# Presentation: 079948

## Land Products from NPP and NPOESS

**Land Products from NPP and NPOESS**

- Jeffrey L. Privette
- NPP Deputy Project Scientist
- Dan Tarpley
- NOAA/NESDIS
- 27 October 2005

## Slide 2

##  NPP and NPOESS Land Product Sensors

** **• **CMIS will be the **_**primary**_** source for the Soil Moisture and **_**augment**_** **
**Ice Age/Surface Temperature and Snow Cover/Depth**

**NPP 1030 Orbit**

*** ******NPP and NPOESS Land Product Sensors***

## VIIRS, Redux

- Multispectral, cross-track-scanning, imager
- Spectral bands: 22 (0.4 – 12.5 mic.)
- Swath width: 3000 km
- Single 20 cm diameter, rotating,  all-reflective telescope
- Solar reflective and IR emissive on-board calibration sources
- Heritage: AVHRR, OLS, MODIS

| Parameter | AVHRR | MODIS-EOS | VIIRS-NPP | VIIRS-NPOESS |
| --- | --- | --- | --- | --- |
| Spatial Resolution (m; nadir) | 1000 | 250, 500, 1000 | 375, 750 | 375, 750 |
| Constrained Pixel Growth Along Scan | No (Edge-of-scan ~6x nadir) | No (Edge-of-scan ~6x nadir) | Yes (Edge-of-scan ~2x nadir) | Yes (Edge-of-scan ~2x nadir) |

**Colorado, March 13, 2003**
**MODIS - Terra**

## Shortwave: VIIRS Similar To MODIS

*Adapted from Raytheon ITSS*

***Shortwave: VIIRS Similar To MODIS***

## VIIRS Thermal: Fewer, Wider Bands

- VIIRS
- MODIS

## Land EDRs Use Most Bands

-  Not (Directly) Ingested into Land Algorithms:  DNB, M6, M9, M14, I4
-  These bands are used by aerosol and cloud algorithms, and therefore indirectly affect land product quality

## VIIRS Products Continue Heritage

***VIIRS Products Continue Heritage***

## Heritage:  AVHRR’s First Land Products

**Global Vegetation Index (8 km weekly, GVI; NOAA)**
**Top-of-atmosphere composited NDVI only**
**Operational**** **
**GIMMS (8 km, 15 day; NASA), and **
**	****Pathfinder I (8 km 10 day; NASA/NOAA)**
**NDVI with some atmospheric correction**
**Multimission cross-calibration, solar angle normalization**
**Post-processed**** **
**FASIR (1****°****, monthly; NASA)**
**GIMMS-derived + Leaf Area Index, Absorbed Radiation (FPAR) and albedo**
**Post-processed**

## Heritage: MODIS “Operationalized” Land

**Global Vegetation Index (8 km GVI; NOAA)**
**Top-of-atmosphere composited NDVI only**
**GIMMS / Pathfinder I (8 km; NASA/NOAA)**
**NDVI with some atmospheric correction**
**Multimission cross-calibration, solar angle normalization**
**FASIR (********; NASA)**
**GIMMS + LAI, FPAR and albedo**** **
**MODIS Land Products (250, 500 and 1000 m; NASA)**
_**Top-of-canopy**_** multiproduct suite (**_**VI**_**, **_**LST**_**, LAI, FPAR, NPP, **_**albedo**_**, **_**fires**_**)**
_**Rigorous Calibration**_**, Quality Assurance Bits, **_**Validation**_** Program**
**Fast (<3 days) for complete suite, Rapid Response (<3 h) for some**

## VIIRS Surface Reflectance IP

**Estimation of**
**Visible Band****Surface Refl.****Using 2.1 mic.**

**Reflectance**
**Model**
**Inversion**
**(parameterized)**

**R’****Surf**

**Reflectance SDR**
** ****(M,I Bands)**

**NCEP Fields:**
**Total O****3**
**P****atm****Water Vapor**

*Algorithm Basis:  MODIS/Vermote et al. (2002)**and Kaufman et al. (1996)*

**R****surf ****IP**

**Aerosol AOT EDR****and Properties IP**

- Algorithm similar to MODIS

## MODIS atmospheric correction

*MODIS Granule over Southern Africa  (Sept,13,2001, 8:45 to 8:50 GMT)*

- RGB no correction
- for aerosol effect

- RGB surface reflectance (corrected for aerosol)

- Corresponding aerosol optical thickness  at 670nm (0 black, 1.0 and above red) linear rainbow scale. Clouds are in magenta, water bodies are outlined in white.

