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Mapping forest structure in Mississippi using LiDAR remote sensing

This study aimed at evaluating the agreement of spaceborne Light Detection and Ranging (lidar) ICESat-2 canopy height with Airborne Laser Scanning (ALS) derived canopy height to inform about the performance of ICESat-2 canopy height metrics and understand its uncertainties and utilities. The agreement was assessed for different forest types, physiographic regions, a range of percent canopy cover, and diverse disturbance histories. Results of this study suggest that best agreements are found using strong beam data collected at night for canopy height retrieval using ICESat-2. The ICESat-2 showed great potential for estimating canopy heights, particularly in evergreen forests with high canopy cover. Statistical models were developed using fixed-effects and mixed-effects modeling approaches to predict ALS canopy height metrics using ICESat-2 parameters and other attributes. Overall, ICESat-2 showed good agreement with ALS canopy height and showed its predictive ability to characterize canopy height. The outcome of this study will help the scientific community understand the capabilities and limitations of ICESat-2 canopy heights; the study also provides a new approach to obtain wall-to-wall ALS standard canopy height maps at landscape level.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6688
Date09 December 2022
CreatorsRai, Nitant
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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