Using drones makes detecting land mines safer. Using AI to fuse data from multiple types of sensors on the drones makes it more efficient.

A new ultrathin photodetector from Duke University can sense light across the entire electromagnetic spectrum and generate a ...

For years, the Prairie Pothole Region has bothered me in a very specific way. On a map, it looks like a normal landscape: ...

Abstract: Deep neural networks have been widely used in remote sensing image segmentation. Nowadays, artificial intelligence methods are increasingly applied to remote sensing feature classification.

Where are habitats available for threatened species? Are they improving or deteriorating? What landscapes could potentially be used for rewilding animals? A new modeling framework has combined years ...

Abstract: With the rapid advancement of remote sensing technology, the acquisition and processing of remote sensing video data, including high-resolution satellite, hyperspectral, and synthetic ...

Across much of America, workers fear their options for remote work are slipping away. But remote work is alive and well, at least for now. Five years into the pandemic workplace revolution, roughly 38 ...

This repository contains the code implementation for the paper RSRefSeg: Referring Remote Sensing Image Segmentation with Foundation Models, developed based on the MMSegmentation project. The current ...

The robots mimic the movements and body temperature of real rabbits, a favored prey of pythons. The project is funded by the South Florida Water Management District and builds upon previous research ...

This package provides a Python implementation of the Leaf Area Index (LAI) algorithm described by Carlson & Ripley (1997) and related literature. It converts NDVI (Normalized Difference Vegetation ...