23.1.4 Workflow for Remote Sensing, Cartography

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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

Laliberte, A.S.[Andrea S.], Goforth, M.A.[Mark A.], Steele, C.M.[Caitriana M.], Rango, A.[Albert],
Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments,
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DOI Link 1203
Award, Remote Sensing, Third. 2015. 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.X.[Ya-Xing], 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
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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
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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.Q.[Ya-Qi], 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.X.[Ya-Xin], 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

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, 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

Eischeid, I.[Isabell], Soininen, E.M.[Eeva M.], Assmann, J.J.[Jakob J.], Ims, R.A.[Rolf A.], Madsen, J.[Jesper], Pedersen, Å.Ø.[Åshild Ø.], Pirotti, F.[Francesco], Yoccoz, N.G.[Nigel G.], Ravolainen, V.T.[Virve T.],
Disturbance Mapping in Arctic Tundra Improved by a Planning Workflow for Drone Studies: Advancing Tools for Future Ecosystem Monitoring,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Ortiz-Villarejo, A.J.[Antonio J.], Soler, L.M.G.[Luís-M. Gutiérrez],
A Low-Cost, Easy-Way Workflow for Multi-Scale Archaeological Features Detection Combining LiDAR and Aerial Orthophotography,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Svendsen, D.H.[Daniel Heestermans], Piles, M.[Maria], Muñoz-Marí, J.[Jordi], Luengo, D.[David], Martino, L.[Luca], Camps-Valls, G.[Gustau],
Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions,
GeoRS(60), 2022, pp. 1-15.
IEEE DOI 2112
Data models, Mathematical model, Time series analysis, Biological system modeling, Microwave radiometry, Remote sensing, time series analysis BibRef

Ha, T.[Thuan], Duddu, H.[Hema], Bett, K.[Kirstin], Shirtliffe, S.J.[Steve J.],
A Semi-Automatic Workflow to Extract Irregularly Aligned Plots and Sub-Plots: A Case Study on Lentil Breeding Populations,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Pakdil, M.E.[Mete Ercan], Çelik, R.N.[Rahmi Nurhan],
Serverless Geospatial Data Processing Workflow System Design,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Feoktistov, A.[Alexander], Gorsky, S.[Sergey], Kostromin, R.[Roman], Fedorov, R.[Roman], Bychkov, I.[Igor],
Integration of Web Processing Services with Workflow-Based Scientific Applications for Solving Environmental Monitoring Problems,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Kempeneers, P.[Pieter], Kliment, T.[Tomas], Marletta, L.[Luca], Soille, P.[Pierre],
Parallel Processing Strategies for Geospatial Data in a Cloud Computing Infrastructure,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Nezhad, M.M.[Meysam Majidi], Neshat, M.[Mehdi], Piras, G.[Giuseppe], Garcia, D.A.[Davide Astiaso], Sylaios, G.[Georgios],
Marine Online Platforms of Services to Public End-Users: The Innovation of the ODYSSEA Project,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Gu, X.W.[Xiao-Wei], Angelov, P.P.[Plamen P.], Zhang, C.[Ce], Atkinson, P.M.[Peter M.],
A Semi-Supervised Deep Rule-Based Approach for Complex Satellite Sensor Image Analysis,
PAMI(44), No. 5, May 2022, pp. 2281-2292.
IEEE DOI 2204
Satellites, Image segmentation, Feature extraction, Semantics, Semisupervised learning, Mathematical model, Prototypes, semi-supervised learning BibRef

