Data include aircraft altitude, wind direction, wind speed, air temperature, potential temperature, water mixing ratio, U and V components of wind velocity, static pressure, surface radiative temperature, downwelling and upwelling total radiation, downwelling and upwelling longwave radiation, net radiation, downwelling and upwelling PAR, greenness index, CO2 concentration, O3 concentration, and CH4 concentration.

The Global Inventory Mapping and Modeling (GIMMS) group at NASA/GSFC provided SAFARI 2000 with remotely sensed satellite data products at the site and regional level. These AVHRR data contain two main sets of data: site extracts of SAFARI core sites (Mongu, Etosha, Kasungu, Maun, Skukuza, and Tshane), and regional 15-day composites from sets of single-day images. These AVHRR data contain four main sets of data:1.5 km daily site extracts of SAFARI core sites (2000)1.5 km 15-day composites of SAFARI core sites (1998-2000)1.5 km 15-day composites of the southern African region (Mar, Sept 2000)6 km 15-day composites of the southern African region (1998-2000)The primary data layers for site extracts and regional composites are fire pixel counts and maximum NDVI. The fire product is different for the daily and for the composited products (see readme file) and a fire product is not included in the 1.5 km regional data set. NDVI composite-associated data layers for the regional data sets include land surface temperature, reflectance, solar zenith angle, view zenith angle, and relative azimuth angle. NDVI composite-associated data layers for the site extracts include these same variables as well as brightness temperature, fire mask composite, latitude, and longitude. The data are stored in binary image format files. There is a metadata file for each site and date/compositing period, in ASCII format.

The Near Real Time (NRT) VIIRS Land Surface Temperature and Emissivity 6-Min L2 Swath 375m product with short-name VNP21IMG_NRT, is the same product but at 375m spatial resolution. The VNP21 algorithm is based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature Emissivity Separation (TES) algorithm. This algorithm uses full radiative transfer simulations for the atmospheric correction, and an emissivity model based on the variability in the surface radiance data to dynamically retrieve both LST and spectral emissivity at native pixel resolution. Additional details regarding the methodology are available in the Algorithm Theoretical Basis Document (ATBD) at:

https://viirsland.gsfc.nasa.gov/PDF/VNP21_LSTE_ATBD_v2.1.pdf

and user guide at:

The Near Real Time (NRT) VIIRS Land Surface Temperature and Emissivity 6-Min L2 Swath 375m product with short-name VJ121IMG_NRT, is the same product but at 375m spatial resolution. The VJ121 algorithm is based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature Emissivity Separation (TES) algorithm. This algorithm uses full radiative transfer simulations for the atmospheric correction, and an emissivity model based on the variability in the surface radiance data to dynamically retrieve both LST and spectral emissivity at native pixel resolution. Additional details regarding the methodology are available in the Algorithm Theoretical Basis Document (ATBD) at:

https://viirsland.gsfc.nasa.gov/PDF/VNP21_LSTE_ATBD_v2.1.pdf

and user guide at:

The Near Real Time (NRT) VIIRSLand Surface Temperature and Emissivity 6-Min L2 Swath 750m product (VNP21_NRT) uses a physics-based algorithm to dynamically retrieve both the LST and emissivity simultaneously for the three VIIRS thermal infrared bands M14 (8.55 micrometer), M15 (10.76 micrometer), and M16 (12 micrometer) at a spatial resolution of 750 m at nadir. The VNP21 algorithm is based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature Emissivity Separation (TES) algorithm. This algorithm uses full radiative transfer simulations for the atmospheric correction, and an emissivity model based on the variability in the surface radiance data to dynamically retrieve both LST and spectral emissivity at native pixel resolution. Additional details regarding the methodology are available in the Algorithm Theoretical Basis Document (ATBD) at:

https://viirsland.gsfc.nasa.gov/PDF/VNP21_LSTE_ATBD_v2.1.pdf

and user guide at:

