Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-17-2023
L. E. Budde, T. Kullmann, D. Iwaszczuk
Abstract. 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 potential to bring closer the achievement of the FAIR principle. Therefore, we (1) analysed available data repositories, (2) identified common keywords in ISPRS publications and (3) developed a tool for searching appropriate repositories. Thus, infrastructures from the field of geosciences, that can already be used, become more accessible.
{"title":"ON THE DEVELOPMENT OF A DATASET PUBLICATION GUIDELINE: DATA REPOSITORIES AND KEYWORD ANALYSIS IN ISPRS DOMAIN","authors":"L. E. Budde, T. Kullmann, D. Iwaszczuk","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-17-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-17-2023","url":null,"abstract":"Abstract. 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 potential to bring closer the achievement of the FAIR principle. Therefore, we (1) analysed available data repositories, (2) identified common keywords in ISPRS publications and (3) developed a tool for searching appropriate repositories. Thus, infrastructures from the field of geosciences, that can already be used, become more accessible.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-145-2023
K. Pargieła, A. Rzonca, M. Twardowski
Abstract. The paper presents the application of lidar data and photo datasets, external orientation parameters (EOPs), ground control points (GCPs), and check points for testing new methods of geometric lidar data correction. These datasets are utilized to validate novel approaches such as altimetric deformation methods based on stereo models or lidargrammetric methods that utilize image matching and specialized lidar data formats. The paper presents specific use cases of these data as examples of two tested processes. After describing these processes, the methods of synthetic and semisynthetic data simulation are presented. The simulation is directed and subordinated to the aspects of the new method being tested. The data must be used for testing starting from basic functionality up to specific and untypical cases of new method application. By presenting specific cases of the application of synthetic and semisynthetic data, the paper introduces the general idea of benchmarking based on synthetic and semisynthetic data as another means of validating new methods. These artificially generated datasets provide a controlled environment for evaluating the effectiveness of new methods to be investigated.
{"title":"THE UTILIZATION OF SYNTHETIC AND SEMISYNTHETIC POINT CLOUDS AND IMAGES FOR TESTING NOVEL APPROACHES FOR CORRECTING LIDAR DATA","authors":"K. Pargieła, A. Rzonca, M. Twardowski","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-145-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-145-2023","url":null,"abstract":"Abstract. The paper presents the application of lidar data and photo datasets, external orientation parameters (EOPs), ground control points (GCPs), and check points for testing new methods of geometric lidar data correction. These datasets are utilized to validate novel approaches such as altimetric deformation methods based on stereo models or lidargrammetric methods that utilize image matching and specialized lidar data formats. The paper presents specific use cases of these data as examples of two tested processes. After describing these processes, the methods of synthetic and semisynthetic data simulation are presented. The simulation is directed and subordinated to the aspects of the new method being tested. The data must be used for testing starting from basic functionality up to specific and untypical cases of new method application. By presenting specific cases of the application of synthetic and semisynthetic data, the paper introduces the general idea of benchmarking based on synthetic and semisynthetic data as another means of validating new methods. These artificially generated datasets provide a controlled environment for evaluating the effectiveness of new methods to be investigated.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135728848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-167-2023
F. Radicioni, A. Stoppini, L. Marconi, G. Tosi
Abstract. In recent years, the possibility of using interoperable global constellations, the growing number of Continuously Operating Reference Stations (CORS) and the technological progress of instrumentation, computing algorithms and GNSS products are significantly marking the evolution of the various satellite survey techniques and the diffusion of mass-market technologies contributing to innovation transfers in different sectors including smart cities, smart mobility, connected automated driving, precision farming and others (Egea-Roca et al., 2022).Currently, the study of low-cost GNSS systems for navigation and precision positioning especially utilised in monitoring applications is the focus of numerous research activities (Joubert et al., 2020; Raza et al., 2022; Bellone et al., 2016; Hamza et al., 2020).The aim of this work is to test the performance of some of the latest generation multi-constellation and multi-frequency GNSS medium and low-cost sensors, evaluating their possible application in the mentioned fields. Differential and undifferential techniques were compared (Dardanelli et al., 2021; Ocalan et al.,2016); Precise Point Positioning (PPP) has become a valid alternative to differential methods allowing to obtain comparable accuracy offering greater flexibility (Lin, 2021). The multi-constellation permanent stations network GPS-Umbria was utilised for differential mode tests (Radicioni and Stoppini, 2019).The tests were carried out in different modes (static and kinematic) and operating conditions; various intermediate and low-cost sensors were employed, while the data of a high precision geodetic receiver were used as reference for the comparison of the different solutions.
