A deep neural network (DNN), evolved from a traditional artificial neural network, has been
seamlessly adapted for the spatial data domain over the years. Deep learning (DL) has …

Sal (Shorea robusta) forests, a dominant forest type in Nepal, experience different
disturbance intensities depending on management regimes. This study compares the impact …

In third world countries, industries mainly cause environmental contamination due to lack of
environmental policies or oversight during their implementation. The Sheikhupura industrial …

Multi-source, multi-temporal, and multi-resolution satellite images have been increasing
over a couple of years. The spatiotemporal data fusion technique could be a promising …

Accurate information on tree species is in high demand for forestry management and further
investigations on biodiversity and environmental monitoring. Over regional or large areas …

There are many disagreements and uncertainties among global land use/land cover (LULC)
products, which make it unsuitable to apply these products directly to a specific region. In …

The species and distribution of trees in a forest are critical to the understanding of forest
ecosystem processes and the development of forest management strategies. Subtropical …

This study aims to establish a deep learning-based classification framework to efficiently and
rapidly distinguish between coniferous and broadleaf forests across the Loess Plateau. By …

The periodic determination of land use changes over large areas is crucial for improving our
understanding of land system dynamics. Jiangsu lies at the center of China's Yangtze Delta …

毛竹是我国南方广泛分布的重要竹种, 具有良好的生态效益和经济价值. 毛竹林与其他森林区分
难度大, 现有提取方法多直接采用已有的晴空观测, 未充分考虑分类时相的影响 …