22.1.4 Workflow for Remote Sensing, Cartography

Chapter Contents (Back)
Workflow.

Paparoditis, N.[Nicolas], Souchon, J.P.[Jean-Philippe], Martinoty, G.[Gilles], Pierrot-Deseilligny, M.[Marc],
High-end aerial digital cameras and their impact on the automation and quality of the production workflow,
PandRS(60), No. 6, September 2006, pp. 400-412.
Elsevier DOI 0610
Digital cameras; Calibration; Surface reconstruction; Orthoimages; Radiometric equalization BibRef

Yue, P.[Peng], Guo, X.[Xia], Zhang, M.[Mingda], Jiang, L.C.[Liang-Cun], Zhai, X.[Xi],
Linked Data and SDI: The case on Web geoprocessing workflows,
PandRS(114), No. 1, 2016, pp. 245-257.
Elsevier DOI 1604
Linked Data BibRef

Vannan, S.[Suresh], Beaty, T.W.[Tammy W.], Cook, R.B.[Robert B.], Wright, D.M.[Daine M.], Devarakonda, R.[Ranjeet], Wei, Y.[Yaxing], Hook, L.A.[Les A.], McMurry, B.F.[Benjamin F.],
A Semi-Automated Workflow Solution for Data Set Publication,
IJGI(5), No. 3, 2016, pp. 30.
DOI Link 1604
BibRef

Stratoulias, D.[Dimitris], Tolpekin, V.[Valentyn], de By, R.A.[Rolf A.], Zurita-Milla, R.[Raul], Retsios, V.[Vasilios], Bijker, W.[Wietske], Hasan, M.A.[Mohammad Alfi], Vermote, E.[Eric],
A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Slocum, R.K.[Richard K.], Parrish, C.E.[Christopher E.],
Simulated Imagery Rendering Workflow for UAS-Based Photogrammetric 3D Reconstruction Accuracy Assessments,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Aasen, H.[Helge], Honkavaara, E.[Eija], Lucieer, A.[Arko], Zarco-Tejada, P.J.[Pablo J.],
Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Chabot, D.[Dominique], Dillon, C.[Christopher], Shemrock, A.[Adam], Weissflog, N.[Nicholas], Sager, E.P.S.[Eric P. S.],
An Object-Based Image Analysis Workflow for Monitoring Shallow-Water Aquatic Vegetation in Multispectral Drone Imagery,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Lancheros, E.[Estefany], Camps, A.[Adriano], Park, H.[Hyuk], Rodriguez, P.[Pedro], Tonetti, S.[Stefania], Cote, J.[Judith], Pierotti, S.[Stephane],
Selection of the Key Earth Observation Sensors and Platforms Focusing on Applications for Polar Regions in the Scope of Copernicus System 2020-2030,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Seyednasrollah, B.[Bijan], Milliman, T.[Thomas], Richardson, A.D.[Andrew D.],
Data extraction from digital repeat photography using xROI: An interactive framework to facilitate the process,
PandRS(152), 2019, pp. 132-144.
Elsevier DOI 1905
Digital repeat photography, xROI, ROI, Time-series, Phenology, PhenoCam BibRef

Stöcker, C.[Claudia], Ho, S.[Serene], Nkerabigwi, P.[Placide], Schmidt, C.[Cornelia], Koeva, M.[Mila], Bennett, R.[Rohan], Zevenbergen, J.[Jaap],
Unmanned Aerial System Imagery, Land Data and User Needs: A Socio-Technical Assessment in Rwanda,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Sun, J., Zhang, Y., Wu, Z., Zhu, Y., Yin, X., Ding, Z., Wei, Z., Plaza, J., Plaza, A.,
An Efficient and Scalable Framework for Processing Remotely Sensed Big Data in Cloud Computing Environments,
GeoRS(57), No. 7, July 2019, pp. 4294-4308.
IEEE DOI 1907
Remote sensing, Task analysis, Cloud computing, Processor scheduling, Big Data, Optimization, Training, task scheduling BibRef

