Recent wildfire outbreaks around the world have prompted concern that climate change is
increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating …

Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Soil moisture observations are of broad scientific interest and practical value for a wide
range of applications. The scientific community has made significant progress in estimating …

Climate change exacerbates the occurence of extreme droughts and heatwaves, increasing
the frequency and intensity of large wildfires across the globe. Forecasting wildfire danger …

This paper presents the generation of a global burned area map** algorithm using MODIS
hotspots and near-infrared reflectance within ESA's Fire_cci project. The algorithm is based …

Abstract Climate Data Records of soil moisture are fundamental for improving our
understanding of long-term dynamics in the coupled water, energy, and carbon cycles over …

This paper presents a new global burned area (BA) product, generated from the Moderate
Resolution Imaging Spectroradiometer (MODIS) red (R) and near-infrared (NIR) reflectances …

Climate change increases fire-favorable weather in forests, but fire trends are also affected
by multiple other controlling factors that are difficult to untangle. We use machine learning to …

Since the late 1970s, space-borne microwave radiometers have been providing
measurements of radiation emitted by the Earth's surface. From these measurements it is …

Fire is an integral component of ecosystems globally and a tool that humans have
harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of …