bluuebunny/crossref_metadata_2025 huggingface dataset:
Matching UAV-Based Simulated High-Resolution SAR and Real SAR Images
Authors: Sultanbekova Aigerim , Balz Timo
Published: May 2024

Abstract. Our experiment focuses on generating simulated high-resolution (HR) Synthetic Aperture Radar (SAR) images from the photogrammetric 3D model derived from Unmanned Aerial Vehicle (UAV) imagery. The goal is to match these simulated images with real SAR data of complex scenes containing vegetation, buildings, roads, and the construction of receiving antennas. Simulated SAR reflectivity map was based on ray tracing techniques.Two feature matching algorithms, namely Scale-Invariant Feature Transform (SIFT) and Oriented FAST and Rotated BRIEF (ORB) were employed for co-registration of the simulated to the real SAR images. The effectiveness of these algorithms is evaluated by their matching rates. The experiment results of the matching process highlight the superior performance of ORB over SIFT, attributed to its robustness against rotation variations and noise. ORB emerges as a versatile choice for high-resolution real and simulated SAR registration tasks.
Analysis of surface deformation and related factors over mining areas based on InSAR: A case study of Fengcheng mine
Authors: Wang Xiaying , Chen Shuaiqiang , Xia Yuanping , Niu Yufen , Gong Jun , Yang Yumei
Published: May 2024

Abstract. Ground surface deformation in mines affects mining production, damages the ecological environment, and endangers human safety. Mastering the detailed time series deformation and related triggering factors can provide key information for the safety of the mining area. Therefore, the Fengcheng mining area, a large and ancient coal mine in Jiangxi Province, China, was selected as the study area in this work, and the following research was conducted: 1. The accuracy and applicability of the Stacking, Small-Baseline Subset InSAR (SBAS-InSAR), and Interferometric Point Target Analysis (IPTA) methods were preliminarily explored while monitoring the annual deformation rate based on Sentinel-1A data from October 2019 to November 2022. 2. The time-series deformation of the Fengcheng mining area was obtained with SBAS-InSAR technology, and the sedimentation was validated with leveling results. 3. The correlation factors of deformation, such as rainfall and land cover, were studied, and the relationship between the influencing factors, such as coal mining dip angle, digital elevation, coal mining elevation, and deformation, was quantitatively explored with the Grey correlation model and Pearson correlation analysis method. The following conclusions were drawn: The SBAS method has the best adaptability in the dense vegetation mining area, and the root-mean-square error of the difference between deformation results and leveling data does not exceed 4mm. The evolution process of deformation centers is mainly divided into the stages of initial deformation, constant velocity deformation, accelerated deformation, and stable condition. Compared with the natural factors, the settlement of the Fengcheng mining area is mainly affected by human-induced mining and construction of artificial facilities.
Non-Destructive Assessment of Stone Heritage Weathering Types Based on Machine Learning Method Using Hyperspectral Data
Authors: Wang Xin , Cheng Yuan , Zhang Ruoyu , Zhang Yue , Huang Jizhong , Yan Hongbin
Published: May 2024

Abstract. Stone cultural heritage is exposed to various environments, resulting in a diverse range of weathering types. The identification of these weathering types is vital for targeted conservation efforts. In this paper, a weathering type classification method based on hyperspectral imaging technology is proposed. Firstly, fresh sandstones are collected from Yungang Grottoes to carry out the simulated weathering experiments, including freeze-thaw cycles and wet-dry cycles with acid, alkali and salt solutions. Subsequently, the hyperspectral imaging system was used to collect the visible-near-infrared (VNIR) and short-wave infrared (SWIR) images of the sandstone samples with different weathering types and degrees. The surface spectral reflectance of sandstone samples with different weathering types were used as training data, with weathering types serving as the labels. Support vector machine (SVM), K-nearest neighbour (KNN), linear discriminant analysis (LDA) and random forest (RF) were used to establish weathering type classification models. The results show that the SVM model and LDA model based on both VNIR and SWIR spectra exhibit outstanding performance, with a best accuracy of 0.994. The framework proposed in this paper facilitates rapid and non-contact assessment of the weathering types of the superficial layers of stone cultural heritage, thereby supporting more targeted conservation work.
Topographic analysis supported by a knowledge graph: A case of ridge landscape recognition
Authors: Wu Hao , Yu Huafei , Ai Tinghua
Published: May 2024

Abstract. The intrinsic connections between geographical elements are important for uncovering hidden geo-scientific laws. However, current research on terrain and landform analysis mainly focuses on the landscapes themselves, with insufficient attention to the connections between them. Therefore, this study proposes a knowledge graph approach based on geographical units (TUKG). Specifically, fi-negrained geographical units are extracted based on three types of data: remote sensing images, DEM, and contour lines. These units serve as entity nodes in the TUKG and are described by their slope and aspect. Additionally, point-based and line-based connections between geographical units are proposed based on spatial topological relationships, serving as connections between entity nodes in the TUKG. Finally, inference rules for ridge landscape problems are extracted from typical cases of ridge land-scapes to support reasoning in the TUKG. Experimental results conducted in the Yarlung Zangbo Grand Canyon in southwest China demonstrate that the TUKG can accurately infer ridge landscapes and has the potential to identify more complex terrain landscapes.
Design and Implementation of Time Point Approval and Dynamic Monitoring for Rural Illegal Occupation of Farmland for Constructing Houses
Authors: Xu Chang , Huang Weizhao , Zhang Miao , Xiong Xiaoqing , Liu Lu , Li Jiangbo , Chun Lan , Wu Miao
Published: May 2024