Doukari, M.[Michaela], Batsaris, M.[Marios], Papakonstantinou, A.[Apostolos], Topouzelis, K.[Konstantinos],
A Protocol for Aerial Survey in Coastal Areas Using UAS,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Hou, Z.W.[Zhi-Wei], Qin, C.Z.[Cheng-Zhi], Zhu, A.X.[A-Xing], Liang, P.[Peng], Wang, Y.J.[Yi-Jie], Zhu, Y.Q.A.[Yun-Qi-Ang],
From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Perko, R.[Roland], Raggam, H.[Hannes], Roth, P.M.[Peter M.],
Mapping with Pléiades: End-to-End Workflow,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

He, Y.H.[Yu-Hong], Yang, J.[Jian], Caspersen, J.[John], Jones, T.[Trevor],
An Operational Workflow of Deciduous-Dominated Forest Species Classification: Crown Delineation, Gap Elimination, and Object-Based Classification,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Siegmann, B.[Bastian], Alonso, L.[Luis], Celesti, M.[Marco], Cogliati, S.[Sergio], Colombo, R.[Roberto], Damm, A.[Alexander], Douglas, S.[Sarah], Guanter, L.[Luis], Hanuš, J.[Jan], Kataja, K.[Kari], Kraska, T.[Thorsten], Matveeva, M.[Maria], Moreno, J.[Jóse], Muller, O.[Onno], Pikl, M.[Miroslav], Pinto, F.[Francisco], Vargas, J.Q.[Juan Quirós], Rademske, P.[Patrick], Rodriguez-Morene, F.[Fernando], Sabater, N.[Neus], Schickling, A.[Anke], Schüttemeyer, D.[Dirk], Zemek, F.[František], Rascher, U.[Uwe],
The High-Performance Airborne Imaging Spectrometer HyPlant: From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Rist, F.[Florian], Gabriel, D.[Doreen], Mack, J.[Jennifer], Steinhage, V.[Volker], Töpfer, R.[Reinhard], Herzog, K.[Katja],
Combination of an Automated 3D Field Phenotyping Workflow and Predictive Modelling for High-Throughput and Non-Invasive Phenotyping of Grape Bunches,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Lv, Y.[Yafei], Zhang, X.H.[Xiao-Han], Xiong, W.[Wei], Cui, Y.[Yaqi], Cai, M.[Mi],
An End-to-End Local-Global-Fusion Feature Extraction Network for Remote Sensing Image Scene Classification,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Sedona, R.[Rocco], Cavallaro, G.[Gabriele], Jitsev, J.[Jenia], Strube, A.[Alexandre], Riedel, M.[Morris], Benediktsson, J.A.[Jón Atli],
Remote Sensing Big Data Classification with High Performance Distributed Deep Learning,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Chen, Y.[Yaxin], Xu, M.Z.[Miao-Zhong], Shen, X.[Xin], Zhang, G.[Guo], Lu, Z.Z.[Ze-Zhong], Xu, J.F.[Jun-Fei],
A Multi-Objective Modeling Method of Multi-Satellite Imaging Task Planning for Large Regional Mapping,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Deibe, D.[David], Amor, M.[Margarita], Doallo, R.[Ramón],
Big Data Geospatial Processing for Massive Aerial LiDAR Datasets,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Sun, Z.H.[Zi-Heng], Di, L.P.[Li-Ping], Burgess, A.[Annie], Tullis, J.A.[Jason A.], Magill, A.B.[Andrew B.],
Geoweaver: Advanced Cyberinfrastructure for Managing Hybrid Geoscientific AI Workflows,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Moreno-Marimbaldo, F.J.[Francisco-Javier], Manso-Callejo, M.Á.[Miguel-Ángel],
Methodological Approach to Incorporate the Involve of Stakeholders in the Geodesign Workflow of Transmission Line Projects,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Shiratori, S.[Shota], Fujimoto, Y.[Yuichiro], Fujita, K.[Kinya],
Predicting Uninterruptible Durations of Office Workers by Using Probabilistic Work Continuance Model,
IEICE(E103-D), No. 4, April 2020, pp. 838-849.
WWW Link. 2004
BibRef

