- 1 Main principles
- 2 Input data for MCYFS
- 3 Pre-processing
- 4 Post-processing
- 4.1 Preliminary adaptations
- 4.2 Vegetation indicators
- 4.3 Time domain indicators and operations
- 4.4 Time series analysis
- 4.5 Databases of Regional Unmixed Means
- 5 Products overview
The series of SPOT satellites are a French initiative which started in 1986 with the launch of SPOT1. The major component of the payload has always been a high resolution, multispectral camera. Since 1998, a low resolution instrument, called VEGETATION or VGT, was added to the SPOT4 (from April 1998 till May 2012) and SPOT5 (since 2002) satellites. The VEGETATION programme was a joint development by France, the European Commission, Belgium, Sweden and Italy. The VGT sensor was built on the lessons learned from twenty years of experiences with NOAA-AVHRR. It tried to keep the positive elements, especially the daily global coverage at 1 km resolution, but without the drawbacks: the platform is well stabilized, protected against orbital drift and the sensor is well calibrated via on-board calibration standards.
The SPOT-platform follows a near-circular, sun-synchronous orbit at a height of approximately 830 km and a frequency of 14.1 cycles per day. SPOT scans the daylight/sunlit part of the earth during the descending part (north to south) of its track, and the local overpass time at the equator is at 10h30’, which statistically increases the likelihood of acquiring cloud free images.
The VGT-sensor registers 1728 pixels in line, with a sub-nadir resolution of 1.15 km which corresponds to a swath width of about 2200 km. Given the orbital frequency, this results in a nearly complete daily coverage of the earth surface (some gaps remain near the equator). Instead of a rotating mirror as used in AVHRR, the VGT-sensor uses the push-broom technology, in which an entire scanline is simultaneously registered by a linear array of 1728 fixed detectors, thereby reducing the geometric deformations near the image edges. The VGT-sensor simultaneously registers in 4 shortwave bands: BLUE, RED, NIR and SWIR. Contrary to AVHRR, VGT monitors the sensor calibration by means of on-board calibration standards which are measured at regular intervals. On the other hand, the lack of thermal bands limits the application domain and the opportunities for cloud screening of the data.
SPOT-VGT was the first civil EO-system with fully centralized processing and distribution facilities, with as main advantage that all data sets are treated with the same algorithms and distributed in a single format. All the land data registered during a single orbit are stored on board and transmitted to a (single) antenna in Kiruna (Sweden). The further processing, archiving and data dissemination is then performed by the “Centre de Traitement d’Images Végétation” (CTIV), which is hosted at VITO (Belgium). The image quality and the calibration accuracy is monitored by the Image Quality Monitoring Centre (QIV) at CNES (Toulouse, France), where also the Programming and Control Centre is located. More information on the VGT programme can be found on the VGT-website (see Links).
Input data for MCYFS
MCYFS does not use the standard composites (S1 and S10) distributed by the VGT Programme, but the P-products (i.e. the image segments) are used instead. Starting from P-products allowed to apply a different method for fAPAR estimation (fAPAR (Gobron et al., 2006)) . The daily VGT-P products are acquired for the European continent. The P-products are physical products, and comprise Top-of-Atmosphere reflectance values for the 4 spectral bands (Blue, Red, NIR and SWIR) and the Sun and observation zenith and azimuth angles. A status map indicating image quality, snow and ice, cloud and cloud shadows is also delivered.
The following steps are executed to pre-process the VGT-P products.
The input VGT-P products are already geometrically corrected with an accuracy of ±300m.
In this step, the freeP archive is checked for files in the user specified period. These files are copied locally, unpacked and converted to ENVI files.
The P-products include Top-of-Atmosphere reflectance values. No additional radiometric calibration is necessary.
The atmospheric correction is done simultaneously with the estimation of the fAPAR using the method of Gobron et al. (2006). When applying this method, so-called rectified reflectance values for the red, NIR and SWIR bands are obtained. These rectified bands are Top-of-Canopy (TOC) reflectance values corrected for atmospheric and angular disturbances, and are used to calculate the NDVI.
The Digital Chart of the World is used to make the distinction between Land and Sea and to get rid of the annoying rim of cloudy observations along the coastlines in the original VGT-products. The status map is used to derive information on cloud cover, cloud shadows and snow cover.
