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- High-resolution remote sensing images123:
- Are obtained from remotely sensed sensors and platforms.
- Include optical imagery, SAR, and LiDAR.
- Reveal finer details such as individual trees, vehicles, buildings, and more2.
- Are widely available, opening new opportunities for geo-related applications1.
- Are characterized by spatial features of large spatial scales across multiple directions, which are crucial for dense prediction tasks such as semantic segmentation and change detection3.
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.With the rapid development of remotely sensed sensors and platforms, multi-source high resolution remote sensing images (e.g., optical imagery, SAR, and LiDAR) are widely available, opening new opportunities for geo-related applications.www.mdpi.com/journal/remotesensing/special_issu…High-resolution remote sensing photography has the apparent benefit of revealing finer details such as individual trees, vehicles, buildings, and more. In EOSDA LandViewer, you may choose from eight data sets from satellites with the highest spatial resolutions, ranging from 5 meters (SPOT 5) to 40 centimeters (Kompsat-3A).eos.com/blog/spatial-resolution/VHR remote sensing images are characterized by spatial features of large spatial scales across multiple directions, which are crucial for dense prediction tasks such as semantic segmentation and change detection.arxiv.org/html/2404.02668v1 - People also ask
WEBThis paper presents an overview of the current problems and challenges associated with remote sensing image instance segmentation, as well as future trends and developments.
Spatial Resolution In Remote Sensing: Which One To Choose?
- The biggest benefit of high spatial resolution vs. low spatial resolution is the precise level of detail it shows. Additionally, high-resolution remote sensing provides coverage whenever and wherever it is needed. However, higher-quality images are typically more expensive and less available to customers. Another drawback of high resolution remote ...
- Occupation: Project
- Gender: Female
- Works For: EOS Data Analytics
- Published: Dec 22, 2022
- Studies of high resolution remote sensing images
WEBNov 15, 2023 · With the rapid development of remotely sensed sensors and platforms, multi-source high resolution remote sensing images (e.g., optical imagery, SAR, and …
WEBApr 27, 2024 · High-resolution remote sensing images can give rich feature information and finely present the spatial structure and textural features due to their complex and …
WEBAug 18, 2016 · Hence, a deep multimodal neural network model for semantic understanding of the high resolution remote sensing images is proposed in this paper, which uses …
WEBIn this paper, deep transfer learning is the core technology of remote sensing image classification model, and VGG16, Inception V3, ResNet50 and MobileNet are used to …
WEBJan 3, 2021 · High-resolution remote sensing images can provide many surface features, such as shape, texture, size and other features, with a richer spatial information that can …
WEBFeb 1, 2019 · Automatic detection of buildings from very high resolution (VHR) satellite images is a current research hotspot in remote sensing and computer vision. However, many irrelevant objects with similar …
WEBAug 1, 2020 · In this paper, we propose a deeply supervised image fusion network (IFN) for change detection in high resolution bi-temporal remote sensing images. Specifically, …
WEBFeb 1, 2020 · To our knowledge, GID is the first and largest well-annotated land-cover classification dataset with high-resolution remote sensing images up to 4 m. It can …
Transformer based on channel-spatial attention for accurate
WEBSep 14, 2022 · The primary goal of high-resolution remote sensing (HRRS) image scene classification is to correctly classify a given remote sensing image according to its …
Automatic registration of urban high-resolution remote sensing …
WEBAug 24, 2022 · Automatic registration of high-resolution remote sensing images (HRRSIs) has always been a severe challenge due to the local deformation caused by …
Using high-resolution remote sensing images to explore the …
WEBMay 28, 2021 · Based on high-resolution images, this study used concentric buffer zones to explore the characteristics and relationship between landscape pattern indexes (LPIs) …
Remote Sensing | Free Full-Text | High-Resolution Remote …
WEBJul 14, 2017 · In this paper, we propose that more powerful features for high-resolution remote sensing image representations can be learned using only several tens of …
A comprehensive review on deep learning based remote sensing …
WEBSep 1, 2022 · Single Remote Sensing Image Super Resolution (SRSISR) provides effective solutions to increase the spatial and/or spectral resolution of low-resolution …
Land-Cover Classification with High-Resolution Remote Sensing …
WEBJul 16, 2018 · In recent years, large amount of high spatial-resolution remote sensing (HRRS) images are available for land-cover mapping. However, due to the complex …
Multiscale Global Context Network for Semantic Segmentation of …
WEBSemantic segmentation of high-resolution remote sensing images (HRSIs) is a challenging task because objects in HRSIs usually have great scale variance and appe.
