User's Guide FPAR, LAI (ESDT: MOD15A2) 8
Contents
1. FPAR LAI User s Guide Terra MODIS Land Team be updated when a more accurate estimate of uncertainties in the surface reflectance product will be available Table 2 Theoretical estimation of uncertainties in atmospherically corrected surface reflectances Wang et al 2001 Spectral Band Red NIR Blue Green Center of Band nm 670 865 443 555 Relative Error 10 33 3 6 50 80 5 12 Uncertainties used 0 2 0 05 0 8 0 1 Dimensionless Our analysis indicates that the algorithm fails when the pixel is corrupted due to clouds or atmosphere effect Wang et al 2001 A back up algorithm is triggered to estimate LAI and FPAR using vegetation indices in this case Empirical MODIS specific NDVI LAI and NDVI FPAR relationships are expected to be derived from MODIS LAI and FPAR fields and MODIS Surface Reflectance Product The collection 3 of the back up algorithm used relationships derived from SeaWiFS the Sea Viewing Wide Field of view Sensor data Wang et al 2001 The collection 4 LUTs for back up algorithm were derived from MODIS surface reflectance product and MODIS LAI product for biome 1 3 only This resulted in a better agreement with field measurements of the LAI Future collections will continue LUT tuning for the remaining biomes The LAI FPAR algorithm is dependent on the spatial resolution of data Two canopy specific wavelength independent variables described in section Derivation Techniques and Algorithm as well as leaf albed2. D Shabanov N V Stroeve J C Knyazikhin Y amp Myneni R B 2003 Analysis of collection 3 MODIS LAI and FPAR products Remote Sens Environ in review Zhang Y Tian Y Knyazikhin J Martonchik J V Diner D J Leroy M and Myneni R B 2000 Prototyping of MISR LAI and FPAR algorithm with POLDER data over Africa IEEE Trans Geosci Remote Sens 38 5 2402 2418 Last updated 9 10 2003 Page 16 of 17 FPAR LAI User s Guide Terra MODIS Land Team Glossary and Acronyms TBD Last updated 9 10 2003 Page 17 of 17
3. and NPP MODIS radiometry inputs define the head of this product suite taken from 1 km resolution spatially aggregated surface reflectances via the intermediate MODAGAGG process The MODAGAGG process transforms the 250 and or 500 meter atmospherically corrected surface reflectances into a normalized 1 km form upon which Last updated 9 10 2003 Page 2 of 17 FPAR LAI User s Guide Terra MODIS Land Team all our biophysical products are based The high level flow of MODIS biophysical land product suite relationships are illustrated in Figure 1 below MODIS Biophysical Product Suite Linkages 1 Km MODIS Surface Reflectances FPAR LAI PSN via 8 day Composite 8 day composite MODAGAGG MOD15A2 MOD17A2 PSN NPP Daily Intermediate MOD17A1 FPAR LAI Daily Intermediate MOD15A1 Annual NPP MOD17A3 The LAI and FPAR as ESDT MOD15A2 products provide global LAI and FPAR fields retrieved from atmospherically corrected Bidirectional Reflectance Factors MOD 09 Surface Reflectance Product using up to 7 spectral bands 648 nm 858 mn 470 nm 555 nm 1240 nm and 2130 nm The resolution of the data is 1 km and the temporal frequencies are 1 and 8 days Upstream Product Requirements The FPAR LAI algorithm requires the MODIS inputs representing the outputs of various upstream data processing phases Table 1 MOD15A2 FPAR LAI 8 day Inputs Input ESDT Variables Used Aggregated
4. 01 1 Shore 10 2 Freshwater 11 3 Ocean SNOW_ICE 0 0 No snow ice detected 2 1 1 Snow ice were detected AEROSOL 0 0 No or low atmospheric aerosol levels detected 3 1 1 Average or high aerosol levels detected CIRRUS 0 0 No cirrus detected 4 1 1 Cirrus was detected 0 0 1 1 _MASK Clouds WERE detected 5 CLOUD SHADOW 0 0 No cloud shadow detected 6 1 1 Cloud shadow was detected SCF_MASK 0 0 Custom SCF mask EXCLUDE this pixel 7 1 1 Custom SCF mask INLUDE this pixel Last updated 9 10 2003 Page 11 of 17 FPAR LAI User s Guide Terra MODIS Land Team FPAR LAI Quality Control Definition for collection 3 data v3 Binary Variable Bitfield Bits Decimal Description of Bitfield