[GRASS-SVN] r66623 - in grass-addons/grass7/raster/r.modis: . r.modis.import
svn_grass at osgeo.org
svn_grass at osgeo.org
Tue Oct 27 10:41:32 PDT 2015
Author: lucadelu
Date: 2015-10-27 10:41:32 -0700 (Tue, 27 Oct 2015)
New Revision: 66623
Modified:
grass-addons/grass7/raster/r.modis/r.modis.html
grass-addons/grass7/raster/r.modis/r.modis.import/r.modis.import.html
Log:
r.modis: updated documentation
Modified: grass-addons/grass7/raster/r.modis/r.modis.html
===================================================================
--- grass-addons/grass7/raster/r.modis/r.modis.html 2015-10-27 17:40:48 UTC (rev 66622)
+++ grass-addons/grass7/raster/r.modis/r.modis.html 2015-10-27 17:41:32 UTC (rev 66623)
@@ -1,6 +1,6 @@
<h2>DESCRIPTION</h2>
-The <em>r.modis</em> suite is a toolset to import MODIS satellite data in GRASS GIS.
+The <em>r.modis</em> suite is a toolset to import MODIS satellite data in GRASS GIS.
It uses the <a href="http://pymodis.fem-environment.eu">pyModis</a>
library and the <a
href="https://lpdaac.usgs.gov/lpdaac/tools/modis_reprojection_tool"> MODIS
@@ -12,98 +12,101 @@
included in the <em>r.modis</em> suite.
The suite offers three modules as interface with MODIS data. Each modules
is dedicated to for a specific operation. The module <em>r.modis.download</em>
-is used to download MODIS HDF products from NASA FTP. These files can then
-be imported with <em>r.modis.import</em> which supports import of Level 3
-MODIS products as single image or daily mosaik into GRASS GIS.
+is used to download MODIS HDF products from NASA servers. These files can then
+be imported with <em>r.modis.import</em> which supports import of Level 3
+MODIS products as single image or daily mosaik into GRASS GIS. At this point
+you can create a temporal dataset using <em>t.create</em> and register the maps
+with <em>t.register</em>, to work with temporal framework you have to remember
+to set the flag <em>w</em> during the import with <em>r.modis.import</em>.
<p>
The user can download several MODIS products, by single or multiple tiles and
-also ranges of observation days retrieving data from the related NASA FTP server.
+also ranges of observation days retrieving data from the related NASA servers.
<!--
The suite process Level 2 data using the <em>r.modis.process</em> module.
-->
It imports Level 3 (georeferenced) products either as single image or as daily mosaik.
<h4>Products</h4>
-The products already supported:
+The products already supported:
<ul>
<li><b>Land Surface Temperature daily 1 Km (Terra/Aqua)</b>: product provides per-pixel temperature
and emissivity values in a sequence of swath-based to grid-based global products.
- The MODIS/Terra-Aqua LST/E Daily L3 Global 1 km Grid product (MOD11A1/MYD11A1), is tile-based
+ The MODIS/Terra-Aqua LST/E Daily L3 Global 1 km Grid product (MOD11A1/MYD11A1), is tile-based
and gridded in the Sinusoidal projection, and produced daily at 1 km spatial resolution. </li>
- <li><b>Land Surface Temperature daily 6 Km (Terra/Aqua)</b>: data are composed from the daily
- 1-kilometer LST product (MOD11A1/MYD11A1) and stored on a 1-km Sinusoidal grid as the
+ <li><b>Land Surface Temperature daily 6 Km (Terra/Aqua)</b>: data are composed from the daily
+ 1-kilometer LST product (MOD11A1/MYD11A1) and stored on a 1-km Sinusoidal grid as the
average values of clear-sky LSTs during an 8-day period.<br>
- MOD11A2/MYD11A2 is comprised of daytime and nighttime LSTs, quality assessment,
- observation times, view angles, bits of clear sky days and nights, and
+ MOD11A2/MYD11A2 is comprised of daytime and nighttime LSTs, quality assessment,
+ observation times, view angles, bits of clear sky days and nights, and
emissivities estimated in Bands 31 and 32 from land cover types.</li>
- <li><b>Land Surface Temperature eight day 1 Km (Terra/Aqua)</b>: products provide per-pixel
- temperature and emissivity values in a sequence of swath-based to grid-based
- global products. The MODIS/Terra-Aqua LST/E Daily L3 Global 5 Km Grid
- (Short name: MOD11B1/MYD11B1), is tile-based and gridded in the Sinusoidal projection,
+ <li><b>Land Surface Temperature eight day 1 Km (Terra/Aqua)</b>: products provide per-pixel
+ temperature and emissivity values in a sequence of swath-based to grid-based
+ global products. The MODIS/Terra-Aqua LST/E Daily L3 Global 5 Km Grid
+ (Short name: MOD11B1/MYD11B1), is tile-based and gridded in the Sinusoidal projection,
and produced daily at 5 km spatial resolution.</li>
- <li><b>VI sixteen days 250 m (Terra/Aqua)</b>: Global MODIS vegetation indices are designed
- to provide consistent spatial and temporal comparisons of vegetation conditions.
