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Investigation:

LC-22 (DeFries / Shimabukuro)

LBA Dataset ID:

LC22_Ground_Validation_GPS_Points

Originator(s):

1. DeFries-Bajpai, Ruth
2. Shimabukuro, Yosio Edemir
3. Anderson, Liana Oighenstein
4. Espirito-Santo, Fernando Del Bon
5. Hansen, Matthew C.
      6. Jasinski, Ellen W.
7. Latorre, Marcelo Lopes
8. Lima, Andre
9. Morton, Douglas C.

Point(s) of Contact:

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

Dataset Abstract:

This data set includes basic land cover and land use observations in three areas: along roads in and around Brasilia, along the BR-163 corridor in Mato Grosso, and in the state of Rondonia. Geographic coordinates are included as well as dates of observation. Descriptions are simple, intended mainly to identify large features of the landscape in order to match them with remote sensing signatures. Data are given in three Excel spreadsheets, one for each region. These observations were made in June-July 2003 as part of a validation effort for the University of Maryland\'s Vegetation Continuous Fields (VCF) product and to provide ground observations for the comparative assessment of automated deforestation monitoring methods and for the land cover classification being undertaken by this team. Funding for the research was provided by NASA\'s Terrestrial Ecology program.

Beginning Date:

2003-06-24

Ending Date:

2003-07-05

Metadata Last Updated on:

2010-09-16

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 ORNL DAAC:  Search at ORNL DAAC

Citation Information - Other Details:

DeFries, R.S., Y.E. Shimabukuro, M.C. Hansen, D.C. Morton, L.O. Anderson, M.L. Latorre, and E.W. Jasinski. 2008. Field Validation, MODIS Deforestation Detection and LC Classification, July 2003: Land Cover Observations. 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
VEGETATION COVER BIOSPHERE VEGETATION GROUND-BASED OBSERVATION HUMAN OBSERVER

Uncontrolled Theme Keyword(s):  GPS points, agriculture, land cover, land use

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
Brasilia Brasilia area -15.47556 -15.96825 -47.57481 -48.08892
Mato Grosso Mato Grosso area -11.09417 -15.34694 -55.23611 -56.43543
Rondonia Rondonia area -8.78981 -10.84161 -61.75433 -63.84506

Related Publication(s):

Anderson, L.O., Y.E. Shimabukuro, R.S. DeFries, and D. Morton, 2005: Assessment of land cover and land use changes in the Brazilian Amazon using multitemporal fraction images derived from Terra MODIS: Examples from the state of Mato Grosso. IEEE Geoscience and Remote Sensing Letters, 2(3): 315-318

Jasinski, E.W, D.C. Morton, R.S. DeFries, Y.E. Shimabukuro, L.O. Anderson, M.C. Hansen (2005). Physical Landscape Correlates of the Expansion of Mechanized Agriculture in Mato Grosso, Brazil. Earth Interactions (in press).

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:

File structure and contents:



Data are in a single comma-delimited ASCII file: LC22_GPS_points_all.csv



Coordinates are in degrees-minutes-seconds across three columns.

Land cover/land use descriptions are free text.

Records refer to a variety of spatial extents, from a single point to several hundred hectares. Spatial extents are not described in most cases, only coordinates of the location from which each observation was made (typically a point along a road adjacent to the patch of land being described).

Descriptions are simple, intended mainly to identify large features of the landscape in order to match them with remote sensing signatures.



Filename: LC22_GPS_points_all.csv

File date: 08-Jul-2008

Data contact: Doug Morton

LBA Data Set ID: LC22_Ground_Validation_GPS_Points



Column Column Units/format Description

Number Heading

1 Region Study region: Brasilia, Mato Grosso, Rondonia

2 Date mm/dd/yyyy Measurement date

3 GPS_unit GPS operator: Doug, Marcelo, Matt

4 Point ID Point ID

5 Lat_degree_s Latitude degrees (S)

6 Lat_minute_s Latitude minutes (S)

7 Lat_second_s Latitude seconds (S)

8 Lon_degree_w Longitude degrees (W)

9 Lon_minute_w Longitude minutes (W)

10 Lon_second_w Longitude seconds (W)

11 LULC_descriptions Land use / Land cover descriptions: descriptions are simple,

intended mainly to identify large features of the landscape

in order to match them with remote sensing signatures.



Note: Missing values are represented as -9999




Sample data records:

Region,Date,GPS_unit,Point ID,Lat_degree_s,Lat_minute_s,Lat_second_s,Lon_degree_w,Lon_minute_w,Lon_second_w,LULC_description

Brasilia,6/24/2003,Doug,15,15,32,28.8,47,34,29.3,Original gallery forest point

Brasilia,6/24/2003,Doug,17,15,32,29.2,47,34,36.8,SE corner of gallery forest transect at Aguas Emendadas

Brasilia,6/24/2003,Doug,16,15,32,29.2,47,34,37.0,SW corner of gallery forest transect at Aguas Emendadas

Brasilia,6/24/2003,Doug,14,15,32,34.4,47,34,41.7,Car at gallery forest, Aguas Emendadas

Brasilia,6/24/2003,Marcelo,AEmendadas,15,32,34.4,47,34,41.6,Aguas Emendadas: Entrance into gallery forest area. Two transects measured in this area

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 specific locations for comparison with remote sensing products from that same time period, in order to identify and understand certain signatures for use in training or validation of algoriths for deforestation detection and/or land cover classification.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

The files have been reviewed and deemed reasonable, consistent with human observations made at the time.

Process Description:

Data Acquisition Materials and Methods:

These data represent human visual observations in conjunction with readings from GPS units. Free text descriptions of observed landscapes in most cases give viewing direction.

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