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Investigation:

LC-22 (DeFries / Shimabukuro)

LBA Dataset ID:

LC22_MODIS_Field_Validation_2004

Originator(s):

1. DeFries-Bajpai, Ruth
2. Shimabukuro, Yosio Edemir
3. Anderson, Liana Oighenstein
4. Coura, Samuel Martins da Costa
5. Espirito-Santo, Fernando Del Bon
6. Hansen, Matthew C.
      7. Jasinski, Ellen W.
8. Latorre, Marcelo Lopes
9. Lima, Andre
10. Morton, Douglas C.
11. Piromal, Rodrigo Sbravatti
12. DeFries-Bajpai, Ruth

Point(s) of Contact:

Morton, Douglas C. (morton@geog.umd.edu)

Dataset Abstract:

This dataset contains field observations and corresponding GPS points, data sets for MODIS deforestation detection in the state of Mato Grosso, Brazil for the period August 2003 to July 2004, and point and polygon samples with corresponding site descriptions.

Beginning Date:

2004-07-14

Ending Date:

2004-07-21

Metadata Last Updated on:

2008-07-08

Data Status:

In Preparation for Archive

Access Constraints:

Public

Data Center URL:

Distribution Contact(s):

LBA-DIS User Services (lba-dis@cptec.inpe.br)

Access Instructions:

Public

Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.
Datafile(s):

Access data via LBA DIS: ftp://lba.cptec.inpe.br/lba_archives/LC/LC-22/2004/:  Search at ORNL DAAC
Access data via ORNL DAAC:  Search at ORNL DAAC

Documentation/Other Supporting Documents:

Data Set User's Guide (Draft):  Search at ORNL DAAC

Citation Information - Other Details:

DeFries, R., Y.E. Shimabukuro, D.C. Morton, L.O. Anderson, and F. del Bon Espirito-Santo. 2008. LBA-ECO LC-22 Field Validation of MODIS Deforestation/Land Cover Detection Products. Data set. Available on-line [http://lba.cptec.inpe.br/] from LBA Data and Information System, National Institute for Space Research (INPE/CPTEC), Cachoeira Paulista, Sao Paulo, Brazil.

Keywords - Theme:

Parameter Topic Term Source Sensor
LAND USE CLASSES LAND SURFACE LAND USE/LAND COVER GPS (GLOBAL POSITIONING SYSTEM SATELLITES) MODIS (MODERATE-RESOLUTION IMAGING SPECTRORADIOMETER)

Uncontrolled Theme Keyword(s):  deforestation, ground-truth, land cover, validation

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
Mato Grosso Sinop -10.96000 -15.65000 -54.00000 -58.25000

Related Publication(s):

Jasinski, E., D. Morton, R. DeFries, Y. Shimabukuro, L. Anderson, and M. Hansen. 2005. Physical Landscape Correlates of the Expansion of Mechanized Agriculture in Mato Grosso, Brazil. Earth Interactions 9(16):1-18.

Morton, D.C., R.S. DeFries, Y.E. Shimabukuro, L.O. Anderson, F. Del Bon Espirito-Santo, M. Hansen, and M. Carroll. 2005. Rapid Assessment of Annual Deforestation in the Brazilian Amazon Using MODIS Data. Earth Interactions 9(8):1-22.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

br163_sample_points_classified.xls



Field and image classification values for a 100 random roadside samples between Sinop and Cuiaba, MT. Samples

were generated by buffering the road vector for BR163 (Cuiaba-Santarem highway) to identify the dataset of

possible sample points visible from the road. These points were numbered, and a random sample was thrown to

identify 100 points in order to examine the accuracy of various map classes. These points correspond to

the point shapefile br163_sample_points_wgs84.shp. Legend identification values are listed in the table, as is a

preliminary estimate of map accuracy for an initial version of the 2002-2003 Mato Grosso land cover classification

based on NDVI and EVI time series.





br163_sample_points_wgs84.shp



Shapefile of 98 randomly selected points along the BR163 between Sinop and Cuiaba, Mato Grosso. Observations for

these points can be found in the table br163_sample_points_classified.xls referenced above. The file is in datum

WGS84, decimal degrees, created in ArcGIS 9.0.





mt_road_intersect_mod13_red161_deforestation_polygons.shp



Shapefile containing potential deforestation polygons derived from MOD13 red reflectance data from composite 161-176

(julian days) 2004. Only polygons that intersect dirt or asphalt roads (coverage from FEMA, 2002) are shown (n=513).

