Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images
is a challenge given the diversity of sensors available and the heterogeneity of forests …

Accurate land cover mapping is important for urban planning and management. Remote
sensing data have been widely applied for urban land cover mapping. However, obtaining …

Atmospheric correction is one of the key parts of remote sensing preprocessing because it
can influence and change the final classification result. This research examines the impact …

This paper assesses hybrid spatial models with the use of auxiliary variables based on
machine learning algorithms for predicting soil Organic Matter (OM) content in Kastoria area …

Coastal mangrove forests provide important ecosystem goods and services, including
carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are …

Critical micelle concentration (CMC) is one of the main physico-chemical properties of
surface-active agents, also known as surfactants, with diverse theoretical and industrial …

It is of great significance to timely, accurately, and effectively monitor land use/cover in city
regions for the reasonable development and utilization of urban land resources. The …

Cloud detection is a necessary phase in satellite images processing to retrieve the
atmospheric and lithospheric parameters. Currently, some cloud detection methods based …

The increased open-access availability of radar and optical satellite imagery has
engendered numerous land use and land cover (LULC) analyses combining these data …

The database of 254 rockburst events was examined for rockburst damage classification
using stochastic gradient boosting (SGB) methods. Five potentially relevant indicators …