GLanCE EVIamp image, acquired over Montrose, Colorado on July 1, 2004.View full-size image
NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Land Cover Mapping and Estimation (GLanCE) annual 30 meter (m) Version 1 data product provides global land cover and land cover change data derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI). These maps provide the user community with land cover type, land cover change, metrics characterizing the magnitude and seasonality of greenness of each pixel, and the magnitude of change. GLanCE data products will be provided using a set of seven continental grids that use Lambert Azimuthal Equal Area projections parameterized to minimize distortion for each continent and are available at 30 m spatial resolution. This dataset is useful for a wide range of applications, including ecosystem, climate, and hydrologic modeling; monitoring the response of terrestrial ecosystems to climate change; carbon accounting; and land management.
The GLanCE data product provides seven layers: the land cover class, the estimated day of year of change, integer identifier for class in previous year, median and amplitude of the Enhanced Vegetation Index (EVI2) in the year, rate of change in EVI2, and the change in EVI2 median from previous year to current year. A low-resolution browse image representing EVI2 amplitude is also available for each granule.
|File Size||~250 MB|
|Temporal Extent||2001-07-01 to 2019-07-01|
|Coordinate System||Lambert Azimuthal Equal Area|
|Datum||World Geodetic System (WGS84)|
|Number of Science Dataset (SDS) Layers||7|
|Columns/Rows||5000 x 5000|
|Pixel Size||30 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|LC||Integer identifier for class in the current year||Class||8-bit unsigned integer||255||N/A||1 to 7||N/A|
|ChgDate||Estimated day of year of change; N/A if no change||Day||16-bit unsigned integer||32767||N/A||1 to 365||N/A|
|PrevClass||Integer identifier for class in previous year, if change has occurred; N/A if no change||Class||8-bit unsigned integer||255||N/A||1 to 7||N/A|
|EVI2med||Median EVI2 in the current year||N/A||16-bit signed integer||32767||N/A||-10000 to 10000||0.0001|
|EVIamp||Amplitude of EVI2 in the current year||N/A||16-bit unsigned integer||32767||N/A||0 to 20000||0.0001|
|EVI2rate||Rate of change in EVI2||N/A||16-bit signed integer||32767||N/A||-20000 to 20000||0.0001|
|EVI2chg||Change in EVI2 median from previous year to current year; N/A if no change in land cover||N/A||16-bit signed integer||32767||N/A||-20000 to 20000||0.0001|
|QA Value||QA Name||Description|
|1||Water||Areas covered with water throughout the year: streams, canals, lakes, reservoirs, and oceans.|
|2||Ice/Snow||Land areas where snow and ice cover is greater than 50% throughout the year.|
|3||Developed||Areas of intensive use; land covered with structures, including any land functionally related to developed/built-up activity.|
|4||Barren/Sparsely Vegetated||Land consists of natural occurrences of soils, sand, or rocks where less than 10% of the area is vegetated.|
|5||Tree Cover||Land where the tree cover is greater than 30%. Note that cleared trees (i.e., clear-cuts) are mapped according to current cover (e.g., barren/sparsely vegetated, shrubs, or grasses).|
|6||Shrublands||Land with less than 30% tree cover, where total vegetation cover exceeds 10% and shrub cover is greater than 10%.|
|7||Herbaceous||Land covered by herbaceous cover. Total vegetation cover exceeds 10%, tree cover is less than 30%, and shrubs comprise less than 10% of the area.|
Quality information for the GLanCE product can be found on the GLanCE website.
• Version 1.0 of the dataset does not include Quality Assurance, Leaf Type, or Leaf Phenology. These layers are populated with fill values. These layers will be included in future releases of the data product.
• EVI2 Science Data Set (SDS) values may be missing, or of lower quality, at years when land cover change occurs. This issue is a by-product of the fact that Continuous Change Detection and Classification (CCDC) does not fit models or provide synthetic reflectance values during short periods of time between time segments.
• The accuracy of mapping results varies by land cover class and geography. Specifically, distinguishing between shrubs and herbaceous cover is challenging at high latitudes and in arid and semi-arid regions. Hence, the accuracy of shrub cover, herbaceous cover, and to some degree bare cover, is lower than for other classes.
• Due to the combined effects of large solar zenith angles, short growing seasons, lower availability of high resolution imagery to support training data, the representation of land cover at land high latitudes in the GLanCE product is lower than in mid latitudes.
• Shadows and large variation in local zenith angles decrease the accuracy of the GLanCE product in regions with complex topography, especially at high latitudes.
• Mapping results may include artifacts from variation in data density in overlap zones between Landsat scenes relative to mapping results in non-overlap zones.
• Regions with low observation density due to cloud cover, especially in the tropics, and/or poor data density (e.g. Alaska, Siberia, West Africa) have lower map quality.
• Artifacts from the Landsat 7 Scan Line Corrector failure are occasionally evident in the GLanCE map product.
• High proportions of missing data in regions with snow and ice at high elevations result in missing data in the GLanCE SDSs.
• The GlanCE data product tends to modestly overpredict developed land cover in arid regions.
• Pixels with low data density (particularly towards the end of the time series) may result in mismatches among the change date and previous land cover class layers. This issue is present in the North America dataset (v001) but may be addressed for the remaining continents.
• Some pixels may present incorrect EVI2 rate values of -32768, due to an error in the computation of predicted EVI2 values. Thus, resultant values may be outside the valid range and in very large, negative, incorrect rate values that exceed the range of the pixel data type. This issue is present in the North America dataset (v001) but will be fixed for the remaining continents.