摘要近年来，使用可互操作的全球星座的可能性、不断增加的连续运行参考站(CORS)数量以及仪器、计算算法和GNSS产品的技术进步，显著标志着各种卫星测量技术的发展和大众市场技术的扩散，有助于不同领域的创新转移，包括智慧城市、智能移动、互联自动驾驶、精准农业等(Egea-Roca et al.， 2022)。目前，研究用于导航和精确定位的低成本GNSS系统，特别是用于监测应用，是许多研究活动的重点(Joubert et al.， 2020;Raza et al.， 2022;Bellone et al.， 2016;Hamza等人，2020)。本工作旨在测试部分最新一代多星座多频GNSS中低成本传感器的性能，评估其在上述领域的应用可能性。对微分和非微分技术进行了比较(Dardanelli et al.， 2021;Ocalan et al.，2016);精确点定位(PPP)已成为差分方法的有效替代方案，允许获得相当的精度，提供更大的灵活性(Lin, 2021)。利用多星座永久站网络GPS-Umbria进行差模态测试(Radicioni和Stoppini, 2019)。测试在不同的模式(静态和运动)和操作条件下进行;采用各种中低成本传感器，并以高精度大地测量接收机的数据为参考，对不同方案进行比较。
{"title":"LOW-COST MULTI-FREQUENCY GNSS RECEIVERS: PERFORMANCE EVALUATION FOR POSITIONING AND NAVIGATION","authors":"F. Radicioni, A. Stoppini, L. Marconi, G. Tosi","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-167-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-167-2023","url":null,"abstract":"Abstract. In recent years, the possibility of using interoperable global constellations, the growing number of Continuously Operating Reference Stations (CORS) and the technological progress of instrumentation, computing algorithms and GNSS products are significantly marking the evolution of the various satellite survey techniques and the diffusion of mass-market technologies contributing to innovation transfers in different sectors including smart cities, smart mobility, connected automated driving, precision farming and others (Egea-Roca et al., 2022).Currently, the study of low-cost GNSS systems for navigation and precision positioning especially utilised in monitoring applications is the focus of numerous research activities (Joubert et al., 2020; Raza et al., 2022; Bellone et al., 2016; Hamza et al., 2020).The aim of this work is to test the performance of some of the latest generation multi-constellation and multi-frequency GNSS medium and low-cost sensors, evaluating their possible application in the mentioned fields. Differential and undifferential techniques were compared (Dardanelli et al., 2021; Ocalan et al.,2016); Precise Point Positioning (PPP) has become a valid alternative to differential methods allowing to obtain comparable accuracy offering greater flexibility (Lin, 2021). The multi-constellation permanent stations network GPS-Umbria was utilised for differential mode tests (Radicioni and Stoppini, 2019).The tests were carried out in different modes (static and kinematic) and operating conditions; various intermediate and low-cost sensors were employed, while the data of a high precision geodetic receiver were used as reference for the comparison of the different solutions.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135729313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-71-2023
M. Jäger, B. Jutzi
Abstract. Generating geometric 3D reconstructions from Neural Radiance Fields (NeRFs) is of great interest. However, accurate and complete reconstructions based on the density values are challenging. The network output depends on input data, NeRF network configuration and hyperparameter. As a result, the direct usage of density values, e.g. via filtering with global density thresholds, usually requires empirical investigations. Under the assumption that the density increases from non-object to object area, the utilization of density gradients from relative values is evident. As the density represents a position-dependent parameter it can be handled anisotropically, therefore processing of the voxelized 3D density field is justified. In this regard, we address geometric 3D reconstructions based on density gradients, whereas the gradients result from 3D edge detection filters of the first and second derivatives, namely Sobel, Canny and Laplacian of Gaussian. The gradients rely on relative neighboring density values in all directions, thus are independent from absolute magnitudes. Consequently, gradient filters are able to extract edges along a wide density range, almost independent from assumptions and empirical investigations. Our approach demonstrates the capability to achieve geometric 3D reconstructions with high geometric accuracy on object surfaces and remarkable object completeness. Notably, Canny filter effectively eliminates gaps, delivers a uniform point density, and strikes a favorable balance between correctness and completeness across the scenes.