s Values FparLai_QC MODLAND QC 00 0 Best possible 0 1 01 1 OK but not the best 10 2 Not produced due to cloud 11 3 Not produced due to other reasons ALGOR PATH 0 0 Used empirical backup method to retrieve 2 FPAR LAI 1 1 Used main RT method to retrieve FPAR LAI DEAD DETECTOR 0 0 Detectors apparently fine for up to 50 of 3 channels 1 2 1 1 Dead detectors caused gt 50 adjacent detector retrievals CLOUDSTATE 00 0 Significant clouds NOT present clear 4 5 01 1 Significant clouds WERE present 10 2 Mixed cloud present on pixel 11 3 Cloud state not defined assumed clear SCF_QC 00 0 Very best possible 6 7 01 1 Good very usable
5. 1Km MODAGAGG Surface_refl Surface reflectances for surface reflectances channels 1 2 3 4 5 6 7 Note channels in bold are used now and channels in brackets denote potential bands not yet used in production Angles Sensor and solar azimuth and zenith angles deg from each band Global 1Km quarterly MOD12Q1 Land _Cover_Type_3 6 biome land cover land cover definition used for collection 4 In collection 1 3 Land_Cover_Type_1 IGBP classification was used crosswalked to 6 biomes Ancillary data MOD15_ANC_ Radiative transfer coefficient lookup RIx hdf tables backup algorithm lookup tables and output variable properties Last updated 9 10 2003 Page 3 of 17 FPAR LAI User s Guide Terra MODIS Land Team Applications and Derivation Usage Large scale ecosystem modeling is used to simulate a range of ecological responses to changes in climate and chemical composition of the atmosphere including changes in the distribution of terrestrial plant communities across the globe in response to climate changes Leaf area index LAT is a state parameter in all models describing the exchange of fluxes of energy mass e g water and CO2 and momentum between the surface and the planetary boundary layer Analyses of global carbon budget indicate a large terrestrial middle to high latitude sink without which the accumulation of carbon in the atmosphere would be higher than the present rate The problem of accu
6. for multiple solutions the algorithm provides a weighted mean in accordance with the frequency of occurrence of a given value of LAI The dispersion magnitude indicates the reliability of the corresponding LAI value The accuracy of retrievals can not be improved if no additional information are available In order to better describe natural variability of vegetation canopies a three dimensional formulation of the LAI FPAR inverse problem underlies the algorithm Accounting for features specific to the problem of radiative transfer in plant canopies we adapt powerful techniques the Green s function and adjoint formulation for our retrieval algorithm It allowed us to explicitly separate the contribution of canopy ground to the observed reflectances as well as split a complicated three dimensional radiative transfer in vegetation canopies into two independent sub problems namely the radiation field in the Last updated 9 10 2003 Page 4 of 17 FPAR LAI User s Guide Terra MODIS Land Team canopy calculated for a black surface and the radiation field in the same medium with the black surface generated by anisotropic sources located at the canopy bottom Knyazikhin and Marshak 2000 Solutions to these subproblems include information on intrinsic canopy properties This underlies the following parameterization of canopy structure Empirical and theoretical analyses of spectral hemispherical reflectances and transmittances of individual l
