BOREAS TE-06 Multiband Vegetation Imager Data Summary A newly developed ground-based canopy imaging system called an MVI was tested and used by the BOREAS TE-06 team to collect measurements of the canopy gap fraction (sky fraction), canopy gap-size distribution (size and frequency of gaps between foliage in canopy), branch architecture, and leaf angle distribution (fraction of leaf area in specific leaf inclination classes assuming azimuthal symmetry). Measurements of the canopy gap-size distribution are used to derive canopy clumping indices that can be used to adjust indirect LAI measurements made in nonrandom forests. These clumping factors will also help to describe the radiation penetration in clumped canopies more accurately by allowing for simple adjustments to Beer's law. Measurements of the above quantities were obtained at BOREAS NSA OJP site in IFC-2 in 1994, at the SSA OA in July 1995, and at the SSA OBS and SSA OA sites in IFC-2 in 1996. Modeling studies were also performed to further validate MVI measurements and to gain a more complete understanding of boreal forest canopy architecture. By using MVI measurements and Monte Carlo simulations, clumping indices as a function of zenith angle were derived for the three main boreal species studied during BOREAS. The analyzed data are stored in tabular ASCII files. Table of Contents * 1 Data Set Overview * 2 Investigator(s) * 3 Theory of Measurements * 4 Equipment * 5 Data Acquisition Methods * 6 Observations * 7 Data Description * 8 Data Organization * 9 Data Manipulations * 10 Errors * 11 Notes * 12 Application of the Data Set * 13 Future Modifications and Plans * 14 Software * 15 Data Access * 16 Output Products and Availability * 17 References * 18 Glossary of Terms * 19 List of Acronyms * 20 Document Information 1. Data Set Overview 1.1 Data Set Identification BOREAS TE-06 Multiband Vegetation Imager Data 1.2 Data Set Introduction A newly developed ground-based canopy imaging system called a Multiband Vegetation Imager (MVI) was tested and used during BOREAS to collect measurements of the canopy gap fraction (sky fraction), canopy gap-size distribution (size and frequency of gaps between foliage in canopy), branch architecture and leaf angle distribution (fraction of leaf area in specific leaf inclination classes assuming azimuthal symmetry). Measurements of the canopy gap-size distribution are used to derive canopy clumping indices that can be used to adjust indirect leaf area index (LAI) measurements made in nonrandom forests. These clumping factors will also help to describe the radiation penetration in clumped canopies more accurately by allowing for simple adjustments to Beer's law. All of these quantities are essential in performing accurate modeling studies of the exchange of carbon dioxide, water, and heat between the boreal forest and the atmosphere. The MVI is the combination of a charge-coupled device (CCD) camera, a two-band filter exchange mechanism (visible 400-620 nm and near-infrared 720-950 nm), a laptop computer and is powered by a DC to AC inverter and sealed lead acid batteries. The MVI is used to capture rapid, successive images of plant canopies in two wavelength bands. The first image is taken in the visible wavelength band, and the second in the near-infrared band. The purpose of using two wavelength bands is to allow for identification of sunlit and shaded LAI, branch area, clouds, and blue sky based upon the camera's resolution (16 bit) and the varying spectral properties that canopy components have in the two wavelength bands being used. By classifying these images into the above categories, the MVI can be used as a tool to help quantify the canopy structure in terms of leaf angle distribution, LAI, sunlit and shaded LAI, branch architecture, and clumping effects (foliage spatial distributions). This approach is different from other canopy imaging systems (such as fisheye photography) because it allows for rapid acquisition of a digitized two-band image pair that can be used in a variety of sky conditions. The entire process of capturing an image pair is on the order of 50 ms (see Chapter 2; Kucharik, 1997). This data set provides values of the zenith canopy gap fraction, indirect LAI and total LAI estimates, branch area visible from below the canopy and the spatial distribution of branches, and canopy clumping indices derived from canopy gap-size distributions (measured toward the canopy zenith) in the canopies of BOReal Ecosytem-Atmosphere Study (BOREAS) Southern Study Area (SSA) Old Black Spruce (OBS), Old Aspen (OA) and Northern Study Area (NSA) Old Jack Pine (OJP). The Multiband Vegetation Imager (MVI) generally measures only a small amount of stem area; thus, stems are considered to be negligible in the total measurement of woody area derived from image data. The canopy gap-size distribution and clumping factors are for scales greater than or equal to the smallest element size the MVI is able to resolve; in conifers, the basic and smallest element size measured by the MVI is a shoot, and in deciduous canopies (aspen), the basic element size is a leaf. An additional clumping factor is needed in conifers to describe the clumping of needles on shoots. The canopy leaf angle distribution for SSA OA was derived from measurements of the light distribution over sunlit leaves coupled with modeling results (Kucharik et al., 1997b). 