1. No category

GIO-GL Lot 1, GMES Initial Operations
Date Issued: 19.08.2014
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Gio Global Land Component - Lot I
”Operation of the Global Land Component”
Framework Service Contract N° 388533 (JRC)
PRODUCT USER MANUAL
NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)
VERSION 2
Issue I1.40
Organisation name of lead contractor for this deliverable:
Book Captain:
Bruno Smets (VITO)
Contributing Authors: T. Jacobs and E. Swinnen (VITO)
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Dissemination Level
PU
PP
RE
CO
Public
Restricted to other programme participants (including the Commission Services)
Restricted to a group specified by the consortium (including the Commission Services)
Confidential, only for members of the consortium (including the Commission Services)
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Document Release Sheet
Book captain:
Bruno Smets
Sign
Date 19.08.2014
Approval
Roselyne Lacaze
Sign
Date 26.08.2014
Endorsement:
Michael Cherlet
Sign
Date
Distribution:
Public
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Change Record
Issue/Rev
Date
Page(s)
Description of Change
Release
21.06.2013
All
Draft
D1.00
Draft
13.11.2013
11,12
Updated, removed smoothed product
D1.10
Draft
14.11.2013
All
Minor updated after review R. Lacaze
D1.20
24.12.2013
Added references, abbreviations and validation
summary. Updated data policies.
I1.30
I1.30
21.01.2014
Fixed references
I1.31
I1.31
19.08.2014
20
Update scientific contact
21-23
Clarification after external review
I1.40
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TABLE OF CONTENTS
1
Background of the document ................................................................................................ 8
1.1
Executive Summary .................................................................................................................... 8
1.2
Scope and Objectives ................................................................................................................. 8
1.3
Content of the document ........................................................................................................... 8
1.4
Related documents .................................................................................................................... 9
1.4.1
1.4.2
1.4.3
2
Algorithm ............................................................................................................................ 10
2.1
Overview ................................................................................................................................. 10
2.2
Retrieval Methodology ............................................................................................................ 10
2.2.1
2.2.2
2.2.3
3
Applicable document .................................................................................................................................... 9
Input.............................................................................................................................................................. 9
External document........................................................................................................................................ 9
Background ................................................................................................................................................. 10
Input data ................................................................................................................................................... 10
Processing steps .......................................................................................................................................... 12
Product Description ............................................................................................................. 14
3.1
File Format ............................................................................................................................... 14
3.2
Product Content ....................................................................................................................... 17
3.2.1
3.2.2
3.3
Image Files .................................................................................................................................................. 17
NDVI ‘quicklook’ image ............................................................................................................................... 18
Product Characteristics ............................................................................................................ 19
3.3.1
3.3.2
3.3.3
Projection and grid information ................................................................................................................. 19
Spatial information ..................................................................................................................................... 20
Temporal information ................................................................................................................................. 20
3.4
Data Policies ............................................................................................................................ 20
3.5
Contacts ................................................................................................................................... 20
4
Validation ........................................................................................................................... 21
5
