Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

Mapping the distribution, pattern, and composition of urban land use categories plays a
valuable role in understanding urban environmental dynamics and facilitating sustainable …

With the rapid development of deep learning technology and improvement in computing
capability, deep learning has been widely used in the field of hyperspectral image (HSI) …

In this paper, we propose a new method for hyperspectral images (HSI) classification,
aiming to take advantage of both manifold learning‐based feature extraction and neural …

Hyperspectral and multispectral information processing systems and technologies have
demonstrated its usefulness for the improvement of agricultural productivity and practices by …

With recent advance in Earth Observation techniques, the availability of multi-sensor data
acquired in the same geographical area has been increasing greatly, which makes it …

In an increasingly open electricity market environment, short-term load forecasting (STLF)
can ensure the power grid to operate safely and stably, reduce resource waste, power …

Hyperspectral image (HSI) classification plays a crucial role in remote sensing (RS)
applications, enabling the precise identification of materials and land cover based on …

Dust storms have many negative consequences, and affect all kinds of ecosystems, as well
as climate and weather conditions. Therefore, classification of dust storm sources into …

Hyperspectral images (HSI) are obtained from hyperspectral imaging sensors to capture the
object's information in hundreds of spectral bands. However, how to make full advantage of …