The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

NASA Technical Reports Server (NTRS)

Huang, Dong; Yang, Wenze; Tan, Bin; Rautiainen, Miina; Zhang, Ping; Hu, Jiannan; Shabanov, Nikolay V.; Linder, Sune; Knyazikhin, Yuri; Myneni, Ranga B.

2006-01-01

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

Intercomparison and validation of MODIS and GLASS leaf area index (LAI) products over mountain areas: A case study in southwestern China

NASA Astrophysics Data System (ADS)

Jin, Huaan; Li, Ainong; Bian, Jinhu; Nan, Xi; Zhao, Wei; Zhang, Zhengjian; Yin, Gaofei

2017-03-01

The validation study of leaf area index (LAI) products over rugged surfaces not only gives additional insights into data quality of LAI products, but deepens understanding of uncertainties regarding land surface process models depended on LAI data over complex terrain. This study evaluated the performance of MODIS and GLASS LAI products using the intercomparison and direct validation methods over southwestern China. The spatio-temporal consistencies, such as the spatial distributions of LAI products and their statistical relationship as a function of topographic indices, time, and vegetation types, respectively, were investigated through intercomparison between MODIS and GLASS products during the period 2011-2013. The accuracies and change ranges of these two products were evaluated against available LAI reference maps over 10 sampling regions which standed for typical vegetation types and topographic gradients in southwestern China. The results show that GLASS LAI exhibits higher percentage of good quality data (i.e. successful retrievals) and smoother temporal profiles than MODIS LAI. The percentage of successful retrievals for MODIS and GLASS is vulnerable to topographic indices, especially to relief amplitude. Besides, the two products do not capture seasonal dynamics of crop, especially in spring over heterogeneously hilly regions. The yearly mean LAI differences between MODIS and GLASS are within ±0.5 for 64.70% of the total retrieval pixels over southwestern China. The spatial distribution of mean differences and temporal profiles of these two products are inclined to be dominated by vegetation types other than topographic indices. The spatial and temporal consistency of these two products is good over most area of grasses/cereal crops; however, it is poor for evergreen broadleaf forest. MODIS presents more reliable change range of LAI than GLASS through comparison with fine resolution reference maps over most of sampling regions. The accuracies of direct

[Tasseled cap triangle (TCT)-leaf area index (LAI)model of rice fields based on PROSAIL model and its application].

PubMed

Li, Ya Ni; Lu, Lei; Liu, Yong

2017-12-01

The tasseled cap triangle (TCT)-leaf area index (LAI) isoline is a model that reflects the distribution of LAI isoline in the spectral space constituted by reflectance of red and near-infrared (NIR) bands, and the LAI retrieval model developed on the basis of this is more accurate than the commonly used statistical relationship models. This study used ground-based measurements of the rice field, validated the applicability of PROSAIL model in simulating canopy reflectance of rice field, and calibrated the input parameters of the model. The ranges of values of PROSAIL input parameters for simulating rice canopy reflectance were determined. Based on this, the TCT-LAI isoline model of rice field was established, and a look-up table (LUT) required in remote sensing retrieval of LAI was developed. Then, the LUT was used for Landsat 8 and WorldView 3 data to retrieve LAI of rice field, respectively. The results showed that the LAI retrieved using the LUT developed from TCT-LAI isoline model had a good linear relationship with the measured LAI R 2 =0.76, RMSE=0.47. Compared with the LAI retrieved from Landsat 8, LAI values retrieved from WorldView 3 va-ried with wider range, and data distribution was more scattered. Resampling the Landsat 8 and WorldView 3 reflectance data to 1 km to retrieve LAI, the result of MODIS LAI product was significantly underestimated compared to that of retrieved LAI.

Deriving Leaf Area Index (LAI) from multiple lidar remote sensing systems

NASA Astrophysics Data System (ADS)

Tang, H.; Dubayah, R.; Zhao, F.

2012-12-01

LAI is an important biophysical variable linking biogeochemical cycles of earth systems. Observations with passive optical remote sensing are plagued by saturation and results from different passive and active sensors are often inconsistent. Recently lidar remote sensing has been applied to derive vertical canopy structure including LAI and its vertical profile. In this research we compare LAI retrievals from three different types of lidar sensors. The study areas include the La Selva Biological Station in Costa Rica and Sierra Nevada Forest in California. We first obtain independent LAI estimates from different lidar systems including airborne lidar (LVIS), spaceborne lidar (GLAS) and ground lidar (Echidna). LAI retrievals are then evaluated between sensors as a function of scale, land cover type and sensor characteristics. We also assess the accuracy of these LAI products against ground measurements. By providing a link between ground observations, ground lidar, aircraft and space-based lidar we hope to demonstrate a path for deriving more accurate estimates of LAI on a global basis, and to provide a more robust means of validating passive optical estimates of this important variable.

