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Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2021-01-18 Ali Mokhtari, Hamideh Noory, Abdullah Balkhi, Sina Alaghmand
Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated
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Road Surface Reconstruction by Stereo Vision PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-11-18 Hauke Brunken, Clemens Gühmann
This paper covers the problem of road surface reconstruction by stereo vision with cameras placed behind the windshield of a moving vehicle. An algorithm was developed that employs a plane-sweep approach and uses semi-global matching for optimization. Different similarity measures were evaluated for the task of matching pixels, namely mutual information, background subtraction by bilateral filtering
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Geometrically Corrected 50 Megapixel Thermal Imaging with Full Radiometric Information PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-11-09 Sebastian Fiedler, Roland Clauß, Stefan Knoblach
Thermal imaging has become a valuable method for quality control, damage detection and the identification of energy losses. As in every other method, the resolution is crucial for the outcome of analyses and experiments. State of the art thermography cameras have sensors with 1024 \(\times \) 768 pixels, which can record thermal images up to 3.1 megapixels via sensor motion and interpolation. Being
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Investigating the Potential of a Newly Developed UAV-based VNIR/SWIR Imaging System for Forage Mass Monitoring PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-10-28 Alexander Jenal, Ulrike Lussem, Andreas Bolten, Martin Leon Gnyp, Jürgen Schellberg, Jörg Jasper, Jens Bongartz, Georg Bareth
Remote sensing systems based on unmanned aerial vehicles (UAVs) are well suited for airborne monitoring of small to medium-sized farmland in agricultural applications. An imaging system is often used in the form of a multispectral multi-camera system to derive well-established vegetation indices (VIs) efficiently. This study investigates the potential of such a multi-camera system with a novel approach
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On the Evaluation of CNN Models in Remote-Sensing Scene Classification Domain PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-10-23 Ozlem Sen, Hacer Yalim Keles
Land-cover and land-use classification from aerial images is a challenging problem due to high intra-class diversity and inter-class similarities of the images. To analyze the performances of deep convolutional neural network (CNN) models in this domain, we provide three pre-trained CNN models that are adapted to NWPU-RESISC45 dataset using three different training splits, i.e., 80%, 20%, and 10% ratios
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Optimizing the Achievable Information Content Extraction from WorldView-4 Stereo Imagery PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-09-29 Umut G. Sefercik, Mehmet Alkan, Can Atalay, Karsten Jacobsen, Gürcan Büyüksalih, Serkan Karakış
In 2016, DigitalGlobe’s third-generation commercial Earth observation satellite WorldView-4 (WV-4), which offered 31 cm spatial resolution for panchromatic imagery, was launched and was active up to January 2019. Together with WorldView-3, this is the highest ground resolution of civilian optical space-borne missions. In this study, the information content of WV-4′s pan-sharpened stereo imagery is
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A Hybrid Deep ResNet and Inception Model for Hyperspectral Image Classification PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-09-03 Bandar Alotaibi, Munif Alotaibi
Over the past few decades, hyperspectral image (HSI) classification has garnered increasing attention from the remote sensing research community. The largest challenge faced by HSI classification is the high feature dimensions represented by the different HSI bands given the limited number of labeled samples. Deep learning and convolutional neural networks (CNNs), in particular, have been shown to
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Monitoring Forage Mass with Low-Cost UAV Data: Case Study at the Rengen Grassland Experiment PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-31 Ulrike Lussem, Jürgen Schellberg, Georg Bareth
Monitoring and predicting above ground biomass yield of grasslands are of key importance for grassland management. Established manual methods such as clipping or rising plate meter measurements provide accurate estimates of forage yield, but are time consuming and labor intensive, and do not provide spatially continuous data as required for precision agriculture applications. Therefore, the main objective
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Comparison of Direct and Indirect Determination of Leaf Area Index in Permanent Grassland PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-20 Andreas Klingler, Andreas Schaumberger, Francesco Vuolo, László B. Kalmár, Erich M. Pötsch
Indirect, non-destructive methods to derive biophysical parameters, such as leaf area index (LAI), are of major importance for optimal grassland growth modelling and management. In this study, we compared different methods for the estimation of LAI in permanent grassland including (i) two direct methods, (ii) two indirect optical methods (AccuPAR and LAI-2200C), (iii) a proximal (field spectrometer)
