- Related Research Areas
- Carbon Cycle & Ecosystems, Climate Variability & Change
The Land Satellite Data Systems (LSDS) Science Research and Development (LSRD) project at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate high-level data products from Landsat 5-7 inputs to support the USGS Terrestrial Monitoring activities with Essential Climate Variables (ECV) and Climate Data Records (CDR). The LSRD is currently developing on-demand surface reflectance (SR), land surface temperature (LST), and leaf area index (LAI) products from Landsat TM and ETM+ data. LSRD's EROS Science Processing Architecture (ESPA) prototype utilizes Apache Hadoop to move algorithms across a multi-server cluster to process input data files. ESPA technology elegantly facilitates the shortest path to massive data production by normalizing any software languages and enabling multiple servers to join or disconnect from the cluster without impacting processing. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS; Jeff Masek, Feng Gao, and Eric Vermote) has been integrated into ESPA for production of Landsat SR, an algorithm developed by John Schott and Simon Hook will be used to generate Landsat LST/Emissivity products, and code from Rama Nemani, Petr Votava, and Sangram Ganguly will serve to create an LAI ECV.
A Dataset, USGS ECV/CDR Development - 2 years, 10 months ago
Landsat Surface Reflectance products are offered provisionally, with the intent of presenting an opportunity for user evaluation and input. LSRD welcomes user opinions on data ...
Log in to start a discussion.
- Any registered users can join
- Anybody can view this project
- Any registered users can leave comments
- Anybody can view comments
- Joined 2 years, 7 months ago
Visit our help center