1.3 Objective/Purpose One purpose of this study was to determine how Beer's law could be adjusted in a simplistic manner so that it could be applied to nonrandom forest canopies. This would allow for indirect LAI measurement biases to be understood and would provide a means to adjust ecological models that use the Beer-Lambert law to describe the penetration of radiation as a function of angle. Furthermore, because many coniferous species are highly efficient at using diffuse light to perform photosynthesis, accurate characterization of the diffuse light environment in canopies is also necessary. Because the same law (Beer's) applies to direct and diffuse radiation, clumping effects as a function of sun angle need to be properly characterized. Detailed canopy architecture information obtained with the MVI would allow for more accurate modeling and scaling studies to be performed for the BOREAS region. The development of the MVI was justified by the need to make measurements of the architecture of plant canopies. Studying plant canopy architecture is important to many fields of research, including ecology, forestry, meteorology, and other agricultural sciences. Leaf angle distribution, sunlit LAI, shaded LAI, and clumping factors are quantities that are important to exchanges of energy, water, and carbon in forests. Many indirect architectural measurements obtained in forests assume that the spatial distribution of foliage elements (wood, leaves, shoots, needles) is random. These assumptions often lead to measurement and modeling errors of clumped forest canopies that are typical of the boreal region and of many other coniferous species around the world. The MVI has the ability to measure the sunlit fraction of LAI with respect to sun zenith angle, and thus the ability to provide essential information for scaling photosynthesis and carbon fixation from the leaf to larger scales. Canopy structure influences many biophysical processes in forests, and virtually all models that attempt to quantify plant-environment interactions, such as effects of climate change on boreal-forest carbon budgets, require the kind of information that is provided by the MVI. An important finding of this study shows that in clumped boreal forest canopies (all boreal species examined in this study exhibit some varying degrees of grouping of foliage at different scales) the transmission of radiation through the canopy can be coupled to clumping indices that are a function of view angle through the canopy. One single clumping index does not accurately describe the foliage distribution as a function of view angle through the canopy. This will be essential in adjusting indirect LAI measurements made using gap fraction inversion techniques that assume a random spatial foliage distribution. Furthermore, multi-angular clumping factors also allow for the Beer-Lambert law to be adjusted in a simple manner so that it can be applied to nonrandom forest canopies. This adjustment will aid in the most accurate modeling of the radiation regime (direct and diffuse) in nonrandom forest canopies (see Kucharik et al., 1997a). By coupling MVI measurements of canopy gap fraction, branch architecture and canopy clumping indices it can also provide an accurate indirect method to determine the canopy hemisurface LAI. This has allowed for theory to be developed to correct indirect LAI measurements obtained with other optical instrumentation that simply measure the canopy gap fraction with the assumption of a random foliage distribution in canopy space. Additionally, MVI measurements made during BOREAS and Monte Carlo simulations of various forest canopy architecture allowed for the derivation of a simple approach that can estimate canopy clumping factors without having detailed information about the canopy gap-size distribution (see Chapter 5; Kucharik, 1997). 1.4 Summary of Parameters and Variables This data set is divided into two sections. The first part contains point location measurements of the zenith gap fraction (fgap(0)), indirect measurements of LAI (Le(0)) based on gap fraction values, hemisurface branch area visible from below the canopy (Be), foliage clumping indices obtained from canopy gap-size distribution measurements made toward the zenith (Omega(0)), and estimates of the total hemisurface LAI (L). The second part contains average values of the quantities of Le(0), L, and Omega(0) for each forest area studied (at some BOREAS sites, more than one general area was measured within the site) and provides estimates of the total hemisurface branch area (B) (no stems) and the fraction of Le(0) that is branch area that blocks gaps in the canopy (fb). These branches are not shaded by leaf area (i.e., needles, shoots, or leaves) and thus bias indirect LAI measurements obtained from gap fraction values. Measurements of fb were made during the middle of the growing season (July) when LAI was highest. 