The importance of snow cover extent (SCE) has been proven to strongly link with various
natural phenomenon and human activities; consequently, monitoring snow cover is one the …

Due to the unique feature of the three-dimensional convolution neural network, it is used in
image classification. There are some problems such as noise, lack of labeled samples, the …

Forests are a major component of the global carbon cycle, and accurate estimation of forest
carbon stocks and fluxes is important in the context of anthropogenic global change …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

Hyperspectral sensors record the reflectance from the Earth's surface over the full range of
solar wavelengths with high spectral resolution. The resulting high-dimensional data contain …

Tree species map** in forest areas is an important topic in forest inventory. In recent
years, several studies have been carried out using different types of hyperspectral sensors …

Currently, accurate information on crop area coverage is vital for food security and industry,
and there is strong demand for timely crop map**. In this study, we used MODIS time …

In this paper, we propose an analysis on the joint effect of hyperspectral and light detection
and ranging (LIDAR) data for the classification of complex forest areas. In greater detail, we …

In this paper, we propose a new optimization-based framework to reduce the dimensionality
of hyperspectral images. One of the most problems in hyperspectral image classification is …

Accurately map** the spatial distribution of tree species in tropical environments provides
valuable insights for ecologists and forest managers. This process may play an important …