Originally, the use of hyperspectral images was for military applications, but their use has
been extended to precision agriculture. In particular, they are used for activities related to …

Developments in space-based hyperspectral sensors, advanced remote sensing, and
machine learning can help crop yield measurement, modelling, prediction, and crop …

The ever-increasing global population presents a looming threat to food production. To meet
growing food demands while minimizing negative impacts on water and soil, agricultural …

Abstract Knowledge of the extent and distribution of irrigated and rainfed croplands is critical
in providing the necessary baseline data for enhancing agricultural efficiency and making …

Long-term and large scale spatiotemporal patterns of planted forests are essential for
evaluating local plantation effectiveness and to promote sustainable afforestation. Satellite …

The recent availability of satellite hyperspectral imaging combined with the developments in
the classification techniques have paved the way towards improving our ability to obtain …

Identifying, characterising and map**, unique vegetable crops grown on small mixed
lands in the eastern Himalayan mountain ecosystem (EHME) using traditional methods is a …

Using new remote sensing technology to study agricultural crops will support advances in
food and water security. The recently launched, new generation spaceborne hyperspectral …

An integrated approach that utilises hyperspectral and chlorophyll a fluorescence sensors to
predict biochemical and biophysical parameters represents a new generation of remote …

Thoroughly investigating the characteristics of new generation hyperspectral and high
spatial resolution spaceborne sensors will advance the study of agricultural crops …