Usage .................................................................................................................................. 23
6
References ........................................................................................................................... 24
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List of Figures
Figure 1: Spectral response of VGT-1 (solid line) and VGT-2 (dashed line) for the 4 bands.......... 11
Figure 2 : NDVI processing ............................................................................................................. 13
Figure 3: Regions of NDVI product. ................................................................................................ 15
Figure 4: The cut-out of tiles ........................................................................................................... 19
Figure 5 : Relative comparison amongst NDVI datasets. Upper left: X: NDVI V2, Y: AVHRR, upper
middle: X: NDVI V2, Y: GEOV1, upper right: X: AVHRR, Y: GEOV1 ...................................... 21
Figure 6 : Agreement between different NDVI datasets ................................................................. 22
Figure 7 : NDVI in Africa, from 1 to 10 May 2006 ........................................................................... 23
List of Tables
Table 1: Spectral characteristics of VEGETATION sensor ............................................................. 11
Table 2 : Masking operation ............................................................................................................ 13
Table 3: Definition of the continental tiles. ...................................................................................... 15
Table 4: Definition of the continents. ............................................................................................... 15
Table 5: Range of values and scaling factors of NDVI. .................................................................. 17
Table 6: Description of HDF-5 file attributes ................................................................................... 18
Table 7: Description of HDF-5 layer attributes ................................................................................ 18
Table 8: Color coding for quicklook images .................................................................................... 18
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List of Acronyms
AC
Agreement Coefficient
ATBD
Algorithm Theoretical Basis Document
AVHRR
Advanced Very High Resolution Radiometer
CCD
Charge Coupled Device
CEOS
Committee on Earth Observation System
CTIV
Centre de Traitement des Images VEGETATION
GEOV1
First version of the Geoland2 products
GIO
GMES Initial Operations
GIO-GL
GMES Initial Operations Global Land service
LPV
Land Product Validation group of CEOS
MBE
Mean Bias Error
MVC
Maximum Value Composite
NDVI
Normalized Difference Vegetation Index
NIR
Near-infrared reflectance band
NRT
Near Real Time
PUM
Product User Manual
RED
Red reflectance band
RMSE
Root Mean Square Error
RRMSE
Relative Root Mean Square Error
S10
10-daily Top Of Canopy synthesis
SPOT
Système Pour l’Observation de la Terre
SRF
Spectral Response Function
SWIR
Short Wave Infrared band
TOC
Top Of Canopy
VCI
Vegetation Condition Index
VGT
VEGETATION sensor onboard SPOT4/5
VGT-S10
10-daily Top Of Canopy synthesis from VEGETATION sensor
VPI
Vegetation Productivity Index
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1 BACKGROUND OF THE DOCUMENT
1.1
EXECUTIVE SUMMARY
The Global Land (GL) Component in the framework of GMES Initial Operations (GIO) is earmarked
as a component of the Land service to operate “a multi-purpose service component” that will
provide a series of bio-geophysical products on the status and evolution of land surface at global
scale. Production and delivery of the parameters are to take place in a timely manner and are
complemented by the constitution of long term time series.
The Product User Manual (PUM) is a self-contained document which gathers all necessary
information to use the product on an efficient and reliable way.
The Copernicus Global Land Service contains already a Normalized Difference Vegetation Index
(NDVI) product, version 1 also known as GEOV1 NDVI [PUM-NDVI-V1]. This NDVI product is
derived from directionally corrected RED and NIR reflectances. The product is updated every 10
days, with a temporal basis for compositing of 30 days and delivered with a 12 days lag in Near
Real Time (NRT).
To comply with the Copernicus Global Land Service technical requirements [AD1], a new version
of the NDVI product, named version 2, was added derived from the SPOT/VEGETATION 10-daily
synthesis reflectance values. This product is provided every 10 days, with a temporal basis of the
10-daily compositing period and delivered with a maximum of 3 days lag in Near Real Time.
This document describes the GIO-GL Normalized Difference Vegetation Index version 2 (NDVI V2)
product, derived from SPOT/VEGETATION 10-daily synthesis data. The product is calculated
globally on a 10-daily basis, and made available to the user in near-real time every 10 days.
1.2
SCOPE AND OBJECTIVES
The Product User Manual (PUM) is the primary document that users have to read before handling
the products.
It gives an overview of the product characteristics, in terms of algorithm, technical characteristics,
and main validation results.
1.3
CONTENT OF THE DOCUMENT
This document is structured as follows:



Chapter 2 presents a description of the algorithm.
Chapter 3 describes the technical characteristics of the product.
Chapter 4 summarizes the validation procedure and the results.