7. form follows the HDF conventions as Analyticalpixe scale_factor digitalpixe offset Last updated 9 10 2003 Page 7 of 17 FPAR LAI User s Guide A summary of the SDS appears in the table below Table 3 FPAR LAI ESDT MOD15A2 Summary of Scientific Data Sets Terra MODIS Land Team Variable SDS Datatype Fill value Gain Offset Valid Range Fpar_lkm Uint8 255 0 01 0 0 0 100 Lai Ikm Uint8 255 0 10 0 0 0 100 FparLai QC Uint8 255 N a 0 0 0 254 FparExtra_QC Uint8 255 N a 0 0 0 254 Local Attributes A complete updated description of each MODIS land product is found in the MODIS File Specification for FPAR LAT document With each SDS or gridfield a series of local attributes are included e Scale factor and offset if appropriate e Data range minimum maximum e Fill value e Longname Global Attributes Each FPAR LAI product file contains a considerable amount of extra information that describes various properties of the data The majority of this information is classic metadata describing the geolocation quality and source of the tile and pixel data The standard portion of the metadata written out as part of the EOSDIS Core System is the CoreMetadata 0 and ArchiveMetadata 0 blocks as HDF global file level character attributes Entries in these blocks appear as a series of Object Data Language Parameter Value Language ODL PVL stanza
8. of canopy structure in the spectral variation of transmission and absorption of solar radiation in vegetation canopies IEEE Trans Geosci Remote Sens 39 241 253 Last updated 9 10 2003 Page 15 of 17 FPAR LAI User s Guide Terra MODIS Land Team Privette J L Myneni R B Knyazikhin Y Mukelabai M Roberts G Tian Y Wang W and Leblanc S G 2002 Early spatial and temporal validation of MODIS LAI product in Africa Remote Sens Environ 83 232 243 Shabanov N V Wang Y Buermann W Dong J Hoffman S Smith G Tian Y Knyazikhin Y Myneni R B 2003 Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests Remote Sens Environ 85 4 410 423 Tan B Hu J Huang D Shabanov N V Weiss M Knyazikhin Y amp Myneni R B 2003 Validation of MODIS LAI product in croplands of Alpilles France and Bondville USA Remote Sens Environ in review Tian Y Zhang Y Knyazikhin J Myneni R B Glassy J Dedieu G and Running S W 2000 Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data JEEE Trans Geosci Remote Sens 38 5 2387 2401 Tian Y Wang Y Zhang Y Knyazikhin Y Bogaert J amp Myneni R B 2002a Radiative transfer based scaling of LAI FPAR retrievals from reflectance data of different resolutions Remote Sens Environ 84 143 159 Tian Y Woodcock C E Wang Y Privette J Shabanov N V Zh
9. 0 4 Could not retrieve FparExtra_QC VIS_MODLAND 00 0 Highest overall quality 0 1 01 1 Good quality 10 2 Not produced cloud 11 3 Not able to produce SNOW_ICE 0 0 No snow on pixel 2 1 1 Significant snow detected AEROSOL 0 0 Low or no aerosol on pixel 3 1 1 Med Or High aerosol on pixel CIRRUS 0 0 No cirrus cloud detected 4 1 1 Cirrus clouds present ADJACENT CLOUD 0 0 No adjacent clouds detected 5 1 1 Adjacent clouds detected CLOUDSHADOW 0 0 No cloud shadow detected 6 1 1 Cloud shadow was detected SCF_MASK 0 0 User mask bit un set 7 1 1 User mask bit set Last updated 9 10 2003 Page 13 of 17 FPAR LAI User s Guide Terra MODIS Land Team MOD15A2 bit patterns are parsed from right to left Individual bits within a bitword are read from left to right The following examples illustrate the interpretation of FparLai_QC for the collection 4 3 and 1 Example FparLai_QC 00110000 e Collection 4 interpretation 001 10 0 00 Il d cba Parsed from right to left a MODLAND QC _ 00 Best Possible b DEADDETECTOR _ 0 Detectors apparently fine for up to 50 of channels 1 2 c CLOUDSTATE 10 Mixed cloud present on pixel d SCF_QC 001 Main RT method used with saturation e Collection 3 interpretation 00 11 0 0 00 to e dcb a Parsed from right to left a MODLAND QC _ 00 Best Possible b ALGOR_PATH 0 Used empirical back up method to retr
10. BJECT DataField_1 DataFieldName Fpar_1km DataType DFNT_UINT8 DimList YDim XDim END_OBJECT DataField_1 OBJECT DataField_2 DataFieldName Lai_1km DataType DFNT_UINT8 DimList YDim XDim END_OBJECT DataField_2 OBJECT DataField_3 DataFieldName FparLai_QC DataType DFNT_UINT8 DimList YDim XDim END_OBJECT DataField_3 OBJECT DataField_4 DataFieldName FparExtra_QC DataType DFNT_UINT8 DimList YDim XDim END_OBJECT DataField_ 4 END_GROUP DataField GROUP MergedFields END_GROUP MergedFields END_GROUP GRID_1 END_GROUP GridStructure GROUP PointStructure END_GROUP PointStructure END The SCF adds several other metadata