Abstract Google Earth Engine (GEE) is a cloud-based geospatial processing platform for
large-scale environmental monitoring and analysis. The free-to-use GEE platform provides …

Improved access to remotely sensed imagery and time series algorithms in combination with
increased availability of cloud computing resources and platforms such as Google Earth …

Abstract The United States (US) federal government provides imagery obtained by federally
funded Earth Observation satellites typically at no cost. For many years Landsat was an …

Abstract Changes in forest disturbances can have strong impacts on forests, yet we lack
consistent data on Europe's forest disturbance regimes and their changes over time. Here …

Summary geemap is a Python package for interactive map** with Google Earth Engine
(GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery …

Compared with disturbance maps produced at annual or multi-year time steps, monthly
map** of forest harvesting can provide more temporal details needed for studying the …

Purpose This paper reviews the most recent literature related to the use of remote sensing
(RS) data in wildland fire management. Recent Findings Studies dealing with pre-fire …

Understanding changes to aboveground biomass (AGB) in forests undergoing degradation
is crucial for accurately and completely quantifying carbon emissions from forest loss and for …

Background Few studies have examined post-fire vegetation recovery in temperate forest
ecosystems with Landsat time series analysis. We analyzed time series of Normalized Burn …

Despite its critical importance to carbon storage modeling, forest vertical structure remains
poorly characterized over large areas. Canopy height estimates from current satellite …