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https://github.com/JavierLopatin/Peatland-carbon-stock

Codes for: Lopatin, J., et al. (2019). Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks. Remote Sens. Environ. 231, 111217
https://github.com/JavierLopatin/Peatland-carbon-stock

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Codes for: Lopatin, J., et al. (2019). Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks. Remote Sens. Environ. 231, 111217

Host: GitHub
URL: https://github.com/JavierLopatin/Peatland-carbon-stock
Owner: JavierLopatin
Created: 2017-03-01T16:06:03.000Z (almost 8 years ago)
Default Branch: master
Last Pushed: 2019-06-10T18:41:32.000Z (over 5 years ago)
Last Synced: 2024-08-04T03:05:57.527Z (5 months ago)
Language: R
Homepage:
Size: 333 KB
Stars: 3
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

awesome-earthobservation-code - Peatland-carbon-stock - Codes for: Lopatin, J., et al. (2019). Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks. Remote Sens. Environ. 231, 111217 `R` (Resources for `R` / Testing your code)

README

![alt text](https://github.com/JavierLopatin/Peatland-carbon-stock/blob/master/paper_front.png)

### Codes for the paper published in RSE entitled: '*Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks*'. The article can be found at [ScienceDirect](https://www.sciencedirect.com/science/article/abs/pii/S0034425719302305) or in [ResearchGate](https://www.researchgate.net/publication/333618822_Using_aboveground_vegetation_attributes_as_proxies_for_mapping_peatland_belowground_carbon_stocks).

### The Python 3.X codes used for Brightness Normalization of Hyperspectral data and Minimum Noise fraction Transformation can be found [here](https://github.com/JavierLopatin/Python-Remote-Sensing-Scripts/blob/master/BrightnessNormalization.py) and [here](https://github.com/JavierLopatin/Python-Remote-Sensing-Scripts/blob/master/MNF.py)