Multispectral remote sensing images are the primary source in the land use and land cover
(LULC) monitoring. This is achieved by LULC classification and LULC change detection …

Urban vegetation map** is critical in many applications, ie, preserving biodiversity,
maintaining ecological balance, and minimizing the urban heat island effect. It is still …

Segmentation and classification are two imperative, yet challenging tasks in image analysis
for remote-sensing applications. In the former, an image is divided into spatially continuous …

Arid and semi-arid regions are particularly vulnerable to global environmental change
because of their fragile climatic conditions. The rapid development of land use is expected to …

The main goal of this research was to evaluate the potential of the HYDRUS-1D numerical
model for estimating the soil moisture (θ) at different depths, actual crop evapotranspiration …

Image-based handwritten signature verification is important in most of the financial
transactions when a hard copy of signature is needed. Considering the lack of dynamic …

The semiarid region in the state of Sergipe, Brazil, approximately 11,000 km 2, has
experienced high deforestation rates in the last decades, which ultimately contribute to …

Probabilistic neural networks (PNNs) are artificial neural network algorithms widely used in
pattern recognition and classification problems. In the traditional PNN algorithm, the …

Landsat time series commonly contain missing observations, ie, gaps, due to the orbit and
sensing geometry, data acquisition strategy, and cloud contamination. A spectral-angle …

The accurate and timely access to the spatial distribution information of crops is of great
importance for agricultural production management. Although widely used, supervised …