A new approach to evaluate the MODIS annual NPP product (MOD17A3) using forest field data from Turkey

O Gulbeyaz, B Bond-Lamberty, Z Akyurek… - International journal of …, 2018 - Taylor & Francis
International journal of remote sensing, 2018Taylor & Francis
In this study, we present the first evaluation of the MODIS (Moderate Resolution Imaging
Spectroradiometer) annual net primary production (NPP) for Turkey's forest ecosystems
using field measurements. Due to lack of country scale field measurements (ie flux tower for
forest ecosystems), tree DBH (diameter at breast height) data set provided by Ministry of
Forest and Water Affairs (MFWA) of Turkey is used to calculate NPP of Turkey's forest
ecosystems. The lack of a reliable NPP data set leads the researchers to use global NPP …
Abstract
In this study, we present the first evaluation of the MODIS (Moderate Resolution Imaging Spectroradiometer) annual net primary production (NPP) for Turkey’s forest ecosystems using field measurements. Due to lack of country scale field measurements (i.e. flux tower for forest ecosystems), tree DBH (diameter at breast height) data set provided by Ministry of Forest and Water Affairs (MFWA) of Turkey is used to calculate NPP of Turkey’s forest ecosystems. The lack of a reliable NPP data set leads the researchers to use global NPP models such as MODIS annual NPP product. The MODIS MOD17A3 product of vegetation NPP is one of the most highly used data sources for studies of global carbon cycle. However, it is still necessary to test its predictions in multiple biomes, especially for heterogeneous areas in terms of its accuracy and potential bias. Here, we studied a new approach to evaluate coarse scale NPP estimates from the MODIS NPP-MOD17A3 data product, using 2008–2013 field measurements of tree growth throughout Turkey. Three different methods were used to calculate field NPP, including standardized growth coefficients (ministry coefficients [MC]), growth coefficients from North America (Jenkins coefficients [JC]), and annual expected increment (AEI). The average NPP values for all the country is calculated as 2.06 kgC m–1/5 years (0.412 kgC m2 year1) (SD = 1.15 kgC m1/5 years) from MOD17A3, 0.90 kgC m1/5 years (0.18 kgC m2 year1) (SD = 0.57 kgC m1/5 years) with MC, 0.63 kgC m1/5 years (0.126 kgC m2 year1) (SD = 0.37 kgC m1/5 years) with JC and 0.58 kgC m2 year1 (SD = 0.29 kgC m1/5 years) with AEI for the studied plots. We found that the MODIS NPP product has a clear relation with both the NPP estimates obtained by using MC (R2 = 0.34, root mean square error (RMSE) = 1.51 kgC m1/5 years) and JC (R2 = 0.32, RMSE = 1.73 kgC m1/5 years). In addition to that, the relation between MOD17A3 product and AEI-derived NPP is relatively strong (R2 = 0.48, RMSE = 0.26 kgC m2 year1). We discuss possible reasons for these trade-offs among different methods. This study lays out a new approach to validate coarse scale MODIS product using field data directly, including for highly heterogeneous areas.
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