Preliminary validation of leaf area index sensor in Huailai

NASA Astrophysics Data System (ADS)

Cai, Erli; Li, Xiuhong; Liu, Qiang; Dou, Baocheng; Chang, Chongyan; Niu, Hailin; Lin, Xingwen; Zhang, Jialin

2015-12-01

Leaf area index (LAI) is a key variable in many land surface models that involve energy and mass exchange between vegetation and the environment. In recent years, extracting vegetation structure parameters from digital photography becomes a widely used indirect method to estimate LAI for its simplicity and ease of use. A Leaf Area Index Sensor (LAIS) system was developed to continuously monitor the growth of crops in several sampling points in Huailai, China. The system applies 3G/WIFI communication technology to remotely collect crop photos in real-time. Then the crop photos are automatically processed and LAI is estimated based on the improved leaf area index of Lang and Xiang (LAILX) algorithm in LAIS. The objective of this study is to primarily verify the LAI estimated from LAIS (Lphoto) through comparing them with the destructive green LAI (Ldest). Ldest was measured across the growing season ntil maximum canopy development while plants are still green. The preliminary verification shows that Lphoto corresponds well with the Ldest (R2=0.975). In general, LAI could be accurately estimated with LAIS and its LAI shows high consistency compared with the destructive green LAI. The continuous LAI measurement obtained from LAIS could be used for the validation of remote sensing LAI products.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial

Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM+ data over a boreal forest.

Treesearch

Mercedes Berterretche; Andrew T. Hudak; Warren B. Cohen; Thomas K. Maiersperger; Stith T. Gower; Jennifer Dungan

2005-01-01

This study compared aspatial and spatial methods of using remote sensing and field data to predict maximum growing season leaf area index (LAI) maps in a boreal forest in Manitoba, Canada. The methods tested were orthogonal regression analysis (reduced major axis, RMA) and two geostatistical techniques: kriging with an external drift (KED) and sequential Gaussian...

Joint Leaf chlorophyll and leaf area index retrieval from Landsat data using a regularized model inversion system

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) and leaf chlorophyll (Chl) content represent key biophysical and biochemical controls on water, energy and carbon exchange processes in the terrestrial biosphere. In combination, LAI and leaf Chl content provide critical information on vegetation density, vitality and photosynt...

Allometric method to estimate leaf area index for row crops

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) is critical for predicting plant metabolism, biomass production, evapotranspiration, and greenhouse gas sequestration, but direct LAI measurements are difficult and labor intensive. Several methods are available to measure LAI indirectly or calculate LAI using allometric method...

Costs of measuring leaf area index of corn

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Hollinger, S. E.

1984-01-01

The magnitude of plant-to-plant variability of leaf area of corn plants selected from uniform plots was examined and four representative methods for measuring leaf area index (LAI) were evaluated. The number of plants required and the relative costs for each sampling method were calculated to detect 10, 20, and 50% differences in LAI using 0.05 and 0.01 tests of significance and a 90% probability of success (beta = 0.1). The natural variability of leaf area per corn plant was nearly 10%. Additional variability or experimental error may be introduced by the measurement technique employed and by nonuniformity within the plot. Direct measurement of leaf area with an electronic area meter had the lowest CV, required that the fewest plants be sampled, but required approximately the same amount of time as the leaf area/weight ratio method to detect comparable differences. Indirect methods based on measurements of length and width of leaves required more plants but less total time than the direct method. Unless the coefficients for converting length and width to area are verified frequently, the indirect methods may be biased. When true differences in LAI among treatments exceed 50% of mean, all four methods are equal. The method of choice depends on the resources available, the differences to be detected, and what additional information, such as leaf weight or stalk weight, is also desired.

Seasonal Dynamics in Leaf Area Index in Intensively Managed Loblolly Pine

Treesearch

Timothy B. Harrington; Jason A. Gatch; Bruce E. Borders

2002-01-01

Leaf area index (LAI; leaf area per ground area) was measured monthly or bimonthly for two years (March 1999 to February 2001) with the LAI-2000 in intensively managed plantations of loblolly pine (Pinus taeda L.) at Eatonton and Waycross GA. Since establishment of the three age classes at each site, the stands have received combinations of complete...

