Method of processing MODIS images for Colombia

0 downloads 0 Views 1MB Size Report
ABSTRACT. MODIS images play an important role in land systems analysis, deforestation monitoring, global change prediction and for scientific information for ...
Method of processing MODIS images for Colombia Elizabeth Barona A.a , Ernesto Girona, Kelly L. Feistnerb, John L. Dwyer b Glenn Hymana a

Centro Internacional de Agricultura Tropical CIAT, Cali, Colombia.

b

U.S. Geological Survey - EROS Data Center, Sioux Falls SD, USA.

ABSTRACT MODIS images play an important role in land systems analysis, deforestation monitoring, global change prediction and for scientific information for environmental policy-making. Vegetation indices are designed to provide a consistent comparison of temporal and spatial changes in vegetation as a response to the quantity of photosynthetically-active radiation in a given pixel, the chlorophyll content, leaf area and structural characteristics of plants. The MODIS system has two types of vegetation indices: normalized difference vegetation index (NDVI), sensitive to chlorophyll and the enhanced vegetation index (EVI), focused on plant structural variation such as physiognomy and leaf type and area. How can these images be processed for different institutions and users in Colombia? In a partnership between USGS-EROS Data Center and CIAT, methods were applied to the processing of MODIS images for all of Colombia in the Marco Geocéntrico Nacional de Referencias – Sistema de Referencia Geocéntrico para América del Sur (MAGNA-SIRGAS) projection. The method allowed us to acquire imagery for 23 periods of 16 days each in 2004. The images were developed in the GeoTiff format, compatible with most GIS software. The image products generated include NDVI, EVI, MIR reflectance band #7, EVI Quality, NDVI Quality MODIS mixed cloud, NDVI Quality MODIS Aerosol, MIR reflectance band #7, NIR reflectance band #2, Blue reflectance band #1, NDVI Quality QA and EVI Quality QA, which can used to extract information on clouds, aerosol quality and vegetation indices. An important step is to re-project the images to standard coordinate system for Colombia that is compatible with image processing and GIS software. Colombia recently replaced the Bogotá Datum adopted in 1941 with a modern system compatible with international standards and current technologies. Known as MAGNA-SIRGAS, this system supports the exchange of georeferenced information between users in Colombia. In the case of MODIS images for Colombia, the conversion to a standard national projection system and the creation of a mosaic of seven tiles that cover the entire national territory are key pre-processing steps. We demonstrate methods that can be replicated for different years. The data could be made available for the remote sensing community in Colombia. The EVI improves vegetation monitoring by separating spectral signals of soils and atmosphere from that of vegetation. The combined use of EVI with other indices can be used for modeling crops and climate variability and its effect on harvests. All this information is useful for different communities of experts working in Colombia.

Introduction The purpose of this work is to obtain products for Colombia, that will be used in crop modeling and in turn to estimate the effects of climate variability on yield. The images will be made available on a website using open source tools and groupware. This will permit sharing with the expert community in Colombia and with partners who work in projects monitoring vegetation and climate.

Materials and methods The study area was focused mainly on the Cauca valley (Valle de Cauca) but it also covers of all Colombia and in the future will cover all of South America.

Moderate resolution imaging spectroradiometer (MODIS) includes data from two satellites (MODIS Terra and MODIS Aqua) that take images of the whole surface of the globe every one or two days. These images contain information of high sensitivity radiometry in 36 spectral bands and at three different resolutions, 250 m, 500 m, and 1000 m. The coverage is 10 arc-degrees tiles of the whole globe. For Colombia we selected images with a resolution of 500 m each 16 days according to the Julian calendar for 2004 giving a total of 23 periods. MODIS contains various products that are currently available. This article is mainly focused on the vegetation products at 16 day intervals derived from the normalized difference vegetation index (NDVI), sensitive to chlorophyll and the enhanced vegetation index (EVI). For preprocessing the images in a format compatible with GIS software it was necessary to obtain software code from the US Geological Survey (USGS) (http://LDPAAC.usgs.gov), which are available for different users’ operating systems. In the case of Colombia we used Linux as the operating system because of its capacity to handle large files and because it uses command line instructions, which facilitates batch processing through scripts. The software programs were: a) MODIS Reprojection Tool (MRT) b) MODIS Land Data Operation Product Evaluation (LDOPE) c) MODIS Swath Reprojection Tool (MRT Swath) d) MODIS Data Pool Extraction Tool (MODextract) These tools can be installed on the Windows 2000, Windows XP, Linux, SGI IRIX 6.5 and Solarios 2.7 operating systems. The methodology used is based mainly on written code of command line instructions, which allows the execution of each of the programs above. The outputs are images in formats compatible with GIS software and with a coordinate system designed for the whole country. Before initiating the program in Colombia it was necessary to take into account the following requirements: ∗ ∗ ∗ ∗ ∗

