Preprints
Filtering by Subject: Computer Engineering
HydroSuite-AI: Facilitating Hydrological Research with LLM-Driven Code Assistance
Published: 2024-11-26
Subjects: Civil Engineering, Computational Engineering, Computer Engineering, Environmental Engineering, Science and Mathematics Education, Systems and Communications
In the hydrology and environmental domains, researchers often encounter complex hydrological models, evolving frameworks and libraries, and complex documentation, which necessitate both domain knowledge and coding expertise. This paper introduces HydroSuite-AI, a large language model-enhanced web application designed to address these challenges by integrating three open-source libraries: [...]
Tree level change detection over Ahmedabad city using very high resolution satellite images and Deep Learning
Published: 2024-11-03
Subjects: Computer Engineering
In this study, 0.5m high resolution satellite datasets over Indian urban region was used to demonstrate the applicability of deep learning models over Ahmedabad, India. Here, YOLOv7 instance segmentation model was trained on well curated trees canopy dataset (6500 images) in order to carry out the change detection. During training, evaluation metrics such as bounding box regression and mask [...]
ml4xcube: Machine Learning Toolkits for Earth System Data Cubes
Published: 2024-10-09
Subjects: Computer and Systems Architecture, Computer Engineering, Engineering, Geography, Remote Sensing, Social and Behavioral Sciences
Rapidly changing climate conditions and the increase in extreme events are posing severe challenges to human life and infrastructure, requiring sophisticated analytical capabilities for hazard prediction and disaster risk management. Earth System Data Cubes (ESDCs) have become an essential tool in Earth System Sciences (ESS) by organizing large-scale, multivariate environmental datasets into a [...]
Comparative Analysis of SVM and CNN for Hyperspectral Image Classification
Published: 2024-08-13
Subjects: Computer Engineering, Computer Sciences, Other Computer Sciences, Physical Sciences and Mathematics
This paper presents a comparative analysis of tra- ditional machine learning methods and Convolutional Neural Networks (CNNs) for hyperspectral image classification. Utilizing the Indian Pines dataset, we explore the efficacy of Principal Component Analysis (PCA) combined with a Support Vector Machine (SVM) classifier against a deep learning approach involving CNNs. Our methodology includes [...]
HydroSignal: Open-Source Internet of Things Information Communication Platform for Hydrological Education and Outreach
Published: 2024-07-16
Subjects: Civil and Environmental Engineering, Computer Engineering, Electrical and Computer Engineering, Engineering Education, Environmental Engineering
This study introduces HydroSignal, a low-cost, open-source platform designed to democratize hydrological monitoring by leveraging the power of Internet of Things (IoT) technology. With its web-based interface, HydroSignal aims to make vital hydrological data easily accessible to a wide range of users, including professionals, educators, and students, thereby promoting improved environmental [...]
Geo-WC: Custom Web Components for Earth Science Organizations and Agencies
Published: 2024-04-16
Subjects: Civil and Environmental Engineering, Civil Engineering, Computer Engineering, Engineering Education, Hydraulic Engineering
The development of web technologies and their integration into various fields has allowed a new era in data-driven decision-making and public information accessibility, especially through their adoption of monitoring and quantification environmental data resources provided by governmental institutions. While the use of web technologies has given way to the creation of democratized applications, [...]
Towards an Open and Integrated Cyberinfrastructure for River Morphology Research in the Big Data Era
Published: 2024-02-16
Subjects: Computer and Systems Architecture, Computer Engineering, Computer Sciences, Databases and Information Systems, Engineering, Environmental Education, Environmental Engineering, Geomorphology, Hydrology, Systems and Communications, Water Resource Management
The objective of this paper is to present the initial illustration of a cyberinfrastructure named the River MORPhology Information System (RIMORPHIS) that addresses the current limitations related to river morphology data and tools. A new specification for data and semantics on river morphology datasets has been developed to support the web-based platform for discovering and visualization of [...]
Spatial Downscaling of Streamflow Data with Attention Based Spatio-Temporal Graph Convolutional Networks
Published: 2023-03-31
Subjects: Civil and Environmental Engineering, Computer Engineering, Engineering
Accurate streamflow data is vital for various climate modeling applications, including flood forecasting. However, many streams lack sufficient monitoring due to the high operational costs involved. To address this issue and promote enhanced disaster preparedness, management, and response, our study introduces a neural network-based method for estimating historical hourly streamflow in two [...]
