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Collection 5 MODIS Land Cover Product

 

The MODIS Land Cover Type (MCD12Q1) product is released online via several data portals.  The global land cover maps were produced every year between 2001-2012.  Each map is based on a supervised classification of an annual time series of spectralobservations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Click to read more

 

 

 

 

Northern Eurasia Land Dynamics Analysis (NELDA)

 

The Northern Eurasia Land Dynamics Analysis (NELDA) project was pursued in collaboration with scientists from Oregon State University and Russia.  The purpose of the project was to synthesize information on how the Northern Eurasia landmass is changing under a warming climate and to improve climate models based on these findings. Click to read more

 

 

MODIS-based detection of Trends in Disturbance and Recovery (MODTrendr)

 

The MODIS-based detection of trends in disturbance and recovery (MODTrendr) project is based on a similarly named algorithm called LandTrendr developed by Robert Kennedy and Zhiqiang Yang at Oregon State University.  The approach to temporally segment a Landsat time series into distinct periods representing stable, disturbance, and recovery was adapted to coarser spatial resolution MODIS time series data.  The modified algorithm was tested over a large forested area in the Pacific Northwest of the USA where an existing LandTrendr map already existed. 

Click to read more

 

 

VIIRS Surface Type Validation
 

In collaboration with the GOFC-GOLD organization, a comprehensive global validation dataset was developed.  My role in this project was to use high resolution imagery obtained for each of the 500 selected sites to validate the first version of the planned VIIRS Quarterly Surface Type product that is being generated by the University of Maryland.  This product will represent a continuation of the MODIS Land Cover product but at a lower 1-km spatial resolution.  To create a dataset that can be used to validate this product, we performed visual interpretations of each VIIRS 1-km pixel within the sample of validation sites according to the International Geosphere-Biosphere Programme (IGBP) legend. Click to read more

 

 

Collection 6 MODIS Land Cover Product
 

The Collection 6 MODIS LC product is still under development with the goal to release the maps sometime in early 2015.  The purpose of this project is to update and improve the methodology used to create the C5 MODIS LC product.  The first major improvement is a new set of daily NBAR inputs that will be splined to fill gaps.  In addition to ingesting annual metrics derived from these raw splined bands, the algorithm will also consider additional spectral indices and phenological information.  The second improvement is the implementation of a new hierarchical classification scheme based on the FAO/UNEP Land Cover Classification System (LCCS) in addition to the five existing land cover legends.  Click to read more

 

 

Landsat Analysis of Boreal Forest Change

 

Boreal forests are an important part of the global carbon cycle and recent climate change is putting these massive carbon stores at risk with dangerous consequences for future generations.  A number of studies using time series data from the Advanced Very High Resolution Radiometer (AVHRR) have shown declining trends in the boreal forests of Canada.  We have investigated the nature of these trends using higher resolution Landsat time series for the period 1984-2013. Click to read more

 

 

 

Damien Sulla-Menashe

Research Website 

Direct Measurement of Aboveground Carbon Dynamics in Support of Large-Area CMS Development

 

Information on the amount and global distribution of aboveground forest biomass is critical to decision-making on a host of internationally significant issues ranging from poverty reduction and human health to biodiversity conservation and climate stabilization.  New policy measures to reduce carbon emissions from tropical forest deforestation and degradation are being implemented at many scales from global to sub-national.  In this project we are seeking to demonstrate the potential for large-scale carbon monitoring in Mexico using airborne Lidar and Landsat data. (More to come soon...)

 

 

 

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