fields to every product file to assist data managers and users alike in tracking the version of the data and other operational issues Each of these are character attributes e UM VERSION Last updated 9 10 2003 Page 9 of 17 FPAR LAI User s Guide Terra MODIS Land Team MOD15A1 BUILD CERT MOD15A1 Fill Value Legend FparLai QC Legend FparExtraQC Legend The FparLai QC legend and FparExtraQC legend are shown in the table above The MOD15A1_ BUILD CERT is a version stamp relating to the ancillary file requirements and the UM_VERSION is the main version stamp that indicates which executable program produced the given tile MODISA1 Fill Value Legend Using the MODIS land cover product MOD12Q1 each 1km pixel is classified according to its status as a land or non land pixel A number of no
11. FPAR LAI User s Guide Terra MODIS Land Team User s Guide FPAR LAI ESDT MOD15A2 8 day Composite NASA MODIS Land Algorithm Ranga Myneni Yuri Knyazikhin Joseph Glassy Petr Votava Nikolay Shabanov Contents Synopsis Acknowledgement Algorithm Description SUMMARY Collection Overview Applications and Derivation Scientific Data Sets File Format of FPAR LAI Products Acquisition Materials and Methods Local Attributes Global Attributes Usage Guidance Quality Assurance Documentation Information Glossary and Acronyms Related Internet URLs References Last updated 9 10 2003 Page l of 17 FPAR LAI User s Guide Terra MODIS Land Team Synopsis This User s Guide describes the Fraction of Photosynthetically Active Radiation FPAR and Leaf Area Index LAI MODIS AM 1 algorithm and its associated 8 day data product archived at a NASA DAAC It is intended to provide both a broad overview and sufficient detail to allow the reader to get started working with the data immediately Acknowledgement The MODIS LAI and FPAR Level 4 algorithms were developed jointly by personnel at Boston University and the University of Montana under contract with the National Aeronautic and Space Administration Algorithm Description The MOD15 Leaf Area Index and Fraction of Photosynthetically Active Radiation absorbed by vegetation are km at launch products provided on a daily and 8 days basis LAI defines an important structural prop
12. but not the best 10 2 Substandard use with caution see other QA for reasons 11 3 NOT PRODUCED AT AL non terrestrial biome FparExtra_QC LANDMASK 00 0 Land 0 1 01 1 Shore 10 2 Freshwater 11 3 Ocean SNOW_ICE 0 0 No snow ice detected 2 1 1 Snow ice were detected AEROSOL 0 0 No or low atmospheric aerosol levels detected 3 1 1 Average or high aerosol levels detected CIRRUS 0 0 NO cirrus detected 4 1 1 Cirrus was detected ADJACENT CLOUD 0 0 NO adjacent clouds detected 5 1 1 Adjacent clouds WERE detected CLOUDSHADOW 0 0 NO cloud shadow detected 6 1 1 Cloud shadow was detected SCF MASK 0 0 Custom SCF mask EXCLUDE this pixel 7 1 1 Custom SCF mask INCLUDE this pixel Last updated 9 10 2003 Page 12 of 17 FPAR LAI User s Guide Terra MODIS Land Team FPAR LAI Quality Control Definition for collection 1 data v1 and v2 Binary Variable Bitfield Bits Decimal Description of Bitfield s Values FparLai_QC MODLAND QC 00 0 Highest overall quality 0 1 01 1 Good quality 10 2 Not produced cloud 11 3 Not able to produce ALGOR_ PATH 0 0 Empirical method used 2 1 1 R T Main method used CLOUDSTATE 00 0 Cloud free 3 4 01 1 Cloud covered pixel 10 2 Mixed clouds present 11 3 Not set assume clear SCF_QC 000 0 Best model result 5 6 7 001 1 Good quality not the best 010 2 Use with caution see other QA 011 3 Poor not recommended 10
