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Investigation:

ND-01 (Roberts / Barreto / Soares)

LBA Dataset ID:

ND01_PASTURE_SPECTRA

Originator(s):

1. NUMATA, I.
2. ROBERTS, D.A.
3. CHADWICK, O.A.
      4. SCHIMEL, J.P.
5. GALVAO, L.S.
6. SOARES, J.V.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Dataset Abstract:

The spectral properties of vegetation are strongly determined by their biophysical and chemical attributes such as leaf area index (LAI), the amount of live biomass and senesced biomass, moisture content, pigments (e.g., chlorophyll) and spatial arrangement of structures. Deriving meaningful and accurate measures to quantitatively characterize vegetation still remains a challenge in remote sensing. We used a hyperspectral sensor to test its potential to estimate biophysical properties of grazed pastures in Rondonia in the Brazilian Amazon. Using a field spectrometer, ten remotely sensed measurements (i.e., two vegetation indices, four fractions of spectral mixture analysis, and four spectral absorption features) were generated for two grass species, Brachiaria brizantha and Brachiaria decumbens. These measures were compared to above ground biomass, live and senesced biomass, and grass canopy water content.

Beginning Date:

2003-07-19

Ending Date:

2003-08-03

Metadata Last Updated on:

2013-04-11

Data Status:

Archived

Access Constraints:

PUBLIC

Data Center URL:

http://daac.ornl.gov/

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

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):

LBA-ECO ND-01 Reflectance and Biophysical Measures, Grass Pastures: Rondonia, Brazil :  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1154

Documentation/Other Supporting Documents:

LBA-ECO ND-01 Reflectance and Biophysical Measures, Grass Pastures: Rondonia, Brazil :  http://daac.ornl.gov/LBA/guides/ND01_Pasture_Spectra.html

Citation Information - Other Details:

Numata, I., D.A. Roberts, O.A. Chadwick, J.P. Schimel, L.S. Galvao and J.V. Soares. 2013. LBA-ECO ND-01 Reflectance and Biophysical Measures, Grass Pastures: Rondonia, Brazil. Data set. Available on-line (http://daac.ornl.gov) from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. http://dx.doi.org/10.3334/ORNLDAAC/1154

Keywords - Theme:

Parameter Topic Term Source Sensor
BIOMASS BIOSPHERE VEGETATION FIELD INVESTIGATION WEIGHING BALANCE
LITTER CHARACTERISTICS BIOSPHERE VEGETATION INVESTIGATION WEIGHING BALANCE
REFLECTANCE BIOSPHERE VEGETATION FIELD INVESTIGATION SPECTRORADIOMETER

Uncontrolled Theme Keyword(s):  AMAZON, GRASS, HYPERION, SPECTRAL ABSORPTION FEATURES, SPECTRAL MIXTURE ANALYSIS

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
  RONDONIA -8.00000 -15.00000 -60.00000 -65.00000

Related Publication(s):

Numata, I., D.A. Roberts, O.A. Chadwick, J.P. Schimel, L.S. Galvao and J.V. Soares. 2008. Evaluation of hyperspectral data for pasture estimate in the Brazilian Amazon. Remote Sensing of Environment 112: 1569�1583.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Data are available in three files: one ENVI spectral library file with the spectra data accompanied by it's associated header file (.hdr) and one ASCII comma separated file with the individual sampling points listed along with biophysical measurements where collected.

File #1:Pasture_Rondonia_ASD_spectral_library_all

File #2:Pasture_Rondonia_ASD_spectral_library_all.hdr

File #3:Pasture_spectra_biophysical_measurements.csv



Data organization for the ENVI file of spectra values is described in the associated header file as follows:



ENVI

description = {

New spectral library file [Tue Sep 25 11:28:44 2012]}

samples = 2151

lines = 484

bands = 1

header offset = 0

file type = ENVI Spectral Library

data type = 5

interleave = bsq

sensor type = Unknown

byte order = 0

wavelength units = Nanometers

reflectance scale factor = 1.000000

z plot titles = {Wavelength, Value}

band names = {

Spectral Library}

spectra names

wavelength = {350.00000 through 2500.00000)



The csv file with the biophysical measurements is organized as follows:



File name,Pasture_spectra_biophysical_measurements.csv,,,,,,

File date,27-Sep-12,,,,,,

Associated LME file:, ND01_Pasture_spectra,,,,,,

,,,,,,,

Column,Column_heading,Units/format,Explanation,,,,

1,Point_ID,,Point identification: the first two or three letters indicate the farm sampled: the following letter indicates the transect at the farm and the final number the distance along the transect in meters at which the sampling was done.,,,,

2,County,,County within the state of Rondonia in which sampling was done,,,,

3,Date,YYYYMMDD,Sampling date,,,,

4,Species,,Scientific name of the grass species dominant at the sampling point. Bare soil indicates areas with no vegetation; a dead tree was sampled as a representation of non-photosynthetic vegetation (NPV) and a live palm as a representation of green vegetation (GV) ,,,,

5,Biomass_live,g/m2,Live aboveground biomass based on oven dry weights reported in grams per meter squared (g/m2),,,,

6,Biomass_senesced,g/m2,Senesced aboveground biomass based on oven dry weights reported in grams per meter squared (g/m2),,,,