- Blue, red, and near-infrared reflectances, centered at 469-nanometers,
- 645-nanometers, and 858-nanometers, respectively, are used to determine
+ <li><b>VI sixteen days 250 m (Terra/Aqua)</b>: Global MODIS vegetation indices are designed
+ to provide consistent spatial and temporal comparisons of vegetation conditions.
+ Blue, red, and near-infrared reflectances, centered at 469-nanometers,
+ 645-nanometers, and 858-nanometers, respectively, are used to determine
the MODIS daily vegetation indices.<br>
- The MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's
- Advanced Very High Resolution Radiometer (AVHRR) NDVI products and provides
- continuity for time series historical applications. MODIS also includes a
- new Enhanced Vegetation Index (EVI) that minimizes canopy background variations
- and maintains sensitivity over dense vegetation conditions. The EVI also
- uses the blue band to remove residual atmosphere contamination caused by
- smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are
- computed from atmospherically corrected bi-directional surface reflectances
+ The MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's
+ Advanced Very High Resolution Radiometer (AVHRR) NDVI products and provides
+ continuity for time series historical applications. MODIS also includes a
+ new Enhanced Vegetation Index (EVI) that minimizes canopy background variations
+ and maintains sensitivity over dense vegetation conditions. The EVI also
+ uses the blue band to remove residual atmosphere contamination caused by
+ smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are
+ computed from atmospherically corrected bi-directional surface reflectances
that have been masked for water, clouds, heavy aerosols, and cloud shadows.
- Global MOD13Q1/MYD13Q1 data are provided every 16 days at 250-meter spatial resolution
- as a gridded level-3 product in the Sinusoidal projection. Lacking a 250m
- blue band, the EVI algorithm uses the 500m blue band to correct for residual
+ Global MOD13Q1/MYD13Q1 data are provided every 16 days at 250-meter spatial resolution
+ as a gridded level-3 product in the Sinusoidal projection. Lacking a 250m
+ blue band, the EVI algorithm uses the 500m blue band to correct for residual
atmospheric effects, with negligible spatial artifacts.</li>
- <li><b>VI sixteen days 500 m (Terra/Aqua)</b>: Global MODIS vegetation indices are
- designed to provide consistent spatial and temporal comparisons of vegetation
- conditions. Blue, red, and near-infrared reflectances, centered at
- 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used
+ <li><b>VI sixteen days 500 m (Terra/Aqua)</b>: Global MODIS vegetation indices are
+ designed to provide consistent spatial and temporal comparisons of vegetation
+ conditions. Blue, red, and near-infrared reflectances, centered at
+ 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used
to determine the MODIS daily vegetation indices.<br>
- The MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's
- Advanced Very High Resolution Radiometer (AVHRR) NDVI products provide
- continuity for time series historical applications. MODIS also includes a
- new Enhanced Vegetation Index (EVI) that minimizes canopy background
- variations and maintains sensitivity over dense vegetation conditions.
- The EVI also uses the blue band to remove residual atmosphere contamination
- caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI
- products are computed from atmospherically corrected bi-directional surface
- reflectances that have been masked for water, clouds, heavy aerosols, and
+ The MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's
+ Advanced Very High Resolution Radiometer (AVHRR) NDVI products provide
+ continuity for time series historical applications. MODIS also includes a
+ new Enhanced Vegetation Index (EVI) that minimizes canopy background
+ variations and maintains sensitivity over dense vegetation conditions.