Abstract. The illegal occupation of farmland for building houses has impact not only on the land resources, but also the agricultural production, ecological environment, and food security. In order to protect farmland resources, maintain stable agricultural production activities and improve ecological environment, this paper designs and implements a time-point approval and dynamic monitoring solution and system for the problem of rural illegal occupation of farmland for constructing houses by comprehensively utilizing the satellite remote sensing technology (RS) and geographic information system technology (GIS). The result shows that the time-point approval and dynamic monitoring system can identify the illegal construction of houses accurately, thus this work can curb the generation of new illegal houses, and support the special governance of the construction of illegally occupied farmland effectively and continuously.
FS_YOLOv8: A Deep Learning Network for Ground Fissures Instance Segmentation in UAV Images of the Coal Mining Area
Authors: Xu Zhihua , Lin Yunhao , Zhang Zhenxin
Published: May 2024

Abstract. The ground fissures caused by coal mining have seriously affected the ecological environment of the land. Timely and accurate identification and landfill treatment of ground fissures can avoid secondary geological disasters in coal mine areas. At present, the fissure identification methods based on deep learning show excellent performance on roads and walls, etc. Nevertheless, the automatic and reliable segmentation of ground fissures in remote sensing images poses a challenge for deep learning networks, due to the diverse and complex texture information included in the mining ground fissures and background. To overcome these challenges, we propose an improved YOLOv8 instance segmentation network to automatically and efficiently segment the ground fissures in coal mining areas. In detail, a model called FS_YOLOv8 is proposed. The DSPP (Dynamic Snake convolutional Pyramid Pooling) module is incorporated into the FS_YOLOv8 model to establish a multi-scale dynamic snake convolution feature aggregation structure. This module replaces the conventional convolution found in the SPPF module of YOLOv8 and aims to enhance the model's ability to extract features related to fissures with tubular structures. Furthermore, the D-LKA (Deformable Large Kernel Attention) module is employed to autonomously collect fissure context information. To enhance the detection capability of challenging samples in remote sensing images with intricate background and fissure texture, we employ a Slide Loss function. Ultimately, the ground fissure dataset of unmanned aerial vehicle (UAV) images in coal mine areas is subjected to experimental analysis. The experimental findings demonstrate that FS_YOLOv8 exhibits exceptional proficiency in segmenting ground fissures within intricate and expansive mining areas.
Spectroscopy Detection and Imaging System Based on Line Array Single Photon Detectors
Authors: Xue Ruikai , Kong Wei , Peng Ziqiang , Liu Qiang , Liu Yuanting , Jiang Bin , Huang Genghua , Shu Rong
Published: May 2024

Abstract. Single-photon detectors, with their exceptional sensitivity, provide a reliable means for single-photon-level detection, demonstrating significant advantages in detecting weak signals in complex environments compared to traditional detectors. With the continuous advancement in semiconductor manufacturing technology, single-photon detectors based on linear array configurations have emerged and rapidly developed. This study utilizes a linear array single-photon detector in free-running mode combined with a scanning mechanism to design and implement a spectral detection and imaging system. Through the spectral scanning unit, this system successfully achieves precise spectral detection in the 890 nm to 1710 nm range, with a spectral resolution better than 2 nm. Utilizing the imaging scanning unit, the system effectively performs target spectral imaging under single and multiple wavelength conditions at 1064 nm, 1310 nm, and 1520 nm. By optimizing algorithms for data processing, the system can achieve rapid and accurate spectral detection and imaging even under low-light conditions where the average photon count per pixel is less than 3. The results of this study are expected to provide strong technical support for the application of spectral imaging technology in the field of high-speed detection and imaging.
Semi-automated approach towards efficient HD Maps generation and verification with Lanelet2 formats
Authors: Chang Yi-Feng , Huang Yen-En , Tsai Meng-Lun , Darweesh Hatem , Chiang Kai-Wei , Ai Mengchi , El-Sheimy Naser
Published: May 2024

Abstract. HD Maps (High-Definition Maps) serve as crucial resources for the domain of autonomous vehicle. Because HD Maps can provide detailed and accurate road information, the generation of HD Maps has been a labour-intensive and high cost. This research presents an innovative and semi-automated approach for efficient HD Maps generation by using assure mapping tool with deep learning techniques and mobile laser scanned point cloud geometry. The proposed method starts with data collection from various sources such as images, LiDAR point clouds, and integrated INS/GNSS trajectory data. These data are labelled by using a pre-trained model. After finishing post-labelling, these data are subjected to deep learning training by using VoxelNet and Yolact++ framework and leading to the generation of an AI model. The tool effectively recognizes and categorizes features such as road surface markings, traffic signs, and traffic lights, which can be further expanded as per requirements. Finally, the output format can be converted to OpenDRIVE, Lanelet2, and other else. Hence, the extracted lane lines can compare to the manual mapping data for verifying the accuracy. This study demonstrates that the proposed approach can be instrumental in streamlining the HD Maps generation procedure, reducing manual labour, and enhancing efficiency. The assure mapping tool proves to be an effective instrument, particularly when powered by deep learning algorithms and point cloud geometries, in the creation of reliable, comprehensive, and application-ready HD Maps.
Research on the Joint Construction of a National Multi-source and Multi-resolution image Checkpoint Database
Authors: Yan Qingqing , Liu Chang , Gao Wenchao , Wan Mingying , Wu Xuan , Dong Shuai
Published: May 2024

