Journal
INTERNATIONAL JOURNAL OF REMOTE SENSING
Volume 34, Issue 20, Pages 7400-7423Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2013.820367
Keywords
-
Funding
- Universiti Teknologi Malaysia (UTM) [Q.J130000.7127.01J44, Q.J130000.2527.03H23, Q.J130000.2527.04H96]
- Ministry of Higher Education of Malaysia (MOHE)
- UTM Zamalah Scholarship
Ask authors/readers for more resources
Conducting quantitative studies on the carbon balance or productivity of oil palm is important in understanding the role of this ecosystem in global climate change. In this study, we evaluated the accuracy of MODIS (Moderate Resolution Imaging Spectroradiometer) annual gross primary productivity (GPP) (the product termed MOD-17) and its upstream products, especially the MODIS land cover product (the product termed MOD-12). We used high-resolution Google Earth images to classify the land cover classes and their percentage cover within each 1km spatial resolution MODIS pixel. We used field-based annual GPP for 2006 to estimate GPP for each pixel based on percentage cover. Both land cover and GPP were then compared to MODIS land cover and GPP products. The results show that for pure pixels that are 100% covered by mature oil palm trees, the RMSE (root mean square error) between MODIS and field-based annual GPP is 18%, and that this is increased to 27% for pixels containing mostly oil palm. Overall, for an area of about 42km(2) the RMSE is 26%. We conclude that land cover classification (at 1km resolution) is one of the main factors for the discrepancy between MODIS and field-based GPP. We also conclude that the accuracy of the MODIS GPP product could be improved significantly by using higher-resolution land cover maps.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available