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Time-Series Analysis of Subsidence in Nanning, China, Based on Sentinel-1A Data by the SBAS InSAR Method PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-20 Bing Li, Zemin Wang, Jiachun An, Chunxia Zhou, Yuanyuan Ma
Recent research has demonstrated that the Sentinel-1 constellation can be used for continuous tracking of ground deformation phenomena. In this study, the spatial–temporal subsidence characteristics in Nanning were investigated with 18 Sentinel-1A TOPS synthetic aperture radar (SAR) images acquired from 25 June 2015 to 16 December 2016 based on the small baseline subset interferometric SAR (SBAS InSAR)
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Mapping Invasive Lupinus polyphyllus Lindl. in Semi-natural Grasslands Using Object-Based Image Analysis of UAV-borne Images PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-07 Jayan Wijesingha, Thomas Astor, Damian Schulze-Brüninghoff, Michael Wachendorf
Knowledge on the spatio-temporal distribution of invasive plant species is vital to maintain biodiversity in grasslands which are threatened by the invasion of such plants and to evaluate the effect of control activities conducted. Manual digitising of aerial images with field verification is the standard method to create maps of the invasive Lupinus polyphyllus Lindl. (Lupine) in semi-natural grasslands
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Estimating Grassland Parameters from Sentinel-2: A Model Comparison Study PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-05 M. Schwieder, M. Buddeberg, K. Kowalski, K. Pfoch, J. Bartsch, H. Bach, J. Pickert, P. Hostert
Grassland plays an important role in German agriculture. The interplay of ecological processes in grasslands secures important ecosystem functions and, thus, ultimately contributes to essential ecosystem services. To sustain, e.g., the provision of fodder or the filter function of soils, agricultural management needs to adapt to site-specific grassland characteristics. Spatially explicit information
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Cassava NDVI Analysis: A Nonlinear Mixed Model Approach Based on UAV-Imagery PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-08-05 D. Grados, E. Schrevens
Imagery data captured by unmanned aerial vehicles (\({\text{UAVs}}\)) have become important tools to study crop growth and development in experimental agronomic research. Moreover, growth curve analysis and nonlinear mixed-effects models (\({\text{NLME}}\)) are increasingly being used to study nonlinear crop responses in the context of repeated measurements. An \({\text{NLME}}\) to fit the Normalized
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Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-07-07 Torben Peters, Claus Brenner
We investigate whether conditional generative adversarial networks (C-GANs) are suitable for point cloud rendering. For this purpose, we created a dataset containing approximately 150,000 renderings of point cloud–image pairs. The dataset was recorded using our mobile mapping system, with capture dates that spread across 1 year. Our model learns how to predict realistically looking images from just
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Potential of Large-Scale Inland Water Body Mapping from Sentinel-1/2 Data on the Example of Bavaria’s Lakes and Rivers PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-05-18 Michael Schmitt
The mapping of water bodies is an important application area of satellite-based remote sensing. In this contribution, a simple framework based on supervised learning and automatic training data annotation is shown, which allows to map inland water bodies from Sentinel satellite data on large scale, i.e. on state level. Using the German state of Bavaria as an example and different combinations of Sentinel-1
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Augmented Reality and Virtual Reality Applications Based on Satellite-Borne and ISS-Borne Remote Sensing Data for School Lessons PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-04-30 Andreas Rienow, Claudia Lindner, Torben Dedring, Henryk Hodam, Annette Ortwein, Johannes Schultz, Fabian Selg, Kilian Staar, Carsten Jürgens
Facing global challenges, a qualified education in remote sensing technologies needs to start in school to sensitise teachers and thus young people for ecological issues and develop their technological skills. Remote sensing is part of the STEM (Science, Technology, Engineering and Mathematics) curricular topics, all of which are either a requirement for or benefit from remote sensing. However, implementing
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Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-30 Hubert Lehner, Lionel Dorffner
Virtual 3D city models usually evolved from other geodata sets and were not set up from scratch. As traditional geodata used to be only 2D and 2.5D for a long time, 3D city models started naturally with 3D building models. On the one hand, this has a technical aspect, because buildings, especially when being modelled in a higher level of detail, can neither be described in 2D nor in 2.5D. On the other
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Correction to: Official 3D Spatial Base Data in Germany PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-04-16 Ulrich Gruber
The publication of this article unfortunately contained a mistake. A second author was erroneously added and has been removed. The corrected list of authors is given above.
