Dorota Iwaszczuk

Technical University of Darmstadt | TU · Department of Civil and Environmental Engineering Sciences (Dept.13)

For the accurate and automatic mapping of forest stands based on very-high-resolution satellite imagery and digital orthophotos, precise object detection at the individual tree level is necessary. Currently, supervised deep learning models are primarily applied for this task. To train a reliable model, it is crucial to have an accurate tree crown a...

3D point clouds are a relevant source of information for multiple applications, including digital twins, building modeling, disaster and risk management, forestry, autonomous driving, and many others. Assigning points to the semantic classes is one of the essential data interpretation steps to effectively use them for further analysis. Deep learnin...

Benefiting from advancements in algorithms and computing capabilities, supervised deep learning models offer significant advantages in accurately mapping individual tree canopy cover, which is a fundamental component of forestry management. In contrast to traditional field measurement methods, deep learning models leveraging remote sensing data cir...

The quality of land use maps often refers to the data quality, but distributional uncertainty between training and test data must also be considered. In order to address this uncertainty, we follow the strategy to detect out-of-distribution samples using uncertainty maps. Then, we use supervised machine learning to identify those samples. For the i...

Due to their low cost and portability, using entertainment devices for indoor mapping applications has become a hot research topic. However, the impact of user behavior on indoor mapping evaluation with entertainment devices is often overlooked in previous studies. This article aims to assess the indoor mapping performance of entertainment devices...

Thanks to the open publication in recent years, the general public can now view and evaluate ground motion data. However, the data offered in web portals are often only optimized for display, and there is no automatic detection of hotspots and their analysis. In this study, ground motion patterns are investigated using Persistent Scatterer Interfer...

The aim of this study is to propose evaluation methodology for the quality assessment of depth cameras for indoor mapping applications. Specifically, we evaluate the RGBD sensor Intel Realsense D455 w.r.t. measurement accuracy and noise while investigating their dependence on two central parameters characterizing the measurement scenario simultaneo...

A 3D model can be useful for inventory management and monitoring of forests. For this task, we present our prototype mobile mapping backpack system for collecting 3D point clouds of forest vegetation. However, data collection in forests is challenging due to unreliable GNSS positioning, moving objects caused by winds, unclear object edges, and unev...

The FAIR principle (find, access, interoperability, reuse) forms a sustainable resource for scientific exchange between researchers. Currently, the implementation of this principle is an important process for future research projects. To support this process in the ISPRS community, the usage of data repositories for dataset publication has the pote...

Open science is an important attribute for developing new approaches. Especially, the data component plays a significant role. The FAIR principle provides a good orientation towards open data. One part of FAIR is findability. Thus, domain specific dataset search platforms were developed: the Earth Observation Database and our Benchmark Metadata Dat...

Plants signal their health in a broader spectrum than we can see with our eyes. We compared sunlight reflectance on plants at spectral wavelengths ranging from 430 nm to 870 nm in our study. These are based on multispectral images captured at a distance of 2 m. Indoor plants were observed over a period of 18 days and stressed due to a lack of sunli...

Scan2BIM approaches, i.e. the automated reconstruction of building models from point cloud data, is typically evaluated against the same point clouds which are used as input for the reconstruction process. In doing so, the point clouds are often used as ground truth without considering their own inaccuracies. Thus, in this research, we investigate...

The analysis of forest vegetation at lower heights, up to 2 m, is the focus of this work, while previous approaches primarily focused on trees and their stems. We calculated geometric metrics of point clouds, based on airborne, unmanned, and mobile laser scanning, to segment different vegetation growths and densities. Our results show that metrics...

A 3D model can be useful for inventory management and monitoring of forests. For this task, we present our prototype mobile mapping backpack system for collecting 3D point clouds of forest vegetation. However, data collection in forests is challenging due to unreliable GNSS positioning, moving objects caused by winds, unclear object edges, and unev...

Forests are irreplaceable and are being studied extensively. Better forest inventory and understanding necessitate effective mapping, modeling, and automatic analysis. As a result, considerable research effort is being devoted to digitizing forest environments. Recently, digital twins have come to the attention of the geospatial community as a virt...

Mobile mapping systems are commonly used for surveying buildings. The acquisition of the buildings’ indoor spaces with laser scanning or photogrammetry generates data in the form of point clouds. These point clouds are often used to create a model of those buildings, but so far with a low degree of automation. To automate this process, it is import...

