Data Analysis, Version 1 VIP Laboratory May 2011.

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Presentation transcript:

Data Analysis, Version 1 VIP Laboratory May 2011

Data A 30+ years global CMG daily dataset is downloaded, composed of the following sensors: AVHRR (1981-1999) and MODIS (2000-2010). The daily global data from MODIS and LTDR both have 3600x7200 pixels. Daily data is used to generate composed images. A 15-days and Monthly datasets are generated. Each one based on the following approaches CV-MVC (Constrain View-Maximum Value compositing): it minimizes the off-nadir tendencies of MVC. Average of All values Average of N max values

Image Difference, VI Several images were generated using both NDVI and EVI2. NDVI & EVI2: As a ratio, the NDVI has the advantage of minimizing certain types of band- correlated noise (positively-correlated) and influences attributed to variations in direct/diffuse irradiance, clouds and cloud shadows, sun and view angles, topography, and atmospheric attenuation. On the other hand, EVI (Enhance Vegetation Index) was developed to minimize the atmospheric effect by using the difference in blue and red reflectances as an estimator of the atmosphere influence level.

Image Difference, VI (Cont.) The gaps were filled by using 1. Linear Interpolation 2. Inverse Distance Weighting. 3. Values are constrained by the long term average moving window of 5 years. One standard deviation is used to restrict the boundaries of the values. Values outside of boundaries are replace with a long term average value and labeled within the Rank sds. For AVHRR data, continuity equations (by Tomoaky Miura) were applied. For this analysis, two images from the same day were selected, one prior applying Gap Filling method and the other one after applying the method. The images Vegetation Indices values were subtracted pixel by pixel generating one image.

Image Difference, VI (Cont.) Example (NDVI, YEAR 1985, DOY 244): (BOTTOMUP_GAPFILLED) – (INPUT_GAPFILLED) (GAPFILLED_BOTTOMUP) – (INPUT_GAPFILLED) (GAPFILLED_TOPDOWN) – (INPUT_GAPFILLED) (TOPDOWN_GAPFILLED) – (INPUT_GAPFILLED)

Image Difference, VI (Cont.) Example (NDVI, YEAR 1985, DOY 121): (BOTTOMUP_GAPFILLED) – (INPUT_GAPFILLED (GAPFILLED_BOTTOMUP) – (INPUT_GAPFILLED) (TOPDOWN_GAPFILLED) – (INPUT_GAPFILLED) (GAPFILLED_TOPDOWN) – (INPUT_GAPFILLED)

Image Difference, Phenology Vegetation phenology can be defined as the plants study of the biological cycle events throughout the year and the seasonal and interannual response by climate variations. The following Phenology metrics have been used: Start of the Season (SOS) End of Season (EOS) Length of Season (LOS)

Image Difference, Phenology (Cont.) This analysis has been done by using two different images combinations such as: Gap Filled –Top Down Continuity Top Down Continuity – Gap Filled Gap Filled – Bottom Up Continuity Bottom Up Continuity – Gap Filled

Image Difference, Phenology (Cont.) Example (NDVI, EOS): (TopDown_GapFilled) – (GapFilled_TopDown) 1984 1988 1994 1998

Image Difference, Phenology (Cont.) Example (NDVI, EOS): (BottomUp_GapFilled) – (GapFilled_BottomUp) 1984 1988 1994 1998

Hisrograms Histograms have been done by subtracting the composite data (for both 15 days and monthly) and the same data after applied the continuity equations. Three compositing approaches were used (MVC, AllAvg and N3). Data- Long term average of five years have been used.

Hisrograms (Cont) In general the interval of the vegetation indices in the histograms is about -1200 and 400 (0.12 and 0.04) and the histograms have different shapes.

Cross plots Cross plots were performed using Daily data for both NDVI and EVI2. Several scatter plots were performed. The plot below shows NDVI (BottomUp_GapFilled) vs. NDVI (InputGapFilled) DOY – 121 YEAR – 1985

Cross plots NDVI (GapFilled_BottomUp) vs. NDVI (InputGapFilled) DOY – 121 YEAR – 1985

Cross plots Cross plots were performed using NDVI (GapFilled_TopDown) vs. NDVI (InputGapFilled) DOY – 121 YEAR – 1985

Cross plots NDVI (TopDown_GapFilled) vs. NDVI (InputGapFilled) DOY – 121 YEAR – 1985

Cross plots NDVI (BottomUp_GapFilled) vs. NDVI (InputGapFilled) DOY – 244 YEAR – 1990

Cross plots NDVI (GapFilled_BottomUp) vs. NDVI (InputGapFilled) DOY – 244 YEAR – 1990

Cross plots NDVI (TopDown_GapFilled) vs. NDVI (InputGapFilled) / DOY – 244 YEAR – 1990