Academic Articles & Research Papers

An Unsupervised and End-to-End Registration Method Using Offset Field and Pseudodata for Video SAR Images

Video synthetic aperture radar (video SAR) has been successfully applied in many fields and the registration of the video SAR images has been proven to be a crucial step in their preprocessing. However, video SAR images exhibit more severe ...

Small Object Detection Algorithm Based on Improved YOLOv8 for Remote Sensing

Due to the limitations of small targets in remote sensing images, such as background noise, poor information, and so on, the results of commonly used detection algorithms in small target detection is not satisfactory. To improve the accurac...

Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach

The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), th...

MAINSTREAMING METADATA INTO RESEARCH WORKFLOWS TO ADVANCE REPRODUCIBILITY AND OPEN GEOGRAPHIC INFORMATION SCIENCE

Reproducible open science with FAIR data sharing principles requires research to be disseminated with open data and standardised metadata. Researchers in the geographic sciences may benefit from authoring and maintaining metadata from the e...

Remote Sensing for Operational Surveillance of Mosquito-Borne Diseases.

TranSDet: Toward Effective Transfer Learning for Small-Object Detection

Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular metho...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

A coarse to fine network for fast and accurate object detection in high‐resolution images

Abstract Because of the popularisation of high‐resolution images, detecting objects in these images quickly and accurately has attracted increasing attention in recent studies. Current convolutional neural networks (CNN)‐based detection met...

AutoWindLoc: Precise Localization of Wind Turbines in High-Resolution Orthophotos for Enhanced Registers

The paper proposes a novel framework for automatically detecting wind turbines in orthophotos, transferring this information to a database, and linking detected turbines to an existing registry to minimize location inaccuracy. This inaccura...

AN IMPROVED MASK R-CNN: EXTRACTION OF DOOR AND WINDOW INSTANCES ON VILLAGE BUILDING FAÇADE IMAGES

Rapid access to the basic structure of village buildings is conducive to the investigation of the load-bearing bodies of village houses and provides data support for disaster assessment and post-disaster rescue and reconstruction. The devel...

SnowMapPy: An automated GEE Python tool for snow cover mapping and monitoring in the Moroccan Atlas Mountains

SnowMapPy is an open-source Python-based package developed to streamline the collection, processing, and analysis of MODIS snow cover data from Terra and Aqua satellites. By automating essential steps, including data clipping, reprojection,...

SCM: A Searched Convolutional Metaformer for SAR Ship Classification

Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of ...

Problems In Indoor Mapping and Modelling

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

Monitoring the spread of a pathogenic insect on vineyards using UAS

Globalisation has contributed to rapid economic growth but has also exposed vulnerabilities such as the spread of pests in agriculture. An example is the Popillia Japonica Newman beetle, introduced to Italy in 2014, which has caused signifi...

Remote sensing image road network detection based on channel attention mechanism

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high trainin...

Remote Sensing of Vegetation Structure Using Computer Vision

High spatial resolution measurements of vegetation structure in three-dimensions (3D) are essential for accurate estimation of vegetation biomass, carbon accounting, forestry, fire hazard evaluation and other land management and scientific ...

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DSpix2pix: A New Dual-Style Controlled Reconstruction Network for Remote Sensing Image Super-Resolution

Super-resolution reconstruction is a critical task in remote sensing image classification, and generative adversarial networks (GANs) have emerged as a dominant approach in this field. Traditional generative networks often produce low-quali...