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1.4
RELATED DOCUMENTS
1.4.1
Applicable document
AD1: Annex II – Tender Specifications to Contract Notice 2012/S 129-213277 of 7th July 2012
AD2: Appendix 1 – Product and Service Detailed Technical requirements to Annex II to Contract
Notice 2012/S 129-213277 of 7th July 2012
1.4.2
Input
Document ID
Descriptor
GIOGL1_ATBD_NDVI-VCI-VPI
Algorithm Theoretical Basis Document for NDVI Version 2, and
derived VCI and VPI
GIOGL1_PUM_NDVI-V1
Product User Manual NDVI version 1
GIOGL1_VR_NDVI-V2
Validation Report on NDVI Version 2, and on derived VCI and
VPI
These documents are available on the Global Land service website, on the NDVI product page, at
the address: http://land.copernicus.eu/global/products/NDVI
1.4.3
External document
Document ID
Descriptor
SPOT-VGT
http://www.spot-vegetation.com/index.html
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2 ALGORITHM
2.1
OVERVIEW
NDVI, or Normalized Difference Vegetation Index, is a dimensionless index that is indicative for
vegetation density and is calculated by comparing the visible and near-infrared sunlight reflected
by the surface (reflectance). The Global Land NDVI product is a 10-day synthesis product derived
from Top of Canopy SPOT/VEGETATION data [AD2].
2.2
RETRIEVAL METHODOLOGY
2.2.1
Background
First methods to remove the directional effects in time series were empirical. Duggin et al. (1982)
suggested using only measurements acquired in a limited angular domain. However, this option
does not fit the will to look for a high temporal frequency of observations. Indeed, for regions with
high cloud coverage, removing observations acquired under some angles means a significant loss
of information. Consequently, the interest moved to the Normalized Difference Vegetation Index
(NDVI). Holben (1986) proposed a method based upon the selection, for a given pixel, of the
images corresponding to the maximum value of NDVI over a compositing time window. Gutman
(1989) showed that this method called Maximum Value Composite (MVC) gives a temporal NDVI
profile related to the biomass variations. Nevertheless, the MVC principle implies that there is a risk
to select NDVI values resulting from undetected cloudy observations. One improvement came with
the BISE (Best Index Slope Extraction) method (Viovy et al., 1992) which takes into account the
slope of the NDVI profile. The change in the length of the compositing period affects entirely the
resulting MVC profile whereas it affects the resulting BISE profile only when its sign changes.
However, neither takes into account the seasonal variations of the geometry of illumination and the
resulting shadow effects. Nonetheless, the MVC is used operationally to derive the standard NDVI
from the 10 days synthesis reflectances of SPOT/VEGETATION sensor.
2.2.2
Input data
The input data of the NDVI processing line are the standard VGT-S10 (Top of Canopy 10-daily
synthesis reflectance) products generated and provided by the SPOT VEGETATION programme
through VITO (http://free.vgt.vito.be/).
Since April 1998, the VEGETATION sensor has been operational on board the SPOT 4 and 5
earth observation satellite system. It provides a global observation of the world on a daily basis.
The instrumental concept relies on a linear array of 1728 CCD detectors with a large field of view
(101°) in four optical spectral bands described in Table 1 and Figure 1. Although very similar, some
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differences between VEGETATION 1 and VEGETATION 2 instruments have to be noticed [SPOTVGT], particularly regarding the spectral sensitivity (Figure 1).
Acronym
B0
B2
B3
SWIR
Centre (nm)
450
645
835
1665
Width (nm)
40
70
110
170
Potential Applications
Vegetation-Atmosphere
Vegetation
Vegetation
Vegetation
Table 1: Spectral characteristics of VEGETATION sensor
Figure 1: Spectral response of VGT-1 (solid line) and VGT-2 (dashed line) for the 4 bands.
The spatial resolution is 1.15 km at nadir and presents minimum variations for off-nadir
observations. The 2200 km swath width implies a maximum off nadir observation angle of 50.5°.
About 90% of the equatorial areas are imaged each day, the remaining 10% being imaged the next
day. For latitudes higher than 35° (North and South), all regions are acquired at least once a day.
The multi-temporal registration is about 300 meters.
