Works by Tenneson, Karis
Results: 10
Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon.
- Published in:
- PLoS ONE, 2024, v. 19, n. 2, p. 1, doi. 10.1371/journal.pone.0289437
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- Article
Slowly getting there: a review of country experience on estimating emissions and removals from forest degradation.
- Published in:
- Carbon Balance & Management, 2024, v. 19, n. 1, p. 1, doi. 10.1186/s13021-024-00281-1
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- Publication type:
- Article
A Near Real-Time Mapping of Tropical Forest Disturbance Using SAR and Semantic Segmentation in Google Earth Engine.
- Published in:
- Remote Sensing, 2023, v. 15, n. 21, p. 5223, doi. 10.3390/rs15215223
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- Article
Uncovering Dynamics of Global Mangrove Gains and Losses.
- Published in:
- Remote Sensing, 2023, v. 15, n. 15, p. 3872, doi. 10.3390/rs15153872
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- Publication type:
- Article
Lessons Learned While Implementing a Time-Series Approach to Forest Canopy Disturbance Detection in Nepal.
- Published in:
- Remote Sensing, 2021, v. 13, n. 14, p. 2666, doi. 10.3390/rs13142666
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- Article
A Comparison of Three Temporal Smoothing Algorithms to Improve Land Cover Classification: A Case Study from NEPAL.
- Published in:
- Remote Sensing, 2020, v. 12, n. 18, p. 2888, doi. 10.3390/rs12182888
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- Article
Predictive Analytics for Identifying Land Cover Change Hotspots in the Mekong Region.
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- Remote Sensing, 2020, v. 12, n. 9, p. 1472, doi. 10.3390/rs12091472
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- Publication type:
- Article
Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu.
- Published in:
- Remote Sensing, 2019, v. 11, n. 19, p. 2296, doi. 10.3390/rs11192296
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- Publication type:
- Article
Mapping Plantations in Myanmar by Fusing Landsat-8, Sentinel-2 and Sentinel-1 Data along with Systematic Error Quantification.
- Published in:
- Remote Sensing, 2019, v. 11, n. 7, p. 831, doi. 10.3390/rs11070831
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- Publication type:
- Article
Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA.
- Published in:
- Remote Sensing, 2018, v. 10, n. 3, p. 442, doi. 10.3390/rs10030442
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- Publication type:
- Article