22.1.4 Workflow for Remote Sensing, Cartography

Chapter Contents (Back)

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

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

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

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

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

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

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

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.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Tamiminia, H.[Haifa], Salehi, B.[Bahram], Mahdianpari, M.[Masoud], Quackenbush, L.[Lindi], 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

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

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

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

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.
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

Melet, O., Youssefi, D., L'Helguen, C., Michel, J., Sarrazin, E., Languille, F., Lebčgue, L.,
CO3D Mission Digital Surface Model Production Pipeline,
DOI Link 2012

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,
DOI Link 2012

Evers, M., Hammer, H., Thiele, A., Schulz, K.,
Strategies for PS Processing of Large Sentinel-1 Datasets,
DOI Link 2012

Tachi, T., Wang, Y., Abe, R., Kato, T., Maebashi, N., Kishimoto, N.,
Development of Versatile Mobile Mapping System on A Small Scale,
DOI Link 2012

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,
DOI Link 2012

Buuveibaatar, M., Kim, M.G., Shin, S.P.,
Towards Application of Landinfra Standard for Highway Management In Korea,
DOI Link 2012

Holland, D.A., Hurst, I., Heathcote, G., Horgan, J., Capstick, D.,
The Changing Nature of Geospatial Data: Challenges for A National Mapping Agency,
DOI Link 2012

Xi, K., Duan, Y.,
AMS-3000 Large Field View Aerial Mapping System: Basic Principles And The Workflow,
DOI Link 2012

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,

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,
DOI Link 2012

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,
DOI Link 2012

Zhang, K., Snavely, N., Sun, J.,
Leveraging Vision Reconstruction Pipelines for Satellite Imagery,
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,
DOI Link 1912

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,
DOI Link 1912

Radford, C.R., Bevan, G.,
A Calibration Workflow for 'Prosumer' UAV Cameras,
DOI Link 1912

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,
DOI Link 1912

Herbig, U., Stampfer, L., Grandits, D., Mayer, I., Pöchtrager, M., Ikaputra, Setyastuti, A.,
Developing a Monitoring Workflow for The Temples of Java,
DOI Link 1912

Sammartano, G., Spanň, A., Teppati Losč, L.,
A Fusion-based Workflow for Turning Slam Point Clouds and Fisheye Data Into Texture-enhanced 3d Models,
DOI Link 1912

Pamart, A., Morlet, F., de Luca, L.,
A Fully Automated Incremental Photogrammetric Processing Dedicated For Collaborative Remote-computing Workflow,
DOI Link 1904

Previtali, M.[Mattia], Banfi, F.[Fabrizio],
Towards the Definition of Workflows for Automation in HBIM Generation,
Springer DOI 1811

Federman, A., Santana Quintero, M., Kretz, S., Gregg, J., Lengies, M., Ouimet, C., Laliberte, J.,
UAV Photgrammetric Workflows: A Best Practice Guideline,
DOI Link 1805

Gonizzi Barsanti, S., Guidi, G.,
A Geometric Processing Workflow for Transforming Reality-based 3d Models in Volumetric Meshes Suitable for FEA,
DOI Link 1805
Finite Element Analysis. BibRef

Santana Quintero, M.,
Harnessing Digital Workflows for Conserving Historic Places,
DOI Link 1805

Pfarr-Harfst, M.[Mieke],
Typical Workflows, Documentation Approaches and Principles of 3D Digital Reconstruction of Cultural Heritage,
Springer DOI 1611

Yu, H.[Huai], Yan, T.[Tianheng], Yang, W.[Wen], Zheng, H.[Hong],
An Integrative Object-based Image Analysis Workflow For UAV Images,
ISPRS16(B1: 1085-1091).
DOI Link 1610

Anca, P., Calugaru, A., Alixandroae, I., Nazarie, R.,
A Workflow For UAV's Integration Into A Geodesign Platform,
ISPRS16(B1: 1099-1103).
DOI Link 1610

Proctor, C., He, Y.,
Workflow for Building a Hyperspectral UAV: Challenges and Opportunities,
DOI Link 1512

Meijer, M., Vullings, L.A.E., Bulens, J.D., Rip, F.I., Boss, M., Hazeu, G., Storm, M.,
Spatial Data Quality and a Workflow Tool,
DOI Link 1602

Sun, Z., Cao, Y.K.,
Data processing workflows from low-cost digital survey to various applications: three case studies of Chinese historic architecture,
DOI Link 1508

Markelin, L., Honkavaara, E., Näsi, R., Nurminen, K., Hakala, T.,
Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV,
DOI Link 1404

Hong, J.H., Huang, M.L.,
The Design of Intelligent Workflow for GIS Functions: A Data Quality Perspective,
HTML Version. 1311

Holland, D., Gladstone, C., Sargent, I., Horgan, J., Gardiner, A., Freeman, M.,
Automating The Photogrammetric Workflow In A National Mapping Agency,
AnnalsPRS(I-4), No. 2012, pp. 83-88.
HTML Version. 1209

Lübker, T., Schaab, G.,
A Work-Flow Design for Large-Area Multilevel Geobia: Integrating Statistical Measures and Expert Knowledge,
PDF File. 1007

Zhang, Y.G.[Yan-Gu], Chen, S.P.[Sai-Ping], Shen, B.[Bin],
Modeling and analysis using Knowledge-flow and workflow based eXtended Time WorkFlow-net,

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Remote Sensing Hardware Implementations, Vehicles, UAV Systems, Drones, UAS .

Last update:Jan 17, 2021 at 16:22:28