Frequently Asked Questions - Land Cover
The MODIS Land Cover Type product is a global land cover classification data layer produced annually from 2001 through 2013 (as of this writing). For each year there are five land cover schemes, developed by different research groups. Data are distributed by the USGS at 500m resolution in standard MODIS grid tiles. These tiles use the sinusoidal projection and cover approximately 1200 x 1200 km (~10° x 10° at the equator). The following USGS site has detailed meta data and download access:
https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
The MODIS Terra + Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid product incorporates the following five different land cover classification schemes, each derived through a supervised decision-tree classification method:
Land Cover Type 1: IGBP global vegetation classification scheme
Land Cover Type 2: University of Maryland (UMD) scheme
Land Cover Type 3: MODIS-derived LAI/fPAR scheme
Land Cover Type 4: MODIS-derived Net Primary Production (NPP) scheme
Land Cover Type 5: Plant Functional Type (PFT) scheme
The five research groups developed their own classification schemes to categorize land cover properties using one year of Terra and Aqua MODIS data. The International Geosphere Biosphere Programme (IGBP) Type 1 land cover scheme identifies 17 land cover classes (0 – 16) which includes 11 natural vegetation classes, 3 developed and mosaicked land classes, and three non-vegetated land classes. Information about all of the data layers, including Quality Control are shown below. Also the categories and class codes for the five classification schemes are listed.
Basic File Information
Classification Schemes 1 - 4
Classification Scheme 5
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., andHuang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment, 114, 168–182.
Obtain the land cover data for the location and year(s) that you are interested in from the USGS site:
https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
Data are distributed in the Hierarchical Data Format (HDF) and each file contains multiple layers of data. While you can open this file directly in ENVI, this will not retain any coordinate information. You should use the MODIS Conversion Tool Kit (MCTK) found under the Toolbox | Extension | MCTK.
Select the HDF file then pick the data layer(s) you are interested in. Unless you plan to mosaic multiple tiles, choose Reprojected Rigorous georeferencing under the Select Output Type section. In the right-most panel that opens select Geographic Lat/Lon and enter 255 for the Background Value to Use. Enter an Output Path and Rootname and click the Process button.
When the data are imported ENVI will not recognize this file as a classified image. You can use the ENVI tools to edit the header file but it will be much simpler to modify this with a text editor. Make a backup copy of the ENVI header file that you have just created, the file with the .HDR file extension. Now open the original header file with a text editor and paste the contents of the IGBP-Class-Info.txt file at the end of the header file. Save the header file then use the ENVI Data Manager to close the file. Reopen the file in ENVI and it will be recognized as a classification image, with the appropriate Class names and colors, and the Data Ignore value will be set to 255. You can use this same IGBP Class file for the University of Maryland Type 2 classification scheme.
If you have already imported these data following the MODIS Land Cover data in ArcGIS FAQ you can simply open the TIF file in ENVI. If you used ArcGIS to reproject the raster from sinusoidal to Geographic then ENVI will recognize the coordinate system.
Obtain the land cover data for the location and year(s) that you are interested in from the USGS site:
https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
Data are distributed in the Hierarchical Data Format (HDF) and each file contains multiple layers of data. Once you have downloaded the MCD12Q1 data for the MODIS tile(s) covering your study area you can open the file in ArcGIS. When you select the HDF file the Subdataset Selection dialog opens. Choose the data layer corresponding to the classification type you want to work with and click OK. There is no need to create a pyramid layer at this time.
The data are displayed as a gray scale image and you cannot adjust the display using the unique land cover class codes. Export this layer as a TIF by right-clicking on the file name then selecting Data | Export Data and selecting the TIFF format when you save the new file. Next you need to build an Attribute Table. Open the Attribute Table for editing and add a new field for the land cover Class names. Enter the Class names for the classification scheme you have selected. These names can be found in the FAQ describing the product.
You should then apply a consistent color scheme to your classification data. Here is an example Color Map designed for the IGBP Type 1 classification layer. Right-click on the link and save the file with a new name MCD12Q1.clr or copy and paste the data into a new file with this name. You can apply this to your TIF by right-clicking on the file in the Table of Contents and selecting Properties | Symbology then click on the Colormap button and import the Color Map. This Color Map can also be used with the Type 2 University of Maryland classification scheme.
These data are in a MODIS sinusoidal projection. You should consider reprojecting the raster dataset to the Geographic WGS84 coordinate system.
The Global Land Cover Characterization (GLCC) dataset is a collection of land cover classification schemes based on AVHRR data from April 1992 through March 1993. These data are available by continent or a single global coverage in either the Interrupted Goode Homolosine projection or in geographic coordinates (latitude/longitude). These data are available at the USGS Earth Explorer site.
You can learn more about the product at the USGS Global Land Cover Characterization site.