Gencarelli, C.N.[Christian Natale], Voltolina, D.[Debora], Hammouti, M.[Mohammed], Zazzeri, M.[Marco], Sterlacchini, S.[Simone],
Geospatial Information Technologies for Mobile Collaborative Geological Mapping: The Italian CARG Project Case Study,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Lin, M.[Mingsen], Jia, Y.J.[Yong-Jun],
Past, Present and Future Marine Microwave Satellite Missions in China,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Wu, J.[Jin], Wu, M.B.[Ming-Bo], Li, H.Y.[Hai-Yan], Li, L.J.[Li-Juan], Li, L.L.[Lei-Lei],
A Serverless-Based, On-the-Fly Computing Framework for Remote Sensing Image Collection,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Questad, E.J.[Erin J.], Antill, M.[Marlee], Liu, N.F.[Nan-Feng], Stavros, E.N.[E. Natasha], Townsend, P.A.[Philip A.], Bonfield, S.[Susan], Schimel, D.[David],
A Camera-Based Method for Collecting Rapid Vegetation Data to Support Remote-Sensing Studies of Shrubland Biodiversity,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Casal, G.[Gema], Cordeiro, C.[Clara], McCarthy, T.[Tim],
Using Satellite-Based Data to Facilitate Consistent Monitoring of the Marine Environment around Ireland,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Hagos, D.H.[Desta Haileselassie], Kakantousis, T.[Theofilos], Sheikholeslami, S.[Sina], Wang, T.Z.[Tian-Ze], Vlassov, V.[Vladimir], Payberah, A.H.[Amir Hossein], Meister, M.[Moritz], Andersson, R.[Robin], Dowling, J.[Jim],
Scalable Artificial Intelligence for Earth Observation Data Using Hopsworks,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
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Li, S.Q.[Sheng-Qi], Han, X.Z.[Xiu-Zhen], Weng, F.Z.[Fu-Zhong],
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Ferreira, B.[Bruno], Silva, R.G.[Rui G.], Iten, M.[Muriel],
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Feng, J.F.[Jiang-Fan], Wang, D.[Dini], Gu, Z.J.[Zhu-Jun],
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Howe, C.[Cassandra], Tullis, J.A.[Jason A.],
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Guo, L.H.[Ling-Hui], Zhao, S.[Sha], Gao, J.B.[Jiang-Bo], Zhang, H.[Hebing], Zou, Y.[Youfeng], Xiao, X.M.[Xiang-Ming],
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Varga, L.A.[Leon Amadeus], Koch, S.[Sebastian], Zell, A.[Andreas],
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Wang, H.[Han], Xuan, Y.Q.[Yun-Qing],
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Kastrisios, C.[Christos], Dyer, N.[Noel], Nada, T.[Tamer], Contarinis, S.[Stilianos], Cordero, J.[Jose],
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Petrushevsky, N.[Naomi], Guarnieri, A.M.[Andrea Monti], Manzoni, M.[Marco], Prati, C.[Claudio], Tebaldini, S.[Stefano],
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Feng, Y.X.[Yan-Xiang], Zhang, R.P.[Rui-Peng], Ren, S.[Sida], Zhu, S.[Shuailin], Yang, Y.[Yikang],
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Mestre-Runge, C.[Christian], Lorenzo-Lacruz, J.[Jorge], Ortega-Mclear, A.[Aaron], Garcia, C.[Celso],
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Thiery, F.[Florian], Veller, J.[Jonas], Raddatz, L.[Laura], Rokohl, L.[Louise], Boochs, F.[Frank], Mees, A.W.[Allard W.],
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Zhu, L.[Lilu], Wu, F.[Feng], Fu, K.[Kun], Hu, Y.F.[Yan-Feng], Wang, Y.[Yang], Tian, X.[Xinmei], Huang, K.[Kai],
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Lucas, S.[Sylvain], Johannessen, J.A.[Johnny A.], Cancet, M.[Mathilde], Pettersson, L.H.[Lasse H.], Esau, I.[Igor], Rheinlænder, J.W.[Jonathan W.], Ardhuin, F.[Fabrice], Chapron, B.[Bertrand], Korosov, A.[Anton], Collard, F.[Fabrice], Herlédan, S.[Sylvain], Olason, E.[Einar], Ferrari, R.[Ramiro], Fouchet, E.[Ergane], Donlon, C.[Craig],
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Implementing Cloud Computing for the Digital Mapping of Agricultural Soil Properties from High Resolution UAV Multispectral Imagery,
RS(15), No. 12, 2023, pp. xx-yy.
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Liu, R.[Runzi], Ding, X.[Xu], Wu, W.H.[Wei-Hua], Guo, W.[Wei],
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Romano, G.[Gerardo], Capozzoli, L.[Luigi], Abate, N.[Nicodemo], de Girolamo, M.[Michele], Liso, I.S.[Isabella Serena], Patella, D.[Domenico], Parise, M.[Mario],
An Integrated Geophysical and Unmanned Aerial Systems Surveys for Multi-Sensory, Multi-Scale and Multi-Resolution Cave Detection: The Gravaglione Site (Canale di Pirro Polje, Apulia),
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Jose, K.[Karun], Chaturvedi, R.K.[Rajiv Kumar], Jeganathan, C.[Chockalingam], Behera, M.D.[Mukunda Dev], Singh, C.P.[Chandra Prakash],
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Pál, M.[Márton], Hajdú, E.[Edina],
Methodological Innovations for Establishing Cemetery Spatial Databases: A UAV-Based Workflow Helping Small Communities,
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Wu, Q.Y.[Qian-Yu], Pan, J.[Jun], Wang, M.[Mi],
Dynamic Task Planning Method for Multi-Source Remote Sensing Satellite Cooperative Observation in Complex Scenarios,
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Döweler, F.[Fabian], Fransson, J.E.S.[Johan E. S.], Bader, M.K.F.[Martin K.F.],
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Wang, Z.X.[Zhi-Xing], Zhou, G.[Gaofan], Yao, J.Z.[Jin-Zhen], Zhang, J.L.[Jian-Lin], Bao, Q.L.[Qi-Liang], Hu, Q.[Qintao],
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Gao, W.Q.[Wen-Qi], Chen, N.[Ninghua], Chen, J.Y.[Jian-Yu], Gao, B.[Bowen], Xu, Y.[Yaochen], Weng, X.[Xuhua], Jiang, X.[Xinhao],
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van Gasselt, S.[Stephan], Naß, A.[Andrea],
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Sarkar, A.[Anindya], Lanier, M.[Michael], Alfeld, S.[Scott], Feng, J.R.[Jia-Rui], Garnett, R.[Roman], Jacobs, N.[Nathan], Vorobeychik, Y.[Yevgeniy],
A Visual Active Search Framework for Geospatial Exploration,
WACV24(8301-8310)
IEEE DOI 2404
Visualization, Training data, Reinforcement learning, Search problems, Distance measurement, Geospatial analysis, Social good BibRef

