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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
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 …
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WEB4 days ago · This methodology first creates a comprehensive dataset of high-resolution remote sensing images, then progresses through the Xception baseline network for …
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 …
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.
- 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
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 …
WEBSemantic segmentation of high-resolution remote sensing images (HRSIs) is a challenging task because objects in HRSIs usually have great scale variance and appe.
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 24, 2023 · This study aims to develop a deep learning model to improve the accuracy of identifying tiny targets on high resolution remote sensing (HRS) images. We …
Spatial Resolution In Remote Sensing: Which One To …
WEBDec 22, 2022 · Based on the distance to the object and the equipment’s capabilities, remote sensing can be performed at low, medium, and high spatial resolutions. For example, drones flying close to the ground can …
Remote Sensing | Free Full-Text | Global-Local Collaborative …
WEB2 days ago · However, the analysis of dual-temporal change detection (CD) remains a challenge in high-resolution optical remote sensing images due to the complexities in …
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WEBJun 20, 2024 · Change detection with multi-temporal high-resolution remote sensing imagery is a fundamental Earth vision task, which aims to provide prompt and accurate …
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 …
A deeply supervised image fusion network for change detection in …
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, …
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) …
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 …
SOENet: a multi-resolution network for sheep extraction from high ...
WEB2 days ago · It is a typical grassland area with flat terrain and numerous lakes. High spatial resolution (0.5 m) remote sensing images taken by the Beijing-3 satellite were …
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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 …
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 …
Full article: Improve unsupervised Learning-based landslides …
WEBJun 22, 2024 · Lv et al. (Citation 2018) based on change detection and multi-scale segmentation methods, realized high-resolution remote sensing image drawing …
High-Resolution Remote Sensing Bitemporal Image Change …
WEBWith the development of remote sensing technology, high-resolution (HR) remote sensing optical images have gradually become the main source of change detection.
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WEBJan 23, 2022 · High-resolution remote sensing image analysis plays an important role in geosciences, including disaster control, environmental monitoring, utilization and …
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 …
Vectorized building extraction from high-resolution remote …
WEBVectorized building extraction from high-resolution remote sensing images using spatial cognitive graph convolution model Du, Zhuotong; ... ISPRS Journal of Photogrammetry …
High Resolution Remote Sensing Sensors - Geospatial World
WEBDec 7, 2010 · HIGH RESOLUTION OPTICAL REMOTE SENSING. Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images 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 …
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 …
Land | Free Full-Text | Feature-Differencing-Based Self ... - MDPI
WEB3 days ago · Land-use and land-cover (LULC) change detection (CD) is a pivotal research area in remote sensing applications, posing a significant challenge due to variations in …
AUXG: Deep Feature Extraction and Classification of Remote …
WEBThe proposed approach was evaluated on a dataset of high-resolution remote sensing images from the NWPU-RESISC45 and RSI-CB256 datasets. The results show that the …
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 …
Remote sensing image registration method based on …
WEBImage registration is a crucial preprocessing step in remote sensing applications, integrating information from multiple images to achieve synergistic advantages. …
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 | Free Full-Text | Feature-Differencing-Based Self ... - MDPI
WEB3 days ago · AMA Style. Feng W, Guan F, Sun C, Xu W. Feature-Differencing-Based Self-Supervised Pre-Training for Land-Use/Land-Cover Change Detection in High …
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