a real ecological disaster. A long-term series of satellite data are needed to monitor the dynamics of changes. The active operation of remote sensing satellites usually exceeds their estimated lifetime. For example, spacecrafts “Terra” and “Aqua”, launched in 1999 and 2002, respectively, have an estimated lifetime of sensor MODIS as 6 years, but they are still used in the NASA EOS program aimed at Earth exploration. With the aging sensors has been a degradation of its optics equipment which affects the quality of the data in some channels. It limits the simple creation of a color image in TRUE colors by put the bands spectral range of visible radiation to corresponding layers RGB-composite. The article describes the technology of making quality images by digital operations with MODIS channels. It eliminate such a problem as “banding” of the image and create new synthesized bands. The results of processing are demonstrated using annual Terra/MODIS data for the autumn period from 2000 to 2019. Besides, taking into account that a water body has been chosen as the object of monitoring, the article presents the options of water surface detection based on spectral indices - indices calculated in mathematical operations with different spectral ranges (channels) of remote sensing data related to certain parameters. Thematic processing in Geomatica software is shown on Landsat-8 images: the sample profile of index image is demonstrated. Taking into account that the survey area exceeds the size of the standard Landsat scene, a mosaic image was made for complete coverage of the region.


Author(s):  
Rupali Dhal ◽  
D. P. Satapathy

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.


2019 ◽  
Vol 943 (1) ◽  
pp. 110-118
Author(s):  
A.A. Kadochnikov

Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities’results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography. The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation of geospatial data.


2018 ◽  
Vol 78 (4) ◽  
pp. 4311-4326 ◽  
Author(s):  
Weijing Song ◽  
Lizhe Wang ◽  
Peng Liu ◽  
Kim-Kwang Raymond Choo

Author(s):  
N. Aparna ◽  
A. V. Ramani ◽  
R. Nagaraja

Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National &amp; International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &amp;RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).


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