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Augmented Reality Geovisualisation for Underground Utilities PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-04-07 E. Stylianidis, E. Valari, A. Pagani, I. Carrillo, A. Kounoudes, K. Michail, K. Smagas
Prior to an excavation for a construction project, fieldwork is necessary to identify the location of all underground utilities. There is a demand for identifying the accurate positioning of the underground utilities, in order to support the contractors in avoiding damages to existing underground infrastructures. Such damages could cost thousands of euros, needless to underline the danger in human
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Stuttgart City Walk: A Case Study on Visualizing Textured DSM Meshes for the General Public Using Virtual Reality PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-27 Stefan Schmohl, Patrick Tutzauer, Norbert Haala
Within this paper, we present the implementation of a walkable virtual city model, created from aerial images of downtown Stuttgart. For this purpose, textured 3D meshes were automatically generated using commercial off-the-shelf multi-view stereo image matching software. This data provided the content for a VR framework based on the Unity game engine. Thus, an interactive data presentation using the
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An Empirical Study on Spatial Presence in Immersive Geo-Environments PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-25 Florian Hruby, León F. Álvarez Sánchez, Rainer Ressl, Elva G. Escobar-Briones
Research on immersive virtual reality (VR) indicates that VR technologies facilitate understanding through the formation of spatial presence, which is the user’s feeling of “being there” in a virtual place. These findings make VR a highly interesting tool for geographic information science and the visualization of geospatial phenomena. However, immersion and presence are often studied under laboratory
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On the Use of Complex Flower Pollination Algorithm for Coherence Optimisation In Polarimetric SAR Interferometry PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-19 Sofiane Tahraoui, Mounira Ouarzeddine, Boularbah Souissi
This paper presents a new interferometric coherence optimisation approach based on the flower pollination algorithm, called flower pollination interferometric coherence optimisation (FPICO). FPA is a newly developed algorithm based on the pollination process of plants that is used to solve constrained and/or multiobjective optimisation problems. The proposed approach gives us the possibility to control
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Augmented Reality (AR) and Spatial Cognition: Effects of Holographic Grids on Distance Estimation and Location Memory in a 3D Indoor Scenario PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-19 Julian Keil, Annika Korte, Anna Ratmer, Dennis Edler, Frank Dickmann
Recent advances in augmented reality (AR) technology enable the projection of holograms to a fixed location in 3D space. This renders new possibilities for influencing peoples’ spatial perception and to address cognitive limitations as structural distortions in cognitive representations of space. The study presented in this paper investigated whether these structural distortions can be reduced by projecting
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Architects, Urban Planners and Further Development of the 3D City Model Kassel PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-03 Christoph Meise, Wolfgang Schmidt, Sandra Rus
In the last years, 3D city models have become an important topic in the Geoinformation Departments of many German cities. The city of Kassel began building such a database more than 10 years ago. The most important application area of the now quite extensive database is the support of urban development processes as well as a visually sustainable improvement in the preparation and integration of construction
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A Concept of Quality Management of 3D City Models Supporting Application-Specific Requirements PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-03-03 Volker Coors, Matthias Betz, Eric Duminil
In this paper, a novel approach to specify application-specific requirements for 3D City Models is proposed. A modular set of geometric and semantic requirements that are based on the OGC CityGML Quality Interoperability Experiment (Coors and Wagner in Fernerkundung und Geoinformation eV 24:288–295, 2015) has been specified. Depending on the purpose of the model, not all requirements are mandatory
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Preserving the Knowledge of the Past Through Virtual Visits: From 3D Laser Scanning to Virtual Reality Visualisation at the Istanbul Çatalca İnceğiz Caves PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-28 Gürcan Büyüksalih, Tuna Kan, Gözde Enç Özkan, Müge Meriç, Lale Isın, Thomas P. Kersten