The daily data are composited to 10-daily values using the maximum fAPAR compositing rule, considering only cloudfree observations. All bands (reflectances, angles, NDVI and fAPAR) are composited according to that rule. More information on the compositing method can be found in 10-daily composites.
As quality indicators, a number of additional images are created:
- the number of good observations per compositing period
- the time grid including segment ID
- geolocation quality
The latter is realized by applying a chip matching procedure using fixed geolocation points for which the distortions are calculated. More information is provided on the page Quality of the compositing. A new status map is created after the compositing. More information on the meaning of the bits can be found in the table below.
All algorithms and procedures of the post-processing are explained in detail in the concerned section. A short description of the SPOT-VEGETATION post-processing products is provided here.
The information contained in the status mask, derived from the 10-daily compositing, is applied on all composite layers, such that the flag information is easily available for further processing. The procedure is described here.
Smoothing reduces the noise in a pixel’s time series and results in time profiles that are more close to reality instead of containing e.g. undetected clouds. The operation is optional and can only be applied on vegetation indicators, because they have a gradual seasonal evolution. Reflectances cannot be smoothed. The method is described in the section Smoothing.
In the case of SPOT-VEGETATION, the fAPAR was calculated during the pre-processing, simultaneously with the atmospheric correction (see Radiometric corrections). The procedure is described in the section fAPAR. The fAPAR is also used in the estimation of the DMP after smoothing.
The Normalized Difference Vegetation Index (NDVI) is derived from the normalized RED and NIR surface reflectances.
Dry Matter Productivity (DMP) expresses the primary productivity (expressed in g DM/ha/day) in a 10-daily time step. The method uses smoothed fAPAR and meteo parameters (from Weather monitoring ), and is based on the Monteith equation explained in detail in the section DMP .
Time domain indicators and operations
The smoothed and non-smoothed vegetation indicators (NDVI, fAPAR and DMP) are further aggregated to monthly composites. A different method is used than for the 10-daily composites and is described here.
Differences to previous year
Two difference operators (absolute and relative) are used to calculate the difference between the current composite and the corresponding one from the previous year. The difference operators are discussed in the section Difference Images.
The historical year is a kind of climatology derived from the entire time series of vegetation indicators (NDVI, fAPAR and DMP) derived from SPOT-VEGETATION since April 1998. The historical year is updated every two years. It contains the average value, the standard deviation, minimum , maximum and deciles per 10% per composite. More information is provided in the section Long Term Statistics.
Difference to historical year
The same difference operators are applied between the current composite and the historical year for the vegetation indicators NDVI, fAPAR and DMP. For NDVI, two additional differences are calculated, i.e. the Vegetation Condition Index (VCI) and the Vegetation Productivity Index (VPI). The methods are described in the section Difference Images.
Time series analysis
The purpose of the similarity analysis is to identify the most similar year compared to the current year. This analysis is performed on the time series evolution per pixel since last October or last March. Only pixels from the classes ‘arable land’, ‘pasture’ and ‘rice’ are considered. The similarity analysis is applied on the smoothed time series of NDVI and fAPAR. The method is described in the section Time series analysis.
The purpose of the cluster classification is to group pixels which have a similar evolution during the current season. pixels from the classes ‘arable land’, ‘pasture’ and ‘rice’ are considered. It is applied on the smoothed time series of NDVI and fAPAR. The method is described in the section Time series analysis.
Databases of Regional Unmixed Means
Some of the above described products are also delivered in the form of Regional Unmixed Means (RUM) which are then added to the database of the Marsop viewer. Briefly described, RUM-values are derived by averaging (part of) the pixels of a certain administrative region which belong to a certain land cover class. In this way, the derived database can be ingested in a GIS-system. The method to derive the RUM-values is described in the section Databases with Regional Unmixed Means (RUM-values).
The table below provides an overview of all 10-daily and monthly composite products that are generated for MCYFS from SPOT-VEGETATION input data.
Ten-daily and monthly composited data are generated in the form of images (I), quicklooks (Q) and databases of RUM-values (R).
Images. The column V[D] refers to the filename suffix, and is explained in the section on Filename conventions.
MCYFS SPOT-VEGETATION products