Indirect Field Measurement of Wine-Grape Vineyard Canopy Leaf Area Index

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Pierce, Lars L.; Skiles, J. W. (Technical Monitor)

2002-01-01

Leaf area index (LAI) indirect measurements were made at 12 study plots in California's Napa Valley commercial wine-grape vineyards with a LI-COR LI-2000 Plant Canopy Analyzer (PCA). The plots encompassed different trellis systems, biological varieties, and planting densities. LAI ranged from 0.5 - 2.25 sq m leaf area/ sq m ground area according to direct (defoliation) measurements. Indirect LAI reported by the PCA was significantly related to direct LAI (r(exp 2) = 0.78, p less than 001). However, the PCA tended to underestimate direct LAI by about a factor of two. Narrowing the instrument's conical field of view from 148 deg to 56 deg served to increase readings by approximately 30%. The PCA offers a convenient way to discern relative differences in vineyard canopy density. Calibration by direct measurement (defoliation) is recommended in cases where absolute LAI is desired. Calibration equations provided herein may be inverted to retrieve actual vineyard LAI from PCA readings.

Modeling variability and scale integration of LAI measurements

Treesearch

Kris Nackaerts; Pol Coppin

2000-01-01

Rapid and reliable estimation of leaf area at various scales is important for research on chance detection of leaf area index (LAI) as an indicator of ecosystem condition. It is of utmost importance to know to what extent boundary and illumination conditions, data aggregation method, and sampling scheme influence the relative accuracy of stand-level LAI measurements....

Validation of Leaf Area Index measurements based on the Wireless Sensor Network platform

NASA Astrophysics Data System (ADS)

Song, Q.; Li, X.; Liu, Q.

2017-12-01

The leaf area index (LAI) is one of the important parameters for estimating plant canopy function, which has significance for agricultural analysis such as crop yield estimation and disease evaluation. The quick and accurate access to acquire crop LAI is particularly vital. In the study, LAI measurement of corn crops is mainly through three kinds of methods: the leaf length and width method (LAILLW), the instruments indirect measurement method (LAII) and the leaf area index sensor method(LAIS). Among them, LAI value obtained from LAILLW can be regarded as approximate true value. LAI-2200,the current widespread LAI canopy analyzer,is used in LAII. LAIS based on wireless sensor network can realize the automatic acquisition of crop images,simplifying the data collection work,while the other two methods need person to carry out field measurements.Through the comparison of LAIS and other two methods, the validity and reliability of LAIS observation system is verified. It is found that LAI trend changes are similar in three methods, and the rate of change of LAI has an increase with time in the first two months of corn growth when LAIS costs less manpower, energy and time. LAI derived from LAIS is more accurate than LAII in the early growth stage,due to the small blade especially under the strong light. Besides, LAI processed from a false color image with near infrared information is much closer to the true value than true color picture after the corn growth period up to one and half months.

Techniques for the estimation of leaf area index using spectral data

NASA Technical Reports Server (NTRS)

Badhwar, G. D.; Shen, S. S.

1984-01-01

Based on the radiative transport theory of a homogeneous canopy, a new approach for obtaining transformations of spectral data used to estimate leaf area index (LAI), is developed. The transformations which are obtained without any ground knowledge of LAI show low sensitivity to soil variability, and are linearly related to LAI with relationships which are predictable from leaf reflectance, transmittance properties, and canopy reflectance models. Evaluation of the SAIL (scattering by arbitrarily inclined leaves) model is considered. Using only nadir view data, results obtained on winter and spring wheat and corn crops are presented.

Leaf area and tree increment dynamics of even-aged and multiaged lodgepole pine stands in Montana

Treesearch

Cassandra L. Kollenberg; Kevin L. O' Hara

1999-01-01

Age structure and distribution of leaf area index (LAI) of even and multiaged lodgepole pine (Pinus contorta var. latifolia Engelm.) stands were examined on three study areas in western and central Montana. Projected leaf area was determined based on a relationship with sapwood cross-sectional area at breast height. Stand structure and LAI varied considerably between...

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Forest Productivity, Leaf Area, and Terrain in Southern Appalachian Deciduous Forests

Treesearch

Paul V. Bolstad; James M. Vose; Steven G. McNulty

2000-01-01

Leaf area index (LAI) is an important structural characteristic of forest ecosystems which has been shown to be strongly related to forest mass and energy cycles and forest productivity. LAI is more easily measured than forest productivity, and so a strong relationship between LAI and productivity would be a valuable tool in forest management. While a linear...

