# Presentation: 129186

## Inter-Sensor Validation of NDVI time series from AVHRR, SPOT-Vegetation, SeaWIFS, MODIS, and LandSAT ETM+ 

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**Inter-Sensor Validation of ****NDVI time series from ****AVHRR, SPOT-Vegetation, SeaWIFS, MODIS, and LandSAT ETM+**

**Molly E. Brown ****+**
**Jorge E. Pinzon****+**
**Jeffery T. Morisette****x**** **
**Kamel Didan***
**Compton J. Tucker****x**
**+ ****SSAI, NASA Goddard Space Flight Center         * Soil, Water and Environmental Sciences**
**Greenbelt, MD 20771                                                University of Arizona**** **
**x****NASA Goddard Space Flight Center**
-   **Greenbelt, MD 20771 **

## Overview

- Data used in study
- Global NDVI datasets, LandSAT ETM+ for comparison
- Methods
- Spectral, spatial and temporal considerations
- Global 1 degree datasets
- CEOS sites and drought locations
- Results
- Discussion – data continuity from AVHRR through MODIS to VIIRS

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## VIS/NIR/SWIR Band Comparison

**VIS/NIR/SWIR Band Comparison**

**AVHRR**

**SeaWiFS**

**VGT**

**MODIS**

- Differences in spectral range will necessitate increased processing in
- AVHRR and SPOT due to water vapor sensitivity.

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Data

| Sensor | Data Source | Spatial Resolution | Time
domain | Temporal Resolution |
| --- | --- | --- | --- | --- |
| AVHRR | GIMMS NDVIg
Pinzon et al (2005) | 8000 m
1 degree | 81-04
280 mon | 15 day
monthly |
| SPOT VGT | FAS-GIMMS, VITO
Achard, F. et al. (1992) | 1000 m
1 degree | 98-04
67 mon | 10 day
monthly |
| MODIS
NDVI | MODIS-Land, University of Arizona (K.Didan) 
Huete, A. et al. (2002) | ~5000 m, 500m
1 degree | 00-04
52 mon | 16 day
monthly |
| SeaWIFS | SeaWIFS / GSFC / GIMMS
Tucker et al (2002) | 4633 m
1 degree | 97-02
62 mon | monthly |
| LandSAT | CEOS website
Morisette et al (2004) | 30 m | 1-9 scenes  | periodic |

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Validation  Methods:59 Sites

**Aggregations** to monthly time step and 1 degree resolution for pixel by pixel comparison.
**Global hemispherical means** created to provide direct comparison of NDVI behavior.
**Comparisons of time series** created from 25x25 km box at native temporal and spatial resolutions: CEOS sites, locations of droughts, deserts, agricultural production regions, etc.
**Anomaly and seasonal characteristics** evaluated
- Atmospherically corrected, 25x25km subsets of selected **LandSAT ETM+** scenes provide a base for comparison of datasets.

- CEOS Land Validation Sites

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Maps of NDVI correlation at 1degree

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

**Notes:**
Although AVHRR is matched to the SPOT range, correlations are higher in SeaWIFS.  PAL and GIMMS NDVIg are similar to SPOT-AVHRR.

## Global averages show that

**Global averages show that**
- Four sensors have similar
-  signals.
- Improvements in AVHRR
-  NDVI have reduced many
-  differences between the
-  sensors, enabling a direct
-  comparison between the
-  records:
- Longer base means for anomaly
- Multiple data sources for NDVI
- More work to be done for
-  data integration to be operational

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Results from CEOS Sites: Harvard, Massachusetts

- Note: similarity in range, seasonality of NDVI
- LandSAT scene range of variation
- Differences in treatment of winter, clouds

- Correlations:
- AV-SP  0.89
- AV-MO 0.84
- AV-SW 0.86

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Correlations:

**Correlations:**
**AV-SP  0.59**
**AV-MO 0.65**
**AV-SW 0.59**

**Correlations:**
**AV-SP  0.85**
**AV-MO 0.82**
**AV-SW 0.66**

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## MODIS cloud and aerosol atmospheric correction 

- MODIS cloud and aerosol atmospheric correction
- explains the differences between MODIS and the other sensors.

**Correlations**
**AV-SP  0.60**
**AV-MO 0.33**
**AV-SW 0.38**

**+**

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

**Notes:**
NDVI seasonality observed in the southern Amazon forest region with PAL and GIMMS is primary caused by variations in atmospheric conditions associated with biomass-burning aerosols and cloudiness (Koba- Dye this AGU)
All atmospheric corrections need a clear understanding of what fraction of signal is vegetation and what fraction is not.

## Anomaly Time Series: Drought Detection

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Conclusions

- Many lessons have been learned from the creation of a consistent NDVI record from AVHRR
- How to integrate sensors with different gains (NOAA 7-14 and NOAA 16-17)
- Overcome sensor limitations to reduce clouds, reduce noise and improve image coherence
- More work to be done on further integrating the records of AVHRR, MODIS, SPOT, SeaWIFS to maximize their various strengths, minimizing their weaknesses
- AVHRR – MODIS – VIIRS data continuity will be required to maximize length of record to answer important science questions

- Molly E. Brown, PhD

- Dec 15, 2004 AGU

## Thanks go to Brad Doorn, Assaf Anyamba and Jennifer Small for providing the SPOT data, Gene Feldman, Norman Kuring and Jacques Descloitres for the monthly global SeaWIFS data.
URLs: 
GIMMS NDVIg:  http://landcover.org
SeaWIFS: http://daac.gsfc.nasa.gov/data/dataset/SEAWIFS_LAND
MODIS: http://edcdaac.usgs.gov/modis/dataproducts.asp
SPOT VGT: http://free.vgt.vito.be/
Subsets of SPOT, AVHRR, MODIS tiles, and Landsat ETM+ data at CEOS sites: http://landval.gsfc.nasa.gov/MODIS/index.php

Thank you!

**URLs: **
**GIMMS NDVIg**:  http://landcover.org
**SeaWIFS:** http://daac.gsfc.nasa.gov/data/dataset/SEAWIFS_LAND
**MODIS:** http://edcdaac.usgs.gov/modis/dataproducts.asp
**SPOT VGT:** http://free.vgt.vito.be/
- Subsets of SPOT, AVHRR, MODIS tiles, and **Landsat ETM+** data at **CEOS sites**: http://landval.gsfc.nasa.gov/MODIS/index.php
**Thank you!**

- Molly E. Brown, PhD

- Dec 15, 2004 AGU