Soil moisture and temperature profile sensors were deployed at flux tower sites in Mongu, Zambia and Skukuza, South Africa. In addition, thermal infrared sensors were deployed to monitor surface temperature at the sites, and soil samples were collected for physical property analysis. A heat-flux plate was also installed at 10 cm depth at the Mongu site. The data cover the period variously from August, 1999 to December, 2001.At the Mongu site, three profiles of soil moisture and temperature were obtained to a maximum depth of 125 cm. These profiles were located approximately 30 meters north of the Mongu flux tower, within the Kataba Local Forest. Surface radiometric temperature was measured by thermal infrared sensors deployed on top of the 30-meter tower and on a tree. At the Skukuza site, two profiles of soil moisture and temperature were obtained to a maximum depth of 40 cm in a Combretum stand. The radiometric temperature of the tree crown and the background surface were monitored by infrared thermocouple sensors deployed on a pole at 2.5 m and 5 m heights. Soil samples were collected at different depths in the vicinity of the soil profiles at each site and were analyzed at CSIR in Pretoria to determine bulk density, texture, and particle size distribution. The data files are stored as ASCII text files, in comma-separated-value (.csv) format. Associated with each data file is a metadata (.txt ) file. Among other information, the metadata files indicate periods of missing data.

A physically-based model, Energy: Surface Towards Atmosphere (ESTA), was used to model and map the energy and water balances of a heterogeneous land surface in a savanna environment on the southern fringe of the Okavango Delta, near Maun, Botswana. ESTA is governed by remotely sensed values of surface temperature, reflection, and vegetation density. Surface reflectance data from the MODIS sensor aboard the Terra satellite were obtained for the Okavango Delta region for September of 2001.

Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water stress, and soil moisture. A daily, day and night, LST data set for continental Africa, including Madagascar, was derived from Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC; 4 km resolution) data for the 6-year lifetime of the NOAA-14 satellite (from 1995 to 2000) using a modified version of the Global Inventory Mapping and Monitoring System (GIMMS) (Tucker et al., 1994). The data were projected into Albers Equal Area and aggregated to 8 km spatial resolution. The data were cloud-filtered with CLAVR-1 algorithm (Stowe et al., 1999). The LST values were estimated with a split-window technique (Ulivieri et al., 1994) that takes advantage of differential absorption of the thermal infrared signal in bands 4 and 5. The emissivity of the surface was generated using a land cover classification map (Hansen et al., 2000) combined with the FAO soil map of Africa (FAO-UNESCO, 1977) and additional maps of tree, herbaceous, and bare soil percent cover (DeFries et al., 2000). Collateral products include cloud mask, time-of-scan, latitude and longitude, and land/water mask files.The data are in flat binary files. Each data file contains 1152 columns and 1152 rows, in signed integer format (2 bytes), with 8 km by 8 km spatial resolution. A unique map exists for each day and each night of the 6-year NOAA-14 lifetime. The data are best used to infer broad temporal and spatial trends rather than pixel-by-pixel values.

These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to determine the accuracy of the moderate resolution MODIS active fire product. Our main objective was to develop a methodology to use ASTER data for quantitative evaluation of the MODIS active fire product and to apply it to fires in Southern Africa during the 2001 burning season. We utilize 18 ASTER scenes distributed throughout Southern Africa covering the time period 5 August 2001 to 6 October 2001.

The VNP09_NRT is a Near Real Time (NRT) S-NPP/VIIRS 375 m, 750 m Atmospherically Corrected Surface Reflectance product. The NPP/VIIRS surface reflectance products are estimates of surface reflectance in each of the VIIRS reflective bands I1-I3, M1-M5, M7, M8, M10, and M11. The VNP09 Level-2 surface reflectance product contains approximately 6 minutes' worth of data. Surface reflectance for each moderate-resolution (750m) or imagery-resolution (375m) pixel is retrieved separately for the Level-2 products.

Surface reflectance is obtained by adjusting top-of-atmosphere reflectance to compensate for atmospheric effects. Corrections are made for the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. The inputs to the surface reflectance algorithm include top-of-atmosphere reflectance for the VIIRS visible bands (VNP02MOD, VNP02IMG), the VIIRS cloud mask and aerosol product (NPP-CMIP_L2), aerosol optical thickness (NPP_VAOTIP_L2, NPP_VAMIP_L2), and atmospheric data obtained from a reanalysis (surface pressure, atmospheric precipitable water, and ozone concentration).

All surface reflectance products are produced for daytime conditions only. The product is produced under all atmospheric conditions except for night and oceans. Pixels when not produced are replaced by fill values in the Level-2 and Level-2G products.

For more information read Suomi-NPP VIIRS Surface Reflectance User's Guide at https://viirsland.gsfc.nasa.gov/PDF/VIIRS_Surf_Refl_UserGuide_v1.3.pdf

or

visit VIIRS Land website at https://viirsland.gsfc.nasa.gov/index.html