{"title":"3D DENSITY-GRADIENT BASED EDGE DETECTION ON NEURAL RADIANCE FIELDS (NERFS) FOR GEOMETRIC RECONSTRUCTION","authors":"M. Jäger, B. Jutzi","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-71-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-71-2023","url":null,"abstract":"Abstract. Generating geometric 3D reconstructions from Neural Radiance Fields (NeRFs) is of great interest. However, accurate and complete reconstructions based on the density values are challenging. The network output depends on input data, NeRF network configuration and hyperparameter. As a result, the direct usage of density values, e.g. via filtering with global density thresholds, usually requires empirical investigations. Under the assumption that the density increases from non-object to object area, the utilization of density gradients from relative values is evident. As the density represents a position-dependent parameter it can be handled anisotropically, therefore processing of the voxelized 3D density field is justified. In this regard, we address geometric 3D reconstructions based on density gradients, whereas the gradients result from 3D edge detection filters of the first and second derivatives, namely Sobel, Canny and Laplacian of Gaussian. The gradients rely on relative neighboring density values in all directions, thus are independent from absolute magnitudes. Consequently, gradient filters are able to extract edges along a wide density range, almost independent from assumptions and empirical investigations. Our approach demonstrates the capability to achieve geometric 3D reconstructions with high geometric accuracy on object surfaces and remarkable object completeness. Notably, Canny filter effectively eliminates gaps, delivers a uniform point density, and strikes a favorable balance between correctness and completeness across the scenes.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135728738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-191-2023
P. Trybała, P. Kujawa, K. Romańczukiewicz, A. Szrek, F. Remondino
Abstract. Mobile Mapping Technology (MMT) has evolved rapidly over the past few decades, especially in using low-cost sensors. This progress is primarily attributed to the appearance of innovative simultaneous localization and mapping (SLAM) algorithms. This article focuses on evaluating the efficiency of a new LiDAR-based portable SLAM system for mapping in dynamic real-world environments. The work proposed a technical solution based on a Livox Avia LiDAR sensor enhanced by gimbal stabilization. The system, named Portable Livox-based Mapping system (PoLiMap), is compared to other similar solutions by acquiring data from various environments, including urban sceneries, underground tunnels and forested areas, and processing them using a modified FAST-LIO-SLAM algorithm. The research presented in the article contributes to the understanding of the capabilities of PoLiMap systems under various conditions and offers significant insight into its potential applications. Accuracy evaluation results prove that the proposed MMT system can successfully tackle various demanding environments and challenge the results of other more costly state-of-the-art portable mobile laser scanning methods.
摘要移动地图技术(MMT)在过去几十年中发展迅速，特别是在使用低成本传感器方面。这一进展主要归功于创新的同步定位和地图绘制(SLAM)算法的出现。本文着重于评估一种新的基于lidar的便携式SLAM系统在动态现实环境中的映射效率。该工作提出了一种基于Livox Avia激光雷达传感器的技术解决方案，该传感器通过框架稳定增强。该系统名为便携式Livox-based Mapping system (PoLiMap)，通过从各种环境(包括城市景观、地下隧道和森林地区)获取数据，并使用改进的fast - livox - slam算法对数据进行处理，与其他类似解决方案进行了比较。本文中介绍的研究有助于理解PoLiMap系统在各种条件下的功能，并对其潜在应用提供了重要的见解。精度评估结果证明，所提出的MMT系统可以成功应对各种苛刻的环境，并挑战其他更昂贵的最先进的便携式移动激光扫描方法的结果。
{"title":"DESIGNING AND EVALUATING A PORTABLE LIDAR-BASED SLAM SYSTEM","authors":"P. Trybała, P. Kujawa, K. Romańczukiewicz, A. Szrek, F. Remondino","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-191-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-191-2023","url":null,"abstract":"Abstract. Mobile Mapping Technology (MMT) has evolved rapidly over the past few decades, especially in using low-cost sensors. This progress is primarily attributed to the appearance of innovative simultaneous localization and mapping (SLAM) algorithms. This article focuses on evaluating the efficiency of a new LiDAR-based portable SLAM system for mapping in dynamic real-world environments. The work proposed a technical solution based on a Livox Avia LiDAR sensor enhanced by gimbal stabilization. The system, named Portable Livox-based Mapping system (PoLiMap), is compared to other similar solutions by acquiring data from various environments, including urban sceneries, underground tunnels and forested areas, and processing them using a modified FAST-LIO-SLAM algorithm. The research presented in the article contributes to the understanding of the capabilities of PoLiMap systems under various conditions and offers significant insight into its potential applications. Accuracy evaluation results prove that the proposed MMT system can successfully tackle various demanding environments and challenge the results of other more costly state-of-the-art portable mobile laser scanning methods.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135729257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-227-2023