Lightweight Target Detection in High Resolution Remote Sensing …
WEBMar 10, 2023 · Based on YOLOv3 network, this paper uses lightweight networks to identify aircraft, oiltank, overpasses and other targets in high resolution remote sensing …
High-resolution remote sensing images semantic segmentation …
WEBMay 1, 2023 · Semantic segmentation for high-resolution (HR) remote sensing (RS) images under the condition of a small number of training samples with imprecise labels …
Research on forest land classification method of remote sensing …
WEBMay 22, 2024 · Multi-scale features of different levels of U-Net are used to extract forest land from high-resolution remote sensing images and a boundary attention module is …
Semantic Segmentation of Very-High-Resolution Remote …
WEBJan 23, 2022 · High-resolution remote sensing image analysis plays an important role in geosciences, including disaster control, environmental monitoring, utilization and …
A Multiple Prediction Mechanisms Ensemble for Complex …
WEBMultiple classifier combination is used to hyperspectral remote sensing image classification in this paper, and some classifier combination algorithms are …
High-Resolution Remote Sensing Image Semantic Segmentation …
WEBOct 17, 2022 · It combines the benefits of the self-attention mechanism with CNN to improve the segmentation quality of various remote sensing images. The MSCSANet extracts …
Single-Temporal Supervised Learning for Universal Remote …
WEB5 days ago · Bitemporal supervised learning paradigm always dominates remote sensing change detection using numerous labeled bitemporal image pairs, especially for high …
A method for fast detection of wind farms from remote sensing …
WEBJan 1, 2024 · DOI: 10.1515/geo-2022-0645 Corpus ID: 270490473; A method for fast detection of wind farms from remote sensing images using deep learning and …
Intelligent Detection of Marine Offshore Aquaculture with High ...
WEBJun 18, 2024 · The results indicated that despite improving the image clarity and resolution, the SR methods negatively affected the performance of the YOLO models …
Remote Sensing | Free Full-Text | Self-Calibration Strip Bundle
WEBJun 17, 2024 · The attitude accuracy of high-resolution satellite images is the main factor affecting their geometric positioning accuracy. Bundle block adjustment is the main …
Scene Classification of High Resolution Remote Sensing Images …
WEBIn this paper, we focus on tackling the problem of HRSS scene classification using a small pool of unlabeled images and only a few labeled images per category, namely, few-shot …
A method for fast detection of wind farms from remote sensing …
WEBThe wind power industry is increasing worldwide every year. Thus, obtaining timely and detailed information on wind farms' number and spatial distribution is critical for …
Semantic Descriptions of High-Resolution Remote Sensing …
WEBSemantic Descriptions of High-Resolution Remote Sensing Images Abstract: Image captioning has attracted more and more attention in remote sensing filed since it …
A Novel Object-Oriented Rotated Intensity Matching Method for …
WEB1 day ago · Iceberg information in polar regions is crucial for various applications. Synthetic Aperture Radar (SAR) satellites provide high-resolution remote sensing images …
Remote Sensing | Free Full-Text | EWMACD Algorithm in Early …
WEB1 day ago · Currently, deep learning-based super-resolution reconstruction is one of the most popular image fusion methods, enabling images to be collaborative at high spatial …
An Object Fine-Grained Change Detection Method Based on …
WEBNov 30, 2023 · Change detection is a prominent research direction in the field of remote sensing image processing. However, most current change detection methods focus …
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