3D indoor mapping is becoming increasingly critical for a variety of applications such as path planning and navigation for robots. In recent years, there is a growing interest in how low-cost sensors, such as monocular or depth cameras, can be used for 3D mapping. In our paper, we present an octree-based approach for real-time 3D indoor mapping usi...

In dieser Arbeit werden ein konturpunktbasierter und ein ebenenbasierter Ansatz zur Extraktion von Kanten und Ecken aus Innenraumpunktwolken untersucht. Dabei liegt der Fokus auf der Detektion verdeckter Kanten und Ecken. Der ebenenbasierte Ansatz erweist sich robuster gegenüber stark verrauschten und unvollständigen Punktwolken. Der konturpunktbas...

Simultaneous localization and mapping (SLAM) is widely used for robot perception of the environment. It supports the robot in determining its own position as well as the position of surrounding objects. Due to the low cost and the intuitive approach to capture the environment, there are many visual SLAM (vSLAM) systems that have been published in t...

Aufgrund des Klimawandel und Naturkatastrophen wird es immer wichtiger den Wald zu dokumentieren, überwachen und natürliche Zusammenhänge zu verstehen. Aus diesem Grund, soll ein "digitaler Zwilling" vom Wald erstellt werden. In dieser Arbeit wurde auf Testflächen die Vegetation eines Waldes und Parks mittels personengetragenen Mobile La-serscannin...

Peatlands as natural carbon sinks have a major impact on the climate balance and should therefore be monitored and protected. The hydrology of the peatland serves as an indicator of the carbon storage capacity. Hence, we investigate the question how suitable different remote sensing data are for monitoring the size of open water surface and the wat...

Data are a key component for many applications and methods in the domain of photogrammetry and remote sensing. Especially data-driven approaches such as deep learning rely heavily on available annotated data. The amount of data is increasing significantly every day. However, reference data is not increasing at the same rate and finding relevant dat...

The identification of Land Use and Land Cover is an important task for creating maps or monitoring surface changes. The results in this work were obtained using a deep neural network called VGG19-Unet. Influenced by the increasing success of separately implementing edge-extracted inputs in a model, this work used the Canny method to create such edg...

Classification, and in particular semantic segmentation, plays a major role in remote sensing. In remote sensing, the classes usually correspond to landcover or landuse types while the data elements are image pixels. The results are so-called semantically segmented pixels describing the content of the data for each pixel. The identification of misc...

Having a good estimate of the position and orientation of a mobile agent is essential for many application domains such as robotics, autonomous driving, and virtual and augmented reality. In particular, when using LiDAR and IMU sensors as the inputs, most existing methods still use classical filter-based fusion methods to achieve this task. In this...

Indoor mapping has been gaining importance recently. One of the main applications of indoor maps is personal navigation. For this application, the connection to the outdoor map is very important, as users typically enter the building from outside and navigate to their destination inside. Obtaining this connection, however, is challenging, as the ge...

Construction site planning is based on both explicit knowledge, as retrieved from regulations, and implicit knowledge, arising from experience. To retrieve and formalize rules from implicit knowledge, past construction projects can be analyzed. In this paper, we present an image analysis pipeline to retrieve information on past construction sites f...

Indoor maps are required for multiple applications, such as navigation, building maintenance, and robotics. One of the common methods for map generation is laser scanning. In such maps, not only the geometry of the map is of interest, but also it's quality. This study aims at developing methods for real-time generation of indoor maps using features...

In the last decade, we have observed an increasing demand for indoor scene modeling in various applications, such as mobility inside buildings, emergency and rescue operations, and maintenance. Automatically distinguishing between structural elements of buildings, such as walls, ceilings, floors, windows, doors etc., and typical objects in building...

In this paper, we present our novel approach for the crowdsourced dynamic vertical mapping of buildings. For achieving this, we use the barometric sensor of smartphones to estimate altitude differences and the moment of the outdoor to indoor transition to extract reference pressure. We have identified the outdoor–indoor transition (OITransition) vi...

Thermal infrared (TIR) images are often used to picture damaged and weak spots in the insulation of the building hull, which is widely used in thermal inspections of buildings. Such inspection in large-scale areas can be carried out by combining TIR imagery and 3D building models. This combination can be achieved via texture mapping. Automation of...

In this paper, we present our developed and evaluated method for the dynamic mapping of the vertical characteristics inside a building. For achieving that, we extract data from smart-phone sensors and use those data for altitude estimation via the barometric formula. We introduce a novel approach for the extraction of reference pressure during th...

Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal in...

Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal in...

This contribution is focused on the selection of building textures extracted from thermal infrared (TIR) image sequences acquired both from terrestrial and aerial platforms by introducing a quality assessment. Extracted quality features are completeness of the texture, projection accuracy, viewing angle, and geometric resolution. The calculation of...

Thermal infrared imagery of urban areas became interesting for urban climate investigations and thermal building inspections. Using a flying platform such as UAV or a helicopter for the acquisition and combining the thermal data with the 3D building models via texturing delivers a valuable groundwork for large-area building inspections. However, su...

This paper presents a method for identification of errors in 3D building models which are results of inaccurate creation process. Error detection is carried out within the camera pose estimation. As observations, parameters of the building corners and of the line segments detected in the image are used and conditions for the coplanarity of correspo...

For image fusion in remote sensing applications the georeferencing accuracy using position, attitude, and camera calibration measurements can be insufficient. Thus, image processing techniques should be employed for precise coregistration of images. In this article a method for multimodal object-based image coregistration refinement between hypersp...

ESPACE is an interdisciplinary Master's study programme of Technische Universitaet Muenchen (TUM) positioned at the interface between space technology and the engineering and natural science-based use of satellite data. It combines the technical aspects of the satellite and observation systems with scientific and commercial applications. A core top...

3D city models are used in many fields. Photorealistic building textures find applications such as façade reconstruction, thermal building inspections and heat leakage detection using thermal infrared (TIR) images, quantitative evaluation or study of the materials lying on the object’s surface using multispectral images. Often texturing cannot be d...

Data fusion techniques require a good registration of all the used datasets. In remote sensing, images are usually geo-referenced using the GPS and IMU data. However, if more precise registration is required, image processing techniques can be employed. We propose a method for multi-modal image coregistration between hyperspectral images (HSI) and...

1 Zusammenfassung: Die Position und Orientierung eines Luftfahrzeuges im Raum wird durch GPS, oft mit einer IMU, bestimmt. Oft ist die mit GPS/IMU aufgenommene Position und Orientierung nicht genau genug um die in den aufgenommen Daten detektierten Objekte besser zu georeferenzieren und um die Daten aus verschiedenen Quellen zu fusionieren. In dies...

Thermal building textures are used for the detection of damaged or weak spots in the insulation of building hulls. These textures can be extracted from directly geo-referenced oblique airborne infrared (IR) image sequences by projecting a 3D building model into the images. However, the direct geo-referencing is often not sufficiently accurate and t...

Generation and texturing of building models is a fast developing field of research. Several techniques have been developed to extract building geometry and textures from multiple images and image sequences. In this paper, these techniques are discussed and extended to automatically add new textures from infrared (IR) image sequences to existing bui...

Thermal building textures can be used for detection of damaged and weak spots in the building structure. These textures can be extracted from airborne infrared (IR) image sequences by projecting the 3D building model into the images. However, the direct georeferencing is often not sufficiently accurate and the projected 3D model does not match the...

The aim of this article is to investigate methods for the automatic extraction of the infrared (IR) textures for the roofs and facades of existing building models. We focus on the correction of the measured exterior orientation parameters of the IR camera mounted on a mobile platform. The developed method is based on point-to-point matching of the...

Thermal inspections of buildings contribute to detection of damaged and weak spots in the building hull. 3D spatial reference for this purpose can be achieved combining infrared images with 3D building models via texture mapping. Using terrestrial image sequences from a camera mounted in a mobile platform frontal faces can be captured, while airbor...

Infrared (IR) images depict thermal radiation of physical objects. Imaging the building hull with an IR camera allows thermal inspections. Mapping these images as textures on 3D building models, 3D georeferencing of each pixel can be carried out. This is helpful for large area inspections. In IR images glass reflects the surrounding and shows false...

Automatic texture mapping is an important task in enrichment of the common 3D city models. A significant part of all algorithms for automated texture mapping is the visibility checking. Nowadays most algorithms for texture extraction use visibility check based on z-buffer or polygon intersection in the image plane. Thus, the visibility of particula...

Energy and climate changes are big topics in near future. In the European countries a significant part of consumed energy is used for heating in the buildings. Much effort is required for reducing this energy loss. Inspection and monitoring of buildings contribute in further development saving energy. For detection of areas with the highest loss of...