P. Zachar, K. Bakuła, W. Ostrowski
Abstract. Benchmarking is an essential tool for scientific and technological progress. This article reviews the benchmarks for 3D point cloud segmentation and classification. Based on the analysis of the articles and the knowledge gathered, it can be concluded that there has been an increase in the number of benchmarks, allowing to compare research results against specific performance metrics independently. However, benchmarks vary regarding the number of classes, spatial size, nomenclature, and class division. In this article, we introduce a new annotated 3D dataset - CENAGIS-ALS Benchmark. We propose a benchmark of highly dense lidar point clouds acquired by Leica CityMapper-2 for the Centre of Warsaw, Poland. The area covers 2 km2, and the data has a density of 275 pts/m2. The dataset consists of a number of classes that are distinguishable for this type of data. In addition to the basic classes, more specialized classes, important from the perspective of urban space, are also distinguished. Moreover, the division of classes consists of three levels of detail from coarse (e.g., a building) to refined elements (e.g., roofs, chimneys, and other rooftop objects). This benchmark can contribute to geospatial societies, considering the large spatial size of the study area with unified data quality and the higher number of classes with the hierarchical division compared to other benchmarking data.
{"title":"CENAGIS-ALS BENCHMARK - NEW PROPOSAL FOR DENSE ALS BENCHMARK BASED ON THE REVIEW OF DATASETS AND BENCHMARKS FOR 3D POINT CLOUD SEGMENTATION","authors":"P. Zachar, K. Bakuła, W. Ostrowski","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-227-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-227-2023","url":null,"abstract":"Abstract. Benchmarking is an essential tool for scientific and technological progress. This article reviews the benchmarks for 3D point cloud segmentation and classification. Based on the analysis of the articles and the knowledge gathered, it can be concluded that there has been an increase in the number of benchmarks, allowing to compare research results against specific performance metrics independently. However, benchmarks vary regarding the number of classes, spatial size, nomenclature, and class division. In this article, we introduce a new annotated 3D dataset - CENAGIS-ALS Benchmark. We propose a benchmark of highly dense lidar point clouds acquired by Leica CityMapper-2 for the Centre of Warsaw, Poland. The area covers 2 km2, and the data has a density of 275 pts/m2. The dataset consists of a number of classes that are distinguishable for this type of data. In addition to the basic classes, more specialized classes, important from the perspective of urban space, are also distinguished. Moreover, the division of classes consists of three levels of detail from coarse (e.g., a building) to refined elements (e.g., roofs, chimneys, and other rooftop objects). This benchmark can contribute to geospatial societies, considering the large spatial size of the study area with unified data quality and the higher number of classes with the hierarchical division compared to other benchmarking data.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135729392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-107-2023
J. P. Mills, M. V. Peppa, A. Alma'Amari, L. Davidson, J. Goodyear, N. T. Penna
Abstract. In 2021 EuroSDR initiated a benchmark study with the aim to evaluate the geometric quality of real-world survey data generated from state-of-practice commercial Remotely Piloted Aircraft System (RPAS) photogrammetry (including DJI P4 RTK and DJI P1) and lidar (including DJI L1 and Riegl MiniVUX). The particular benchmark focus was on achievable data quality from real-world network configurations in the absence of ground control, on-the-fly Real Time Kinematic (RTK) corrections, and/or local GNSS base station information. Successive custom datasets were released to registered benchmark participants who submitted individual outputs that were independently evaluated against reference surveys. Without the inclusion of any supporting ground information, DJI P4 RTK and DJI P1 RPAS solutions were found to deliver m- and dm-level accuracies, respectively, in both plan and height. RTK solutions were found to provide cm-level precisions and accuracies, with some outliers. The introduction of ground control points resulted in similar planimetric accuracy to the RTK solutions, but with slight improvements in height. In terms of lidar datasets, the Riegl MiniVUX solution, using corrections from a local base station, was found to provide smaller discrepancies than the DJI L1 RTK solution, when independently compared against terrestrial laser scanning surveys. This paper provides various quality statistics and demonstrates multiple ways of assessing the geometric quality of RPAS data. The EuroSDR RPAS benchmark datasets are now openly available online in order to support and facilitate further investigation by the community.