Abstract. In the process of quality inspection of Remote sensing image data results, the reuse of spatial location information of multiple units, multiple projects and multiple sources can not only overcome the problems of long time to obtain control information, high cost and difficulty in obtaining some areas, but also the basis for achieving efficient and high-precision geometric correction. From the perspective of reusability of checkpoints and saving the cost of quality inspection of remote sensing images, this paper discusses the necessity of joint construction of multi-source and multi-resolution image checkpoint database. And put forward the construction principle and management objectives of checkpoint database. At last, this paper briefly introduces and prospects the application of the national multi-source and multi-resolution image checkpoint database.
The Research of Collaborative System of Remote Sensing Monitoring Based on Bimodal Cloud
Authors: Yang Kaijun , Lei Fan , Cao Li , Wei Jide , Zhang Zhe
Published: May 2024

Abstract. Cloud service is based on cloud computing, Offering a On-Demand service to every terminal equipment of computing resource pool. This paper designed and developed a coordinated operating system based on bimodal cloud. This system is taken mutual scheduling mechanism into account, which is capable of storing massive amounts of heterogeneous remote sensing data and provides fast indexing of data based on various characteristics, integrated Satellite transit forecast, DOM Produce, coordinated change information extraction and results sharing based on Nginx load balancing, in addition, the system designed two layer security system to ensure the safety of data results.The "YunYao" geographic information service rendering engine built on the dual-state cloud platform significantly outperforms mainstream platforms in the same testing environment. Its rendering speed surpasses ArcGIS Desktop by more than two times, exceeds GeoServer by more than four times, and is over seven times faster than ArcGIS Server. Remote sensing practitioners can quickly and conveniently utilize this system, while providing convenient functionalities that enable remote sensing scientists to independently conduct scientific research and development using this system. Experimentation and practice shows that this system simplified routine work flow, improved work efficiency, has a important reference meaning to remote sensing monitoring.
A Transformer and Visual Foundation Model-Based Method for Cross-View Remote Sensing Image Retrieval
Authors: Yin Changjiang , Ye Qin , Luo Junqi
Published: May 2024

Abstract. Retrieving UAV images that lack POS information with georeferenced satellite orthoimagery is challenging due to the differences in angles of views. Most existing methods rely on deep neural networks with a large number of parameters, leading to substantial time and financial investments in network training. Consequently, these methods may not be well-suited for downstream tasks that have high timeliness requirements. In this work, we propose a cross-view remote sensing image retrieval method based on transformer and visual foundation model. We investigated the potential of visual foundation model for extracting common features from cross-view images. Training is only conducted on a small, self-designed retrieval head, alleviating the burden of network training. Specifically, we designed a CVV module to optimize the features extracted from the visual foundation model, making these features more adept for cross-view image retrieval tasks. And we designed an MLP head to achieve similarity discrimination. The method is verified on a publicly available dataset containing multiple scenes. Our method shows excellent results in terms of both efficiency and accuracy on 15 sub-datasets (10 or 50 scene categories) derived from the public dataset, which holds practical value in engineering applications with streamlined scene categories and constrained computational resources. Furthermore, we initiated a comprehensive discussion and conducted ablation experiments on the network design to validate its efficacy. Additionally, we analyzed the presence of overfitting within the network and deliberated on the limitations of our study, proposing potential avenues for future enhancements.
Technical Framework and Preliminary Practices of Global Geographic Information Resource Construction
Authors: Zhang Hongwei , Chen Jiage , Wu Chenchen , Chen Lijun
Published: May 2024

Abstract. High-precision and real-time global geographic information data are fundamental and strategic resources in various fields such as safeguarding global strategic interests, studying global environmental changes, and planning for sustainable development. However, due to challenges related to ground control and obtaining reference information, the development of global geographic information resources faces significant hurdles in terms of geometric positioning, information extraction, and data mining. This paper starts with the characteristics of domestically produced remote sensing images and proposes a comprehensive technical framework centered around "uncontrolled geometric positioning, intelligent interpretation of typical elements, mining of multi-source data from abroad, and intelligent hybrid collection and compilation of Digital Elevation Models (DEMs)." The paper elaborates on the key technical challenges that need to be overcome and their corresponding solutions. It also outlines the development of relevant data products and production technical specifications. Multiple production-oriented software tools were developed, leading to the creation of a variety of data products in multiple types and scales, including global 30-meter land cover data, DEM data, core vector data, and more.
Neural Cellular Automata-based Land Use Changes Simulation
Authors: Zhang Jinian , Liu Lanfa
Published: May 2024