13. c nasa gov hdfeos workshop html e http daac gsfc nasa gov CAMPAIGN DOCS MODIS index html MODIS Tile Projection Characteristics All MODIS land products are reprojected on the Integerized Sinusoidal IS 10 degree grid where the globe is tiled for production and distribution purposes into 36 tiles along the east west axis and 18 tiles along the north south axis each ca 1200x1200 kilometers An illustration of the 10 deg grid used in MODIS land production is shown below The color coding is as follows land tiles with land products generated regularly are shown in Green 286 tiles globally land tiles with land products not generated are in Orange ocean tiles are in Blue and tiles with only sea ice product generated are in Pink ae 14 Baao in mhar ee 16 i EHEH a Scientific Data Sets The FPAR LAI Level 4 MODIS land product files each contain 4 scientific data sets SDSs output as 2 dimensional HDFEOS gridfields of 1200 lines by 1200 samples All fields are produced using the HDF uint8 data type which is an unsigned 8 bit integer variable whose values may range from 0 255 Biophysical values are stored in their digital form with a scale factor gain and offset which is applied to transform the stored values to their biophysical counterparts for analysis The QC variables are integer measures without a gain or offset The expression used to decode the digital values to their analysis
14. e common to the all MODLAND products and specifies the overall quality of the product Also several bitfields in the MOD15A2 QA are passed thru from the corresponding bitfields of the MODAGAGG surface reflectances product CLOUDSTATE LANDSEA etc The key indicator of retrieval quality of the LAI FPAR product is SCF_QC bitfield Last updated 9 10 2003 Page 10 of 17 FPAR LAI User s Guide Terra MODIS Land Team FPAR LAI Quality Control Definition for collection 4 data v4 INTERNAL CLOUD No clouds detected Binary Variable Bitfield Decimal Description of Bbitfield s Values FparLai_QC MODLAND 00 0 Best possible 0 1 01 1 OK but not the best 10 2 Not produced due to cloud 11 3 Not produced due to other reasons DEAD DETECTOR 0 0 Detectors apparently fine for up to 50 of 2 channels 1 2 1 1 Dead detectors caused gt 50 adjacent detector retrievals CLOUDSTATE 00 0 Significant clouds NOT present clear 3 4 01 1 Significant clouds WERE present 10 2 Mixed cloud present on pixel 11 3 Cloud state not defined assumed clear SCF_QC 000 0 Main RT method used with the best possible 5 6 7 results 001 1 Main RT method used with saturation 010 2 Main RT method failed due to geometry problems empirical method used 011 3 Main RT method failed due to problems other than geometry empirical method used 100 4 Couldn t retrieve pixel FparExtra_QC LANDSEA 00 0 Land 0 1
15. eaf optical properties and solutions of the above mentioned sub problems are stored in the form of Look up Table LUT which then used to routinely model patterns of canopy reflectances as a function of canopy structure and soil type This approach provide convergence of the algorithm that is the more the spectral information and the more accurate this information is the more reliable and accurate the algorithm output will be Wang et al 2001 Special Correction Adjustment Given the set of observed canopy reflectances it may be the case the inverse problem has no solutions A pixel for which the algorithm retrieves a value of LAI and FPAR is termed a retrieved pixel The ratio of the number of retrieved pixels to the total number of vegetated pixels is the retrieval index RI The retrieval index is an important characteristic of algorithm performance and quality of the input data Wang et al 2000 It is a function of uncertainties in the observed and modeled canopy reflectances and number N of spectral bands used Generally the retrieval index increases with increasing uncertainties However the quality of the LAI FPAR product may decrease Uncertainties are input to the algorithm and therefore must be carefully evaluated in order to produce optimal algorithm performance Table 2 presents uncertainties in model and surface reflectance product currently used by the algorithm This information should Last updated 9 10 2003 Page 5 of 17