Marsh canopy leaf area and orientation calculated for improved marsh structure mapping

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, Amina; Jones, Cathleen E.; Bannister, Terri

2015-01-01

An approach is presented for producing the spatiotemporal estimation of leaf area index (LAI) of a highly heterogeneous coastal marsh without reliance on user estimates of marsh leaf-stem orientation. The canopy LAI profile derivation used three years of field measured photosynthetically active radiation (PAR) vertical profiles at seven S. alterniflora marsh sites and iterative transform of those PAR attenuation profiles to best-fit light extinction coefficients (KM). KM sun zenith dependency was removed obtaining the leaf angle distribution (LAD) representing the average marsh orientation and the LAD used to calculate the LAI canopy profile. LAI and LAD reproduced measured PAR profiles with 99% accuracy and corresponded to field documented structures. LAI and LAD better reflect marsh structure and results substantiate the need to account for marsh orientation. The structure indexes are directly amenable to remote sensing spatiotemporal mapping and offer a more meaningful representation of wetland systems promoting biophysical function understanding.

Canopy cover and leaf area index relationships for wheat, triticale, and corn

USDA-ARS?s Scientific Manuscript database

The AquaCrop model requires canopy cover (CC) measurements to define crop growth and development. Some previously collected data sets that would be useful for calibrating and validating AquaCrop contain only leaf area index (LAI) data, but could be used if relationships were available relating LAI t...

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

NASA Technical Reports Server (NTRS)

Kala, Jatin; Decker, Mark; Exbrayat, Jean-Francois; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Abramowitz, Gab; Mocko, David

2013-01-01

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.

Application and Evaluation of MODIS LAI, fPAR, and Albedo Products in the WRFCMAQ System

EPA Science Inventory

Leaf area index (LAI), vegetation fraction (VF), and surface albedo are important parameters in the land surface model (LSM) for meteorology and air quality modeling systems such as WRF/CMAQ. LAI and VF control not only leaf to canopy level evapotranspiration flux scaling but al...

A sensitivity analysis of a surface energy balance model to LAI (Leaf Area Index)

NASA Astrophysics Data System (ADS)

Maltese, A.; Cannarozzo, M.; Capodici, F.; La Loggia, G.; Santangelo, T.

2008-10-01

The LAI is a key parameter in hydrological processes, especially in the physically based distribution models. It is a critical ecosystem attribute since physiological processes such as photosynthesis, transpiration and evaporation depend on it. The diffusion of water vapor, momentum, heat and light through the canopy is regulated by the distribution and density of the leaves, branches, twigs and stems. The LAI influences the sensible heat flux H in the surface energy balance single source models through the calculation of the roughness length and of the displacement height. The aerodynamic resistance between the soil and within-canopy source height is a function of the LAI through the roughness length. This research carried out a sensitivity analysis of some of the most important parameters of surface energy balance models to the LAI time variation, in order to take into account the effects of the LAI variation with the phenological period. Finally empirical retrieved relationships between field spectroradiometric data and the field LAI measured via a light-sensitive instrument are presented for a cereal field.

Seasonal LAI in slash pine estimated with LANDSAT TM

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.; Gholz, Henry L.

1990-01-01

The leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LAI seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values derived using LANDSAT Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on 3 dates. Linear relationships existed between NDVI and LAI with R(sup 2) values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March, 1989, respectively. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass. Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6 percent of the mean LAI. This demonstrates the potential use of LANDSAT TM data for studying seasonal dynamics in forest canopies.

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

NASA Astrophysics Data System (ADS)

Lin, Yi; West, Geoff

2016-08-01

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like-;can ALS now work better on the task of LAI prediction?; As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R2 = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi

BOREAS RSS-4 1994 Southern Study Area Jack Pine LAI and FPAR Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Plummer, Stephen

2000-01-01

The RSS-4 team collected several data sets related to leaf, plant, and stand physical, optical, and chemical properties. This data set contains leaf area indices and FPAR measurements that were taken at the three conifer sites in the BOREAS SSA during August 1993 and at the jack pine tower flux and a subset of auxiliary sites during July and August 1994. The measurements were made with LAI-2000 and Ceptometer instruments. The measurements were taken for the purpose of model parameterization and to test empirical relationships that were hypothesized between biophysical parameters and remotely sensed data. The data are stored in tabular ASCII files.