Datum=WGS84, decimal degrees. The subset of polygons that were visited in the field (n=120) are found in a companion

shapefile (120_field_visited_mod13_red161_2004_polygons.shp).





mt_offroad_mod13_red161_deforestation_polygons.shp



Shapefile containing potential deforestation polygons derived from MOD13 red reflectance data from composite 161-176

(julian days) 2004. Shapefile includes only polygons that do not intersect roads in the FEMA 2002 coverage. Some

field-visited polygons were drawn from this sample of potential deforestation. Datum=WGS84, decimal degrees.





120_field_visited_mod13_red161_2004_polygons.shp



Subset of all potential deforestation polygons identified in MOD13 composite 161-177 2004 that were visited in the

field. Field observations for each polygon can be found in the accomponying table (polygon_fieldobs_all.xls).





polygon_fieldobs_all.xls/.dbf



Microsoft Excel table (and .dbf format file) listing the polygon ID, observation notes, observation date, and clearing status for 120

polygons observed during the field campaign. The spatial locations for each observed deforestation polygon are

found in the corresponding shapefile (120_field_visited_mod13_red161_2004_polygons).





central_mt_mod13_red161_points_on_road_wgs84.shp



Sample of all MOD13 250m resolution pixel center points within the forest mask that lie within a 100m buffer of

roads in Mato Grosso. Sample points are futher classified as either forest or deforested for field validation

purposes. A subsample of these points was visited in the field for validation of classification accuracy on a

pixel-by-pixel basis (n=482). Datum=WGS84, decimal degrees.





field_visited_482_points_with_observations_wgs84.shp



Subsample of all MOD13 gridded product pixel center points that fall within 100m of a road in Mato Grosso (FEMA 2002

road coverage) that were observed during the field campaign. Forested (0) or deforested (1) status and date of

observation are noted in the companion Excel table (points_fieldobs_all.xls).





point_fieldobs_all.xls/.dbf



Table listing observations, dates, and agreement between observational teams for each MODIS pixel visited in the field.

Disagreement between observers was 5 percent.





forest_disagree_points_wgs84.shp



Subset of all visited MODIS pixel center points where field and classification results differed. In all cases where

points classified as forest were observed as deforested in the field, pixels contained some subpixel fraction of

deforestation. Stated differently, these pixels lie at the forest/non-forest edge.





gps_track_final.shp



Shapefile of points mapping the areas visited during the field campaign (7-14 to 7-22). The focal area for the campaign

was the transition forest region of central Mato Grosso, and field observations concentrate on the forested areas

between Nova Mutum and Sinop, MT. Datum=WGS84, decimal degrees.





omission_waypoints.xls



Omission of deforestation detections was difficult to estimate in a statistically rigorous fashion. However, the team

did record the size, condition, and location of deforestation areas that were not detected in the MODIS classification

results. These observations are listed in this separate table.





doug_waypoints_final.shp



Other waypoints of interest in addition to the condition and location of new deforestation events were noted during

the field campaign in this separate shapefile and accompanying table description

(doug_7-14_to_7-20_waypoint_descriptions_final.xls/.dbf. The shapefile datum is WGS84, decimal degrees.





doug_7-14_to_7-20_waypoint_descriptions_final.xls/.dbf



Waypoint descriptions that correspond to the shapefile doug_waypoints_final.shp. The table is included in both

Microsoft excel and the more generic .dbf format for greater accessibility.





ruth_gps_points_final.shp



Other waypoints of interest marking boundaries of visited polygons, locations of specific land cover classes, or other

relevant information from the field campaign. The descriptions can also be found in tabular format in file

ruth_waypoint_fieldobs.xls. Datum=WGS84, decimal degrees.





ruth_waypoint_fieldobs.xls



Tabular description of waypoints that are found in the shapefile ruth_gps_points_final.shp. The table is included

in both Microsoft excel and the more generic .dbf format for greater accessibility.

Data Application and Derivation:

These data were collected to serve as validation information for classification of remotely sensed data. Field information and observations describe the ground conditions at particular MODIS 250 m pixels and polygons of new deforestation that can be used to train or validate algorithms for deforestation detection.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

Field observations contain measurements of inter-observer accuracy (e.g., +/- 5% for point observations). In addition, all field observations are used to validate preliminary MODIS-based estimates of annual deforestation. Specific references to quality assessment are given in the datasets, as well as in referenced publications.

Process Description:

Data Acquisition Materials and Methods:

Land cover classifications (e.g., deforestation detections) are derived from MODIS 250 m resolution data. Field observations and records were kept using a Garmin 76s GPS unit. Locational accuracy of GPS point observations is +/- 15 m.

References:

MODIS data can be downloaded from the EDC: http://edcimswww.cr.usgs.gov/pub/imswelcome/



PRODES deforestation data, including remaining forest cover, for the Brazilian Amazon can be downloaded in shapefile or Spring format at: http://www.obt.inpe.br/prodes



Please see related journal citations for relevant pre-processing methodology and related results.

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