Abstract. Simulating land use and land cover changes (LUCC) is important for urban planning and environmental studies. In this study, we introduce a neural cellular automata (NCA) model that integrates biological principles and convolutional neural networks (CNNs) for land use simulation. We conduct experiments in the city of Wuhan, China. The NCA model achieved the highest performance with an OA of 0.858, F1 score of 0.753, Kappa coefficient of 0.799, and FOM of 0.427. Comparisons of land use data of Wuhan city from 2000 and 2010 with the simulated optimal results indicate that forest areas closer to urban centers are more susceptible to modernization processes, showing the advantage of NCA in accurately simulating land use changes in the central urban area.
A Smart Application Frame of Remote Sensing in Non-grain Production Data Governance
Authors: Zhang Longqi , He Wenwen , Guo Yunkai , Teng Xiao
Published: May 2024

Abstract. This study addresses the intricate challenges encountered in the data governance process of Non-grain Production (NGP) on Arable land. This involves managing data from diverse sources, with varying accuracies and formats, and utilizing multiple specialized software tools. An object-oriented approach is adopted to encapsulate experiential knowledge related to the data and associated processing methods, thus creating an Application Knowledge Body Model (AKBM). This model acts as a conduit between users and computational resources, encompassing various types of data and their corresponding processing and analysis methods. Moreover, by employing model inference techniques to devise methods for transitioning from raw data models to target models, a foundation is laid for the accumulation, sharing, and intelligent application of expertise on data, methods, models, and knowledge.The application examples demonstrate that users can directly construct new solutions containing relevant data and associated processing methods, rather than grappling with a multitude of data files and complex specialized software when encountering novel challenges. This promotes collaborative development in data governance on geospatial big data platforms, significantly enhancing governance efficiency, improving the quality of information support in NGP cultivation management, advancing current technological capabilities, and fostering the progression of related technologies.
The time-series GF-1 WFV data monitoring of sugarcane using a Random Forest Algorithm in South China
Authors: Chen Chen , Lou Linjiang , Cheng Tao , Gao Xinyuan , Liu Yu
Published: May 2024

Abstract. There is large distribution of sugarcane growth in south China which is play an important role of sugar industry. Remote sensing technology is used in sugarcane monitoring for large areas. However, the optical satellite data coverage is influenced by the rainy weather especially in the grand growth period of sugarcane. GF-1 WFV has widely swath 800km and short revisit time which is ideal data for this study area. In this paper, the random forest model was chosen to get a precise classification result of sugarcane based on time-series band value and 5 spectral indexes image is 89.73% and the Kappa coefficient is 0.65 which is satisfied the overall extraction of sugarcane for large area is the southern China. Furthermore, the decision tree classification was chosen as a comparative experience research.
Multi-temporal Monitoring for Road Slope Collapse by Means of LUTAN-1 SAR Data and High Resolution Optical Data
Authors: Zhang Xiang , Tang Xinming , Li Tao , Zhou Xiaoqing , Hu Haifeng , Zhang Xuefei , Lu Jing
Published: May 2024

Abstract. Collapse is one of the most destructive natural disaster, being sudden, frequent, and highly concealed, causing large-scale damage. On August 10, 2023, the slope of 108 national highway in Weinan, Shaanxi Province collapsed. The lower edge of the collapse slope body is the Luohe river, and the collapse body rushes into the river to form a barrier lake. Remote sensing technique can provide multiple dimensional information for disaster emergency and management. Lutan-1 SAR satellites are the first group L-band SAR constellation for multiple applications in China. Owing to the precise orbit control ability and high revisit characteristics for Lutan-1 SAR satellites, surface deformation monitoring with centimeter even millimeter accuracy may be achieved. Based on the multi-temporal pre-disaster and post-disaster Lutan-1 SAR data and high resolution optical data, the collapse information including the pre-disaster and post-disaster were extracted and analysed. From July 11 to 27, 2023, the pre-collapse deformation was obtained with the maximum value of 6 cm, and obvious deformation occurred before the collapse. Lutan-1 monitored results pre-collapse can provide certain information for disaster early identification. From July 27 to August 24, 2023, due to the serious incoherence caused by large deformation and ground changes, effective deformation information cannot be obtained based on the InSAR technique. In addition, the collapse information was clearly extracted by the high resolution optical data acquired pre-collapse and post collapse. After the collapse, significant deformation was extracted from August 24 to September 21 with the maximum value of 6 cm, indicating that obvious deformation still occurred over the collapse area. Through the analysis for the series results obtained by SAR and optical data, it is favourable for disaster emergency and management.
A Robust Registration Method for Multi-view SAR Images based on Best Buddy Similarity
Authors: Zhang Yifan , Li Zhiwei , Wang Wen , Mu Minzheng , Zuo Bangwei
Published: May 2024