Estimation of Leaf Area Index and its Sunlit Portion from DSCOVR EPIC data

NASA Astrophysics Data System (ADS)

Knyazikhin, Y.; Yang, B.; Mottus, M.; Rautiainen, M.; Stenberg, P.; Yan, L.; Chen, C.; Yan, K.; Park, T.; Myneni, R. B.; Song, W.

2016-12-01

The NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth at 16 km resolution (in equatorial zone) every 65 to 110 min in June 2015. It provides imageries in near backscattering directions with the scattering angle between 168o and 176o at ten UV to Near-IR narrow spectral bands centered at 317.5 (band width 1.0) nm, 325.0 (1.0) nm, 340.0 (3.0) nm, 388.0 (3.0) nm, 433.0 (3.0) nm, 551.0 (3.0) nm, 680.0 (1.7) nm, 687.8 (0.6) nm, 764.0 (1.7) nm and 779.5 (2.0) nm. This poster presents the theoretical basis of the algorithm designed for the generation of leaf area index (LAI) and diurnal course of sunlit leaf area index (SLAI) from EPIC Bidirectional Reflectance Factor of vegetated land. LAI and SLAI are defined as the total hemi-surface and sunlit leaf semi-surface per unit ground area. Whereas LAI is a standard product of many satellite the SLAI is a new satellite-derived parameter. Sunlit and shaded leaves exhibit different radiative response to incident Photosynthetically Active Radiation (400-700 nm), which in turn triggers various physiological and physical processes required for the functioning of plants. Leaf area and its sunlit portion are key state parameters in most ecosystem productivity and carbon/nitrogen cycle. Status of the EPIC LAI/SLAI product and its validation strategy are also discussed in this poster.

Extracting forest canopy structure from spatial information of high resolution optical imagery: tree crown size versus leaf area index

Treesearch

C. Song; M.B. Dickinson

2008-01-01

Leaves are the primary interface where energy, water and carbon exchanges occur between the forest ecosystems and the atmosphere. Leaf area index (LAI) is a measure of the amount of leaf area in a stand, and the tree crown size characterizes how leaves are clumped in the canopy. Both LAI and tree crown size are of essential ecological and management value. There is a...

A comparison of tools for remotely estimating leaf area index in loblolly pine plantations

Treesearch

Janet C. Dewey; Scott D. Roberts; Isobel Hartley

2006-01-01

Light interception is critical to forest growth and is largely determined by foliage area per unit ground, the measure of which is leaf area index (LAI). Summer and winter LAI estimates were obtained in a 17-year-old loblolly pine (Pinus taeda L.) spacing trial in Mississippi, using three replications with initial spacings of 1.5, 2.4, and 3.0 m....

Discrete return lidar-based prediction of leaf area index in two conifer forests

Treesearch

Jennifer L. R. Jensen; Karen S. Humes; Lee A. Vierling; Andrew T. Hudak

2008-01-01

Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical...

Evaluation of Multispectral Based Radiative Transfer Model Inversion to Estimate Leaf Area Index in Wheat

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) is a critical variable for predicting the growth and productivity of crops. Remote sensing estimates of LAI have relied upon empirical relationships between spectral vegetation indices and ground measurements that are costly to obtain. Radiative transfer model inversion based o...

Microwave Backscatter and Attenuation Dependence of Leaf Area Index for Flooded Rice Fields

NASA Technical Reports Server (NTRS)

Durden, Stephen L.; Morrissey, Leslie A.; Livingston, Gerald P.

1995-01-01

Wetlands are important for their role in global climate as a source of methane and other reduced trace gases. As part of an effort to determine whether radar is suitable for wetland vegetation monitoring, we have studied the dependence of microwave backscatter and attenuation on leaf area index (LAI) for flooded rice fields. We find that the radar return from a flooded rice field does show dependence on LAI. In particular, the C-band VV cross section per unit area decreases with increasing LAI. A simple model for scattering from rice fields is derived and fit to the observed HH and VV data. The model fit provides insight into the relation of backscatter to LAI and is also used to calculate the canopy path attenuation as a function of LAI.

Modeling the effect of photosynthetic vegetation properties on the NDVI--LAI relationship.