Vegetation indices EVI and NDVI Temporal resolution sufficient to understand the progress of the growing season at a spatial resolution of 500 m The year 2004 Coverage for Colombia and the Valle del Cauca re-projected to the MAGNA-SIRGAS coordinate system (Table 1); Output format: GeoTiff Table 1 near here

Once the requirements were defined and the programs installed on the Linux platform, the MODIS images can be downloaded. The MODIS website provides a search engine that permits the user to search the MODIS product for particular areas of interest and to select the resolution of the data and specific dates. Note that products earlier than the current year are available from the USGS at the website http://lpdaac.usgs.gov/main.asp. The download options for data stored in the “Data Pool” can be accessed through an FTP server of the USGS. To give an example, the selected product of interest for Colombia was: “Vegetation Indices 500m” MOD13A, for the whole of the year 2004 and the specific tiles we needed were h09v09, h10v07, h10v08, h10v09, h11v07, h11v08 y h11v09. Figure one shows how these tiles are distributed within a Cartesian coordinates starting in the position (0,0) in the upper left-hand corner and continuing to (35,17) in the bottom right-hand corner. Each “tile” covers 10 arc degrees with rows denoted by the letter “h” and columns by the letter “v” to select the tiles detailed above. Figure 1 near here

The downloaded MODIS data are stored in a compressed format with the extension HDF. The next step is to define the information stored within each file that is needed for the study in question. In the case of Colombia we extracted the following data: ∗ ∗ ∗

500m 16 days NDVI 500m 16 days EVI 500m 16 days NDVI Quality

∗ ∗ ∗ ∗

500m 16 days EVI Quality 500m 16 days red reflectance MODIS Band #1, 620-670 nm 500m 16 days NIR reflectance MODIS Band #2, 841-876 nm 500m 16 days blue reflectance MODIS Band #3, 459-479 nm

∗ 500m 16 days MIR reflectance MODIS Band #7, 2105-2155 nm The programs used to process the data for the required images are controlled by scripts to extract information, generate mosaics and re-project the data. The output data files are in GeoTiff format, so that they can be used for spatial analysis in the different GIS software packages. Figure 2 shows an example of one of the scripts used with the tool MODIS Data Pool Extraction Tool (MODextract), which generates an archive log of the HDF formats that might be used to generate the mosaic for Colombia. The MODIS Swath Reprojection Tool (MRT Swath) generates a mosaic of tiles specified in the archive log created by the script shown in Figure 1. The archive log that contains the tiles corresponding to the study area is used with the instruction mrtmosaic on the command line, for example: /> mrtmosaic –i MODextract.log –o TmpMosaic.hdf –s ‘1 1 0 0 1 1 1 1 0 0 0’ This instruction creates a mosaic from the data NDVI, EVI, red reflectance, NIR reflectance, blue reflectance and MIR reflectance. The values 1 in the instruction parameters indicate the data selected for extraction, while zeros indicate the data that will be skipped in the process. The output data are stored in a new HDF file, not by individual tiles, but as a mosaic for entire area under consideration. Figure 2 near here The MODIS Reprojection Tool (MRT) is used to re-project the data SIN (Sinusoidal) to one of the more common projections, in the case of Colombia to UTM MAGNA-SIRGAS. It is necessary to use a new script to generate each one of the GeoTiff files with the selected parameters. The command line scripts generate GeoTiff files corresponding to EVI, NDVI, NDVI Quality, EVI Quality, red reflectance MODIS Band #1, NIR reflectance MODIS Band #2, blue reflectance MODIS Band # 3, and MIR reflectance MODIS Band #7. Note that the MODIS EVI and NDVI data have additional qualitative information that can also be extracted from the images such as: 0-1

VI Quality (MODLAND Mandatory QA Bits)

2-5

VI Usefulness Index (Indice de utilidad)

6-7

Aerosol Quality

8

Atmosphere (Adjacency Correction)

9

Atmosphere (BRDF Correction)

10

Mixed Clouds

11-12 Land/Water Mask 13

Snow/ice

14

Shadow

15

Compositing Method

These qualitative data may be extracted using the MODIS Land Data Operational Product Evaluation (LDOPE) tools, using SDS commands with 35 parameters for the command line instruction. The processes, especially the MRT Tool, can cause problems by exceeding the size limit on files. To avoid this, one must consider the study areas to be processed by reducing the number of tiles and the extraction parameters. This is especially important for spatial information with resolutions less than 500m.

