Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …

Wildland fires are one of the most dangerous natural risks, causing significant economic
damage and loss of lives worldwide. Every year, millions of hectares are lost, and experts …

Cloud cover is a common and inevitable phenomenon that often hinders the usability of
optical remote sensing (RS) image data and further interferes with continuous cartography …

In this study, building extraction in aerial images was performed using csAG-HRNet by
applying HRNet-v2 in combination with channel and spatial attention gates. HRNet-v2 …

Cloud detection is an important and difficult task in the pre-processing of satellite remote
sensing data. The results of traditional cloud detection methods are often unsatisfactory in …

Geographic information such as the altitude, latitude, and longitude are common but
fundamental meta-records in remote sensing image products. In this paper, it is shown that …

Cloud detection (CD) with deep learning (DL) algorithms has been greatly developed in the
applications involving the predictions of extreme weather and climate. In this review, the …

The presence of clouds in satellite imagery may pose hindrances to the accurate and
reliable analysis of the objects present on the land. Therefore, automatic cloud detection is a …

Cloud and cloud shadow segmentation are fundamental processes in optical remote
sensing image analysis. Current methods for cloud/shadow identification in geospatial …

Crack detection on roads' surfaces is an important issue in pavement management, as it
provides an indication of the quality of the road and its deterioration over time. Pavement …