PubMed

Steltzer, Heidi; Welker, Jeffrey M

2006-11-01

Developing a relationship between the normalized difference vegetation index (NDVI) and the leaf area index (LAI) is essential to describe the pattern of spatial or temporal variation in LAI that controls carbon, water, and energy exchange in many ecosystem process models. Photosynthetic vegetation (PV) properties can affect the estimation of LAI, but no models integrate the effects of multiple species. We developed four alternative NDVI-LAI models, three of which integrate PV effects: no PV effects, leaf-level effects, canopy-level effects, and effects at both levels. The models were fit to data across the natural range of variation in NDVI for a widespread High Arctic ecosystem. The weight of evidence supported the canopy-level model (Akaike weight, wr = 0.98), which includes species-specific canopy coefficients that primarily scale fractional PV cover to LAI by accounting for the area of unexposed PV. Modeling the canopy-level effects improved prediction of LAI (R2 = 0.82) over the model with no PV effect (R2 = 0.71) across the natural range of variation in NDVI but did not affect the site-level estimate of LAI. Satellite-based methods to estimate species composition, a variable in the model, will need to be developed. We expect that including the effects of PV properties in NDVI-LAI models will improve prediction of LAI where species composition varies across space or changes over time.

A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

2016-05-01

Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a

View angle effects on relationships between leaf area index in wheat and vegetation indices

NASA Astrophysics Data System (ADS)

Chen, H.; Li, W.; Huang, W.; Niu, Z.

2016-12-01

The effects of plant types and view angles on the canopy-reflected spectrum can not be ignored in the estimation of leaf area index (LAI) using remote sensing vegetation indices. While vegetation indices derived from nadir-viewing remote sensors are insufficient in leaf area index (LAI) estimation because of its misinterpretation of structural characteristecs, vegetation indices derived from multi-angular remote sensors have potential to improve detection of LAI. However, view angle effects on relationships between these indices and LAI for low standing crops (i.e. wheat) has not been fully evaluated and thus limits them to applied for consistent and accurate monitoring of vegetation. View angles effects of two types of winter wheat (wheat 411, erectophile; and wheat 9507, planophile) on relationship between LAI and spectral reflectance are assessed and compared in this study. An evaluation is conducted with in-situ measurements of LAI and bidirectional reflectance in the principal plane from -60° (back-scattering direction ) ot 60° (forward scattering direction) in the growth cycle of winter wheat. A variety of vegetation indices (VIs) published are calculated by BRDF. Additionally, all combinations of the bands are used in order to calculate Normalized difference Spectral Indices (NDSI) and Simple Subtraction Indices (SSI). The performance of the above indices along with raw reflectance and reflectance derivatives on LAI estimation are examined based on a linearity comparison. The results will be helpful in further developing multi-angle remote sensing models for accurate LAI evaluation.

Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data

NASA Astrophysics Data System (ADS)

Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

2018-03-01

In this paper, Bayesian inversion of a physically-based forest reflectance model is investigated to estimate of boreal forest canopy leaf area index (LAI) from EO-1 Hyperion hyperspectral data. The data consist of multiple forest stands with different species compositions and structures, imaged in three phases of the growing season. The Bayesian estimates of canopy LAI are compared to reference estimates based on a spectral vegetation index. The forest reflectance model contains also other unknown variables in addition to LAI, for example leaf single scattering albedo and understory reflectance. In the Bayesian approach, these variables are estimated simultaneously with LAI. The feasibility and seasonal variation of these estimates is also examined. Credible intervals for the estimates are also calculated and evaluated. The results show that the Bayesian inversion approach is significantly better than using a comparable spectral vegetation index regression.

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

Leaf Area Influence on Surface Layer in a Deciduous Forest. Part 2; Detecting Leaf Area and Surface Resistance During Transition Seasons

NASA Technical Reports Server (NTRS)

Sakai, Ricardo K.; Fitzjarrald, David R.; Moore, Kathleen E.; Sicker, John W.; Munger, Willian J.; Goulden, Michael L.; Wofsy, Steven C.

1996-01-01

Temperate deciduous forest exhibit dramatic seasonal changes in surface exchange properties following on the seasonal changes in leaf area index. The canopy resistance to water vapor transport r(sub c) decreased abruptly at leaf emergence in each year but then also continued to decrease slowly during the remaining growing season due to slowly increasing LAI. Canopy resistance and PAR-albedo (albedo from photosynthetically active radiation) began to increase about one month before leaf fall with the diminishment of CO2 gradient above the canopy as well. At this time evaporation begun to be controlled as if the canopy were leafless.