Deep Learning-Based Super-Resolution of Digital Elevation Models in Data Poor Regions.
Published: 2022-10-29
Subjects: Artificial Intelligence and Robotics, Computer Engineering, Geomorphology
In order to develop reliable models, the geoscientific community requires high-resolution data sets. However, the collection of such data is a persistent challenge due to the limitations of resources. The concept of super-resolution, a method from the field of machine learning, can be used to predict a high-resolution version of a low-resolution dataset to improve usability in geoscientific [...]
Knowledge graph construction and application in geosciences: A review
Published: 2021-04-30
Subjects: Artificial Intelligence and Robotics, Computer Engineering, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Sciences
Knowledge graph (KG) is a topic of great interests to geoscientists as it can be deployed throughout the data life cycle in data-intensive geoscience studies. Nevertheless, comparing with the large amounts of publications on machine learning applications in geosciences, summaries and reviews of geoscience KGs are still limited. The aim of this paper is to present a comprehensive review of KG [...]
River Planform Extraction From High-Resolution SAR Images Via Generalised Gamma Distribution Superpixel Classification
Published: 2020-10-21
Subjects: Computer Engineering, Electrical and Computer Engineering, Engineering, Geology, Geomorphology, Hydrology
The extraction of river planforms from remotely sensed satellite images is a task of crucial importance to many applications such as land planning, water resource monitoring or flood prediction. In this paper we present a novel framework for the extraction of rivers from Synthetic Aperture Radar (SAR) images, based on superpixel segmentation and subsequent classification. Superpixel segmentation [...]
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Published: 2020-06-19
Subjects: Civil and Environmental Engineering, Computer Engineering, Engineering, Environmental Engineering
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety, and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combined with the growing availability of computational resources and popularity of deep learning, these [...]
D-SRGAN: DEM Super-Resolution with Generative Adversarial Networks
Published: 2020-04-18
Subjects: Civil and Environmental Engineering, Computer Engineering, Engineering
LIDAR (light detection and ranging) is an optical remote-sensing technique that measures the distance between sensor and object, and the reflected energy from the object. Over the years, LIDAR data has been used as the primary source of Digital Elevation Models (DEMs). DEMs have been used in a variety of applications like road extraction, hydrological modeling, flood mapping, and surface [...]
Interferometric Processing of ScanSAR Data Using Stripmap Processor: New Insights from Coregistration
Published: 2020-04-13
Subjects: Aerospace Engineering, Civil and Environmental Engineering, Computer Engineering, Earth Sciences, Electrical and Computer Engineering, Engineering, Geology, Geophysics and Seismology, Glaciology, Hydrology, Mining Engineering, Other Earth Sciences, Physical Sciences and Mathematics, Tectonics and Structure, Volcanology
Processing scanning synthetic aperture radar (ScanSAR) data using a stripmap processor, which is called full-aperture processing, has been the choice of many researchers. ScanSAR data are known to require very high azimuth coregistration precision which is usually achieved by a geometrical coregistration followed by a spectral diversity coregistration on the ScanSAR burst. However, for [...]
Measuring Azimuth Deformation With L-Band ALOS-2 ScanSAR Interferometry
Published: 2020-04-06
Subjects: Aerospace Engineering, Civil and Environmental Engineering, Computational Engineering, Computer Engineering, Earth Sciences, Electrical and Computer Engineering, Engineering, Geology, Geomorphology, Geophysics and Seismology, Glaciology, Hydrology, Mining Engineering, Other Earth Sciences, Physical Sciences and Mathematics, Signal Processing, Tectonics and Structure, Volcanology
We analyze the methods for measuring azimuth deformation with the L-band Advanced Land Observing Satellite-2 (ALOS-2) scanning synthetic aperture radar (ScanSAR) interferometry. To implement the methods, we extract focused bursts from the ALOS-2 full-aperture product, which is the only product available for ScanSAR interferometry at present. The extracted bursts are properly processed to measure [...]