{"title":"THE EUROSDR RPAS BENCHMARK: OPEN DATASET DESCRIPTION AND SUMMARY OF KEY RESULTS","authors":"J. P. Mills, M. V. Peppa, A. Alma'Amari, L. Davidson, J. Goodyear, N. T. Penna","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-107-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-107-2023","url":null,"abstract":"Abstract. In 2021 EuroSDR initiated a benchmark study with the aim to evaluate the geometric quality of real-world survey data generated from state-of-practice commercial Remotely Piloted Aircraft System (RPAS) photogrammetry (including DJI P4 RTK and DJI P1) and lidar (including DJI L1 and Riegl MiniVUX). The particular benchmark focus was on achievable data quality from real-world network configurations in the absence of ground control, on-the-fly Real Time Kinematic (RTK) corrections, and/or local GNSS base station information. Successive custom datasets were released to registered benchmark participants who submitted individual outputs that were independently evaluated against reference surveys. Without the inclusion of any supporting ground information, DJI P4 RTK and DJI P1 RPAS solutions were found to deliver m- and dm-level accuracies, respectively, in both plan and height. RTK solutions were found to provide cm-level precisions and accuracies, with some outliers. The introduction of ground control points resulted in similar planimetric accuracy to the RTK solutions, but with slight improvements in height. In terms of lidar datasets, the Riegl MiniVUX solution, using corrections from a local base station, was found to provide smaller discrepancies than the DJI L1 RTK solution, when independently compared against terrestrial laser scanning surveys. This paper provides various quality statistics and demonstrates multiple ways of assessing the geometric quality of RPAS data. The EuroSDR RPAS benchmark datasets are now openly available online in order to support and facilitate further investigation by the community.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-91-2023
A. Malczewska, J. Malczewski, B. Hejmanowska
Abstract. Benchmark datasets is an significant aspect in in many areas such as computer vision, deep learning, geospatial data as they serve as standardized test sets for evaluating the performance of models. Among many techniques of image processing, there is super-resolution (SR) which is aimed at reconstructing a low-resolution (LR) image into a high-resolution (HR) image. For training and validation SR models as a dataset the pairs of HR and LR images are needed, which should be the same apart from resolution. There is a lot of benchmark datasets for super-resolution methods, but they usually include conventional photographs of an common objects, while remote sensing data have different characteristic in general. This paper focuses on the process of preparing datasets for super-resolution in satellite images, where high-resolution and low-resolution image data come from different sources. The case of the single-image super-resolution method was considered. The experiment was performed on Sentinel-2 and PlanetScope data, but the assumptions can also be transferred to data obtained from other satellites. The procedure on how to make the pairs of HR and LR images consistent in terms of time, location and spectral values was proposed. The impact of the processes carried out was measured using image similarity measurement methods such as PSNR, SSIM and SCC.
{"title":"CHALLENGES IN PREPARING DATASETS FOR SUPER-RESOLUTION ON THE EXAMPLE OF SENTINEL-2 AND PLANET SCOPE IMAGES","authors":"A. Malczewska, J. Malczewski, B. Hejmanowska","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-91-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-91-2023","url":null,"abstract":"Abstract. Benchmark datasets is an significant aspect in in many areas such as computer vision, deep learning, geospatial data as they serve as standardized test sets for evaluating the performance of models. Among many techniques of image processing, there is super-resolution (SR) which is aimed at reconstructing a low-resolution (LR) image into a high-resolution (HR) image. For training and validation SR models as a dataset the pairs of HR and LR images are needed, which should be the same apart from resolution. There is a lot of benchmark datasets for super-resolution methods, but they usually include conventional photographs of an common objects, while remote sensing data have different characteristic in general. This paper focuses on the process of preparing datasets for super-resolution in satellite images, where high-resolution and low-resolution image data come from different sources. The case of the single-image super-resolution method was considered. The experiment was performed on Sentinel-2 and PlanetScope data, but the assumptions can also be transferred to data obtained from other satellites. The procedure on how to make the pairs of HR and LR images consistent in terms of time, location and spectral values was proposed. The impact of the processes carried out was measured using image similarity measurement methods such as PSNR, SSIM and SCC.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-161-2023
F. Pöppl, G. Mandlburger, N. Pfeifer
Abstract. Airborne laser scanning allows for efficient acquisition of accurate 3D data for large areas. Because georeferencing of the LiDAR data requires knowledge of the platform trajectory, the laser scanner system commonly comprises a global navigation satellite system (GNSS) receiver/antenna and an inertial measurement unit (IMU). The standard processing pipeline consists of GNSS/IMU integration, georeferencing, and subsequent adjustment of the laser data. Here, we consider a holistic GNSS/IMU/LiDAR-integration approach based on least-squares adjustment. The GNSS is loosely coupled, and the GNSS positions are obtained using either postprocessing kinematic or precise point positioning GNSS processing strategies using the open-source software RTKLib. In this contribution, we compare the resulting point clouds to those of a standard processing workflow and evaluate the impact of the different processing strategies on point cloud quality in terms of internal consistency and absolute accuracy for a airborne laser bathymetry (ALB) dataset. Although the GNSS solutions themselves differ strongly, both the PPK- and the PPP-derived point clouds show better strip differences (below 2.5 cm) and similar absolute accuracy (<4 cm RMSE w.r.t. reference targets after correction of constant datum shift) compared to the reference solution.