1.5 Discussion The MVI was used to measure canopy gap fraction (LAI), branch architecture, and foliage spatial distributions to characterize spatial variation between species and within species in the boreal region. Furthermore, these key quantities are essential input to models that are used to study the exchange of carbon dioxide, heat, and water vapor between forests and the atmosphere. Measurements were made along transects used by other BOREAS science groups and within allometric plots so that specific comparisons could be performed. Reported data quality is considered excellent except for some branch area measurements reported for NSA OJP that were influenced by forest fires in 1994. Data for NSA OJP are considered adequate, but not of the highest possible quality compared to the other data sets. Some viewed branch area data are missing for several image locations because of a low confidence level in image classification results at all three sites (SSA OA, NSA OJP, SSA OBS). Because the MVI captures image pairs of canopies at a small scale (i.e., meters), some image locations contain little or no canopy overstory, which prevented a clumping factor from being calculated for a few image locations at NSA OJP and SSA OBS. 1.6 Related Data Sets BOREAS RSS-07 LAI, Gap Fraction, and fPAR data. BOREAS TE-18 Landsat TM Physical Classification image of the SSA BOREAS TE-18 Biomass Density Image of the SSA BOREAS TE-18 Landsat TM Physical Classification Image of the NSA 2. Investigators 2.1 Investigator(s) Name and Title Dr. Christopher J. Kucharik Research Associate University of Wisconsin-Madison Department of Soil Science Dr. John M. Norman Professor University of Wisconsin-Madison Department of Soil Science 2.2 Title of Investigation Measurement and Scaling of Carbon Budgets for Contrasting Boreal Forest Species 2.3 Contact Information Contact 1 --------------------------- Dr. Christopher J. Kucharik University of Wisconsin-Madison Dept. of Soil Science Madison, WI (608) 262-0415 (608) 265-2595 (fax) kucharik@bob.soils.wisc.edu Contact 2 --------------------------- Dr. John M. Norman University of Wisconsin-Madison Dept. Of Soil Science Madison, WI (608) 262-4576 (608) 265-2595 (fax) norman@calshp.cals.wisc.edu Contact 3 ------------- Shelaine Curd Raytheon STX Corporation NASA/GSFC Greenbelt, MD (301) 286-2447 (301) 286-2039 (fax) shelaine.curd@gsfc.nasa.gov 3. Theory of Measurements In order to study the exchange of carbon dioxide, heat and water vapor between the atmosphere and a forest, proper characterization of the interception of sunlight is essential because of its coupling to canopy photosynthesis, which controls the assimilation of carbon dioxide and release of H20 back into the atmosphere. The most important factors that influence light transmission in forest canopies are the amount of leaf surface area that intercepts beam radiation and the distribution of foliage elements in canopy space. In many previous studies, the amount of surface area of foliage that is able to exchange CO2 and H2O with the atmosphere has been measured using direct, destructive methods, while the spatial distribution of foliage is typically assumed to be random. Because destructive measurements are generally time consuming and restricted in many areas, new instruments have been developed that can estimate LAI using only light transmission measurements made at various view angles from above or below vegetative canopies. Typically, the Beer-Lambert law is used to invert a value of LAI using these gap fraction measurements. Unfortunately, this technique assumes that the foliage elements in space are randomly distributed. Furthermore, these instruments are unable to distinguish between green or leafy foliage (photosynthetically active) and branches. Thus, the LAI obtained from gap fraction measurement techniques may include the effects of light intercepting branch area in the canopy. Therefore, some estimate of this bias is necessary to adequately adjust indirect measurements. In many conifer stands and all of the boreal species examined in this study, foliage is typically clumped. This phenomenon generally causes indirect leaf area measurements to be underestimated compared to the actual leaf area present. Furthermore, algorithms that are used to calculate sunlit and shaded leaf area fractions as a function of angle (i.e., Beer's law) will also yield inaccurate results if randomness is assumed for a clumped