Projections of leaf area index in earth system models

NASA Astrophysics Data System (ADS)

Mahowald, Natalie; Lo, Fiona; Zheng, Yun; Harrison, Laura; Funk, Chris; Lombardozzi, Danica; Goodale, Christine

2016-03-01

The area of leaves in the plant canopy, measured as leaf area index (LAI), modulates key land-atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO2), and other trace gases and aerosols, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. Here our goal is to characterize the LAI projections from the latest generation of earth system models (ESMs) for the Representative Concentration Pathway (RCP) 8.5 and RCP4.5 scenarios. On average, the models project increases in LAI in both RCP8.5 and RCP4.5 over most of the globe, but also show decreases in some parts of the tropics. Because of projected increases in variability, there are also more frequent periods of low LAI across broad regions of the tropics. Projections of LAI changes varied greatly among models: some models project very modest changes, while others project large changes, usually increases. Modeled LAI typically increases with modeled warming in the high latitudes, but often decreases with increasing local warming in the tropics. The models with the most skill in simulating current LAI in the tropics relative to satellite observations tend to project smaller increases in LAI in the tropics in the future compared to the average of all the models. Using LAI projections to identify regions that may be vulnerable to climate change presents a slightly different picture than using precipitation projections, suggesting LAI may be an additional useful tool for understanding climate change impacts. Going forward, users of LAI projections from the CMIP5 ESMs evaluated here should be aware that model outputs do not exhibit clear-cut relationships to vegetation carbon and precipitation. Our findings underscore the need for more attention to LAI projections, in terms of understanding the drivers of projected changes and improvements to model skill.

Projections of leaf area index in earth system models

DOE PAGES

Mahowald, Natalie; Lo, Fiona; Zheng, Yun; ...

2016-03-09

The area of leaves in the plant canopy, measured as leaf area index (LAI), modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO 2), and other trace gases and aerosols, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. Here our goal is to characterize the LAI projections from the latest generation of earth system models (ESMs) for the Representative Concentration Pathway (RCP) 8.5 and RCP4.5 scenarios. On average, the models project increases in LAI in both RCP8.5 and RCP4.5 over most of the globe, but also show decreases in somemore » parts of the tropics. Because of projected increases in variability, there are also more frequent periods of low LAI across broad regions of the tropics. Projections of LAI changes varied greatly among models: some models project very modest changes, while others project large changes, usually increases. Modeled LAI typically increases with modeled warming in the high latitudes, but often decreases with increasing local warming in the tropics. The models with the most skill in simulating current LAI in the tropics relative to satellite observations tend to project smaller increases in LAI in the tropics in the future compared to the average of all the models. Using LAI projections to identify regions that may be vulnerable to climate change presents a slightly different picture than using precipitation projections, suggesting LAI may be an additional useful tool for understanding climate change impacts. Going forward, users of LAI projections from the CMIP5 ESMs evaluated here should be aware that model outputs do not exhibit clear-cut relationships to vegetation carbon and precipitation. Lastly, our findings underscore the need for more attention to LAI projections, in terms of understanding the drivers of projected changes and improvements to model skill.« less

Measurement of Leaf Mass and Leaf Area of Oaks In A Mediterranean-climate Region For Biogenic Emission Estimation

NASA Astrophysics Data System (ADS)

Karlik, J.

Given the key role played by biogenic volatile organic compounds (BVOC) in tro- pospheric chemistry and regional air quality, it is critical to generate accurate BVOC emission inventories. Because several oak species have high BVOC emission rates, and oak trees are often of large stature with corresponding large leaf masses, oaks may be the most important genus of woody plants for BVOC emissions modeling in the natural landscapes of Mediterranean-climate regions. In California, BVOC emis- sions from oaks may mix with anthropogenic emissions from urban areas, leading to elevated levels of ozone. Data for leaf mass and leaf area for a stand of native blue oaks (Quercus douglasii) were obtained through harvest and leaf removal from 14 trees lo- cated in the Sierra Nevada foothills of central California. Trees ranged in height from 4.2 to 9.9 m, with trunk diameters at breast height of 14 to 85 cm. Mean leaf mass density was 730 g m-2 for the trees and had an overall value of 310 g m-2 for the site. Consideration of the surrounding grassland devoid of trees resulted in a value of about 150 g m-2, less than half of reported values for eastern U.S. oak woodlands, but close to a reported value for oaks found in St. Quercio, Italy. The mean value for leaf area index (LAI) for the trees at this site was 4.4 m2 m-2. LAI for the site was 1.8 m2 m-2, but this value was appropriate for the oak grove only; including the surrounding open grassland resulted in an overall LAI value of 0.9 m2 m-2 or less. A volumetric method worked well for estimating the leaf mass of the oak trees. Among allometric relationships investigated, trunk circumference, mean crown radius, and crown projec- tion were well correlated with leaf mass. Estimated emission of isoprene (mg C m-2 h-1) for the site based these leaf mass data and experimentally determined emission rate was similar to that reported for a Mediterranean oak woodland in France.

