Full catalog/MOD21
MOD21·v061·dataset

How hot the land surface gets (Terra, 1 km)

MODIS/Terra Land Surface Temperature/3-Band Emissivity 5-Min L2 1km V061
land NASA LPCLOUD Level 2 active HDF-EOS2
In plain English

What it measures. How warm the land surface looks from space and how efficiently it gives off heat (emissivity in three infrared bands), at 1-km detail, in roughly 5-minute snapshots.

How it's made. Produced daily from Terra MODIS thermal-infrared measurements using a physics-based method that solves for temperature and emissivity together, with extra correction for humid conditions.

How & where you'd use it. Useful for studying land heat, surface materials, drought, and climate; note this version can show occasional unrealistically high temperatures over deserts.

What's measured

LAND SURFACE › SURFACE THERMAL PROPERTIES › LAND SURFACE TEMPERATURELAND SURFACE › SURFACE RADIATIVE PROPERTIES › EMISSIVITY

Coverage & cadence

  • Time span2000-02-24 → ongoing
  • Measured byTerra (MODIS)
  • Processing levelLevel 2
  • Spatial extent-180, -90, 180, 90
  • FormatsHDF-EOS2
  • StatusACTIVE

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

The MOD21 Land Surface Temperature and Emissivity (LST&E) swath data product is produced daily in five minute temporal increments of satellite acquisition. The swath is approximately 2,030 pixels along track and 1,354 pixels per line, at a nadir resolution of 1,000 meters. The MOD21 Land Surface Temperature (LST) algorithm differs from the [MOD11](https://doi.org/10.5067/modis/mod11_l2.061) algorithm in that the MOD21 LST algorithm is based on the ASTER Temperature/Emissivity Separation (TES) technique, whereas the MOD11 uses the split-window technique. The MOD21 TES algorithm uses a physics-based algorithm to dynamically retrieve both LST and spectral emissivity simultaneously from the MODIS thermal infrared bands 29, 31, and 32. The TES algorithm is combined with an improved Water Vapor Scaling (WVS) atmospheric correction scheme to stabilize the retrieval during very warm and humid conditions. Additional details regarding the method used to create this Level 2 (L2) product are available in the Algorithm Theoretical Basis Document (ATBD). Known Issues * Users of MODIS LST products may notice an increase in occurrences of [extreme high temperature outliers](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=117) in the unfiltered MxD21 Version 6 and 6.1 products compared to the heritage MxD11 LST products. This can occur especially over desert regions like the Sahara where undetected cloud and dust can negatively impact both the MxD21 and MxD11 retrieval algorithms. * In the MxD11 LST products, these contaminated pixels are flagged in the algorithm and set to fill values in the output products based on differences in the band 32 and band 31 radiances used in the generalized split window algorithm. In the MxD21 LST products, values for the contaminated pixels are retained in the output products (and may result in overestimated temperatures), and users need to apply Quality Control (QC) filtering and other error analyses for filtering out bad values. High temperature outlier thresholds are not employed in MxD21 since it would potentially remove naturally occurring hot surface targets such as fires and lava flows. * High atmospheric aerosol optical depth (AOD) caused by vast dust outbreaks in the Sahara and other deserts highlighted in the example documentation are the primary reason for high outlier surface temperature values (and corresponding low emissivity values) in the MxD21 LST products. Future versions of the MxD21 product will include a dust flag from the MODIS aerosol product and/or brightness temperature look up tables to filter out contaminated dust pixels. It should be noted that in the MxD11B day/night algorithm products, more advanced cloud filtering is employed in the multi-day products based on a temporal analysis of historical LST over cloudy areas. This may result in more stringent filtering of dust contaminated pixels in these products. * In order to mitigate the impact of dust in the MxD21 V6 and 6.1 products, the science team recommends using a combination of the existing QC bits, emissivity values, and estimated product errors, to confidently remove bad pixels from analysis. For more details, refer to this dust and cloud contamination [example documentation](https://landweb.modaps.eosdis.nasa.gov/data/userguide/MOD21_dust_QC_examples.pdf). * For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Terra&as=61).

Get the data

mod21_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MOD21",
    version="061",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from LPCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.