Results Each HDF-EOS file was re-projected using scripts as described above to generate output files in GeoTiff format with the same names as the input files (but different extensions). The output files correspond to each sixteen day period between 1 January and 31 December 2004. The SDS commands in the LDOPE tool generated masks of cloud and the amount of aerosol, which can be combined with maps of EVI and NDVI. These combined processes were carried out in the ESRI tool of ArcGIS (Figure 3). Figure 3 near here One of the objectives of this work is to distribute the images through a website where users are not only able to access data but as well visualize them in a web mapping tool like MapServer. For this application, the problem of large size of the image files must be eliminated, since this prevents them from being displayed in the common web navigators. The solution was to convert GeoTiff data to JPEG2000 using the GDAL library of MapServer (an OpenSource tool) with kakadu software, which creates images with better resolution and smaller size. All the data were integrated within a collaborative tool and made available to different users through the website http://gismap.ciat.cgiar.org/valle. While this work is in its preliminary stages, it is possible to access some images for the Cauca valley. The images available are for the first sixteen days of each month and are available to whoever wishes to access them.

Conclusions Having a methodology to process MODIS images has added greatly to the value of the different research projects in CIAT’s Land-use project as well as being able to make the data available to whoever needs them. Without the help of the USGS it would have been difficult to generate the maps and mosaics and to extract information on vegetation indices. Our use of the USGS programs often required modifications, depending on the resolution of the data, the size of the data files to be processed and the inherent limitations of the platform used. It was not possible to give more detail in this paper of the scripts we used. Future use of these scripts would benefit from additional documentation on the types of problems that can be encountered. We found that the method has the advantage that it can be replicated easily and at present we are generating data for all of South America. Moreover, thanks to the experience gained in this exercise, CIAT was able to obtain in native format data for the whole of South America for the years 2000 to 2005

(500 DVDs in HDF-EOS format) and for the whole Africa for the years 2000 to 2006 (more than two terabytes of image data).

Acknowledgments Each of the processes was evaluated and carried out by Kelly L. Feistner (USGS) under the supervision of John Dwyer (USGS). This research was carried out as part of a program of visiting scientists from UNEPGRID at the EROS Data Center, Sioux Falls SD. We thank Michelle Anthony and Ashbindu Singh for making the scientific exchange between UNEP and CIAT possible.

References GSFC/NASA (2005). Especificaciones Técnicas MODIS. URL: http://modis.gsfc.nasa.gov/about/specifications.php Huete, A., Justice, C and Leewen, W. (1999). MODIS vegetation index (MOD 13). Algorithm theoretical basis document ATBD13. URL: http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf U.S. Geological Survey, 2006. MODIS Reprojection Tool v3.3a Software. URL: http://edcdaac.usgs.gov/landdaac/tools/modis/index.asp U.S. Geological Survey, 2006. MODIS LDOPE Tools Release 1.4 Software. URL: http://edcdaac.usgs.gov/landdaac/tools/ldope/index.asp U.S. Geological Survey, 2006. MODIS Swath Reprojection Tool v2.1 Software. URL: http://edcdaac.usgs.gov/landdaac/tools/mrtswath/index.asp

Table 1.

Parameters for re-projection on to the MAGNA-SIRGAS projection. Colombia Projection:

Valle del Cauca

Transversal Mercator Parameters:

False_Easting

1000000.000000

1000000.000000

False_Northing:

1000000.000000

1000000.000000

Central_Meridian

-74.077508

-77.077508

Scale_Factor:

0.999600

0.999600

Latitude_of_Origin:

4.596200

4.596200

Figure 1. Cartesian system for selecting tiles in the MODIS product. The area marked in red corresponds to the tiles for Colombia. MOD13Q1.004

#input dataset and version –avg size 125 MB

2004.01.01 2004.12.25

#start date #end data

09,09 10, 07 08 09 11, 07 08 09

#horizontal, vertical grids (09,09) #horizontal, vertical grids (10,07) (10,08) (10,09) #horizontal, vertical grids (11,07) (11,08) (11,09)

Figure 2. Code used to generate the log file for the HDF format.

Figure 3. Example of an EVI map of Colombia and the same image overlain with a mask of cloudiness corresponding to the first 16 days of January, 2004.