Abstract. Due to the influence of imaging angle and terrain undulation, multi-view synthetic aperture radar (SAR) images are difficult to be directly registered by traditional methods. Although feature matching solves the issue of image rotation and maintains scale invariance, these methods often lead to non-uniformity of interest points and may not achieve subpixel accuracy. The traditional template matching method makes it difficult to generate correct matches for multi-view SAR oblique images. In this paper, a multi-view SAR image template matching method based on Best Buddy Similarity (BBS) is proposed to solve the traditional methods' problem. Firstly, the initial correspondences between images are established according to the Range-Doppler model of SAR images. Secondly, a sliding window search is performed on the established correspondence, the BBS is calculated, and the subpixel locations of the peaks on the similarity map are estimated to achieve a fine match. In the calculation process of BBS, the SAR-ROEWA operator is used to suppress the speckle noise of SAR images. The experiment demonstrated that SAR-BBS can accurately match SAR images with large rotation angle. The peak value on the search window is significant. The registration accuracy of SAR-BBS outperforms the other state-of-the-art methods.
Research on Photovoltaic Development in Northwestern China using Remote Sensing Images
Authors: Zou Yunjia , Zhang Tao , Wang Guanghui , Zhang Wei , Liu Ting , Dai Hailun
Published: May 2024

Abstract. Photovoltaics, a clean energy source, have received widespread attention worldwide recently. Many countries are carrying out photovoltaic construction, while also compiling and analyzing their photovoltaic development status. The same goes for China. In northwestern China, a considerable number of cities lack electricity. Meanwhile, its vast plains and abundant sunlight are conducive to the construction of photovoltaics. Therefore, the northwestern China has vigorously carried out photovoltaic construction nowadays. With the support of high-resolution and multi-temporal remote sensing images, we are able to analyze the development status of photovoltaics in these regions. We chose six provinces in northwestern China as our research areas and took three steps to complete our studies. Firstly, we extracted patterns of photovoltaics using deep learning methods. Secondly, based on the patterns and national land use survey data, we calculated the distribution and development status of photovoltaics in each province. Thirdly, we present the statistical results in figures and charts, showing the photovoltaic construction status and its development trend. We finally made conclusions and discussions about our insufficiency in work and future plans for further study.
Polar-vision1: A Novel Collinearity Equation of Perspective Projection in Polar Coordinate System
Authors: Zuo Zhengkang , Zhang Bin
Published: May 2024

Abstract. Progress has been made in the community of photogrammetry and 3d computer vision in addressing the mathematical challenge posed by the collinearity equation. We introduce a new method for establishing the coordinate reference for 2d pixels and 3d landmarks using 'angular coordinates'. The mathematical relationships required for converting 3d landmarks, expressed in angular coordinates, to the camera framework are presented. The landmarks are then projected using perspective projection to obtain 2d pixels represented in angular coordinates. This framework is formally nominated as the 'Polar-vision1', which has been developed and integrated into the commercial software G3D-Cluster. Its application to pinhole camera image processing has demonstrated superior efficiency and admission rates of tie points, as well as reconstruction detail capabilities, compared to OpenMVG, achieving approximately a 1.4× improvement. The project 'Key Technologies and Tool System for Realistic 3D Modeling through Integration of Multi-Source Information in the Space-Air-Ground Domain' was awarded First Prize at the 2023 Surveying Science and Technology Awards, with Polar-vision1 as one of the innovative points.
Development of Multi-Strip Image Mosaicking for KOMPSAT-3A Images
Authors: Son Jong-Hwan , Park Sumin , Ban Hyeon-Ju , Kim Taejung
Published: May 2024

Abstract. High-resolution satellite imagery has a limitation in terms of coverage area. This limitation presents challenges for extensive-scale analysis at regional or national levels. To maximize the utility of high-resolution satellite imagery, the implementation of image mosaicking techniques is essential. In this paper, we have developed seamline extraction techniques and relative geometric correction optimized for high-resolution satellite imagery. Ultimately, we proposed a multi-strip image mosaicking method for KOMPSAT-3A (Korea Multi-Purpose Satellite-3A) images. We applied the Dijkstra's shortest path algorithm to efficiently extract seamlines. we also performed image registration based on feature matching and homography transformation to correct the relative geometric errors between input images. We conducted experiments with our methods using 29 scenes from KOMPSAT-3A L1G data. The results indicated high relative geometric accuracy, with an average error of 1.63 pixels. Furthermore, we were able to obtain high-quality seamless mosaic images. Our proposed method is expected to enhance the utility of KOMPSAT-3A imagery for large-scale environmental and urban analysis and to provide more accurate and comprehensive data.
Preface: ISPRS Technical Commission I Midterm Symposium on “Intelligent Sensing and Remote Sensing Application”
Authors: Tang Xinming , Tommaselli Antonio Maria Garcia , Zhang Tao , Xie Junfeng
Published: May 2024