forest. Typically, these algorithms are a part of large-scale models that are used to study the functioning of the entire forest biome. Therefore, corrections must be applied to Beer's law to account for canopy nonrandomness and branch or stem area that intercepts light in forest canopies and biases indirect measurements of LAI. Direct measurements may provide accurate measurements of LAI but are unable to lend any data on the spatial distribution of the various foliage components in the canopy and how they might intercept incoming solar radiation over the course of a day. With the advent of the MVI, it is now possible to characterize canopy foliage distributions, characterize the spatial relationship of photosynthetically active foliage and woody components, and measure canopy gap fraction values. Because the MVI uses two wavelength bands, specific foliage classes (sunlit/shaded LAI, branches, sky, clouds) can be identified at a small scale. Using image processing algorithms, the canopy gap fraction and canopy gap-size distribution can be determined. Using canopy clumping factors derived from gap- size distribution measurements, adjustments to indirect leaf area values can be applied. However, because of image pixel resolution problems, the MVI cannot resolve (measure) individual needles in conifers because they are typically only a few millimeters wide; thus, the clumping index reported is for scales greater than or equal to the smallest measured element size, which is a shoot. An additional clumping factor (within-shoot) is used to characterize the clumping of needles on shoots in coniferous canopies. Additional image processing is able to determine the amount of branch area that intercepts light in the canopy and biases gap fraction measurements used to determine LAI. In aspen, the near- infrared image band is used to study the light distribution present over sunlit leaves in the canopy and is compared with Monte Carlo simulations to provide an estimate of the canopy leaf angle distribution (see Kucharik et al., 1997a, 1997b). 4. Equipment 4.1 Sensor/Instrument Description SpectraSource, Inc., CCD camera with Texas Instruments silicon detector (TC-213b; frame transfer) cooled by Peltier coolers and controlled by a 16-bit adapter card; two-band filter exchange mechanism controlled by solenoid, 24-mm Nikon camera lens with minimal antireflection coatings, laptop computer and docking station (contains control card), tripods, powered by sealed lead acid batteries and DC to AC power inverter; 50-ft. of associated cables; 100- MB Zip Drive used to store image pairs that are 2 MB each. An HP-9000 workstation was used for all image processing work (see Kucharik et al., 1997a for a more detailed instrumentation description). 4.1.1 Collection Environment Data were collected under varied sky conditions, from completely overcast to completely clear. Some data were collected under smoky conditions. At NSA OJP, data were collected under clear to smoky conditions; at SSA OBS under clear to partly cloudy sky conditions; and at SSA OA, in clear to partly cloudy sky conditions. Data were collected when wind speed was minimal (< 5 m/s); however, in some cases, this was not possible, and data quality can be influenced under particularly windy conditions because of slight foliage movements between the visible and near infrared band exposures. The instrument was not operated under rainy conditions or temperatures under 45 F. The camera was pointed toward the canopy zenith positioned at a height of 1.5 m above ground level; each image (band) represents a 5 m x 10 m canopy area in aspen and a 3.5 m x 7 m canopy area in black spruce and jack pine. Each image is 512 x 1024 pixels where 1 pixel represents 1 cm at a distance of 10 m from the camera. The camera lens field-of-view (FOV) is 15 x 30 degrees; thus all digitized image pairs represent canopy areas within 15 degrees of the canopy zenith. All area parameters are expressed on a hemisurface area basis. 4.1.2 Source/Platform The CCD camera was mounted on a tripod at a height of 1.5 m looking upward toward the canopy zenith. 4.1.3 Source/Platform Mission Objectives The overall goal was to capture image pairs of boreal forest canopies and identify the canopy gap fraction, LAI, branch area, and canopy gap-size distribution by partitioning image data into sunlit and shaded foliage pixels, branch pixels, and sky pixels. Theory will be combined with canopy gap-size distribution measurements to obtain canopy clumping indices. 4.1.4 Key Variables Canopy gap fraction Indirect LAI Canopy hemisurface branch area Light intercepting branch area Canopy clumping factors Leaf angle distribution in aspen 4.1.5 Principles of Operation Script language was programmed to control the solenoid and the operation of the camera system so that a two-band image pair (digitized) within 15 degrees of the canopy zenith was obtained in about 50 ms. The exposure time of each band and the delay between exposures was adjusted accordingly within the script language to adjust to changing environmental conditions (light and wind). 