16. eaves and the vegetation canopy in the case of dark ground indicate that some simple algebraic combinations of leaf and canopy spectral transmittances and reflectances eliminate their dependencies on wavelength through the specification of two canopy specific wavelength independent variables Panferov et al 2001 Shabanov et al 2003 These variables and leaf optical properties drive the short wave energy conservation in vegetation canopies that is partitioning of the incoming radiation between canopy absorption transmission and reflection These canopy specific wavelength independent variables characterize the capacity of the canopy to intercept and transmit solar radiation under two extreme situations namely when individual leaves 1 are completely absorptive and 2 totally reflect and or transmit the incident radiation The interactions of photons with the canopy at red and near infrared spectral bands approximate these extreme situations well One can treat the vegetation canopy as a dynamical system and the canopy spectral interception and transmission as dynamical variables The system has two independent states canopies with totally absorbing and totally scattering leaves Intermediate states are a superposition of these pure states Such an interpretation provides powerful means to accurately specify changes in canopy structure both from ground based measurements and remotely sensed data The variables mentioned above soil patterns l
17. erty of a plant canopy which is the one sided leaf area per unit ground area FPAR measures the proportion of available radiation in the photosynthetically active wavelengths 0 4 to 0 7 mm that a canopy absorbs LAI and FPAR are biophysical variables which describe canopy structure and are related to functional process rates of energy and mass exchange Both LAI and FPAR have been used extensively as satellite derived parameters for calculation of surface photosynthesis evapotranspiration and annual net primary production These products are essential in calculating terrestrial energy carbon water cycle processes and biogeochemistry of vegetation The MODIS LAI FPAR algorithm consists of a main procedure that exploits the spectral information content of MODIS surface reflectances at up to 7 spectral bands A three dimensional formulation of the LAI FPAR inverse problem underlies this procedure Should the main algorithm fail a back up algorithm is triggered to estimate LAI and FPAR using vegetation indices The algorithm requires a land cover classification Therefore the algorithm has interfaces with the MODIS Surface Reflectance Product MODAGAGG and the MODIS Land Cover Product MOD12Q1 Collection Overview The Functional Linkage of the MODIS Biophysical Land Products The MODIS biophysical land products form a tightly coupled functionally linked set of satellite driven models These biophysical products currently include FPAR LAI PSN
18. ieve FPAR LAI c DEADDETECTOR 0 Detectors apparently fine for up to 50 of channels 1 2 d CLOUDSTATE 11 Cloud state not defined assume clear e SCF_ QC 00 Very best possible e Collection 1 interpretation 001 10 0 00 Il d cba Parsed from right to left a MODLAND QC _ 00 Highest overall quality b ALGOR_ PATH 0 Empirical method used c CLOUDSTATE 10 Mixed clouds present d SCF_ QC 001 Good quality not the best Last updated 9 10 2003 Page 14 of 17 FPAR LAI User s Guide Terra MODIS Land Team Document Information Several supporting documents are available for the FPAR LAI product The main theoretical basis of the product is described in the peer reviewed Algorithm Theoretical Basis Document ATBD which may be obtained at the Web site http modland nascom nasa gov TBD URL References Huang D Yang W Tan B Shabanov N V Knyazikhin N V amp Myneni R B 2003 Performance of the MODIS LAI amp FPAR algorithm over grasslands as a function of uncertainties in the MODIS surface reflectance and land cover products Remote Sens Environ in review Knyazikhin Y J V Martonchik D J Diner R B Myneni M M Verstraete B Pinty and N Gobron 1998a Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere corrected MISR data J Geophys Res 103 32239 32256 Knya
