Samuel Hislop

Orcid: 0000-0002-0176-0410

According to our database1, Samuel Hislop authored at least 12 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Identifying phase-specific environmental drivers of drought-induced vegetation dynamics via spectral Proxies.
Environ. Model. Softw., 2026

2024
Mapping Windthrow Severity as Change in Canopy Cover in a Temperate Eucalypt Forest.
Remote. Sens., 2024

2023
Using Landsat time series and bi-temporal GEDI to compare spectral and structural vegetation responses after fire.
Int. J. Appl. Earth Obs. Geoinformation, August, 2023

2022
Intercomparison of Real and Simulated GEDI Observations across Sclerophyll Forests.
Remote. Sens., 2022

2021
A reference data framework for the application of satellite time series to monitor forest disturbance.
Int. J. Appl. Earth Obs. Geoinformation, 2021

2020
Landsat Time-Series for Estimating Forest Aboveground Biomass and Its Dynamics across Space and Time: A Review.
Remote. Sens., 2020

Monitoring aboveground forest biomass dynamics over three decades using Landsat time-series and single-date inventory data.
Int. J. Appl. Earth Obs. Geoinformation, 2020

A satellite data driven approach to monitoring and reporting fire disturbance and recovery across boreal and temperate forests.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Estimate Forest Biomass Dynamics Using Multi-Temporal Lidar And Single-Date Inventory Data.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
A Comparison of Imputation Approaches for Estimating Forest Biomass Using Landsat Time-Series and Inventory Data.
Remote. Sens., 2018

Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery.
Remote. Sens., 2018

A New Semi-Automatic Seamless Cloud-Free Landsat Mosaicing Approach Tracks Forest Change Over Large Extents.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018


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