4.1.6 Sensor/Instrument Measurement Geometry The camera system was mounted on a tripod at a height of 1.5 m above the ground pointed directly toward the canopy zenith using leveling devices. The solar disk was blocked from the camera lens using an object to shade the lens; image pairs were captured between wind gusts to minimize foliage movements between the visible and near-infrared exposures. Any foliage within 3 m of the ground that interfered with measurement of the overstory was moved so that the camera lens had a clear view of the forest canopy. Each image pair is 512 x 1024 pixels and represents a canopy section that was within 15 degrees of the zenith from the camera location vantage point (24 mm lens has an FOV of 15 x 30 degrees). 4.1.7 Manufacturer of Sensor/Instrument SpectaSource Instruments 31324 Via Colinas, Suite 114 Westlake Village, CA 91362 (818) 707-9035 A filter exchange mechanism was developed by investigators (See Kucharik et al., 1997a). 4.2 Calibration Calibration was necessary for the gain and bias of the silicon detector. The gain was determined in May 1994 using a flat halon plate (1.5 m x 1.5 m) uniformly illuminated under sunny sky conditions (calibration performed outside). Each image pixel's relative response was determined and applied to each image taken with the MVI system. The bias of the silicon detector (dark pixel current) is temperature dependent. The camera was used only when an optimum temperature of 249 K was obtained by running the camera coolers for 15- 30 minutes before data collection. A dark pixel image was typically collected with each data set and was subtracted from each image accordingly. 4.2.1 Specifications Gain calibration is temperature dependent (detector) (see Kucharik et al., 1997a, for graph of calibration). 4.2.1.1 Tolerance None. 4.2.2 Frequency of Calibration Gain calibration was performed at the laboratory in May 1994; dark pixel bias was obtained each day that data were collected. 4.2.3 Other Calibration Information None. 5. Data Acquisition Methods The camera system was mounted on a tripod at a height of 1.5 m above the ground pointed directly toward the canopy zenith using leveling devices. The solar disk was blocked from the camera lens using an object to shade the lens; image pairs were captured between wind gusts to minimize foliage movements between the visible and near-infrared exposures. Any foliage within 3 m of the ground that interfered with measurement of the overstory was moved so that the camera lens had a clear view of the forest canopy. Each image pair is 512 x 1024 pixels and represents a canopy section that was within 15 degrees of the zenith from the camera location vantage point (24-mm lens has a FOV of 15 x 30 degrees). Please refer to the following sources for more complete documentation: Kucharik et al., 1997a; Kucharik et al., 1997b; Kucharik, 1997. 6. Observations 6.1 Data Notes Because smoky conditions existed during Intensive Field Campaign (IFC)-2 1994, some image pairs do not have branch area data because image processing algorithms could not distinguish between leafy foliage and branches or stems. Additional branch classification problems were caused by moss and lichens growing on woody material at NSA OJP and SSA OBS. These missing data values are reported as -999 in the data set. Some image locations at NSA OJP and SSA OBS had little or no foliage present in the camera FOV; this prevented canopy clumping indices from being derived for these image locations denoted by -999 in the data set. 6.2 Field Notes One large bear confronted S.T. Gower during IFC-2 1996 at SSA OBS. 7. Data Description 7.1 Spatial Characteristics 7.1.1 Spatial Coverage Measurement (camera) locations were spaced at each site by 3 m along the ground (position of tripod) so that there was at least 1 m of overlap (between successive images) in the actual canopy area measured. Measurement sites were as follows: NSA OJP flux tower site, Lat/Long: 55.842 N, 98.62 W. Measurements were made within Terrestrial Ecology (TE) 23's plot and along Transect B set up by Remote Sensing Science (RSS) 07. A total of 50+ image pairs, each covering approximately 25 m2 of canopy area, were collected within the plot and along Transect B. Therefore, approximately 1000 m2 of total canopy area was digitized and analyzed at this site. Seven additional image pairs each were collected in one plot of TE-06 without alder (Plot1 NA) and on one plot with alder growing (Plot2Alder). SSA-OBS flux tower site, Lat/Long: 53.987 N, 105.12 W. A total of 30 image pairs were taken along Transect B from 40 m to 120 m away from the flux tower, spaced approximately 3 m apart along the ground. Fifteen image pairs were collected within allometry plot 1 (TE-06), and 