Research Article
A Multiscale Delayed Channel Attention Network-Based Method for Pansharpening
Dajiang Lei,
Lang Xiao,
Yujia Li,
Hefeng Huang,
Xiaoyu Chen,
Tingting Zhou,
Shixing Ou,
Liping Zhang*
Issue:
Volume 12, Issue 1, June 2024
Pages:
1-13
Received:
15 December 2023
Accepted:
28 December 2023
Published:
21 January 2024
DOI:
10.11648/j.ajrs.20241201.11
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Abstract: Nowadays, remote sensing images are widely used in many fields. To obtain high-quality remote sensing images, remote sensing image fusion methods have attracted much attention. Although convolutional neural network-based pansharpening methods have good results, these methods focus on the forward propagation of the network, which cannot effectively seek the mapping relationship between images. Moreover, it is difficult to obtain global information due to the limitations of convolutional operations. In this paper, we propose a pansharpening method based on multiscale delayed channel attention networks. The method iteratively seeks to correlate high-resolution stage features with the original low-resolution multispectral image, providing a mechanism for error feedback to map the error of each stage. Meanwhile, it designs a multiscale feature fusion module to fuse feature information from different fields of view. The design of the delayed channel attention mechanism makes the network acquire the association relationship between low-frequency information and high-frequency information through adaptive learning, giving different weights to high-frequency information, and making it more flexible in dealing with different types of information. Finally, the feature aggregation module is used to generate fused images and adjust the corresponding feature information. The experimental results obtained from the Gaofen-2 and WorldView-2 experimental data show that the method achieves a significant improvement compared to the current fusion algorithms.
Abstract: Nowadays, remote sensing images are widely used in many fields. To obtain high-quality remote sensing images, remote sensing image fusion methods have attracted much attention. Although convolutional neural network-based pansharpening methods have good results, these methods focus on the forward propagation of the network, which cannot effectively ...
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Research Article
Characterization of Non-Methane Hydrocarbons Fingerprint Prevalence in Urban Areas of Fujairah - UAE Using eNose Sensor Technology
Reem Yaqoub Yousif Ahmed Abdalla,
Aseela Al Moalla,
Mohamed Ateeg,
Muhammed Sirajul Huda Kalathingal,
Shaher Bano Mirza*,
Fouad Lamghari Ridouane
Issue:
Volume 12, Issue 1, June 2024
Pages:
14-17
Received:
3 January 2024
Accepted:
24 January 2024
Published:
5 February 2024
Abstract: Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules and emission ratios is required, in contrast to pristine locations, where reliance on a single or a few chemical tracers is frequently sufficient. We have characterized the prevalence of NMHCs fingerprints in the urban areas and quantified the correlation of windspeed with the concentration of these pollutants. eNose sensors and Air quality management stations provide the data to identify the emission sources of such pollutants. Based on our analysis, the average NMHC concentration in 2021 has been recorded 0.424 ppm at point 1 AQMS whereas at point 2 AQMS it was 0.256 ppm. Such outcomes could be attributed to the proximity of emissions sources, the direction and speed of the wind, or both. Moreover, traffic can be a major contributor to pollution levels in any urban area. More research based on a larger dataset is required before definitive conclusions can be drawn, and viable solutions can be proposed.
Abstract: Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules...
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