Academic literature on the topic 'Geo-processing workflow'

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Journal articles on the topic "Geo-processing workflow"

1

Schäffer, Bastian, and Theodor Foerster. "A client for distributed geo-processing and workflow design." Journal of Location Based Services 2, no. 3 (2008): 194–210. http://dx.doi.org/10.1080/17489720802558491.

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2

Chen, Nengcheng, Liping Di, Genong Yu, and Jianya Gong. "Geo-processing workflow driven wildfire hot pixel detection under sensor web environment." Computers & Geosciences 36, no. 3 (2010): 362–72. http://dx.doi.org/10.1016/j.cageo.2009.06.013.

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3

Lemmens, R., B. Toxopeus, L. Boerboom, et al. "IMPLEMENTATION OF A COMPREHENSIVE AND EFFECTIVE GEOPROCESSING WORKFLOW ENVIRONMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W8 (July 11, 2018): 123–27. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w8-123-2018.

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<p><strong>Abstract.</strong> Many projects and research efforts implement geo-information (GI) workflows, ranging from very basic ones to complicated software processing chains. The creation of these workflows normally needs considerable expertise and sharing them is often hampered by undocumented and non-interoperable geoprocessing implementations. We believe that the visual representation of workflows can help in the creation, sharing and understanding of software processing of geodata. In our efforts we aim at bridging abstract and concrete workflow representations for th
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Li, Chunlin, Jun Liu, Min Wang, and Youlong Luo. "Fault-tolerant scheduling and data placement for scientific workflow processing in geo-distributed clouds." Journal of Systems and Software 187 (May 2022): 111227. http://dx.doi.org/10.1016/j.jss.2022.111227.

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Chen, Nengcheng, Liping Di, Genong Yu, and Jianya Gong. "Automatic On-Demand Data Feed Service for AutoChem Based on Reusable Geo-Processing Workflow." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3, no. 4 (2010): 418–26. http://dx.doi.org/10.1109/jstars.2010.2049094.

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6

Chen, Wuhui, Incheon Paik, and Patrick C. K. Hung. "Transformation-Based Streaming Workflow Allocation on Geo-Distributed Datacenters for Streaming Big Data Processing." IEEE Transactions on Services Computing 12, no. 4 (2019): 654–68. http://dx.doi.org/10.1109/tsc.2016.2614297.

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7

Toschi, I., E. Nocerino, F. Remondino, A. Revolti, G. Soria, and S. Piffer. "GEOSPATIAL DATA PROCESSING FOR 3D CITY MODEL GENERATION, MANAGEMENT AND VISUALIZATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 527–34. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-527-2017.

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Recent developments of 3D technologies and tools have increased availability and relevance of 3D data (from 3D points to complete city models) in the geospatial and geo-information domains. Nevertheless, the potential of 3D data is still underexploited and mainly confined to visualization purposes. Therefore, the major challenge today is to create automatic procedures that make best use of available technologies and data for the benefits and needs of public administrations (PA) and national mapping agencies (NMA) involved in “smart city” applications. The paper aims to demonstrate a step forwa
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Iacone, Brooke, Ginger R. H. Allington, and Ryan Engstrom. "A Methodology for Georeferencing and Mosaicking Corona Imagery in Semi-Arid Environments." Remote Sensing 14, no. 21 (2022): 5395. http://dx.doi.org/10.3390/rs14215395.

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High-resolution Corona imagery acquired by the United States through spy missions in the 1960s presents an opportunity to gain critical insight into historic land cover conditions and expand the timeline of available data for land cover change analyses, particularly in regions such as Northern China where data from that era are scarce. Corona imagery requires time-intensive pre-processing, and the existing literature lacks the necessary detail required to replicate these processes easily. This is particularly true in landscapes where dynamic physical processes, such as aeolian desertification,
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Lucas, G. "CONSIDERING TIME IN ORTHOPHOTOGRAPHY PRODUCTION: FROM A GENERAL WORKFLOW TO A SHORTENED WORKFLOW FOR A FASTER DISASTER RESPONSE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 19, 2015): 249–55. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-249-2015.

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This article overall deals with production time with orthophoto imagery with medium size digital frame camera. The workflow examination follows two main parts: data acquisition and post-processing. The objectives of the research are fourfold: 1/ gathering time references for the most important steps of orthophoto production (it turned out that literature is missing on this topic); these figures are used later for total production time estimation; 2/ identifying levers for reducing orthophoto production time; 3/ building a simplified production workflow for emergency response: less exigent with
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Liakos, Leonidas, and Panos Panagos. "Challenges in the Geo-Processing of Big Soil Spatial Data." Land 11, no. 12 (2022): 2287. http://dx.doi.org/10.3390/land11122287.

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This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales. Here, the manuscript presents the results of a systematic effort to geo-process and analyze soil-relevant data. In addition, the main highlights include the difficulties associated with using data infrastructures, managing big geospatial data, decentralizing operations through remote access, mass processing, and automating the data-processing workflow using
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