Blanch, X.[Xabier], Abellan, A.[Antonio], Guinau, M.[Marta],
Point Cloud Stacking: A Workflow to Enhance 3D Monitoring Capabilities Using Time-Lapse Cameras,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Bebortta, S.[Sujit], Das, S.K.[Saneev Kumar], Kandpal, M.[Meenakshi], Barik, R.K.[Rabindra Kumar], Dubey, H.[Harishchandra],
Geospatial Serverless Computing: Architectures, Tools and Future Directions,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Tamiminia, H.[Haifa], Salehi, B.[Bahram], Mahdianpari, M.[Masoud], Quackenbush, L.J.[Lindi J.], Adeli, S.[Sarina], Brisco, B.[Brian],
Google Earth Engine for geo-big data applications: A meta-analysis and systematic review,
PandRS(164), 2020, pp. 152-170.
Elsevier DOI 2005
Google Earth Engine, Geo-big data, Cloud-based platform, Remote sensing, Planetary-scale, Geospatial, Machine learning, Environmental monitoring BibRef

Ghorbanian, A.[Arsalan], Kakooei, M.[Mohammad], Amani, M.[Meisam], Mahdavi, S.[Sahel], Mohammadzadeh, A.[Ali], Hasanlou, M.[Mahdi],
Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples,
PandRS(167), 2020, pp. 276-288.
Elsevier DOI 2008
Land cover classification, Sentinel, Google Earth Engine, Big data, Remote sensing, Iran BibRef

Alkadri, M.F.[Miktha Farid], de Luca, F.[Francesco], Turrin, M.[Michela], Sariyildiz, S.[Sevil],
A Computational Workflow for Generating A Voxel-Based Design Approach Based on Subtractive Shading Envelopes and Attribute Information of Point Cloud Data,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Farella, E.M.[Elisa Mariarosaria], Torresani, A.[Alessandro], Remondino, F.[Fabio],
Refining the Joint 3D Processing of Terrestrial and UAV Images Using Quality Measures,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Kammerhofer, D.[David], Scholz, J.[Johannes],
An Approach to Decompose and Evaluate a Complex GIS-Application Design to a Simple, Lightweight, User-Centered App-Based Design Using User Experience Evaluation,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Deininger, M.E.[Martina E.], von der Grün, M.[Maximilian], Piepereit, R.[Raul], Schneider, S.[Sven], Santhanavanich, T.[Thunyathep], Coors, V.[Volker], Voß, U.[Ursula],
A Continuous, Semi-Automated Workflow: From 3D City Models with Geometric Optimization and CFD Simulations to Visualization of Wind in an Urban Environment,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Tao, W., Hua, X., Yu, K., Chen, X., Zhao, B.,
A Pipeline for 3-D Object Recognition Based on Local Shape Description in Cluttered Scenes,
GeoRS(59), No. 1, January 2021, pp. 801-816.
IEEE DOI 2012
Object recognition, Shape, Clutter, Indexes, Histograms, Pipelines, Clutter, local reference frame (LRF), point cloud BibRef

