|
|
|
Rossana Caroni, Monica Pinardi, Gary Free, Daniela Stroppiana, Lorenzo Parigi, Giulio Tellina, Mariano Bresciani, Clément Albergel and Claudia Giardino
A study was carried out to investigate the effects of wildfires on lake water quality using a source dataset of 2024 lakes worldwide, covering different lake types and ecological settings. Satellite-derived datasets (Lakes_cci and Fire_cci) were used and...
ver más
|
|
|
|
|
|
Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
ver más
|
|
|
|
|
|
Qiyan Li, Zhi Weng, Zhiqiang Zheng and Lixin Wang
The decrease in lake area has garnered significant attention within the global ecological community, prompting extensive research in remote sensing and computer vision to accurately segment lake areas from satellite images. However, existing image segmen...
ver más
|
|
|
|
|
|
Jingxiong Lei, Xuzhi Liu, Haolang Yang, Zeyu Zeng and Jun Feng
High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate back...
ver más
|
|
|
|
|
|
Jiaming Bian, Ye Liu and Jun Chen
In recent times, remote sensing image super-resolution reconstruction technology based on deep learning has experienced rapid development. However, most algorithms in this domain concentrate solely on enhancing the super-resolution network?s performance ...
ver más
|
|
|