Todd A. Schroeder

Global and Planetary Change · 2006–2017

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 16 citations into it; #2,214 of 10,225 by trust here, #4,309 by citations
• Ecology — 15 citations into it; #2,244 of 10,717 by trust here, #5,109 by citations
• Media Technology — 8 citations into it; #1,337 of 3,621 by trust here, #2,114 by citations
• Artificial Intelligence — 5 citations into it

Whom Todd A. Schroeder trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Morton John Canty
2. Warren B. Cohen
3. Allan Aasbjerg Nielsen
4. Curtis E. Woodcock
5. Thomas K. Maiersperger

Who trusts Todd A. Schroeder overall

1. Robert E. Kennedy
2. Zhe Zhu
3. Warren B. Cohen
4. Zhiqiang Yang
5. Yichun Xie
6. M. Wulder
7. Clement Atzberger
8. Morton John Canty
9. Zongyao Sha

Papers from Todd A. Schroeder's perspective

Ordered by how strongly the researchers Todd A. Schroeder trusts endorse each paper. Same corpus, a different order for every researcher.

1. Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects?
2. Automatic radiometric normalization of multitemporal satellite imagery
3. Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges (IEEE Transactions on Geoscience and Remote Sensing)
4. Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon
5. Review ArticleDigital change detection methods in ecosystem monitoring: a review
6. Opening the archive: How free data has enabled the science and monitoring promise of Landsat
7. Disturbance and landscape dynamics in a changing world. (Ecology)
8. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms
9. Continuous change detection and classification of land cover using all available Landsat data
10. Object-based cloud and cloud shadow detection in Landsat imagery

Their papers

• How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms (2017) — 193 citations
• Trajectory-based change detection for automated characterization of forest disturbance dynamics (2007) — 467 citations
• Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon (2006) — 409 citations