## VIIRS Vegetation Indices EDR

***VIIRS Vegetation Indices EDR***

**NDVI****Transform**

**Refl. SDR**

*Algorithm Basis:  AVHRR (NDVI) and MODIS/Huete (EVI)*

**R****surf**** IP**

**TOA NDVI**

**EVI**
**Transform**

**TOC EVI**

**R****surf**** IP**

**NDVI**
**Transform**

**AVI = TOC NDVI ?      (TBD)**

- Differences from MODIS
-  No backup for EVI outliers (e.g., SAVI)
-  No view angle filtering

## MODIS Vegetation Indices (Both TOC)

- MODIS EVI

- MODIS NDVI

***MODIS Vegetation Indices (Both TOC)***

## VIIRS Surface Albedo EDR

**BRDF Model**
**Inversion**

**BRDF ‘Magnitude**
**Inversion’**

**Evaluation of**
**Actual Spectral**
**Albedo**
**(polynomial)**

**BRDF**
**‘****shape’**
**coefficients**

**Current ****R****surf**** IP**

**NCEP Fields:**
**Total O****3**
**P****atm****Water Vapor**

*Algorithm Basis:  1. MODIS BRDF Magnitude Inversion/Schaaf et al. (2002)**2.  RTM Inversion/Liang et al. (2003)*

**R****surf**
**(18 d)**

**‘****Black’ &**
**‘****White-Sky’**
**Spectral Alb.**

**RTM LUT**

**Diffuse Irrad. LUT**

**Current AOT IP**

*offline*

**Broadband**
**Integration****(polynomial)**

**‘****Actual’ (Blue-sky)****Spectral Albedo**

**Look-up**
**Atmospheric**
**Transmissivity**

**Kernel Albedo LUT**

- Tw(,i),Toz(,i)

**‘****Actual’ (Blue-sky)****Broadband Albedo**

## MODIS Albedo:  Always Gridded

- Differences from MODIS:
- Non-BRDF approach is non-heritage
- Instantaneous
- Actual (blue-sky) only; fixed solar zenith angle and atmosphere
- Swath (non-gridded)

**MODIS Shortwave White-Sky Albedo**
**June 10-25, 2003**

- 0.0					0.25

**Terra-only**

**Aqua plus Terra**

## VIIRS Land Surface Temperature

**(Dual) ****Split Window**
**Evaluation**
**(day, night, glint)**

**SDR (TIR, MWIR)**
**Sun-View Geometry**
**Gridded****Surface Type IP**
**Snow Cover IP**

*Algorithm Basis:  Non-Heritage Adaptation of Split Window (Ip, 2004)*

**(Dual) Split Window Coefficients LUT**

**LST, IST**

- Differences from MODIS:
- Dual Split Window
-  MODIS _‘Day/Night’_ and _Single Split Window_

## MODIS Land Surface Temperature

## VIIRS Fire “Application”

**Difference****MIR & TIR;**
**Statistical search ****for outlier vis-a-vis****pixel’s neighborhood**

**Small Fire**
**Rejection Tests**
**Sun glint**
**Warm surface**
**Coastal**

**Candidate fire****locations**

**TOA B(T)**

*Algorithm Basis:  Detection:  MODIS/Giglio et al. (2003)**Characterization:  TBD (Dozier, 1981)*

**‘****Known’ fire****locations**

**Fire Characterization**
**Subpixel Area**
**Subpixel Temperature**

**Fire Detection EDR Application**

**Fire Characterization**
**EDR Application**

- Detection follows MODIS

## MODIS Fire Product

## VIIRS Surface Type EDR

**Monthly****Grid Value****Determination**

**Decision Tree****Classification**
**(commercial C5)**

**Forward Mapping,**
**Overlaying**

**Gridded****Fields for**
**12 mos.**

**Training Data Base (Global Landsat)**

*Algorithm Basis:  1. AVHRR/Hansen et al. (2000)*

**NDVI,****B(T),**
**R****surf**
**(30 d.)**

**Gridded**
**Surface Type**
**IP**

**Swath IPs:  Snow, Fire, Greeness**

*offline*

**Surface Type EDR (Swath)**

- Algorithm similar to MODIS

## AVHRR-based Gridded Surface Type

***AVHRR-based Gridded Surface Type***

## Some Changes From Heritage

## Reduced Pixel Growth Along Scan

**Ratio of Off-nadir pixel to nadir pixel**

**~1500 km**

- Costs:  Stepwise decreased S/N Ratio;
- Undetected detector saturation (single gain)

## Few EDRs Are Gridded or Gap-filled

- Notable exception:  Gridded Surface Type IP

## Land EDR Validation: Tough but Critical

- Below:  Independent “truth” data acquired in a “campaign”
- Right:  MODIS grid cells overlaying ASTER image with fire

## EOS Validation:  Years, Ongoing

- Provisional – **Product quality may not be optimal and incremental product improvements are still occurring **** **
- Validated -- **Product uncertainties are well defined over a range of representative conditions ready for use in scientific publications, and by other agencies there may be later improved versions.  There are three validation stages: **
- Stage 1 Validation:** Product accuracy has been estimated using a **_**small number**_** of independent measurements obtained from selected locations and time periods and ground-truth/field program effort. **
- Stage 2 Validation:** Product accuracy has been assessed over a **_**widely distributed**_** set of locations and time periods via several ground-truth and validation efforts. **
- Stage 3 Validation:** Product accuracy has been assessed and the uncertainties in the product well established via independent measurements in a systematic and statistically robust way representing **_**global conditions**_**.**

**Currently, most MODIS Land Products are at Stage 2**