ul Hussnain, M.Q.[Muhammad Qadeer], Waheed, A.[Abdul], Wakil, K.[Khydija], Jabbar, J.A.[Junaid Abdul], Pettit, C.J.[Christopher James], Tahir, A.[Ali],
Evaluating a Workflow Tool for Simplifying Scenario Planning with the Online WhatIf? Planning Support System,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Apollonio, F.I.[Fabrizio Ivan], Fantini, F.[Filippo], Garagnani, S.[Simone], Gaiani, M.[Marco],
A Photogrammetry-Based Workflow for the Accurate 3D Construction and Visualization of Museums Assets,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Šecerov, I.[Ivan], Popov, S.[Srdan], Sladojevic, S.[Srdan], Milin, D.[Dragana], Lazic, L.[Lazar], Miloševic, D.[Dragan], Arsenovic, D.[Daniela], Savic, S.[Stevan],
Achieving High Reliability in Data Acquisition,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Mancini, F.[Francesco], Grassi, F.[Francesca], Cenni, N.[Nicola],
A Workflow Based on SNAP-StaMPS Open-Source Tools and GNSS Data for PSI-Based Ground Deformation Using Dual-Orbit Sentinel-1 Data: Accuracy Assessment with Error Propagation Analysis,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Rezník, T.[Tomáš], Chytrý, J.[Jan], Trojanová, K.[Katerina],
Machine Learning-Based Processing Proof-of-Concept Pipeline for Semi-Automatic Sentinel-2 Imagery Download, Cloudiness Filtering, Classifications, and Updates of Open Land Use/Land Cover Datasets,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Li, X.X.[Xiu-Xia], Liang, S.L.[Shun-Lin], Jin, H.[Huaan],
An Effective Method for Generating Spatiotemporally Continuous 30 m Vegetation Products,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Schramm, M.[Matthias], Pebesma, E.[Edzer], Milenkovic, M.[Milutin], Foresta, L.[Luca], Dries, J.[Jeroen], Jacob, A.[Alexander], Wagner, W.[Wolfgang], Mohr, M.[Matthias], Neteler, M.[Markus], Kadunc, M.[Miha], Miksa, T.[Tomasz], Kempeneers, P.[Pieter], Verbesselt, J.[Jan], Gößwein, B.[Bernhard], Navacchi, C.[Claudio], Lippens, S.[Stefaan], Reiche, J.[Johannes],
The openEO API-Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Shi, Z.[Zhen], Zhao, Y.[Yong], He, F.[Fei], Yao, Z.H.[Zhong-Hua], Rong, Z.J.[Zhao-Jin], Wei, Y.[Yong],
Automatic Scheduling Tool for Balloon-Borne Planetary Optical Remote Sensing,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Blanch, X.[Xabier], Eltner, A.[Anette], Guinau, M.[Marta], Abellan, A.[Antonio],
Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhou, X.H.[Xiao-Hua], Wang, X.Z.[Xue-Zhi], Zhou, Y.C.[Yuan-Chun], Lin, Q.H.[Qing-Hui], Zhao, J.H.[Jiang-Hua], Meng, X.H.[Xiang-Hai],
RSIMS: Large-Scale Heterogeneous Remote Sensing Images Management System,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Hua, Y.S.[Yuan-Sheng], Mou, L.C.[Li-Chao], Lin, J.Z.[Jian-Zhe], Heidler, K.[Konrad], Zhu, X.X.[Xiao Xiang],
Aerial scene understanding in the wild: Multi-scene recognition via prototype-based memory networks,
PandRS(177), 2021, pp. 89-102.
Elsevier DOI 2106
Convolutional neural network (CNN), Multi-scene recognition in single images, Memory network, Prototype learning BibRef

Iandelli, N.[Niccolò], Coli, M.[Massimo], Donigaglia, T.[Tessa], Ciuffreda, A.L.[Anna Livia],
An Unconventional Field Mapping Application: A Complete Opensource Workflow Solution Applied to Lithological Mapping of the Coatings of Cultural Heritage,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Kavaliauskas, P.[Paulius], Židanavicius, D.[Daumantas], Jurelionis, A.[Andrius],
Geometric Accuracy of 3D Reality Mesh Utilization for BIM-Based Earthwork Quantity Estimation Workflows,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Wang, Z.C.[Zhi-Chao], Zhang, X.Y.[Xiao-Yuan], Zheng, J.[Jun], Zhao, Y.[Yao], Wang, J.[Jia], Schmullius, C.[Christiane],
Design of a Generic Virtual Measurement Workflow for Processing Archived Point Cloud of Trees and Its Implementation of Light Condition Measurements on Stems,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Vong, A.[André], Matos-Carvalho, J.P.[João P.], Toffanin, P.[Piero], Pedro, D.[Dário], Azevedo, F.[Fábio], Moutinho, F.[Filipe], Garcia, N.C.[Nuno Cruz], Mora, A.[André],
How to Build a 2D and 3D Aerial Multispectral Map?: All Steps Deeply Explained,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Carrer, D.[Dominique], Meurey, C.[Catherine], Hagolle, O.[Olivier], Bigeard, G.[Guillaume], Paci, A.[Alexandre], Donier, J.M.[Jean-Marie], Bergametti, G.[Gilles], Bergot, T.[Thierry], Calvet, J.C.[Jean-Christophe], Goloub, P.[Philippe], Victori, S.[Stéphane], Wang, Z.[Zhuosen],
Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zapico, I.[Ignacio], Laronne, J.B.[Jonathan B.], Castillo, L.S.[Lázaro Sánchez], Duque, J.F.M.[José F. Martín],
Improvement of Workflow for Topographic Surveys in Long Highwalls of Open Pit Mines with an Unmanned Aerial Vehicle and Structure from Motion,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Deng, M.[Min], Liu, B.J.[Bao-Ju], Li, S.[Sumin], Du, R.H.[Rong-Hua], Wu, G.H.[Guo-Hua], Li, H.F.[Hai-Feng], Wang, L.[Ling],
A Two-Phase Coordinated Planning Approach for Heterogeneous Earth-Observation Resources to Monitor Area Targets,
SMCS(51), No. 10, October 2021, pp. 6388-6403.
IEEE DOI 2109
Planning, Task analysis, Satellites, Resource management, Monitoring, Optimization, Computer architecture, Area target decomposition, task allocation BibRef