Abstract. The ISPRS Technical Commission I Midterm Symposium on "Intelligent Sensing and Remote Sensing Application" was held in Changsha, China, during May 13–17, 2024, aiming to provide a platform to share the latest researches, advanced technologies and application experience, to discuss the future development and to seek international cooperation in various forms. The Symposium has received 229 full paper and abstract s, among them 45 double-blind peer-reviewed full papers were published in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information, and 165 papers accepted through abstract review were published in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. These papers are mostly dedicated to topics of the 8 TC I Working Groups, 3 Inter-commission Working Groups, including Satellite Missions and Constellations for Remote Sensing, Mobile Mapping Technology, Multispectral, Hyperspectral and Thermal Sensors, LiDAR, Laser Altimetry and Sensor Integration, Microwave and InSAR Technology for Earth Observation, Orientation, Calibration and Validation of Sensors, Data Quality and Benchmark of Sensors, Multi-sensor Modelling and Cross-modality Fusion, Robotics for Mapping and Machine Intelligence, Autonomous Sensing Systems and their Applications, Digital Construction: Reality Capture, Automated Inspection and Integration to BIM, Point Cloud Generation and Processing, Artificial Intelligence Technology Related to Sensor Systems, Multi-sensor Remote Sensing Applications.. These papers presented the latest trends of sensor systems. The full papers and abstracts were reviewed by the members of the Symposium Scientific Committee comprised of Working Group officers and invited experts. We would like to take this opportunity to express our great gratitude to the Scientific Committee, Local Organizing Committee, Sponsors, Exhibitors and all those who have contributed to this successful Symposium. We also want to express our thanks to the authors for their excellent papers and presentations. Tang Xinming, Antonio Maria Garcia Tommaselli, Zhang Tao, Xie JunfengISPRS Technical Commission I on Sensor SystemsMay 2024, Changsha, China
Whereto From Here? A Discussion Among International Scholars of Inclusive Education
Authors: Matheson Ian A. , Merz-Atalik Kerstin , Christou Theodore , Kruschel Robert , Florian Lani , Jahnukainen Markku , Köpfer Andreas , MacCormack Jeffrey , Whitley Jessica
Published: May 2024

Which ideas are central to inclusive education in Canada, and how do educators and researchers build capacity to provide it? Who or what is still missing, and how can international collaboration help us accomplish our goals in inclusive education? This article reports on a discussion among international scholars of inclusive education as they considered these questions together. These scholars, from Canada, Scotland, Finland, and Germany, considered the lessons they (we) have learned from our history of inclusive education in Canada. They drew on their experience with collaborative research to outline some clear benefits of working together, and learning from each other, to find progressive ways forward in inclusive education.
UPAYA DISIPLIN KERJA, MOTIVASI, DAN LINGKUNGAN KERJA TERHADAP KEPUASAN KERJA PADA PT KARYADIBYA MAHARDIKA
Authors: Syafrizal Asnita Putri , Pratama Dewi Yulianti , Hasna Nisrina , Fauziah Sifa , Paramarta Vip
Published: May 2024

Penelitian ini bertujuan untuk mendalami hubungan antara disiplin kerja, motivasi, dan lingkungan kerja terhadap kepuasan kerja karyawan di PT Karyadibya Mahardika dengan menggunakan pendekatan kualitatif. Metode penelitian ini melibatkan pengumpulan data melalui wawancara mendalam dengan sejumlah karyawan serta observasi langsung di lingkungan kerja perusahaan. Analisis data dilakukan dengan menggunakan pendekatan kualitatif deskriptif, di mana temuan dan pola-pola yang muncul dari wawancara dan observasi dianalisis untuk memahami pengaruh disiplin kerja, motivasi, dan lingkungan kerja terhadap kepuasan kerja karyawan. Hasil penelitian menunjukkan bahwa faktor disiplin kerja yang terjaga, motivasi yang terus mendorong, dan lingkungan kerja yang kondusif sangat berpengaruh dalam membentuk kepuasan kerja karyawan di PT Karyadibya Mahardika. Informasi yang diperoleh dari penelitian ini diharapkan dapat memberikan wawasan mendalam kepada manajemen perusahaan untuk mengembangkan strategi yang lebih baik dalam meningkatkan kepuasan kerja karyawan, yang pada gilirannya dapat meningkatkan produktivitas dan kinerja organisasi secara keseluruhan.Kata kunci: Disiplin Kerja, Motivasi, Lingkungan Kerja, Kepuasan, SDM
SISTEM PELAPORAN PENCATATAN AKUNTANSI ATAS PENDAPATAN PAJAK KENDARAAN BERMOTOR DENGAN MENGGUNAKAN METODE CASH BASIS PADA LAYANAN SAMSAT KELILING
Authors: Turini Turini , Hatta Muhammad , Fanisa Nur
Published: May 2024

AbstractRegional Revenue Management Center for Kab. Cirebon 1 Sumber is the center of an organization or agency that is under the local government which has responsibility for receiving regional revenues through coordinating and collecting taxes, levies, tax sharing, balancing funds and others. This study aims to design, implement, analyze, and implement.The data collection methodology used in a study is observation. The system used in this application program is PHP (Hypertext Preprocessor) as the web, MySQL as the database design, using the Google Chrome browser and using a cash-based method (cash basis). In reporting daily receipts at the central office for regional revenue management in the Cirebon Regency, 1 source is still using the manual, namely using HVS paper, there is accumulation of files, data recording errors, and in making reports less efficient and effective. cirebon 1 source is illustrated by using a running flowchart accompanied by explanatory narration, then made computerized into a flowmap to be applied to the system so as to minimize the occurrence of human errors, file stacking, lost data, to be more efficient and effective. Keywords: Income, Motor Vehicle Tax, Cash Basis, Mobile Samsat
LITERATURE REVIEW: SIARAN LANGSUNG TIKTOK TERHADAP KESADARAN MEREK, KEPERCAYAAN MEREK, DAN KEPUTUSAN PEMBELIAN
Authors: Yuningsih Yuningsih , Lukita Chandra , Pranata Sudadi
Published: May 2024