19. n terrestrial pixel classes are now carried through in the product data pixels not QA QC pixels when the algorithm could not retrieve a biophysical estimate Note that these are only present in collection 3 and 4 of MOD15A2 product Table 4 FPAR LAI Fill Value Legend Value Description 249 Unclassified 250 Urban built up class 251 Permanent wetlands marshes 252 Perennial snow ice tundra 253 Barren desert or very sparsely vegetated 254 Water ocean or inland 255 Standard _Fillvalue for non computed pixels or pixels outside projection Quality Control Quality control QC measures are produced at both the file containing one MODIS tile and at the pixel level for the MOD15A2 product At the tile level these appear as a set of EOSDIS core system ECS metadata fields At the pixel level quality control information is represented by 2 data layers FparLai_QC and FparExtra_QC in the file with MOD15A2 product Note that the LAI FPAR algorithm is executed irrespective of input quality Therefore user should consult the QC layers of the LAI FPAR product to select reliable retrievals The QC definition was optimized during data reprocessing for the definition of the QC for different versions collection 1 through 4 of the product refer to the tables below page 11 13 Examples of the QC interpretation follow the tables at the page 14 Note in the FparLai_QC the field MODLAND is the standard on
20. os at MODIS spectral bands are parameters responsible for adjustment of the algorithm for data resolution Tian et al 2002a Summary of the Accomplishments during the Definition and Execution Phases of MODIS LAI FPAR Algorithm 1996 2003 Below the key research performed with LAI FPAR algorithm is summarized and corresponding references are given Theoretical basis of the algorithm Knyazikhin et al 1998a b Myneni et al 1997 e Prototyping of the algorithm Tian et al 2000 Zhang et al 2000 e Evaluation of the physics of the algorithm Panferov et al 2001 Shabanov et al 2003 Tian el 2002a Wang et al 2003a e Product diagnostics Myneni et al 2002 Wang et al 2001 Yang et al 2003 Validation of the product Huang et al 2003 Privette et al 2002 Tan et al 2003 Tian et al 2002b Tian et al 2002c Wang et al 2003b File Format of FPAR LAI Products The NASA MODIS biophysical data products of which the FPAR LAI 8 day product is one are all archived in the NASA HDF EOS data format HDF EOS is a derivative data Last updated 9 10 2003 Page 6 of 17 FPAR LAI User s Guide Terra MODIS Land Team format built upon the Hierarchical Data Format HDF pioneered by the National Center for Supercomputer Applications NCSA in University of Illinois Champaign Urbana The NASA HDF EOS group offers a growing body of software tools Several NASA web sites offering new tools are http hdfeos gsf
21. ou L Zhang Y Buuermann W Dong J Veikkanen B Hame T Anderson K Ozdogan M Knyazikhin Y Myneni R B 2002b Multiscale analysis and validation of the MODIS LAI product over Maun Botswana I Uncertainty Assessment Remote Sens Environ 83 414 430 Tian Y Woodcock C E Wang Y Privette J Shabanov N V Zhou L Zhang Y Buuermann W Dong J Veikkanen B Hame T Anderson K Ozdogan M Knyazikhin Y Myneni R B 2002c Multiscale analysis and validation of the MODIS LAI product over Maun Botswana II Sampling Strategy Remote Sens Environ 83 431 441 Wang Y Tian Y Zhang Y El Saleous N Knyazikhin Y Vermote E and Myneni R B 2001 Investigation of product accuracy as a function of input and model uncertainities case study with SeaWiFS and MODIS LAI FPAR Algorithm Remote Sens Environ 78 296 311 Wang Y Buermann W Stenberg P Smolander H Hame T Tian Y Hu J Knyazikhin Y amp Myneni R B 2003a A new parameterization of canopy spectral response to incident solar radiation Case study with hyperspectral data from pine dominant forest Remote Sens Environ 85 3 304 315 Wang Y Woodcock C E Buermann W Stenberg P Voipio P Smolander H Hame T Tian Y Hu J Knyazikhin Y amp Myneni R B 2003b Validation of the MODIS LAI product in coniferous forest of Ruokolahti Finland Remote Sens Environ in review Yang Y Huang
