ACADSTAFF UGM
| Judul/Title | Evaluating Multi-sensor Combination of Normalized Difference Vegetation Index (NDVI) Time Series Data over Southeast Asia |
| Penulis/Author | Dr.Sc. Sanjiwana Arjasakusuma, S.Si., M.GIS. (1) ; SANDIAGA SWAHYU K (2) |
| Tanggal/Date | 29 2020 |
| Kata Kunci/Keyword | |
| Abstrak/Abstract | Normalized Difference Vegetation Index (NDVI) data is the most commonly used vegetation proxy from remote sensing data to model the vegetation biophysical properties. The longest time-series data of NDVI from the earlier era of remote sensing satellites is available from AVHRR GIMMS employing the red and near-infrared bands in NOAA sensors from 1981 to 2015 in 8-km spatial resolution in the monthly interval. This study aims to evaluate the compatibility of NDVI data from the newer sensors such as MODIS Terra (MOD13C2), Proba-V and Visible Infrared Imaging Radiometer Suite (VIIRS) data when combined with GIMMS data. Calibration between two time-series data from different sensors was constructed by using image-matching Pseudo Invariant Features (PIF) method and the fitness levels using all pixels and at different land-cover classes were assessed. In addition, structural change analysis was conducted to identify the sensor-shift problems at the best data combination. Our results suggested the best fit of GIMMS when being paired with VIIRS data with the R2 of 0.91 (n = 3132) and 0.89 (n = 1044) for model and validation analysis. Although the fitness level from the linear regression showed a good fit, an artifact as a result of sensor-shift problems still can be detected from structural change analysis, revealing the imperfection of linear calibration method. Future works should aim to explore the performance of non-linear methods to calibrate the different time-series data and explore the combination with other sensors. |
| Level | Internasional |
| Status |