15 image pairs were taken within allometry plot 3 (TE-06). Image locations within allometry plots were chosen so that the entire canopy area above the plot was measured. Each image represents a 25 m2 canopy area measured. SSA-OA flux tower site, Lat/Long: 53.629 N, 106.12 W. A total of 30 image pairs were taken along Transect B (RSS-07) from the flux tower to 105 m to the southwest, spaced approximately 3 m apart along the ground (image locations). Ten image pairs were collected to the north of the flux tower from 2 m to 12 m away from the tower underneath the tramway cable system spaced 1 m apart. Fifteen image pairs were taken within allometry plot 4 (TE- 06); image locations were chosen within the plot so that the entire vegetative canopy above the plot could be measured. Each image pair in aspen represents a 50 m2 canopy area (5 m x 10 m). 7.1.2 Spatial Coverage Map Not available. 7.1.3 Spatial Resolution In conifer species (jack pine and black spruce), one image pixel represents approximately 0.6 cm in the canopy; in aspen, one image pixel represents about 1.0 cm in the canopy. Each image in aspen represents a 5 m x 10 m canopy area; for SSA OBS and NSA OJP, each image represents a 3.5 x 7 m canopy sectional area. All canopy areas in each image pair represent the area within 15 degrees of the zenith viewed from the position of the CCD camera 1.5 m above the ground. 7.1.4 Projection Not applicable. 7.1.5 Grid Description Not applicable. 7.2 Temporal Characteristics 7.2.1 Temporal Coverage Images were collected between 8 a.m. and 8 p.m. during summer field campaigns in 1994, 1995, and 1996. Specific dates and times of each measurement are given in the data table. Measurements were made during the middle of the growing season (July) when LAI was highest. 7.2.2 Temporal Coverage Map Site Date NSA OJP (Plot 1-No Alder TE-06) 26-Jul-1994 NSA OJP (Plot 2-Alder TE-06) 26-Jul-1994 NSA OJP (TE-23 plot-Transect B) 29-Jul, 01-Aug-1994 SSA OA (beneath Tram) 02-Jul-1995 SSA OA (Transect B-RSS-07) 14-Jul-1996 SSA OA (Plot 4 TE-06) 14-Jul-1996 SSA OBS(Transect B-RSS-07) 08-Jul-1996 SSA OBS(Plot 1 & 3 TE-06) 09-Jul-1996 7.2.3 Temporal Resolution Measurements were made at each site on multiple occasions but at irregular time intervals. 7.3 Data Characteristics Data characteristics are defined in the companion data definition file (te6mltvg.def). 7.4 Sample Data Record Sample data format shown in the companion data definition file (te6mltvg.def). 8. Data Organization 8.1. Data granularity The Multiband Vegetation Imager Data are contained in one dataset and the mean values are contained in a second dataset. 8.2 Data Format(s) The data files contain a series of numerical and character fields of varying length separated by commas. The character fields are enclosed in single apostrophe marks. Sample data records are shown in the companion data definition file (te6mltvg.def). 9. Data Manipulations 9.1 Formulae Indirect LAI (Le(0)) estimates are derived using canopy gap fraction measurements and Beer's law: fgap(0) = exp[-K(0) Le(0)/cos(0)] (1) where K(0) is the canopy extinction coefficient = 0.5 Total LAI values (L) are derived using Le(0) values and adjustments for canopy nonrandomness (clumping factors - Omega(0)) and estimates of the amount of hemisurface branch area that intercepts light (blocks gaps) in the canopy. L = [Le(0)- b] /Omega(0) (2) where b is the hemisurface branch area that intercepts light in the canopy (not shaded by foliage) and is the within-shoot clumping factor, measured by BOREAS RSS-07 (J.M. Chen, Canadian Centre of Remote Sensing). For a more detailed description, please refer to Kucharik, 1997 or Kucharik et al., 199x. 9.1.1 Derivation Techniques and Algorithms Canopy clumping factors (Omega(0)) were calculated using MVI measurements of the canopy gap-size distribution and theory according to Chen and Cihlar, 1995. Values of L are derived using theory developed as part of C.J. Kucharik's Ph.D. Thesis, University of Wisconsin-Madison, 1997. 9.2 Data Processing Sequence 9.2.1 Processing Steps (1) Images are captured with the camera. (2) Images are corrected for gain-bias of the detector, and visible and near- infrared bands are registered with each other to account for foliage movements between image exposures. (3) An edge enhancement algorithm is applied to each two-band image pair. (4) An image classification algorithm is used (Zhang et al., 1996) to partition foliage pixels (branches, stems, leaves, shoots, needles) from sky pixels so the gap fraction can be determined. (5) Le(0) is calculated. (6) The canopy gap-size distribution is determined; the theory of Chen and Cihlar, 1995 is used to obtain a value of Omega(0). (7) Foliage class in each image is reclassified into sunlit/shaded foliage and branch pixels. (8) Amount of viewed branch area backed by sky (intercepting light) is determined using another computer algorithm. (9) Value of L is determined. 