Over the past ten years, plant phenoty** technologies that utilize sensing and data mining
approaches to estimate crop traits in a high-throughput and objective manner, have been …

When characterizing the processes that shape ecosystems, ecologists increasingly use the
unique perspective offered by repeat observations of remotely sensed imagery. However …

Formal planning and development of what became the first Landsat satellite commenced
over 50 years ago in 1967. Now, having collected earth observation data for well over four …

Ever increasing data volumes of satellite constellations call for multi-sensor analysis ready
data (ARD) that relieve users from the burden of all costly preprocessing steps. This paper …

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover
using all available Landsat data is developed. It is capable of detecting many kinds of land …

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and
Recovery), a new approach to extract spectral trajectories of land surface change from …

Linear spectral unmixing is the practice of decomposing the mixed pixel into a linear
combination of the constituent endmembers and the estimated abundances. This paper …

Since the publishing of the first edition of Classification Methods for Remotely Sensed Data
in 2001, the field of pattern recognition has expanded in many new directions that make use …

A new change detection algorithm for continuous monitoring of forest disturbance at high
temporal frequency is developed. Using all available Landsat 7 images in two years, time …

Remote sensing allows for cost-and time-efficient monitoring of landscapes vital to the
conservation of natural resources, ecosystems, and biodiversity. This review synthesizes …