Above Ground Biomass Estimation

Main Goal

The overall goal of the project is the automation of above ground biomass estimation using available Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer (MODIS) imagery data using NDVI_time series in Malawi, Africa.

Background

The United Nations insight of Reducing Emissions from Deforestation and forest Degradation Programme (UN-REDD), promotes the use of ABG equations for estimating national carbon stock and carbon stock changes as part of the development of their national forest monitoring systems (NFMS) as required under REDD+. REDD programme supports countries around the globe to develop equations and define methodologies for their application by providing expert guidance and country-level capacity building. The above-ground biomass can be estimated through field measurements, remote sensing and GIS methods (Vashum and Jayakumar, 2012). Forest biomass with field measurements can be estimated either directly with destructive method or indirectly with less destructive methods based on allometry (Cutini, A., F. Chianucci, et al. 2013).
AGB has a direct correlation with climate change which is a global concern and every effort is being made at national and international levels to combat the drastic changes that will imminently disrupt the climate. Remote sensing techniques can support in reducing or identifying the effect of changes to our environment that have a negative impact on the climate. Above ground biomass estimation is challenging and various methods are being researched upon to improve the accuracy of estimating carbon emission. As there are no practical methods to directly measure all forest carbon stocks across a country, both ground-based and remote-sensing measurements of forest attributes can be converted into estimates of national carbon stocks using allometric relationships.
AGB estimation is a challenge in developing countries as they often lack appropriate data to carry out such research. In this dissertation, I would like to highlight how such estimates could be derived from use of freely available data from Landsat and MODIS imagery. Specifically, I would like to highlight how AGB can be obtained given Landsat/MODIS imagery spanning a different time periods in order to show carbon variations over the given time period.

Objectives

Main objective of carrying out the project are;
Investigate on the use of low and medium resolution satellite imagery on estimating AGB (Above Ground Biomass) over a given period of time by comparing available Landsat/MODIS imagery data particularly using NDVI index
Compare estimated AGB results with results obtained using remote sensing techniques (with different satellite sensor and methodologies e.g. LiDAR).

Related References

https://www.researchgate.net/publication/266563000_Improving_forest_aboveground_biomass_estimation_using_seasonal_Landsat_NDVI_time-series
http://www.sciencedirect.com/science/article/pii/S0924271614002202
http://www.indiana.edu/~act/files/publications/2005/05-06_AbovegroundBiomass.pdf
https://dspace.library.colostate.edu/bitstream/handle/10217/167124/Gwenzi_colostate_0053A_13095.pdf?sequence=1
http://www.nrs.fs.fed.us/pubs/jrnl/2008/nrs_2008_zheng_001.pdf
https://www.academia.edu/11618867/Global_Biomass_Information_System_Mapping_Above_Ground_Biomass_Uncertainty_and_Forest_Area_using_Multi-Platform_Earth_Observation_Datasets
http://www.fs.fed.us/rm/pubs_other/rmrs_2010_powell_s001.pdf
http://www.mdpi.com/2071-1050/8/2/159
http://www.sciencedirect.com/science/article/pii/S0168192314002214
http://www.afrjournal.org/index.php/afr/article/view/278
http://remotesensing.spiedigitallibrary.org/article.aspx?articleid=2337526
http://www.helsinki.fi/geography/Janne_Heiskanen/pdf/Muukkonen_Heiskanen_07_rse.pdf

Some interesting dissertations

https://www.academia.edu/5666321/Estimation_of_Forest_Aboveground_Biomass_Using_Remote_Sensing_and_GIS_A_Case_of_a_REDD_Pilot_Project_in_Lindi_Tanzania
https://www.itc.nl/library/papers_2012/phd/basuki.pdf

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