Zhao, Q.[Qiang], Yu, L.[Le], Li, X.C.[Xue-Cao], Peng, D.L.[Dai-Liang], Zhang, Y.G.[Yong-Guang], Gong, P.[Peng],
Progress and Trends in the Application of Google Earth and Google Earth Engine,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Hou, Z.W.[Zhi-Wei], Qin, C.Z.[Cheng-Zhi], Zhu, A.X.[A-Xing], Wang, Y.J.[Yi-Jie], Liang, P.[Peng], Wang, Y.J.[Yu-Jing], Zhu, Y.Q.[Yun-Qiang],
Formalizing Parameter Constraints to Support Intelligent Geoprocessing: A SHACL-Based Method,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Frazier, A.E.[Amy E.], Hemingway, B.L.[Benjamin L.],
A Technical Review of Planet Smallsat Data: Practical Considerations for Processing and Using PlanetScope Imagery,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Rosier, I.[Ine], Diels, J.[Jan], Somers, B.[Ben], van Orshoven, J.[Jos],
A Workflow to Extract the Geometry and Type of Vegetated Landscape Elements from Airborne LiDAR Point Clouds,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef


Melet, O., Youssefi, D., L'Helguen, C., Michel, J., Sarrazin, E., Languille, F., Lebègue, L.,
CO3D Mission Digital Surface Model Production Pipeline,
ISPRS20(B2:143-148).
DOI Link 2012
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Swaine, M., Smit, C., Tripodi, S., Fonteix, G., Tarabalka, Y., Laurore, L., Hyland, J.,
Operational Pipeline for A Global Cloud-free Mosaic and Classification Of Sentinel-2 Images,
ISPRS20(B3:195-200).
DOI Link 2012
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Evers, M., Hammer, H., Thiele, A., Schulz, K.,
Strategies for PS Processing of Large Sentinel-1 Datasets,
ISPRS20(B1:99-106).
DOI Link 2012
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Tachi, T., Wang, Y., Abe, R., Kato, T., Maebashi, N., Kishimoto, N.,
Development of Versatile Mobile Mapping System on A Small Scale,
ISPRS20(B1:271-275).
DOI Link 2012
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Li, X.M., Wang, W.X., Tang, S.J., Xia, J.Z., Zhao, Z.G., Li, Y., Zheng, Y., Guo, R.Z.,
A New Cloud-edge-terminal Resources Collaborative Scheduling Framework For Multi-level Visualization Tasks of Large-scale Spatio-temporal Data,
ISPRS20(B4:477-483).
DOI Link 2012
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Buuveibaatar, M., Kim, M.G., Shin, S.P.,
Towards Application of Landinfra Standard for Highway Management In Korea,
ISPRS20(B4:435-439).
DOI Link 2012
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Holland, D.A., Hurst, I., Heathcote, G., Horgan, J., Capstick, D.,
The Changing Nature of Geospatial Data: Challenges for A National Mapping Agency,
ISPRS20(B5:179-183).
DOI Link 2012
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Xi, K., Duan, Y.,
AMS-3000 Large Field View Aerial Mapping System: Basic Principles And The Workflow,
ISPRS20(B1:79-84).
DOI Link 2012
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Ye, J.M.[Jun-Min], Ni, Y.[Yabo], He, Y.M.[You-Min], Wang, R.X.[Ruo-Xi], Jin, C.[Cong], Hao, G.Q.[Guang-Quan],
The design and implementation of a Visual Workflow Modeling tool based on Eclipse plug-ins,
IASP11(572-577).
IEEE DOI 1112
BibRef

