Satellite images provide an accurate, continuous, and synoptic view of seamless global
extent. Within the fields of remote sensing and image processing, land surface change …

Quantities of multi-temporal remote sensing (RS) images create favorable conditions for
exploring the urban change in the long term. However, diverse multi-source features and …

Known as an unpredictable natural disaster, earthquake is one of the most devastating
natural disasters that causes significant life losses and damages, every year. After an …

Imbalanced learning is a common problem in remote sensing imagery-based land-use and
land-cover classifications. Imbalanced learning can lead to a reduction in classification …

Change detection in remote sensing enables identifying alterations in surface characteristics
over time, underpinning diverse applications. However, conventional pixel-based algorithms …

Imbalanced learning is a methodological challenge in remote sensing communities,
especially in complex areas where the spectral similarity exists between land covers …

The increasing need of land for building roads, settlements, and other facilities leads to the
changes of agricultural land to other uses. Uncontrolled changes in rice fields may …

Multispectral sensors have been invaluable for land cover mapping. Nonetheless, cloud
cover is frequent in many parts in the tropics, meaning that relying on single-date …

Remote sensing technologies have been successfully used for deforestation monitoring,
and with the wide availability of satellite products from different platforms, forest monitoring …

Oil palm plantations have been expanding in Indonesia, especially in the islands of
Kalimantan and Papua. In this regard, detailed, frequent monitoring schemes should be …