This research examines the influence of TikTok live streaming in the context of marketing and consumer behavior. It aims to provide deeper insights into how TikTok live streaming affects consumer behavior, including enhancing brand awareness, strengthening brand trust, and influencing purchase decisions. The method used in this research is qualitative research with a literature review approach. The results of the study indicate the importance of TikTok live streaming in the context of marketing and consumer behavior. Marketing strategies utilizing live streaming need to be tailored to the characteristics of the target market and the desired objectives. Creating brand awareness and generating engaging content on social media can enhance consumer trust and drive purchase decisions.Kata kunci: Interaktivitas, Kepercayaan merek, Keputusan pembelian, Kesadaran merek, Siaran Langsung TikTok
Simulation and Modeling of Moisture Distribution in Drip Irrigated Onion
Authors: Neelam Patel  , T.B.S. Rajput
Published: May 2024

The design of drip irrigation system requires the knowledge of water distribution in the soil, which may be described and predicted by solving the flow through porous media equations. The software HYDRUS-2D simulates the three dimensional axi-symmetric water flow; solute transport, root water and nutrient uptake based on finite-element numerical solutions of the flow equations. In a field study, conducted for 3 years (1999-2002), HYDRUS-2D was used for simulation of moisture distribution pattern in the root zone of onion crop grown in sandy loam soil. The performance of HYDRUS -2D was evaluated by comparing its simulated value with the observed soil moisture patterns through certain indicators such as average absolute error (AAE), average relative error (ARE) and root mean square error (RMSE). Range of AAE (-5.65 to -2.86), ARE (0.112 to 0.147) and RMSE (3.58 to 6.10) indicate good match between simulated and observed soil moisture patterns, and hence, HYDRUS-2D is recommended for use as a tool for simulation of soil moisture distribution in onion fields.
Economics of Rainwater Harvesting and Recycling for Winter Vegetable Production in Mid Hills of Meghalaya
Authors: R. K. Singh  , T. D. Lama  , U. S. Saikia  , K. K. Satapathy
Published: May 2024

The economic feasibility of rainwater harvesting and recycling for winter season vegetable cultivation in the mid hills of Meghalaya was analyzed. The weekly rainfall during November to mid March being less than the weekly evaporation, irrigation becomes necessary. The study revealed that rainwater could be successfully harvested and stored in pond with agri. film lining, reducing the seepage loss by 94%. Four locally grown high-value vegetables viz. cabbage, cauliflower, pea and lettuce were cultivated during November to mid March. The harvested rainwater was used through sprinkler system to irrigate the crops. The average yield of cabbage, cauliflower, pea and lettuce was 426, 280, 44 and 120 q/ha. respectively. The overall benefit-cost ratio for the whole system for 1 ha vegetable cultivation area was 2.7 over a period of 15 years. A farm of I ha area totally under vegetable cultivation can recover the initial investment in two years. The benefit-cost ratio may be further enhanced by utilizing the harvested water for fish production and livestock rearing. Thus. efficient utilization and management of rainwater may help transform the subsistence agriculture into a profit earning enterprise in the region.
Development of Relationship between Performance Irrigation Parameters and Furrow Irrigation Design Variables, Yield and Net Returns
Authors: Sunil Garg  , B.S. Gulati  , M.R Kaushal  , A.K. Jain
Published: May 2024

Several parameters that measure the irrigation performance were analyzed for their relation to design variables, relative yield and net return. Water application efficiency (Ea), water requirement efficiency (Er), water distribution efficiency (Ed) and requirement distribution efficiency (Erd) were examined with respect to design variables (inflow rate, length of run and time of inflow). The exponential function was best fit between water requirement efficiency and design variables and quadratic function fitted well between water requirement efficiency and relative yield as well as net return. The water requirement efficiency and requirement distribution efficiency correlated very well with design variables, relative yield and net return. The water distribution efficiency correlated poorly with relative yield and net return. Water application efficiency (Ea), had a poor linear correlation with design variables.
Comparative Assessment of Manual Paddy Drum Seeders
Authors: D.C. Baruah
Published: May 2024

The present investigation was carried out to test the feasibility as well as to assess comparative performance of four different drum type direct sowing devices for paddy. The results of the experiment indicated that mechanical drum seeders ensured increase in field capacity resulting in saving in time compared to manuallinc sowing. Amount of man-hour saving varied within a range of 78% to 95% over the manual sowing, the highest saving obtained for a commercial plastic made drum seeder. The saving of man-hour was negatively correlated with the machine weight. The lighter weight (8.00 kg) and simpler construction were the main reason of speedy operations of plastic drum seeder with highest amount of man-hour saving (95%). Variations of plant population and grain yield were found statistically insignificant amongst the seeding treatments.
Technical Feasibility of Mechanical Planting of Sunflower Seeds
Authors: Sukhbir Singh  , D.N. Sharma
Published: May 2024