9.2.2 Processing Changes None. 9.3 Calculations 9.3.1 Special Corrections/Adjustments None. 9.3.2 Calculated Variables For aspen (SSA OA), the canopy leaf angle distribution was calculated using MVI measurements of light distribution over sunlit leaves and was compared to Monte Carlo simulations of aspen canopy architecture with various leaf angle distributions (LAD) by implementing a beta distribution. Assuming azimuthal symmetry, the mean leaf angle (MLA) was solved for as being equal to 708 and the two parameters (meu and neu) for the beta distribution were equal to meu=0.56 and neu=2.58. Please refer to either Kucharik, 1997, Chapter 3, or Kucharik et al., 1997b, for complete details and estimates of the sunlit LAI if interested. Canopy clumping factors (Omega(0)) were calculated using MVI measurements of the canopy gap-size distribution and theory according to Chen and Cihlar, 1995. Values of L are derived using theory developed as part of C.J. Kucharik's Ph.D. Thesis, University of Wisconsin-Madison, 1997. Values of LAI, gap fraction, and Fraction of absorbed Photosynthetically Acitve Radiation (FPAR) were measured by RSS-07 (J.M. Chen, Canadian Centre of Remote Sensing) and reported in Chen et al., 1997. 9.4 Graphs and Plots None. 10. Errors 10.1 Sources of Error Possible measurement errors exist from poor image registrations between visible and near-infrared image bands; classification errors are possible because of mixed pixels (i.e., half sky and half foliage); and assessment of branch area has possible errors because of lichens and moss growing on branches, which prevented proper classification of the underlying structure (branch or stem) as being part of the actual value. Generally, all of these errors are likely to result in an error value of 10% in derived values of gap fraction, gap-size distribution, and branch area. 10.2 Quality Assessment 10.2.1 Data Validation by Source Comparisons were performed with model simulations, direct LAI measurements (allometric equations/BOREAS TE-06), and clumping factors obtained from BOREAS RSS-07 (J.M. Chen). 10.2.2 Confidence Level/Accuracy Judgment Data quality is considered very reliable, significant comparisons have been performed as discussed in section 10.2.1, and reasoning for any disagreement has been explained scientifically and agreed upon. 10.2.3 Measurement Error for Parameters There is a possible 10% error with values of indirect hemisurface branch area (Be), fraction of the indirect hemisurface leaf area (fb), the fraction of the indirect hemisurface leaf-area (Le(0)), the indirect hemisurface leaf-area (L) and the zenit canopy clumping factor (Omega(0)) because of possible classification errors and other problems discussed in Section 10.1. 10.2.4 Additional Quality Assessment Results have been examined carefully for bias patterns and outliers. The data set presented is considered preliminary at this time. 10.2.5 Data Verification by Data Center Data were examined for general consistency and clarity. 11. Notes 11.1 Limitations of Data None. 11.2 Known Problems with the Data None. 11.3 Usage Guidance None. 11.4 Other Relevant Information One large bear confronted S.T. Gower during IFC-2 1996 at SSA OBS. Because of the complexity and actual usage of the MVI, any questions regarding specific image processing, data manipulation, or construction of the instrument should be directed to: Dr. Christopher J. Kucharik University of Wisconsin-Madison Department of Soil Science Madison, WI (608) 262-0415 kucharik@bob.soils.wisc.edu The most comprehensive, detailed description of the instrument and how data are derived can be found in Kucharik, 1997 (Ph.D. Thesis, available on microfilm from archives at University of Michigan-Ann Arbor) and Kucharik et al., 1997a. 12. Application of the Data Set The data can be used for the study of plant canopy architecture. 13. Future Modifications and Plans None. 14. Software 14.1 Software Description Some calculations were performed using MS Excel for Windows 5.0 and Spyglass Plot. Image analysis were performed using the principal investigatorsí original algorithms. 14.2 Software Access Contact Dr. Christopher J. Kurcharik (see Section 2.3 or 11.4) if interested. 15. Data Access 15.1 Contact Information Ms. Beth Nelson BOREAS Data Manager NASA GSFC Greenbelt, MD (301) 286-4005 (301) 286-0239 (fax) Elizabeth.Nelson@gsfc.nasa.gov 15.2 Data Center Identification See Section 15.1. 15.3 Procedures for Obtaining Data Users may place requests by telephone, electronic mail, or fax. 15.4 Data Center Status/Plans The TE-06 MVI data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The BOREAS contact at ORNL is: ORNL DAAC User Services Oak Ridge National Laboratory (865) 241-3952 ornldaac@ornl.gov ornl@eos.nasa.gov 16. Output Products and Availability 16.1 Tape Products None. 16.2 Film Products None. 16.3 Other Products Actual MVI raw image pairs in FITS or TIFF format for the various sites are available upon request. Contact Dr. Christopher J. Kurcharik listed in Section 2.3 or 11.4. The data are available in tabular ASCII files. 