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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
Recent Advances in High Resolution Remote Sensing Image
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 …
High spatial resolution remote sensing image segmentation
- This article uses high spatial resolution remote sensing images as experimental data. The name of the data set is GaoFen-2 (GF-2), which is from . The GF-2 multispectral image has four bands: blue (0.45–0.52 μm), green (0.52–0.59 μm), red (0.63–0.69 μm), and near-infrared (0.77–0.89 μm). The spatial resolution of GF-2 multispectral image is 3.24 m....
- Author: Xiaoxiong Zheng, Tao Chen
- Estimated Reading Time: 10 mins
- Publish Year: 2021
- Published: Jan 3, 2021
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Water body extraction from high spatial resolution remote sensing ...
WEBJul 12, 2024 — To overcome these difficulties, this paper presents a novel network model named EU-Net, specifically designed to extract water bodies from high-resolution …
An improved semantic segmentation algorithm for high-resolution …
WEBApr 27, 2024 — Semantic segmentation of remote sensing images is the fundamental and critical component of understanding and analyzing remote sensing images, which …
Spatial Resolution In Remote Sensing: Which Is …
WEBDec 22, 2022 — Based on the distance to the object and the equipment’s capabilities, remote sensing can be performed at low, medium, and …
- Occupation: Project
- Gender: Female
- Works For: EOS Data Analytics
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 …
Deep semantic understanding of high resolution remote sensing …
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 …
High Resolution Remote Sensing Image Classification Based on …
WEBTo improve the automatic classification accuracy of remote sensing images, this study raises a high-resolution remote sensing image classification model that combines …
Remote Sensing | Special Issue : Very High Resolution (VHR
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, …
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 …
Classifying High Resolution Remote Sensing Images by Fine …
WEBThe proposed RS-VGGNet is validated by real HR remote sensing images, which were acquired from the National Agriculture Imagery Program(NAIP) dataset. Experimental …
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 …
Land-cover classification with high-resolution remote sensing …
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 …
WEBRemote sensing is obtaining information about an object from a distance. Photography is a very common form of remote sensing. There are different ways to collect data, and …
Disparity Estimation of High-Resolution Remote Sensing Images …
WEBDec 13, 2021 — Disparity estimation from a pair of high-resolution remote sensing stereo images is a fundamental yet challenging task. It provides indepth information that is …
Landsat Image Gallery
WEB1 day ago — This gallery includes all Landsat images published on the Earth Observatory, Visible Earth, and Landsat Science web sites from all seven Landsat satellites (Landsats …
High-Resolution Remote Sensing Image Scene Understanding: A …
WEBJul 28, 2019 — High-resolution remote sensing (HRS) image analysis is a fundamental but challenging problem. To bridge the semantic gap, scene understanding has been …
Self-supervised learning for remote sensing scene ... - Nature
WEBJan 9, 2023 — To address the problem of limited computation resources available to us, our proposed method uses a novel DL architecture that can be trained using both high …
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) …
A Framework for Generating High-Resolution Seamless Remote …
WEBHigh-resolution seamless remote sensing (HRSRS) images are essential foundational data for natural resource monitoring and land-use assessment.
Land-cover classification with high-resolution remote sensing …
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 …
Detecting unknown dams from high-resolution remote sensing …
WEBDec 15, 2021 — Automatic detecting unknown dams from high-resolution remote sensing images in broad areas. Multi object detection models improves the recall rate of dam …
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 …
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