Dubucq, D., Audebert, N., Achard, V., Alakian, A., Fabre, S., Credoz, A., Deliot, P., Le Saux, B.,
A Real-world Hyperspectral Image Processing Workflow for Vegetation Stress and Hydrocarbon Indirect Detection,
ISPRS20(B3:395-400).
DOI Link 2012
BibRef

Murray, J., Sargent, I., Holland, D., Gardiner, A., Dionysopoulou, K., Coupland, S., Hare, J., Zhang, C., Atkinson, P.M.,
Opportunities for Machine Learning and Artificial Intelligence In National Mapping Agencies: Enhancing Ordnance Survey Workflow,
ISPRS20(B5:185-189).
DOI Link 2012
BibRef

Zhang, K., Snavely, N., Sun, J.,
Leveraging Vision Reconstruction Pipelines for Satellite Imagery,
3D-Wild19(2139-2148)
IEEE DOI 2004
computer vision, image reconstruction, remote sensing, solid modelling, stereo image processing, satellite imagery, Remote Sensing BibRef

Li, J.M., Li, C.R., Su, G.Z., Li, W., Ma, L.L., Liu, Y.K.,
Mapping System and Photogrammetric Processing Method for Tethered Balloon Platform,
PIA19(157-161).
DOI Link 1912
BibRef

Olsson, P.O., Johansson, T., Eriksson, H., Lithén, T., Bengtsson, L.H., Axelsson, J., Roos, U., Neland, K., Rydén, B., Harrie, L.,
Unbroken Digital Data Flow in The Built Environment Process - a Case Study in Sweden,
SmartGeoApps19(1347-1352).
DOI Link 1912
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Radford, C.R., Bevan, G.,
A Calibration Workflow for 'Prosumer' UAV Cameras,
UAV-g19(553-558).
DOI Link 1912
BibRef

Ajmar, A., Arco, E., Boccardo, P.,
Road Network Comparison and Matching Techniques. a Workflow Proposal For The Integration of Traffic Message Channel and Open Source Network Datasets,
C3MGBD19(1503-1509).
DOI Link 1912
BibRef

Herbig, U., Stampfer, L., Grandits, D., Mayer, I., Pöchtrager, M., Ikaputra, Setyastuti, A.,
Developing a Monitoring Workflow for The Temples of Java,
CIPA19(555-562).
DOI Link 1912
BibRef

Sammartano, G., Spanò, A., Teppati Losè, L.,
A Fusion-based Workflow for Turning Slam Point Clouds and Fisheye Data Into Texture-enhanced 3d Models,
LC3D19(295-302).
DOI Link 1912
BibRef

Pamart, A., Morlet, F., de Luca, L.,
A Fully Automated Incremental Photogrammetric Processing Dedicated For Collaborative Remote-computing Workflow,
3DARCH19(565-571).
DOI Link 1904
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Previtali, M.[Mattia], Banfi, F.[Fabrizio],
Towards the Definition of Workflows for Automation in HBIM Generation,
EuroMed18(I:52-63).
Springer DOI 1811
BibRef

Federman, A., Santana Quintero, M., Kretz, S., Gregg, J., Lengies, M., Ouimet, C., Laliberte, J.,
UAV Photgrammetric Workflows: A Best Practice Guideline,
CIPA17(237-244).
DOI Link 1805
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Gonizzi Barsanti, S., Guidi, G.,
A Geometric Processing Workflow for Transforming Reality-based 3d Models in Volumetric Meshes Suitable for FEA,
3DARCH17(331-338).
DOI Link 1805
Finite Element Analysis. BibRef

Santana Quintero, M.,
Harnessing Digital Workflows for Conserving Historic Places,
GeomCultural17(9-14).
DOI Link 1805
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Pfarr-Harfst, M.[Mieke],
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Data processing workflows from low-cost digital survey to various applications: three case studies of Chinese historic architecture,
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Lübker, T., Schaab, G.,
A Work-Flow Design for Large-Area Multilevel Geobia: Integrating Statistical Measures and Expert Knowledge,
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Remote Sensing Hardware Implementations, Vehicles, UAV Systems, Drones, UAS .


Last update:Nov 30, 2021 at 22:19:38