Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2
MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land …

Global surface temperature has been setting new record highs in the recent decades,
imposing increasing environmental challenges for societies and ecosystems worldwide …

Land use and land cover maps provide fundamental information that has been used in
different types of studies, ranging from public health to carbon cycling. However, the existing …

The use of time series analysis with moderate resolution satellite imagery is increasingly
common, particularly since the advent of freely available Landsat data. Dense time series …

As the spatial and temporal resolution of remotely sensed imagery has improved over the
last four decades, algorithms for monitoring and mapping seasonal changes in surface …

The hydrologic sciences and water resources management have long depended on a
combination of in situ measurements and remotely sensed data for research and regulatory …

Satellite image time series (SITS) classification is a major research topic in remote sensing
and is relevant for a wide range of applications. Deep learning approaches have been …

Assessing land-use following deforestation is vital for reducing emissions from deforestation
and forest degradation. In this paper, for the first time, we assess the potential of spatial …

Although remote sensing has enabled rapid monitoring of grassland aboveground biomass
(AGB) at a regional scale, it is still a difficult challenge to construct an accurate estimation …