The 10-day synthesis (S10) provides surface reflectance values based on a selection of the “best”
measurements on the entire period. The actual selection is based on the maximum NDVI value, as
it is commonly accepted today, even if many problems associated to that selection are identified
[see GIOGL1_ATBD_NDVI-VCI-VPI].
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2.2.3
Processing steps
The Normalized Difference Vegetation Index (NDVI) can be related to
the vegetation
photosynthetic activity. It is computed from the RED and NIR reflectances only (see Eq. 1).
Eq. 1
where B2 and B3 are the atmospherically corrected surface reflectances in the RED and NIR
bands from the SPOT/VEGETATION 10-daily synthesis dataset.
Besides the surface conditions, these reflectances are also largely dependent on the specifications
of the spectral bands of a sensor, defined by the spectral response functions (SRFs). This means
that there is not a true NDVI for a specific surface, but only an NDVI, according to sensor-specific
SRFs (see e.g. Steven et al. 2003; Trishchenko, 2009; Trishchenko et al. 2002).
During the processing of the NDVI, as shown in Figure 2, the information stored in the Status Mask
is integrated inside the NDVI using the upper values, representing a set of flags. The NDVI
processing also removes falsely land pixels that are wrongly identified in the SPOT/VEGETATION
status map (land is falsely extended with land with about ten pixels around the coasts) by using the
GLC2000 global land classification (Bartholomé et Belward, 2005). All sea pixels in this latter map
receive the flag value 254 in the NDVI images. Boreal pixels in winter time (no light) will be flagged,
since the status map no longer contains the distinction between land and water and hence this
information can’t be extracted immediately as such.
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VGT S10 B2, B3
VGT S10 SM
(dekad N)
(dekad N)
GLC2000
Band
math
NDVI
(dekad N)
Figure 2 : NDVI processing
During the band math calculation of Eq. 1, a masking operation is performed as follows:
VGT S10 SM
GLC2000
NDVI V2
0 (indicates water or boreal winter)
Not Water
Missing Value or data error
Bit 0 and/or 1 set
Not Water
Cloud or Cloud Shadow
Bit 2 set
Not Water
Snow or Ice
Bit 5 and/or 6 set
Not Water
Missing Value or data error
Bits 0 to 6 set or clear (Don’t care)
0 (Sea)
Water
Table 2 : Masking operation
Note that any pixel identified as in-land water in GLC2000 will not be masked out and hence
considered as land. The dynamics of in-land water would mask out land pixels and hence not
providing any NDVI value. To flag out in-land water pixels, one could use the Water Bodies
product. A more detailed description can be found in the ATBD [GIOGL1_ATBD_NDVI-VCI-VPI].
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3 PRODUCT DESCRIPTION
The Normalized Difference Vegetation Index (NDVI) product follows the following naming
standard:
g2_BIOPAR_NDVI[_<YYYYMMDDHHMM>_<AREA>_<SENSOR>_V<Major.Minor>
where

<YYYYMMDDHHMM> gives the temporal location of the file. YYYY, MM, DD, HH, and MM
denote the year, the month, the day, the hour, and the minutes, respectively.

<AREA> gives the spatial coverage of the file. In our case, <AREA> is HxxVyy, the name of
the 10°x10° tile or the continent short name

<SENSOR> gives the name of the sensor used to retrieve the product, so VGT referencing
SPOT-VEGETATION

<Major.Minor> gives the version number of the product. “Major” increases when the
algorithm is updated. “Minor” increases when bugs are fixed or when processing lines are
updated (metadata, color quicklook, etc...). This version refers to Major = 2.
3.1
FILE FORMAT
The NDVI products are distributed in zip archives. The archive contains following files:

single-band HDF-5 format containing the following layers:
o
NDVI : normalized difference vegetation index value

a xml file containing the metadata conform to INSPIRE2.1. An xsl file allows displaying a
friendly view of the metadata file.

