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Finer Resolution Estimation and Mapping of Mangrove Biomass Using UAV LiDAR and WorldView-2 Data

https://doi.org/10.3390/f10100871
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Remote Sensing of Mangrove Forests: Current Techniques and Existing Databases
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Tree growth, dynamics, and productivity in a mature mangrove forest in Malaysia
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Allometric relationships for estimating above-ground biomass in six mangrove species
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Mangrove biomass estimation in Southwest Thailand using machine learning
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Allometry, biomass, and productivity of mangrove forests: A review
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Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach
inferredcites →https://doi.org/10.1016/j.ecss.2018.02.027openalex-snapshot
Terrestrial laser scanning to quantify above-ground biomass of structurally complex coastal wetland vegetation
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Allometry and partitioning of the mangrove, Rhizophora apiculata
inferredcites →https://doi.org/10.1016/j.foreco.2006.09.026openalex-snapshot
General considerations about the use of allometric equations for biomass estimation on the example of Norway spruce in central Europe
inferredcites →https://doi.org/10.1016/j.foreco.2018.06.004openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.jag.2015.01.011openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.proenv.2015.01.007openalex-snapshot
Carbon Biomass Algorithms Development for Mangrove Vegetation in Kemujan, Parang Island Karimunjawa National Park and Demak Coastal Area – Indonesia
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A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery
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inferredcites →https://doi.org/10.1016/j.rse.2014.04.029openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.rse.2016.04.026openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.rse.2018.12.034openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0034-4257(02)00050-0openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0378-1127(00)00460-6openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0921-8009(98)00020-2openalex-snapshot
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inferredcites →https://doi.org/10.1017/s0266467400001826openalex-snapshot
Root biomass of a mangrove forest in southern Thailand. 1. Estimation by the trench method and the zonal structure of root biomass
inferredcites →https://doi.org/10.1017/s0266467400007859openalex-snapshot
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inferredcites →https://doi.org/10.1017/s0266467405002476openalex-snapshot
Common allometric equations for estimating the tree weight of mangroves
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1038/ngeo1123openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41558-018-0090-4openalex-snapshot
Global carbon stocks and potential emissions due to mangrove deforestation from 2000 to 2012
inferredcites →https://doi.org/10.1080/01431160701736471openalex-snapshot
Species identification of individual trees by combining high resolution LiDAR data with multi‐spectral images
inferredcites →https://doi.org/10.1080/01431161.2016.1214302openalex-snapshot
How to assess the accuracy of the individual tree-based forest inventory derived from remotely sensed data: a review
inferredcites →https://doi.org/10.1109/jstars.2017.2748341openalex-snapshot
Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass
inferredcites →https://doi.org/10.1111/2041-210x.12575openalex-snapshot
Tree‐centric mapping of forest carbon density from airborne laser scanning and hyperspectral data
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inferredcites →https://doi.org/10.1186/s13021-019-0117-9openalex-snapshot
Forest degradation and biomass loss along the Chocó region of Colombia
inferredcites →https://doi.org/10.14358/pers.70.3.351openalex-snapshot
Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery
inferredcites →https://doi.org/10.15786/wyoscholar/9645openalex-snapshot
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inferredcites →https://doi.org/10.3390/rs10010039openalex-snapshot
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inferredcites →https://doi.org/10.3390/rs10091468openalex-snapshot
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inferredcites →https://doi.org/10.3390/rs11121459openalex-snapshot
Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data
inferredcites →https://doi.org/10.3759/tropics.1.243openalex-snapshot
An Estimation of Above Ground Tree Biomass of a Mangrove Forest in East Sumatra, Indonesia.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Additional file 1 of Relationships between above- and below-ground carbon stocks in mangrove forests facilitate better estimation of total mangrove blue carbon
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Hybrid Monitoring of Mangroves in the Kamiali Wildlife Management Area, Papua New Guinea
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