Free Access to Landsat Imagery
By Curtis E. Woodcock, R. G. Allen, Martha C. Anderson, A. Belward, Robert Bindschadler, Warren B. Cohen, F. Gao, S. Goward, D. Helder, E. Helmer and 8 more. Science, 2008
927 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/ce061d787499cacc5d30c0acaefd8ab417e3c5c6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Zhe Zhu
- Darius Phiri
- Justin Morgenroth
- Curtis E. Woodcock
- M. Wulder
- David P. Roy
- Joanne C. White
- Gregorio Ignacio Gavier-Pizarro
Citations in the corpus
- Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change (2014, methodology): “The policy providing free access to Landsat data has made Landsat data even more popular (Woodcock et al.,2008) andhascompletelyrevolutionizedtheutilizationof Landsat data (Wulder, Masek, Cohen, Loveland, & Woodcock, 2012).”
- Invasion of glossy privet (Ligustrum lucidum) and native forest loss in the Sierras Chicas of Córdoba, Argentina (2010, background): “Landsat satellite images provide an excellent alternative for mapping the spread of non-native invasive plants at broad scales and at low cost, especially given the increasing availability of the global Landsat archives (Woodcock et al. 2008).”
- Analysis Ready Data: Enabling Analysis of the Landsat Archive (2018, background): “The release of the Landsat archive as free and open data via the internet in 2008 removed the monetary cost of accessing Landsat data [1] and led to a dramatic increase in Landsat data utilization [2].”
- Continuous change detection and classification of land cover using all available Landsat data (2014, background): “The opening of the Landsat archive in 2008 (Woodcock et al., 2008) has led to big changes in the way Landsat images are being used.”
- DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation (2022, methodology): “More-over, the Fusion bands are calibrated to the Harmonized Landsat-Sentinel (HLS) 2 spectrum to make them compatible with other publicly available datasets such as Landsat 8 [45] or Sentinel 2 [1,17].”
- Wheat Yield Forecasting for the Tisza River Catchment Using Landsat 8 NDVI and SAVI Time Series and Reported Crop Statistics (2021, background): “The Landsat 8 produces data with higher spatial resolution (30 m) and free availability [29].”