The Long and Winding Road to MODIS Data
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The Long and Winding Road to MODIS Data. MODIS Land Products. MODIS Land Products – Quick review MODIS Land Products Web Sites – Where to get specifics on land products. MODIS Land Products. Radiation Budget Variables Surface Reflectances Land Surface Temperature (LST) and Emissivity

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The Long and Winding Road to MODIS Data

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The Long and Winding Road to MODIS Data

MODIS Land Products

  • MODIS Land Products – Quick review

  • MODIS Land Products Web Sites –

  • Where to get specifics on land products

MODIS Land Products

Radiation Budget Variables

Surface Reflectances

Land Surface Temperature (LST) and Emissivity

Snow and Ice Cover

Bi-directional Reflection (BRDF) and Albedo

Land Cover Characteristics

Fire and Thermal Anomalies

Land Cover

Vegetation Cover Conversion

Vegetation Continuous Fields

At-Launch Land Cover (derived from AVHRR)

Ecosystem Variables

Vegetation Indices (NDVI & EVI)

Leaf Area Index (LAI) and Fraction Photosynthetically Active Radiation (FPAR)

Vegetation Production, Net Primary Productivity (NPP)

MODIS Land Products

Available Resolutions

note: not all products are currently available

ProductSpatial ResolutionTemporal Resolution


Land Surface Reflectance500m8 day composite

7 band product


Snow Cover500mdaily, 8-day, monthly


Land Cover Type/Change1 kmat-launch, quarterly


Vegetation Indices250m*, 500m, 1km16-day, monthly




Vegetation Productivity1km8-day


Algorithm Technical Basis Document

PI Web Site

PI Web Sites

LOOK FOR “User’s Guide”

The MODIS Web Organigram

EOS DataGateway

Land Validation

Home Site

Direct to PI


MODIS Land Products

  • MODIS Data Processing

  • What’s up with L1, L2, L3, L4 Data ??

MODIS Land Products

The amount of processing performed

by NASA for MODIS Land Application

Products has never been applied for

publicly distributed data.

Level 1 - Level 4 Data

Level 1B

= Raw, Un-calibrated Swath Data (Scene), Not projected

= Includes radiometric and calibration coefficients and

parameters, but not applied

Level 2

= Derived geophysical variables at the same resolution and

location as the Level 1 source data

Level 2G

= Calibrated, IS Map Projection*, Tiled

= Multiple Coincident Swaths (e.g. overlapping pixels)

*Integerized Sinusoidal

Level 1 - Level 4 Data

Level 3 Data

= Variables mapped on uniform space-time grid scales

= “MODIS Land End User”

= Usually composite data

= Tiled, IS Projection, “Best” pixel selection (e.g. one value/pixel)

Level 4 Data

= Model output or results from analysis of lower level data


MODIS Land Tile StructureIntegerized Sinusoidal (IS) ProjectionReferenced by horizontal and vertical position



MODIS Land Tile StructureIntegerized Sinusoidal (IS) ProjectionReferenced by horizontal and vertical position

IS Projection

1 km tile = 1200 x 1200

500 m tile = 2400 x 2400

250 m tile = 4800 x 4800

MODIS Land Tiles for U.S.Lambert Azimuthal Equal Area

Relationship of MODIS tiles to TM scenes

MODIS Land Products

  • Obtaining MODIS (Terra, EOS) data

Obtaining MODIS (Terra, EOS) data

  • Data are available from eight EOSDIS Distributed Active Archive Centers (DAACs), two affiliated datacenters, and a growing number of international partners.

  • Data centers process, archive, and/or distribute EOS and other NASA Earth Science data, and provide full support to users of these data.

  • Each data center holds and provides data pertaining to a particular Earth science discipline.

  • Collectively provide a physically distributed but logically integrated database.

Distributed Active Archive Centers (DAACs)

Single point of entry for multiple Distributed Active Archive Centers (DAACs)

Data and documentation

Wide variety of search parameters

Location, Time period, Sensor, Product, Quality

Can save queries for later use

Good tutorial

The Good NewsThe EOS Data Gateway(

Granule ID



MODXXX = product and level of product

A = Terra (formally known as EOS-AM1)

yyyyddd = year and year day (001 – 366) for the start of the


hxxvxx = MODIS land tile

vvv = a three-digit version number assigned by ECS

yyyydddhhmmss = 4 digit year, 3 digit day, hr, min, and sec of

the time (UTC)at which the granule is


HDFEOS File Formats

Integerized Sinusiodal Projection

The BAD News

MODIS Land Tile StructureIntegerized Sinusoidal (IS) Projectionapprox. 10  x 10  (1200 x 1200, 1km tile)

No common RS/GIS

software supports this

projection (yet).

We will work with

software developed at


(P. Thornton and J. Glassy)

HDF Files

HDF = Hierarchical Data Format

Developed by the National Center for Supercomputing

HDF = Features include platform independence, user extendibility,

and embedded metadata for units, labels, and other


HDF = Standard data types include:

multidimensional array, text, table, raster image, and palette

(all packaged into 1 file).

HDF = Structures of different resolutions can be stored in the same



HDFEOS = Standard HDF with ECS (EOSDIS Core System) conventions,

data types, and metadata added.

HDFEOS = ECS core metadata is essential for search services.

HDFEOS = Read by any tool that processes standard HDF files,

although HDFEOS geolocation and temporal information

generally is not accessible.


Objects: Grids (Swaths and Points)

Science Data Fields (SDS): 2D+ arrays

Coded biophysical values (8 - 16 bit)

Defined Projection

Metadata QC Fields (for each grid)

Per pixel quality codes

Tile Level Metadata

The Good News

Many tools currently exist or are being

developed that will read the hdfeos file format.

Current Tools



IDL/ENVI extensions


Data Flows

1) Search and download data in HDF format (EOS Data Gateway)

2) Extract data and metadata from HDF files (HDFLook, IDL/ENVI, future tools)

3) Project from Integerized Sinusoidal to lat/long or other supported projection (? Custom program, future tools)

4) Import raw binary rasters into GIS/RS package

GIS/RS Package




5) Decode raster values into physical units

6) Tile or subset rasters

And the Result !

The metadata text file that is posted with the

hdf file is generally meant for sophisticated

queries of EOS data.

The hdf file has embedded metadata that the “user” will generally find more meaningful.

Read through tools that read hdfeos files.

A little bit about Metadata


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