A quicklook in a coloured geo-tiff format. The quicklook sub-sampled to 25% in both
horizontal and vertical direction from the NDVI layer. A text file containing the copyright of
the product.
Each file corresponds to a tile of 10° x 10°. A dedicated typology has been chosen to locate easily
each tile when reading its name. The globe is divided in 36 tiles in longitude and 18 in latitude
according to Figure 3. Only the green tiles, covering land, are generated and hence available. In
winter season, the northern hemisphere has less observations, hence the number of available tiles
could be less. The products are also provided by continents (grouping of a set of tiles) as defined
in Figure 3, and named as in Table 3. The 6 colored rectangles, covering most land of our
continents, represent the available continents.
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Figure 3: Regions of NDVI product.
Short name
Continent
AFRI
Africa: 20°W – 60°E, 40°N – 40°S
ASIA
Asia: 60°E – 180°E, 80°N – 0°N
EURO
Europe: 30°W – 60°E, 80°N – 30°N
NOAM
North America: 170°W – 50°W, 80°N – 10°N
OCEA
Oceania: 100°E – 180°E, 0°S – 50°S
SOAM
South America: 110°W – 30°W, 20°N – 60°S
Table 3: Definition of the continental tiles.
Note that the continents distributed over EUMETCast are defined according the DevCoCast
(VGT4Africa) settings and are not bound to 10° (Table 4):
Short name
Continent
Africa
20°W – 60°E, 38°N – 35°S
S-America
93°W – 33°W, 25°N – 56°S
Table 4: Definition of the continents.
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TIPS:
1. You can download and install HDF5 library from http://www.hdfgroup.org.
The library comes with useful tools that could be used to discover the organization and contents of
the hdf5 files. For example, you can use the “h5ls” line command to view the hierarchical
organization of the files (as below):
h5ls -r g2_BIOPAR_NDVI_201307210000_H23V01_VGT_V2.0.h5
You can also download a java viewer called HDFView from the same URL. This tool is more user
friendly oriented than the based line commands.
2. The VGTExtract tool can be used to convert
http://www.geoland2.eu/portal/system/vgtextract.html.
to
other
formats,
see
This tool detects the available Global Land zip files on your local system and is able to extract an
ROI, mosaic tiles together and perform format conversion to another format.
3. Another option is to use the GDAL library from http://www.gdal.org/.
This library comes with useful tools that could be used to inspect and convert the contents of the
hdf5 files into another format. For example, you can use the ‘gdalinfo’ tool to show the available
bands in the hdf5 file (as below):
gdalinfo g2_BIOPAR_NDVI_201302010000_H17V4_VGT_V1.3.h5
or use the ‘gdal_translate’ tool to convert a band to geotiff format (as below):
gdal_translate
–of
Gtiff
HDF5:"g2_BIOPAR_NDVI_201307210000_H17V4_VGT_V2.0.h5"://NDVI
NDVI_201307210000_H17V04_VGT_V2.0.tiff
g2_BIOPAR_NDVI-
Windows users could also install the GDAL library from http://www.gisinternals.com/sdk.
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3.2
PRODUCT CONTENT
3.2.1
Image Files
The physical range of NDVI band is given in Table 5. Note that no uncertainties are associated to
NDVI values. The physical values are retrieved by:
PhyVal = DN / ScalingFactor + Offset
where the scaling factor and the offset are given in the table below.
NDVI
Minimum value
-0.08
Maximum value
0.92
Maximum DN value
250
Missing value or data error
251
Cloud or cloud shadow
252
Snow or ice
253
Sea
254
Other
255
Scaling factor
250
Offset
-0.08
Table 5: Range of values and scaling factors of NDVI.
Note that the NDVI values is now restricted to the range [-0.08; 0.92] compared to the range [-0.1;
0.92] of the original NDVI provided by the SPOT/VEGETATION Programme and delivered by the
CTIV. The loss at the bottom does not affect the data quality because it never concerns clear land
observations (mostly water). On the other hand, the upper digital values between 251 and 255 now
becomes available for “flags”, i.e. dedicated values to indicate special situations
The HDF-5 file contains a number of HDF-5 attributes on the file-level, see Table 6 and on the
layer-level, see Table 7.