Cultural landscapes are those that are shaped through the combined forces of cultural and natural activity, typically over a long period that may reach back to historic and prehistoric times. Amongst these, the documenting, modelling and visualisation of cave landscapes have always been particularly important for scientific communities such as speleology. In the current state of the art, terrestrial
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A New Method of Improving the Azimuth in Mountainous Terrain by Skyline Matching PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-26 Balázs Nagy
Augmented reality (AR) applications have a serious problem with the accuracy of the azimuth angle provided by mobile devices. The fusion of the digital magnetic compass (DMC), accelerometer and gyroscope gives the translation and rotation of the observer in 3D space. However, the precision is not always appropriate since DMC is prone to interference when using it near metal objects or electric currents
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Strategy for Crack Width Measurement of Multiple Crack Patterns in Civil Engineering Material Testing Using a Monocular Image Sequence Analysis PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-26 F. Liebold, H.-G. Maas
An image sequence analysis procedure is developed to quantitatively analyze complex multiple crack patterns in tension tests of fiber-reinforced composite specimens. Planar textured surfaces of such specimens can be observed with a monocular image sequence using a camera of suitable spatial and temporal resolution. Due to the narrow crack paths, a dense high-precision displacement vector field is computed
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Wavelet Thresholding-Based Despeckling of COSMO-SkyMed SAR Image PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-26 Tapas Kumar Dey, Biswajit Samanta, Debashish Chakravarty, Arundhati Misra
The selection of an efficient speckle filter for SAR imagery primarily depends upon a specific application of interest and statistical characteristics of the noise present in SAR datasets. The main goal of this study is to assess the performance of the two wavelet shrinkage-based filtering techniques (VISU shrink and SURE shrink) against two spatial adaptive filters (Enhanced Lee and Gamma MAP) and
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CityGML 3.0: New Functions Open Up New Applications PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-26 Tatjana Kutzner, Kanishk Chaturvedi, Thomas H. Kolbe
The development of the next major version 3.0 of the international OGC standard CityGML is nearing its end. CityGML 3.0 will come up with a variety of new features and revisions of existing modules that will increase the usability of CityGML for more user groups and areas of application. This includes a new space concept, a revised level-of-detail (LOD) concept, the representation of time-dependent
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Geospatial Artificial Intelligence: Potentials of Machine Learning for 3D Point Clouds and Geospatial Digital Twins PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-26 Jürgen Döllner
Artificial intelligence (AI) is changing fundamentally the way how IT solutions are implemented and operated across all application domains, including the geospatial domain. This contribution outlines AI-based techniques for 3D point clouds and geospatial digital twins as generic components of geospatial AI. First, we briefly reflect on the term “AI” and outline technology developments needed to apply
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DecHPoints: A New Tool for Improving LiDAR Data Filtering in Urban Areas PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-04 Sandra Buján, Chester Andrew Sellers, Miguel Cordero, David Miranda
Identifying ground points from LiDAR data remains a challenge more than 2 decades after automatic filtering methods were first developed. The efficacy of filtering methods depends on both the physical characteristics of the environment and on the quality of the data used. Other limitations, affecting accessibility and usability, include the choice of filter and identification of optimal parameter values
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GIM and BIM PFG J. Photogramm. Remote Sens. Geoinf. Sci. (IF 1.395) Pub Date : 2020-02-04 Stefan Herle, Ralf Becker, Raymond Wollenberg, Jörg Blankenbach
Geospatial information modelling (GIM) is used for decades to document phenomena of the real world. Visualizing and analysing GIM data are usually accomplished by geographic information system tools. The construction industry, on the other hand, uses usually computer-aided design (CAD) tools to plan buildings. With the introduction of building information modelling (BIM), modelling in CAD was enhanced