Si, B.[Bo], Wang, Z.[Zhennan], Yu, Z.[Zhoulu], Wang, K.[Ke],
ABNet: An Aggregated Backbone Network Architecture for Fine Landcover Classification,
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Wang, T.H.[Tian-Hang], Chen, G.[Guang], Chen, K.[Kai], Liu, Z.[Zhengfa], Zhang, B.[Bo], Knoll, A.[Alois], Jiang, C.J.[Chang-Jun],
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IEEE DOI 2401
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Robinson, C.[Caleb], Nsutezo, S.F.[Simone Fobi], Ortiz, A.[Anthony], Sederholm, T.[Tina], Dodhia, R.[Rahul], Birge, C.[Cameron], Richards, K.[Kasie], Pitcher, K.[Kris], Duarte, P.[Paulo], Ferres, J.M.L.[Juan M. Lavista],
Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event,
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IEEE DOI 2401
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Qin, H.[Haina], Han, L.F.[Long-Fei], Xiong, W.H.[Wei-Hua], Wang, J.[Juan], Ma, W.T.[Wen-Tao], Li, B.[Bing], Hu, W.M.[Wei-Ming],
Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization,
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Prokofiev, K.[Kirill], Sovrasov, V.[Vladislav],
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Raco, F., Stefani, M., Balzani, M., Ferrari, L.,
Towards Effective Project Documentation, Transparency, and Data-Driven Decision-making Through BIM-Blockchain Based Applications,
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Zhao, H.T., Gao, W.C., Jing, C.F., Li, X.F.,
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Bouziani, M., Mouatassim, H., Fadl, K., Nouari, H.,
Development of a BIM Infrastructure Workflow Adapted To Facilities Of Land Subdivision Projects in Morocco,
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Spallone, R., López González, M.C., Vitali, M., Bertola, G., Natta, F., Ronco, F.,
From Survey to 3d Modelling to Digital Fabrication. a Workflow Aimed at Documenting and Transmitting Built Heritage,
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Cucchetti, E., Latry, C., Blanchet, G., Delvit, J.M., Bruno, M.,
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Lucidi, A., Giordano, E., Clementi, F., Quattrini, R.,
Point Cloud Exploitation for Structural Modeling and Analysis: A Reliable Workflow,
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Melet, O., Youssefi, D., L'Helguen, C., Michel, J., Sarrazin, E., Languille, F., Lebègue, L.,
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Swaine, M., Smit, C., Tripodi, S., Fonteix, G., Tarabalka, Y., Laurore, L., Hyland, J.,
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Evers, M., Hammer, H., Thiele, A., Schulz, K.,
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Tachi, T., Wang, Y., Abe, R., Kato, T., Maebashi, N., Kishimoto, N.,
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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.,
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Buuveibaatar, M., Kim, M.G., Shin, S.P.,
Towards Application of Landinfra Standard for Highway Management In Korea,
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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,
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Xi, K., Duan, Y.,
AMS-3000 Large Field View Aerial Mapping System: Basic Principles And The Workflow,
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Dubucq, D., Audebert, N., Achard, V., Alakian, A., Fabre, S., Credoz, A., Deliot, P., Le Saux, B.,
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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,
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Zhang, K., Snavely, N., Sun, J.,
Leveraging Vision Reconstruction Pipelines for Satellite Imagery,
3D-Wild19(2139-2148)
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computer vision, image reconstruction, remote sensing, solid modelling, stereo image processing, satellite imagery, Remote Sensing BibRef

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Radford, C.R., Bevan, G.,
A Calibration Workflow for 'Prosumer' UAV Cameras,
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Ajmar, A., Arco, E., Boccardo, P.,
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Herbig, U., Stampfer, L., Grandits, D., Mayer, I., Pöchtrager, M., Ikaputra, Setyastuti, A.,
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Sammartano, G., Spanò, A., Teppati Losè, L.,
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Pamart, A., Morlet, F., de Luca, L.,
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Previtali, M.[Mattia], Banfi, F.[Fabrizio],
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Federman, A., Santana Quintero, M., Kretz, S., Gregg, J., Lengies, M., Ouimet, C., Laliberte, J.,
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Gonizzi Barsanti, S., Guidi, G.,
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Santana Quintero, M.,
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Yu, H.[Huai], Yan, T.H.[Tian-Heng], Yang, W.[Wen], Zheng, H.[Hong],
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Anca, P., Calugaru, A., Alixandroae, I., Nazarie, R.,
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Sun, Z., Cao, Y.K.,
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Hong, J.H., Huang, M.L.,
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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:Oct 22, 2024 at 22:09:59