22. rately evaluating the exchange of carbon between the atmosphere and the terrestrial vegetation therefore requires special attention In this context the fraction of photosynthetically active radiation FPAR absorbed by global vegetation is a key state variable in most ecosystem productivity models and in global models of climate hydrology biogeochemestry and ecology Derivation Techniques and Algorithm The inverse problem of retrieving LAI and FPAR from atmospherically corrected Bi directional Reflectance Distribution Function BRDF is formulated as follows Knyazikhin et al 1998a given sun and view directions BRDFs at N spectral bands and uncertainties find LAI and FPAR The algorithm compares observed and modeled canopy reflectances for a suite of canopy structures and soil patterns that represent a range of expected natural conditions All canopy soil patterns for which modeled and observed BRDFs differ by an amount equivalent to or less than the corresponding uncertainty are considered as acceptable solutions FPAR is also calculated for each acceptable solution The mean values of LAI and FPAR averaged over all acceptable solutions and their dispersions are taken as solutions and retrieval uncertainties Knyazikhin et al 1998b Zhang et al 2000 Tian et al 2000 If the inverse problem has a unique solution for a given set of surface reflectances mean LAI coincides with this solution and its dispersion equals zero If it allows
23. s The ECS global file metadata attributes in each MOD15A2 tile are e StructMetadata 0 e CoreMetadata 0 e ArchiveMetaData 0 In addition to these the SCF also writes out several additional file character attributes that are viewable using the common NCSA utility command ncdump h tile hdf as well as being viewable using common HDF EOS visualization tools like HDFLook The HDFEOS data model itself writes a block of geolocation metadata within every file stored as an HDF file level global attribute called StructMetadata 0 Last updated 9 10 2003 Page 8 of 17 FPAR LAI User s Guide Terra MODIS Land Team StructMetadata 0 This tile level metadata block contains all HDFEOS geolocation parameters including the projection corner coordinates for the tile and image dimensions the Global Cartographic Transform Package GCTPv2 x projection type code and others GROUP SwathStructure END_GROUP SwathStructure GROUP GridStructure GROUP GRID_1 GridName MOD_Grid_MOD15A1 XDim 1200 YDim 1200 UpperLeftPointMtrs 0 000000 5559752 598833 LowerRightMtrs 1111950 519767 4447802 079066 Projection GCTP_ISINUS ProjParams 6371007 181000 0 0 0 0 0 0 0 86400 0 1 0 0 SphereCode 1 PixelRegistration HDFE_CENTER GROUP Dimension OBJECT Dimension_1 DimensionName YDim Size 1200 END_OBJECT Dimension_1 OBJECT Dimension_2 DimensionName XDim Size 1200 END_OBJECT Dimension_2 END_GROUP Dimension GROUP DataField O
24. zikhin Y J V Martonchik R B Myneni D J Diner and S W Running 1998b Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data J Geophys Res 103 32257 32275 Knyazikhin Y and Marshak A L 2000 Mathematical aspects of BRDF modeling adjoint problem and Green s function Remote Sens Rev 18 263 280 Marshak A Y Knyazikhin A Davis W Wiscombe and P Pilewskie 2000b Cloud vegetation interaction use of Normalized Difference Cloud Index for estimation of cloud optical thickness Geophys Res Lett 27 1695 1698 Morisette J T Privette J L amp Justice C O 2002 A framework for the validation of MODIS land products Remote Sens Environ 83 77 96 Myneni R B Nemani R R amp Running S W 1997 Algorithm for the estimation of global land cover LAI and FPAR based on radiative transfer models JEEE Trans Geosc Remote Sens 35 1380 1393 Myneni R B Hoffman S Knyazikhin Y Privette J L Glassy J Tian Y Wang Y Song X Zhang Y Smith Y Lotsch A Friedl M Morisette J T Votava P Nemani R R and Running S W 2002 Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data Remote Sens Environ 83 214 231 Panferov O Knyazikhin Y Myneni R B Szarzynski J Engwald S Schnitzler K G and Gravenhorst G 2001 The role
Download Pdf Manuals
Related Search