7,Biomass_total,g/m2,Total aboveground biomass calculated as the sum of the previous two columns and reported in grams per meter squared (g/m2),,,,

8,Water_content,g/m2,Water content of the total aboveground biomass reported in grams per meter squared (g/m2),,,,

,,,,,,,

,Missing data are indicated by -9999,,,,,,



Sample data:

Point_ID,County,Date,Species,Biomass_live,Biomass_senesced,Biomass_total,Water_content



ar_a_000,Porto Velho,20030801,Brachiaria brizantha,496.4,221.4,717.8,218.64

ar_a_020,Porto Velho,20030801,Brachiaria brizantha,541.76,188.52,730.28,256.32

ar_a_040,Porto Velho,20030801,Brachiaria brizantha,254.44,100.96,355.4,104.4

...

pr_c_010,Presidente Medici,20030721,Brachiaria brizantha,-9999,-9999,-9999,-9999

pr_c_015,Presidente Medici,20030721,Brachiaria brizantha,-9999,-9999,-9999,-9999

pr_c_020,Presidente Medici,20030721,Brachiaria brizantha,-9999,-9999,-9999,-9999

Data Application and Derivation:

Hyperspectral sensors provide a continuous spectrum which could improve on our current ability to measure biomass using broad band remote sensing.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

Grass reflectance is strongly affected by canopy structural factors including leaf area, leaf orientation and angular distributions, density of reflective or absorptive structures and the spatial arrangement of structures. These factors can vary considerably within and between species.



ASD field of view (FOV) projected on the grass canopy and 50cm by 50 cm plot for grass biophysical measurements did not perfectly match and many times these two data types collected from the same site were not spatially well calibrated. This mis-registration between grass biophysical data and spectral data possibly resulted in poor relationships.



Changes in substrate reflectance beneath the grass canopy including soil and litter altered grass reflectance and were more pronounced for areas with low standing biomass. Depending upon the background, i.e., soil or litter, the resulting reflectance can change dramatically. In the case of B. decumbens, soil background yields a low ligno-cellulose absorption depth value, while the litter background results in a high ligno-cellulose absorption depth value.

Process Description:

Data Acquisition Materials and Methods:

Study site: The state of Rondonia is located in the southwestern Brazilian Amazon, occupying an area between 8 degrees 40 minutes and 15 degrees 40 minures south and 60 degrees 22 minutes to 65 degrees 50 minutes west. Eight ranches were used for this study, distributed in the cities of Porto Velho,

Ariquemes, Ouro Preto, Ji-Parana and Presidente Medici. These ranches are beef and dairy pastures. Soil types are related to geology and topography of this region. Oxisols and Ultisols, both dystrophic soils, are found mostly over the

Precambrian granitoid and meta-supracrustal rocks with predominantly flat topography in the north of the state, while Alfisols are distributed mainly in central of Rondonia to the south, where they coincide with the presence of intrusive basic and ultrabasic rocks with gently rolling topography.



Pasture sampling:

Pasture biophysical, i.e., biomass, water content and canopy height, and spectral measurements were obtained from the eight cattle ranches mentioned before. Within each study site, these measures were taken from 100 m transects placed on areas. In total, fourteen transects were used for grass measurements in this study, out of which nine transects consisted of Brachiaria brizantha, mostly used for beef pasture, and the rest was of Brachiaria decumbens, primarily utilized for dairy pasture



Field spectral measurements:

An Analytical Spectral Device (ASD) full range spectrometer (350 to 2500 nm, Boulder, CO), on loan from the Jet Propulsion Laboratory (JPL), was used for field optical measurements over transects. The ASD measurements were

conducted for all transects. The ASD spectra were collected with a 22 degree field of view (FOV) with a 1 m sensor height above grass canopies. The spectra were collected at 5 m intervals along each transect initially, however for comparative analysis with grass biophysical data, we used only those spectra collected at the same plots, i.e., at every 20 m intervals along the transects,

used for grass biomass sampling. All spectral measurements were collected within 2 h of local solar noon under clear-sky conditions. Five measurements were taken for each grass canopy. These spectra were standardized to spectralon (Labsphere, Inc, North Sutton, NH) measured at approximately 10 minute intervals, and converted into reflectance. Averaged reflectance out of five replicate for each grass canopy was used for the analysis. In total, 68 reflectance spectra, which coincided with grass biophysical samples, were used for comparison with the field grass data. The reflectance data were smoothed by a 3 nanometer window using mean smoothing filter.



Biophysical measurements

After collecting grass spectra, standing biomass and litter on the soil surface were collected using a 50 cm by 50 cm quadrat at 20 m intervals along each 100 m transect gathering six biomass samples per transect, and the standing biomass was separated into live and senesced biomass. To avoid mismatch between ASD FOV and 50 cm by 50 cm quadrat of grass biomass measurements, a reference stack was placed at the center of each measurement plot for biomass clipping after ASD measurements. All grass materials, live, senesced, and litter were weighed soon after clipping and then dried at 70 degrees C for 36 h. Dried grass materials were weighed again in order to calculate grass water content. During this process, some grass materials were damaged or lost and in total 69 grass samples remained for the analysis.

References:

none cited

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