Remote sensing is widely used to detect forest disturbances (eg, wildfires, harvest, or
outbreaks of pathogens or insects) over spatiotemporal scales that are infeasible to capture …

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 …

In November 2016, after 52 years of armed conflict, the Colombian government and the
primary rebel group, the FARC (Fuerzas Armadas Revolucionarias de Colombia) reached a …

Tackling deforestation remains a significant challenge in tropical countries and even more
so in those affected by armed conflicts. This is partly because of the limited local …

Abstract With 1.76 million inhabitants, Mérida city has recently become the most populated
city in southeast Mexico, being one of the most attractive cities for investment in real-estate …

BFAST Lite is a newly proposed unsupervised time series change detection algorithm that is
derived from the original BFAST (Breaks for Additive Season and Trend) algorithm, focusing …

Vegetation indices (VIs) were used to detect when and where vegetation changes occurred.
However, different VIs have different or even diametrically opposite results, which obstructed …

Access to temporally dense time series such as data from the Landsat and Sentinel-2
missions has lead to an increase in methods which aim to monitor land cover change on a …

Landsat time series images are used for the detection of forest disturbance and the
classification of causal agents. Various studies have classified disturbance agents with …

Time series analysis has gained popularity in forest disturbance monitoring thanks to the
availability of satellite and airborne remote sensing images and the development of different …