17. References 17.1 Platform/Sensor/Instrument/Data Processing Documentation None. 17.2 Journal Articles and Study Reports Chen, J.M. and J. Cihlar. 1995. Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods. IEEE Trans. Geosci. Remote Sens., 33: 777-787. Chen, J.M., P.M. Rich, S.T. Gower, J.M. Norman, and S. Plummer, 1997. Leaf area index of boreal forests: Theory, techniques, and measurements. J. Geophys. Res., BOREAS Special Issue. Kucharik, C.J. 1997. Characterizing the radiation regime in nonrandom forest canopies. Ph.D. Thesis, University of Wisconsin-Madison, 308 pp. Kucharik, C.J., J.M. Norman, and S.T. Gower, 1997b. Measurements of leaf orientation, light distribution, and sunlit leaf area in boreal aspen. Submitted to Agricultural and Forest Meteorology. Kucharik, C.J., J.M. Norman, and S.T. Gower, 1998a. Measurements of leaf orientation, light distribution, and sunlit leaf area in a boreal aspen forest. Agricultural and Forest Meteorology 91(1-2): 127-148. Kucharik, C.J., J.M. Norman, and S.T. Gower, 1998b. Measurements of branch area and adjusting leaf area index indirect measurements. Agricultural and Forest Meteorology, 91 (1-2): 69-88. Kucharik, C.J., J.M. Norman, L.M. Murdock, and S.T. Gower. 1997a. Characterizing canopy nonrandomness with a Multiband Vegetation Imager (MVI). J. Geophys. Res., BOREAS Special Issue. Sellers, P. and F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version 1994-3.0, NASA BOREAS Report (EXPLAN 94) Sellers, P. and F. Hall. 1996. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version 1996-2.0, NASA BOREAS Report (EXPLAN 96) Sellers, P. and F. Hall. 1997. BOREAS Overview Paper. JGR Special Issue. Sellers, P. and F. Hall., K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere Study: 1994 Operations. NASA BOREAS Report (OPS DOC 94). Sellers, P. and F. Hall., K.F. Huemmrich. 1997. Boreal Ecosystem-Atmosphere Study: 1996 Operations. NASA BOREAS Report (OPS DOC 96). Sellers, P., F. Hall, H. Margolis, B. Kelly, D. Baldocchi, G. den Hartog, J. Cihlar, M.G. Ryan, B. Goodison, P. Crill, K.J. Ranson, D. Lettenmaier, and D.E. Wickland. 1995. The boreal ecosystem-atmosphere study (BOREAS): an overview and early results from the 1994 field year. Bulletin of the American Meteorological Society. 76(9): 1549-1577. Zhang, T., R. Ramakrishnan, and M. Livny. 1996. BIRCH: An efficient data clustering method for very large databases. In Proc. of ACM SIGMOD International Conf. on Data Management, June 1996, Montreal, Canada. 17.3 Archive/DBMS Usage Documentation None. 18. Glossary of Terms B - Total hemisurface branch area index Be - Indirect hemisurface branch area viewed from below the canopy with the MVI (visible to camera) Fb - Fraction of Le(0) that is composed of branches that block out gaps in the canopy; i.e., are not shaded by other leafy foliage (shoots or leaves) in the canopy fgap(0) - Zenith canopy gap fraction measured with the CCD camera pointed toward the zenith L - Total hemisurface leaf area derived from indirect LAI measurements and adjusted for branches and nonrandom foliage distributions Le(0) - Indirect hemisurface leaf area; includes both woody and leafy foliage components; derived from MVI measurements of fgap(0) Omega(0)- Zenith canopy clumping factor for scales greater than or equal to the smallest element size (shoots or leaves) 19. List of Acronyms ASCII - American Standard Code for Information Interchange BOREAS - BOReal Ecosystem-Atmosphere Study BORIS - BOREAS Information System CCD - Charge-Coupled Device DAAC - Distributed Active Archive Center EOS - Earth Observing System EOSDIS - EOS Data and Information System FOV - Field of View FPAR - Fraction of absorbed Photosynthetically Active Radiation GSFC - Goddard Space Flight Center IFC - Intensive Field Campaign LAD - Leaf Angle Distribution LAI - Leaf Area Index MLA - Mean Leaf Angle MVI - Multiband Vegetation Imager NASA - National Aeronautics and Space Administration NSA - Northern Study Area OA - Old Aspen OBS - Old Black Spruce OJP - Old Jack Pine ORNL - Oak Ridge National Laboratory PANP - Prince Albert National Park RSS - Remote Sensing Science SSA - Southern Study Area TE - Terrestrial Ecology URL - Uniform Resource Locator 20. Document Information 20.1 Document Revision Date Written: 28-May-1997 Last Updated: 04-Aug-1998 20.2 Document Review Date BORIS Review: 23-Jun-1998 Science Review: 24-Jun-1998 20.3 Document ID 20.4 Citation Please contact investigators in section 2.1. 20.5 Document Curator 20.6 Document URL Keywords ------------ Multiband Vegetation Imager leaf area index leaf angle distribution branch architecture canopy nonrandomness foliage clumping gap-size distribution gap fraction leaf area branch area TE06_Multi_Veg_Imager.doc 08/18/98