The increasing need for accurate bathymetric mapping is essential for a plethora of offshore activities. Even though aerial image datasets through Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques can provide a low-cost alternative compared to LiDAR and SONAR, offering additionally, important visual information, water refraction poses significant obstacles in delivering accurate bathymetry

Topo-bathymetric LiDAR data captured with modern systems are complex. The primary information received is a time-dependent amplitude variation of the reflected light. These so-called waveforms are processed into singular points with 3D coordinates by advanced on-board devices of the LiDAR sensor (online waveform processing), but the full-waveform (FWF) information may be available as well. However

Creating 3D models of the static environment is an important task for the advancement of driver assistance systems and autonomous driving. In this work, a static reference map is created from a Mobile Mapping “light detection and ranging” (LiDAR) dataset. The data was obtained in 14 measurement runs from March to October 2017 in Hannover and consists in total of about 15 billion points. The point cloud

For the need arising from EU, federal and state law for large-scale, area-wide and high-resolution morphological data of the seabed and the adjacent coasts, the Schleswig-Holstein State Agency for Coastal Protection, National Park and Marine Conservation (LKN.SH) uses the method of laser bathymetry, which replaces ship-based hydrographic surveys in shallow water areas of the Wadden Sea and the coastal

Knowledge of the static and morphodynamic components of the river bed is important for the maintenance of waterways. Under the action of a current, parts of the river bed sediments can move in the form of dunes. Recordings of the river bed by multibeam echosounding are used as input data within a morphological analysis in order to compute the bedload transport rate using detected dune shape and migration

To achieve a geometrically accurate representation of the water bottom, airborne LiDAR bathymetry (ALB) requires the correction of the raw 3D point coordinates due to refraction at the air–water interface, different signal velocity in air and water, and further propagation induced effects. The processing of bathymetric LiDAR data is based on a geometric model of the laser bathymetry pulse propagation

Besides airborne laser bathymetry and multimedia photogrammetry, spectrally derived bathymetry provides a third optical method for deriving water depths. In this paper, we introduce BathyNet, an U-net like convolutional neural network, based on high-resolution, multispectral RGBC (red, green, blue, coastal blue) aerial images. The approach combines photogrammetric and radiometric methods: Preprocessing

In recent decades, glaciers outside Greenland and Antarctica have shown increasingly rapid rates of mass loss and retreat of the ice front, which is associated with climatic and oceanic warming. Due to their maritime location, Icelandic glaciers are sensitive to short-term climate fluctuations and have shown rapid rates of retreat and mass loss over the last decade. In this study, historical maps (1941–1949)

The complexity of the atmosphere renders the modelling of the atmospheric delay in multi temporal InSAR difficult. This limits the potential of achieving millimetre accuracy of InSAR-derived deformation measurements. In this paper we review advances in tropospheric delay modelling in InSAR, tropospheric correction methods and integration of the correction methods within existing multi temporal algorithms

A correction to this paper has been published: https://doi.org/10.1007/s41064-021-00143-2

Mapping and monitoring of urban land cover are becoming increasingly important in the face of ongoing climate change. The recently launched pair of Sentinel-2 satellites regularly delivers images with the highest spectral and spatial resolution among the freely available images. Based on these data, we proposed an object-based classification method for urban land-cover mapping at two basic scale levels

Increasing numbers of wind power plants (WPP) are constructed across the globe to reduce the anthropogenic contribution to global warming. There are, however, concerns on the effects of WPP on human health as well as related effects on wildlife. To address potential effects of WPP in environmental impact assessments, existing models accounting for shadow flickering and noise are widely applied. However

Cooling supply is expected to be the fastest growing energy consumer of buildings. However, the majority of both comfort and industrial cooling supply is still based on costly and CO2-intensive supply technologies such as compression chillers (CC). At the same time, only sparse information exists on the spatial distribution and installed cooling capacities of cooling installations worldwide. The aim

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

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

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

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

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

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

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

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

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)

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)

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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