{"title":"EVALUATION OF A GNSS/IMU/LIDAR-INTEGRATION FOR AIRBORNE LASER SCANNING USING RTKLIB PPK AND PPP GNSS SOLUTIONS","authors":"F. Pöppl, G. Mandlburger, N. Pfeifer","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-161-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-161-2023","url":null,"abstract":"Abstract. Airborne laser scanning allows for efficient acquisition of accurate 3D data for large areas. Because georeferencing of the LiDAR data requires knowledge of the platform trajectory, the laser scanner system commonly comprises a global navigation satellite system (GNSS) receiver/antenna and an inertial measurement unit (IMU). The standard processing pipeline consists of GNSS/IMU integration, georeferencing, and subsequent adjustment of the laser data. Here, we consider a holistic GNSS/IMU/LiDAR-integration approach based on least-squares adjustment. The GNSS is loosely coupled, and the GNSS positions are obtained using either postprocessing kinematic or precise point positioning GNSS processing strategies using the open-source software RTKLib. In this contribution, we compare the resulting point clouds to those of a standard processing workflow and evaluate the impact of the different processing strategies on point cloud quality in terms of internal consistency and absolute accuracy for a airborne laser bathymetry (ALB) dataset. Although the GNSS solutions themselves differ strongly, both the PPK- and the PPP-derived point clouds show better strip differences (below 2.5 cm) and similar absolute accuracy (<4 cm RMSE w.r.t. reference targets after correction of constant datum shift) compared to the reference solution.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135728982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.5194/isprs-archives-xlviii-1-w3-2023-219-2023
Z. Yan, G. Mazzacca, S. Rigon, E. M. Farella, P. Trybala, F. Remondino
Abstract. Neural Radiance Field methods are innovative solutions to derive 3D data from a set of oriented images. This paper introduces new real and synthetic image datasets - called NeRFBK - specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. More and more reconstruction algorithms and techniques are available nowadays, raising the need to evaluate and compare the quality of derived 3D products currently used in various domains and applications. However, gathering diverse data with precise ground truth is challenging and may not encompass all relevant applications. The NeRFBK dataset addresses this issue by providing multi-scale, indoor and outdoor datasets with high-resolution images and videos and camera parameters for testing and comparing NeRF-based algorithms. This paper presents the design and creation of the NeRFBK set of data, various examples and application scenarios, and highlights its potential for advancing the field of 3D reconstruction.
{"title":"NERFBK: A HOLISTIC DATASET FOR BENCHMARKING NERF-BASED 3D RECONSTRUCTION","authors":"Z. Yan, G. Mazzacca, S. Rigon, E. M. Farella, P. Trybala, F. Remondino","doi":"10.5194/isprs-archives-xlviii-1-w3-2023-219-2023","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-219-2023","url":null,"abstract":"Abstract. Neural Radiance Field methods are innovative solutions to derive 3D data from a set of oriented images. This paper introduces new real and synthetic image datasets - called NeRFBK - specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. More and more reconstruction algorithms and techniques are available nowadays, raising the need to evaluate and compare the quality of derived 3D products currently used in various domains and applications. However, gathering diverse data with precise ground truth is challenging and may not encompass all relevant applications. The NeRFBK dataset addresses this issue by providing multi-scale, indoor and outdoor datasets with high-resolution images and videos and camera parameters for testing and comparing NeRF-based algorithms. This paper presents the design and creation of the NeRFBK set of data, various examples and application scenarios, and highlights its potential for advancing the field of 3D reconstruction.","PeriodicalId":30634,"journal":{"name":"The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135729593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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