+ The EVI also uses the blue band to remove residual atmosphere contamination
+ caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI
+ products are computed from atmospherically corrected bi-directional surface
+ reflectances that have been masked for water, clouds, heavy aerosols, and
cloud shadows.<br>
- Global MOD13A1/MYD13A1 data are provided every 16 days at 500-meter spatial
- resolution as a gridded level-3 product in the Sinusoidal projection.
- Vegetation indices are used for global monitoring of vegetation conditions
- and are used in products displaying land cover and land cover changes.
- These data may be used as input for modeling global biogeochemical and
- hydrologic processes and global and regional climate. These data also may
- be used for characterizing land surface biophysical properties and processes,
+ Global MOD13A1/MYD13A1 data are provided every 16 days at 500-meter spatial
+ resolution as a gridded level-3 product in the Sinusoidal projection.
+ Vegetation indices are used for global monitoring of vegetation conditions
+ and are used in products displaying land cover and land cover changes.
+ These data may be used as input for modeling global biogeochemical and
+ hydrologic processes and global and regional climate. These data also may
+ be used for characterizing land surface biophysical properties and processes,
including primary production and land cover conversion.</li>
- <li><b>Snow eight days 500 m (Terra/Aqua)</b>: The MOD10A2 and MYD10A2 products
+ <li><b>Snow eight days 500 m (Terra/Aqua)</b>: The MOD10A2 and MYD10A2 products
are composites of eight days of snow maps in the sinusoidal grid.
- An eight-day compositing period was chosen because that is the exact ground
- track repeat period of the Terra and Aqua platforms. Snow cover over eight
- days is mapped as maximum snow extent in one SDS and as a chronology of
- observations in the other SDS. Eight-day periods begin on the first day of
- the year and extend into the next year. The product can be produced with
- two to eight days of input. There may not always be eight days of input,
- because of various reasons, so the user should check the attributes to
- determine on what days observations were obtained. See the validation webpage
+ An eight-day compositing period was chosen because that is the exact ground
+ track repeat period of the Terra and Aqua platforms. Snow cover over eight
+ days is mapped as maximum snow extent in one SDS and as a chronology of
+ observations in the other SDS. Eight-day periods begin on the first day of
+ the year and extend into the next year. The product can be produced with
+ two to eight days of input. There may not always be eight days of input,
+ because of various reasons, so the user should check the attributes to
+ determine on what days observations were obtained. See the validation webpage
for details on the validation and validation definitions.</li>
- <li><b>Snow daily 500 m (Terra/Aqua)</b>: MOD10A1 and MYD10A1 are tiles of daily
- snow cover at 500 m spatial resolution. The daily observation selected from
- multiple observations in a MOD10A1 (or MYD10A1) cell is the observation
+ <li><b>Snow daily 500 m (Terra/Aqua)</b>: MOD10A1 and MYD10A1 are tiles of daily
+ snow cover at 500 m spatial resolution. The daily observation selected from
+ multiple observations in a MOD10A1 (or MYD10A1) cell is the observation
acquired nearest nadir and having the greatest coverage of the grid cell.
- The daily MOD10A1 and MYD10A1 snow products are tiles of data gridded in the
- sinusoidal projection. Tiles are approximately 1200 x 1200 km in area. A
- single scientific data set (SDS) of snow cover and a single SDS of QA data
- along with local and global attributes comprise the data product file. The
- daily level 3 snow product is the result of selecting an observation from
- the multiple observations mapped to a cell of the MOD10_L2G (or MYD10_L2G)
- product. See the validation webpage for details on the validation and
+ The daily MOD10A1 and MYD10A1 snow products are tiles of data gridded in the
+ sinusoidal projection. Tiles are approximately 1200 x 1200 km in area. A
+ single scientific data set (SDS) of snow cover and a single SDS of QA data
+ along with local and global attributes comprise the data product file. The
+ daily level 3 snow product is the result of selecting an observation from
+ the multiple observations mapped to a cell of the MOD10_L2G (or MYD10_L2G)
+ product. See the validation webpage for details on the validation and
validation definitions.</li>
</ul>
@@ -121,7 +124,7 @@
<li> <a href="http://modis-snow-ice.gsfc.nasa.gov/">MODIS Snow homepage</a></li>
<li> <a href="https://lpdaac.usgs.gov/lpdaac/products/modis_products_table">MODIS Land products table</a></li>
</ul>
-
+
<h2>AUTHOR</h2>
Luca Delucchi, Google Summer of Code 2011
Modified: grass-addons/grass7/raster/r.modis/r.modis.import/r.modis.import.html
===================================================================
--- grass-addons/grass7/raster/r.modis/r.modis.import/r.modis.import.html 2015-10-27 17:40:48 UTC (rev 66622)
+++ grass-addons/grass7/raster/r.modis/r.modis.import/r.modis.import.html 2015-10-27 17:41:32 UTC (rev 66623)
@@ -5,58 +5,68 @@
<h2>NOTE</h2>
The input file is given as list of full paths to the MODIS HDF files,
-one per line. The input file(s) have to be inside the folder where
+one per line. The input file(s) have to be inside the folder where
the HDF files are stored.