In Haryana state, broadcasting and dibbling on ridges are the most commonly used conventional practices for sunflower sowing which are very much time consuming and laborious operations. Four different types of rollers were fabricated and evaluated under laboratory condition in terms of quantity of seed metered, volumetric cell fill, seed germination and seed damage at three seed column height in hopper and four different speeds. Uniformly shaped triangular small cell type roller (R) gave optimum performance between 17-40 rpm of its operation. A prototype of single row manually operated sunflower planter was developed by using optimum roller (R4 ) and evaluated at University and farmers' field. The average field capacity of the planter was 0.1030 ha/h. The seed germination was 22.66 plants/m2 and 14.66 plants/m2 for MYCO-8 & HS-l varieties. respectively. The sowing of sunflower by planter resulted in net saving 01'57.16 man-hours and 1.50 tractor-hours per hectare over broadcasting and 57.91 man-hours and 2.25 tractor-hours per hectare over dibbling method
THE EFFECT OF LIQUIDITY, SOLVENCY AND ACTIVITY ON PROFITABILITY WITH SALES GROWTH AS A MODERATING VARIABLE IN PROPERTY AND REAL ESTATE COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE
Authors: Banurea Septina Eka Nia , Nurwati Solikah , Muliyani Agustina
Published: May 2024

Objective –  This study aims to analyze empirically the effect of liquidity, solvency, and activity on profitability with sales growth as a moderating variable in property and real estate companies listed on the Indonesia Stock Exchange.
Design/Methodology/Approach –  This research uses Quantitative research. Sampling was carried out by purposive sampling, and obtained a sample of 20 sample companies. The data analysis method used is SmartPLS software.
Findings – The results of this research analysis show that liquidity has no significant effect on profitability; solvency and activity have a significant effect on profitability; sales growth are not able to moderate the effect of liquidity, solvency, and activity on profitability.
Conclusion and Implications – The liquidity has no significant effect on profitability; solvency and activity have an influence and are significant to profitability; sales growth is not able to moderate the influence of liquidity, solvency and activity on profitability. The company needs to innovate and evaluate strategies to increase the contribution of sales growth to the company. Investors and potential investors are more selective in choosing companies to invest in by paying attention to the company's financial condition.
PROFITABILITY IS NOT A CONSIDERATION FOR INVESTORS IN INDONESIAN BANKING SHARES
Authors: Isman
Published: May 2024

Objective –  This research aims to analyze the effect of profitability on share prices.
Design/Methodology/Approach –  Sample is a go bank public on the Indonesian Stock Exchange. The type of data used is quantitative data. Quantitative data in the form of stock price data, earnings per share, return on assets, and return on equity. The data source for this research is secondary data from bank financial reports for 2018-2021 from the Indonesian Stock Exchange. The sample in this research was 26 banks that fell into the purpose sampling category. The method used in this research is multiple linear regression analysis with SPSS version 26 software.
Findings – The results of this research analysis show that profitability as measured using ROA and ROE does not have a significant effect on share prices. Likewise, it was concluded that EPS had no significant effect on share prices. However, together ROA, ROE and EPS have a significant influence on share prices.
Conclusion and Implications – In the 2018-2021 period, Indonesian banking share prices are not determined by movements in earnings per share, return on equity and return on assets due to the impact of the Covid-19 pandemic, which means the majority of investors tend to wait for the pandemic to end to make investment decisions.
An unusual cause of adult transverse colonic intussusception with obstruction: Multiple large submucosal lipomas in a 50-year-old male
Authors:   Ross University School of Medicine, Bridgetown, Barbados, Merhavy Zachary I
Published: May 2024

Intussusception is a gastrointestinal condition that predominantly affects the pediatric population. Although uncommon, it can occur in adults and is typically due to a pathological lead point that causes telescoping of the intestine during peristalsis. In this case, a 50-year-old male presents with abdominal pain, distension, diarrhea, and unintentional weight loss, which was revealed to be caused by intussusception that originated at a cluster of submucosal lipomas in the transverse colon. This patient had recently immigrated to the U.S. from Africa, and had missed his colorectal screening, which is recommended at age 45 for every person. It is crucial to accurately screen for, diagnose, and surgically treat this condition to prevent downstream complications such as bowel infarction or perforation.
Anorectal Melanoma: A Case Report
Authors: Srivastava Pranjal , Jain NK , Dwivedi Sushant
Published: May 2024

Anorectal melanoma is a rare and aggressive form of mucosal melanoma that is difficult to diagnose early due to nonspecific symptoms like rectal/anal bleeding, anal pain, or the presence of an anal mass. Its prognosis is generally poor, with most cases already metastasized at diagnosis. A case report is presented of a patient initially presenting with anaemia, painful defecation and rectal bleeding, later diagnosed with stage IV anorectal melanoma. There is limited literature on this disease, leading to a lack of comprehensive
understanding. Surgical resection is the main treatment, but over 80% of patients die within five years due to distant metastasis. The 5-year survival rate is estimated to be between 6% and 22%.

Keywords: Anorectal, Melanoma, mucosa