Attribute name
Archive_facility
Centre
Ellipsoid_name
Geodate_name
Attribute description
Name of archiving center
Name of processing/dissemination center
Name of ellipsoid system
Name of date system
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Attribute name
LAT
LONG
Instrument_ID
Overall_quality_flag
Pixel_size
Product_time
Product_algorithm_version
Projection_name
Region_name
Satellite
Attribute description
Lattitude (top left)
Longitude (top left)
Sensor name
Quality indicator
Size of a single pixel (in square)
Time of product creation
Version of algorithm during processing
Name of projection system
Area name
Platform name
Table 6: Description of HDF-5 file attributes
Attribute name
Class
Nb_bytes
Order_bytes
Product
Missing_value
Offset
Scaling_factor
Attribute description
Type of layer (DATA)
Data type (e.g. uint8, uint16, …)
Order data type (1= intel)
Layer name
Data number representing missing value
Offset factor to retrieve physical value
Scale factor to retrieve physical value
Table 7: Description of HDF-5 layer attributes
3.2.2
NDVI ‘quicklook’ image
The quicklook is a geo-referenced tiff file. The spatial resolution is sub-sampled, using nearest
neighbour resampling, to 25% in both directions, hence a quicklook is 1/16th of the size of the data
layer.
The quicklook is coded equal to NDVI. It is a coloured image. The quicklook is coded in 1 byte,
using the same offset and scale parameters as the data layer.
The quicklook is provided with an embedded color table.
Table 8: Color coding for quicklook images
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3.3
3.3.1
PRODUCT CHARACTERISTICS
Projection and grid information
The product is displayed in a regular latitude/longitude grid (plate carrée) with the ellipsoïd WGS
1984 (Terrestrial radius=6378km). The resolution of the grid is 1/112°.
As defined by SPOT-VEGETATION mission, the reference is the centre of the pixel. It means that
the longitude of the upper left corner of the pixel is (pixel_longitude – angular_resolution/2.)
Each tile covers an area of 10°x10°, while the continental tiles cover a multiple of these 10°x10°
tiles as defined in Table 3.
1121 pixels = 10.0089°
10° = 1120 pixels
10° = 1120 pixels
1121 pixels = 10.0089°
Figure 4: The cut-out of tiles
Starting from the upper left center pixel and taking 10° or 1120 pixels into account, the final tile is
an array of 1121 lines and 1121 columns taking the bottom/right upper/left half pixel into account
(Figure 4). As such there is an overlap between the tiles. For example, the last column of tile
H18V4 is the first column of the tile H19V4, and the last line of H18V4 is the first line of the tile
H18V5. Users willing to remove the additional line or column can use gdal_translate or (soon)
VGTExtract tools. For example:
gdal_translate –of Gtiff –srcwin 0 0 1120 1120
g2_BIOPAR_NDVI_201302010000_H17V04_VGT_V2.0.tiff
HDF5:"g2_BIOPAR_NDVI_201302010000_H17V4_VGT_V2.0.h5"://NDVI
Note that the same reasoning holds also for the continental tiles.
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3.3.2
Spatial information
As shown in Figure 3, the NDVI product is provided from longitude -180 °E to +180°W and latitude
+75°N to -56°S. The area above 75°N and below 56°S is filled with no-values (255).
3.3.3
Temporal information
The NDVI products are 10-days composites. The temporal information “YYYYMMDDHHMM” in the
filename corresponds to the start date of the 10-daily period.
For example, the file g2_BIOPAR_NDVI_201308210000_H17V04_VGT_V2.0.h5 corresponds to
the synthesis period from 21/08/2013 to 31/08/2013.