+<b>If <em>mrtpath</em> is not used pyModis will use GDAL to convert HDF
+files to TIF.</b>
<p>
The <em>mrtpath</em> option is the path to the main folder of the
MODIS Reprojection Tools (MRT) binaries, i.e. the folder which contains
the bin/ and the data/ folder since these two folders are essential for
obtaining a successful result.<br>
-It is not possible to use flag <em>--q</em> and the option <em>spectral</em>
-together.
<p>
-<b>Warning</b>:
+<b>Warning</b>:
<ul>
- <li>The module has currently only been tested with Lat/Long locations, but also
+ <li>Using MODIS Reprojection Tools to convert HDF files only
the following projection systems are supported: Lambert Azimuthal Equal Area,
Lambert Conformal Conic, Mercator, Polar Stereographic, Transverse Mercator,
Universal Transverse Mercator</li>
+ <li>Using GDAL you can manage all the projection systems supported by Proj4</li>
</ul>
<h2>EXAMPLES</h2>
-Import a single file with the default subset with QA layer analysis to remove bad pixels:
+Import a single file with the all the subsets with QA layer analysis to
+remove bad pixels using GDAL:
<div class="code"><pre>
-r.modis.import dsn=/path/to/file mrtpath=/path/to/mrt
+r.modis.import dsn=/path/to/file
</pre></div>
-Import more files with the default subset with QA layer:
+Import more files with the default subset with QA layer using MRT:
<div class="code"><pre>
r.modis.import filename=/path/to/listfile mrtpath=/path/to/mrt
</pre></div>
-Import more files like daily mosaic with the default subset without QA layer:
+Import more files like daily mosaic with the default subset without QA
+layer check using MRT:
<div class="code"><pre>
-r.modis.import filename=/path/to/listfile mrtpath=/path/to/mrt
+r.modis.import -mq filename=/path/to/listfile mrtpath=/path/to/mrt
</pre></div>
Import a single file with the default subset without QA layer analysis and without
-rescaling the pixel values:
+rescaling the pixel values using GDAL:
<div class="code"><pre>
-r.modis.import -r dsn=/path/to/file mrtpath=/path/to/mrt
+r.modis.import -rq dsn=/path/to/file
</pre></div>
-Import a single file with your own subset of layers (for power user):
+Import a single file with your own subset of layers (for power user) using GDAL:
<div class="code"><pre>
-r.modis.import dsn=/path/to/file mrtpath=/path/to/mrt spectral="( 1 0 1 0 )"
+r.modis.import dsn=/path/to/file spectral="( 1 0 1 0 )"
</pre></div>
-Import more files with your own subset of layers and without QA layer analysis (for power users):
+Import more files with your own subset of layers and without QA layer
+analysis (for power users) using MRT:
<div class="code"><pre>
r.modis.import -q filename=/path/to/listfile mrtpath=/path/to/mrt spectral="( 1 )"
</pre></div>
+Import more files and write the file to be use in <em>t.register</em>
+to create a temporal dataset using GDAL, you specify only a subset:
+<div class="code"><pre>
+r.modis.import -wq filename=/path/to/listfile spectral="( 1 )"
+</pre></div>
+
<h2>SEE ALSO</h2>
<em>
@@ -65,7 +75,7 @@
<!-- <a href="r.modis.process.html">r.modis.process</a>,-->
</em><br>
<a href="https://lpdaac.usgs.gov/lpdaac/tools/modis_reprojection_tool">MODIS Reprojection Tool</a>
-
+
<h2>AUTHOR</h2>
Luca Delucchi, Google Summer of Code 2011
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