scholarly journals Resolution Enhancement Method of Multispectral Satellite Images for Watershed Monitoring

2007 ◽  
Vol 30 (9) ◽  
pp. 527-533
Author(s):  
Ichiro EMBUTSU
Keyword(s):  
Satellite Images ◽  
Resolution Enhancement ◽  
Multispectral Satellite Images ◽  
Enhancement Method

scholarly journals Forensic Geoarchaeology in the Search for Missing Persons

2021 ◽  
Vol 1 (1) ◽  
pp. 8-15
Author(s):  
Pier Matteo Barone ◽  
Rosa Maria Di Maggio ◽  
Silvia Mesturini
Keyword(s):  
Satellite Images ◽  
Social Phenomenon ◽  
Geographic Profiling ◽  
Missing Persons ◽  
The Social ◽  
Multispectral Satellite Images

Despite widespread concern over missing persons, there has always been little clarity on what the word “missing” means. Although the category of young runaways is, indeed, an important cluster, other popular concepts related to disappearances describe a portion of missing persons. Thus, the following question persists: What exactly does “missing” mean? In this brief communication, we would like to open a discussion about the social phenomenon of missing persons and the consequent deployment of people and techniques to find those persons. In particular, the benefits of some forensic geoarchaeological approaches that are not yet fully standardized will be highlighted, such as geographic profiling and the use of multispectral satellite images, in order to provide materials for future searching protocols.

General Resolution Enhancement Method in Atomic Force Microscopy Using Deep Learning

2018 ◽  
Vol 2 (2) ◽  
pp. 1800137 ◽  
Author(s):  
Yue Liu ◽  
Qiaomei Sun ◽  
Wanheng Lu ◽  
Hongli Wang ◽  
Yao Sun ◽  
...  
Keyword(s):  
Atomic Force Microscopy ◽  
Deep Learning ◽  
Resolution Enhancement ◽  
Force Microscopy ◽  
Atomic Force ◽  
Enhancement Method

scholarly journals A GENERATIVE ADVERSARIAL NETWORK APPROACH FOR SUPER-RESOLUTION OF SENTINEL-2 SATELLITE IMAGES

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 9-14
Author(s):  
F. Pineda ◽  
V. Ayma ◽  
C. Beltran
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Resolution Enhancement ◽  
Super Resolution ◽  
Structural Similarity ◽  
Generative Adversarial Network ◽  
Acceptable Result ◽  
Adversarial Network ◽  
High Resolution Satellite Images ◽  
Sentinel 2

Abstract. High-resolution satellite images have always been in high demand due to the greater detail and precision they offer, as well as the wide scope of the fields in which they could be applied; however, satellites in operation offering very high-resolution (VHR) images has experienced an important increase, but they remain as a smaller proportion against existing lower resolution (HR) satellites. Recent models of convolutional neural networks (CNN) are very suitable for applications with image processing, like resolution enhancement of images; but in order to obtain an acceptable result, it is important, not only to define the kind of CNN architecture but the reference set of images to train the model. Our work proposes an alternative to improve the spatial resolution of HR images obtained by Sentinel-2 satellite by using the VHR images from PeruSat1, a peruvian satellite, which serve as the reference for the super-resolution approach implementation based on a Generative Adversarial Network (GAN) model, as an alternative for obtaining VHR images. The VHR PeruSat-1 image dataset is used for the training process of the network. The results obtained were analyzed considering the Peak Signal to Noise Ratios (PSNR) and the Structural Similarity (SSIM). Finally, some visual outcomes, over a given testing dataset, are presented so the performance of the model could be analyzed as well.

Interactive processing of satellite images for structural and lithological mapping in northeast Africa

1986 ◽  
Vol 123 (4) ◽  
pp. 393-403 ◽  
Author(s):  
S. M. Berhe ◽  
D. A. Rothery
Keyword(s):  
Principal Components ◽  
Satellite Images ◽  
Spatial Filtering ◽  
Digital Processing ◽  
Horn Of Africa ◽  
Lithological Mapping ◽  
Late Precambrian ◽  
Late Proterozoic ◽  
Pan African ◽  
Multispectral Satellite Images

AbstractInteractive digital processing of multispectral satellite images (Landsat MSS) using principal components transformations and spatial filtering has clarified the position of continuous sutures linking apparently isolated Pan African (late Proterozoic) ophiolites. These have been field-checked and an arrangement of Pan African suture zones is proposed. Spatial filtering has also highlighted faults with various trends which can be related to the late Precambrian tectonics of the Horn of Africa region.

scholarly journals Improvement of Clay and Sand Quantification Based on a Novel Approach with a Focus on Multispectral Satellite Images

2018 ◽  
Vol 10 (10) ◽  
pp. 1555 ◽  
Author(s):  
Caio Fongaro ◽  
José Demattê ◽  
Rodnei Rizzo ◽  
José Lucas Safanelli ◽  
Wanderson Mendes ◽  
...  
Keyword(s):  
Model Calibration ◽  
Large Scale ◽  
Satellite Images ◽  
Satellite Image ◽  
Soil Mapping ◽  
Spectral Signatures ◽  
Novel Approach ◽  
Multispectral Satellite Images ◽  
Reduced Costs ◽  
Multispectral Satellite Image

Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aimed to compare multispectral satellite image and relief parameters for the quantification and mapping of clay and sand contents. The Temporal Synthetic Spectral (TESS) reflectance and Synthetic Soil Image (SYSI) approaches were used to identify and characterize texture spectral signatures at the image level. Soil samples were collected (0–20 cm depth, 919 points) from an area of 14,614 km2 in Brazil for reference and model calibration. We compared different prediction approaches: (a) TESS and SYSI; (b) Relief-Derived Covariates (RDC); and (c) SYSI plus RDC. The TESS method produced highly similar behavior to the laboratory convolved data. The sandy textural class showed a greater increase in average spectral reflectance from Band 1 to 7 compared with the clayey class. The prediction using SYSI produced a better result for clay (R2 = 0.83; RMSE = 65.0 g kg−1) and sand (R2 = 0.86; RMSE = 79.9 g kg−1). Multispectral satellite images were more stable for the identification of soil properties than relief parameters.

See the Unseen through Target-Oriented Dip-Steered Seismic Resolution

2021 ◽  
Author(s):  
Muhammad Sajid ◽  
Ahmad Riza Ghazali
Keyword(s):  
Reservoir Characterization ◽  
Resolution Enhancement ◽  
Dominant Frequency ◽  
Seismic Inversion ◽  
Seismic Resolution ◽  
Geological Features ◽  
Spectral Enhancement ◽  
Enhancement Method ◽  
Layer Velocity ◽  
Seismic Volumes

Abstract Seismic resolution plays an important role not only in interpretation and reservoir characterization but also in seismic inversion and seismic attributes analysis. The resolution depends on several factors, including seismic frequency bandwidth, dominant frequency, and layer velocity. This paper presents a spectral resolution enhancement approach that is based on Non-stationary Differential Resolution (NSDR) that honors the local structural dip, better preserves amplitude and improves target-oriented seismic interpretation. The proposed technology is applied to both 2D and 3D seismic volumes and findings are compared with the oil industry common spectral enhancement algorithms. We demonstrate the target-oriented dip steering spectral enhancement method on two 3D field datasets and compare the resulting outcome with those obtained by conventional techniques. It is found that thinly layered subsurface geological features with steeply dipping beds are better defined, with artifacts from the conflicting dips removed.

Sign in / Sign up

Export Citation Format

Share Document