Global 1Km Land Cover - UMD LegendEntry ID: geodata_1377
Abstract: AVHRR data were resampled to a spatial resolution of one by one degree and used to carry out a conventional, supervised classification of global land cover. Classifications have also proceeded at a finer spatial resolution of 8km at a continental scale. In addition to describing vegetative cover according to topological schemes, the project has explored methodologies to represent vegetative cover ... more realistically as gradients and mosaics of cover types.
To identify the pixels to be used for training of the 1 km AVHRR Pathfinder data, we collected a total of over 200 high resolution scenes of which we were confident of which cover type occurs. Most of the scenes used were acquired by the Landsat Multispectral Scanner System (MSS), and a few by Landsat Thematic Mapper and the LISS (Linear Imaging Self-Scanning Sensor), These training data provide the basis for carrying out a global land cover classification. They also provide data for validating other land cover classification products. The methodology and Landsat images used for deriving these training data for classification of AVHRR data at 8km resolution can also be applied to 1km AVHRR data and, in the future, MODIS data at 250m and 500m resolution.
For a full description of the data set, please see: Hansen, M., DeFries, R., Townshend, J. R. G. and Sohlberg, R., 2000, Global land cover classification at 1km resolution using a decision tree classifier, International Journal of Remote Sensing. 21: 1331-1365.
Data Set Citation
Dataset Title: Global 1Km Land Cover - UMD Legend
Dataset Release Date: 2000-01-01
Start Date: 1981-01-01Stop Date: 1994-12-31
Latitude Resolution: 1 km
Longitude Resolution: 1 km
Horizontal Resolution Range: 1 km - < 10 km or approximately .01 degree - < .09 degree
ISO Topic Category
Use Constraints Public
Role: DIF AUTHOR
Role: TECHNICAL CONTACT
Email: geo at unepgrid.ch
Extended Metadata Properties
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Creation and Review Dates
DIF Creation Date: 2013-02-21
Last DIF Revision Date: 2016-11-18