The temporal information is detailed in the metadata (xml file) by 2 fields "EX_TemporalExtent :
beginPosition" and "EX_TemporalExtent : endPosition" as “YYYY-MM-DDTHH:MM::SS” giving the
beginning and the end of the 10-days time period, respectively. The startPosition of the 10-days
time period is always set to the 01st, 11th or 21th day of the month.
3.4
DATA POLICIES
Any use of the NDVI product implies the obligation to include in any publication or communication
using these products the following citation:
"The product was generated by the land service of Copernicus, the Earth Observation program of
the European Commission. The research leading to the current version of the product has received
funding from various European Commission Research and Technical Development programs. The
product is based on VEGETATION data ((c) CNES).
The user accepts to inform Copernicus about the outcome of the use of the above-mentioned
products and to send a copy of any publications that use these products to the following address
[email protected].
3.5
CONTACTS
Accountable contact: European Commission Directorate-General Joint Research Center
Email address: [email protected]
Scientific contact: VITO
Email address: [email protected]
Production and distribution: VITO
Email address: [email protected]
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4 VALIDATION
A relative comparison between the NDVI (version 2), the METOP-AVHRR 10-daily NDVI and NDVI
version1 (GEOV1) is performed. A global evaluation was performed, according to the protocols
and metrics defined by CEOS LPV for the indirect validation. The spatial and temporal consistency
of datasets is checked and a global statistical analysis per major land cover class was carried out.
The details and results are given in the Validation report [GIOGL1_VR_NDVI-V2].
As shown in Figure 5 and Figure 6, a good correlation can be seen among the different validated
NDVI datasets. Note, in the figure below, the NDVI version2 is depicted as MO3.
Figure 5 : Relative comparison amongst NDVI datasets. Upper left: X: NDVI V2, Y: AVHRR, upper
middle: X: NDVI V2, Y: GEOV1, upper right: X: AVHRR, Y: GEOV1
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Figure 6 : Agreement between different NDVI datasets
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5 USAGE
NDVI images are typically visualized through an image processing software and then color coded.
Values range from -0.08 to 0.92, indicating close to 0: no vegetation and close to 1: dense
vegetation. The visualization color coding scheme usually ranges from brown (no vegetation) to
green (dense vegetation), as in the example below. One such NDVI image from just one dekad
(10-day period), shows only the presence or absence of vegetation and allows us to easily
distinguish the deserts (like in the Sahel region) and the dense forests (like in Congo).
Figure 7 : NDVI in Africa, from 1 to 10 May 2006
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6 REFERENCES
Bartholomé, E., & Belward, A. S. (2005). GLC2000: A new approach to global land cover mapping
from earth observation data. International Journal of Remote Sensing, 26(9), 1959−1977.
Duggin, M., D. Piwinski, V. Whitehead, and G. Ryland. 1982. Evaluation of NOAA-AVHRR data for
crop assessment. Appl. Opt. 21: 1873-1875.
Holben, B. (1986). Characteristics of maximum-value composite images from temporal AVHRR
data. International Journal of Remote Sensing, 7, 1417 – 1434.
Steven, M.D, Malthus, T.J., Baret, F., Xu, H., Chopping, M.J. (2003). Intercalibration of vegetation
indices from different sensor systems. Remote Sensing of Environment, 88(4):412-422.
Trishchenko A.P., 2009, Effects of spectral response function on surface reflectance and NDVI
measured with moderate resolution satellite sensors: Extension to AVHRR NOAA-17, 18 and
METOP-A. Remote Sensing of Environment, 113, 335-341.
Trishchenko A. P., J. Cihlar, Z. Li, 2002, Effects of spectral response function on surface
reflectance and NDVI measured with moderate resolution satellite sensors. Remote Sensing of
Environment, 81, 1-18.
Viovy, N., Arino, O. & Belward, A. S. The best index slope extraction (BISE): A method for reducing
noise in NDVI time series. International Journal of Remote Sensing (1992), 13, 1585-1590.
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