Preliminary Results of Mapping Carbon at the Pixel Level in East Kalimantan GCF Kaltim Project Global Observatory for Ecosystem Services, Department of Forestry, Michigan State University 101 Manly Miles Building, 1405 S. Harrison Road, East Lansing, Michigan 48823, (517)

Dataset Landsat 7 ETM+ ( ) – 41 Scenes Landsat 8 OLI ( ) – 54 Scenes GLOVIS ( 16 WRS-2 path/row scenes GCF Kaltim Project

Data and Methods Preliminary Workflow – Atmospheric Corrections, Masking, and gap-filling: Stack bands of raw DN’s – ETM+ bands 1-5 and 7 – OLI bands 1-7 Convert DN’s to at-sensor spectral radiance (2_etm_dn_rads.gmd, 2_oli_dn_rads.gmd) Convert radiance to top-of-atmosphere reflectance (3_etm_rads_toaref.gmd, 3_oli_rads_toaref.gmd) – ETM+ bands 1-5 and 7 – OLI bands 2-7 – Data-type float single Mask clouds and cloud shadows (fmask and/or NDXI methods) Generate Modified Soil-Adjusted Vegetation Index-2 Product (4_toa_ref_msavi2.gmd) Determine endmember values related to bare soil and 100% canopy cover Generate vegetation fractional cover (5_fc_model.gmd) Mosaic fractional cover Calculate pixel-level carbon values for the entire province Scenes processed individually, mosaicked to create path/row gap-filled full-band scene, and then the path/row scenes are mosaicked to create a full-band province scene Scenes processed individually, mosaicked to create path/row gap-filled fC scene, then those path row scenes are mosaicked to create a province wide fC GCF Kaltim Project

Procedure for Cloud & Cloud Shadow Masking GCF Kaltim Project

Full Band Mosaic Pre Gap-Fill Base map scenes comprised of ETM+ and OLI dataThematic map showing data gaps 57% Coverage GCF Kaltim Project

Full Band Mosaic with Gap-Fill (false natural color) ERDAS MosaicPro Settings RMS Tolerance = 0.1 pixels Resample Method = Nearest Neighbor Output Grid Cell Size = 30 x 30 meters Overlap Function = Overlay Output Layers = 1-6 Product dataset clipped using Kaltim political boundary shapefile 91% Coverage GCF Kaltim Project

Pixel Lineage GCF Kaltim Project

Vegetation Fractional Cover (fC) 100 = Full Canopy Cover 30 = Minimum Accepted Canopy Cover < 30 = Non-forest Pixel “un-mixing” for each scene using scene-specific end-member values (MSAVI-2) fC products combined to create gap-filled path/row level product Path/row gap-filled fC products mosaicked to create province-level product Kaltim political boundary shapefile utilized to clip raster dataset Level-slicing applied to remove all fC values less than 30 GCF Kaltim Project

Method 1: Stratified, Up and Down Calibrated Carbon Values GCF Kaltim Project

Kaltim Forest Strata Shapefile Source: Indonesian Ministry of Forestry GCF Kaltim Project

Stratified Carbon Map GCF Kaltim Project

Method 2: OLS Regression GCF Kaltim Project

TNC Biomass Plots 175 total observations Outliers removed 45 observations used fC 3x3 focal mean processing fC values extracted at each point feature using bilinear interpolation OLS Regression to relate fC with observed C Adjusted R squared = Scaled up to province level GCF Kaltim Project

C Map Derived from Biomass Plot Data GCF Kaltim Project

Comparison of Measured C (UNMUL/TNC Data) with Predicted C Using 3 Different Allometric Equations GCF Kaltim Project

Python script to automate image pre- processing New dataset comprised of OLI Possibly negate using ETM + data Fmask over other masking processes reduces errors of omission/ commission Refine mosaic/gap-filling process to improve spectral normalization 2014 biomass plot data Potential Improvements for Next Version GCF Kaltim Project