Carbon economics of LAI drive photosynthesis patterns across an Amazonian precipitation gradient

NASA Astrophysics Data System (ADS)

Flack, Sophie; Williams, Mathew; Meir, Patrick; Malhi, Yadvinder

2017-04-01

The Amazon rainforest is an integral part of the terrestrial carbon cycle, yet whilst the physiological response of its plants to water availability is increasingly well quantified, constraints to photosynthesis through adaptive response to precipitation regime have received little attention. We use the Soil Plant Atmosphere model to apportion variation in photosynthesis to individual drivers for plots with detailed measurements of carbon cycling, leaf traits and canopy properties, along an Amazonian mean annual precipitation (MAP) gradient. We hypothesised that leaf area index (LAI) would be the principal driver of variation in photosynthesis. Differences in LAI are predicted to result from economic factors; plants balance the carbon cost of leaf construction and maintenance with assimilation potential, to maximise canopy carbon export. Model analysis showed that LAI was the primary driver of differences in GPP along the precipitation gradient, accounting for 49% of observed variation. Meteorology accounted for 19%, whilst plant traits accounted for only 5%. To explain the observed spatial trends in LAI we undertook model experiments. For each plot the carbon budget was quantified iteratively using the field measured LAI time-series of the other plots, keeping meteorology, soil and plant traits constant. The mean annual LAI achieving maximum photosynthesis and net canopy carbon export increased with MAP, reflecting observed LAI trends. At the driest site, alternative, higher LAI strategies were unsustainable. The carbon cost of leaf construction and maintenance was disproportional to GPP achieved. At high MAP, increased foliar carbon costs were remunerative and GPP was maximised by high LAI. Our evidence therefore suggests that observed LAI trends across the precipitation gradient are driven by carbon economics. Forests LAI response to temporal changes in precipitation reflects trends observed across spatial gradients, identifying LAI as a key mechanism for plant

Indirect determination of leaf area index to calculate evapotranspiration

USDA-ARS?s Scientific Manuscript database

The plant integrates soil and environmental factors. The purpose of this study was to use nadir photos from 4.9 m height to determine ground cover, leaf area index (LAI), and plant water use (along with micrometeorology measurements). Measurements were completed on plots comparing a four-year organi...

LAI inversion algorithm based on directional reflectance kernels.

PubMed

Tang, S; Chen, J M; Zhu, Q; Li, X; Chen, M; Sun, R; Zhou, Y; Deng, F; Xie, D

2007-11-01

Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

How Universal Is the Relationship Between Remotely Sensed Vegetation Indices (VI) and Crop Leaf Area Index (LAI)?

NASA Technical Reports Server (NTRS)

Kang, Yanghui; Ozdogan, Mutlu; Zipper, Samuel C.; Roman, Miguel

2016-01-01

Global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. This research enables the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

BOREAS RSS-7 LAI, Gap Fraction, and FPAR Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing

2000-01-01

The BOREAS RSS-7 team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Ground measurements of LAI and Fraction of Photosynthetically Active Radiation (FPAR) absorbed by the plant canopy were made using the LAI-2000 and TRAC optical instruments during focused periods from 09-Aug-1993 to 19-Sep-1994. The measurements were intensive at the NSA and SSA tower sites, but were made just once or twice at auxiliary sites. The final processed LAI and FPAR data set is contained in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884).

Relating the radar backscattering coefficient to leaf-area index

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Allen, C.; Eger, G.; Kanemasu, E.

1983-01-01

The relationship between the radar backscattering coefficient of a vegetation canopy, sigma(0) sub can, and the canopy's leaf area index (LAI) is examined. The relationship is established through the development of a model for corn and sorghum and another for wheat. Both models are extensions of the cloud model of Attema and Ulaby (1978). Analysis of experimental data measured at 8.6, 13.0, 17.0, and 35.6 GHz indicates that most of the temporal variations of sigma(0) sub can can be accounted for through variations in green LAI alone, if the latter is greater than 0.5.

Mapping Vineyard Leaf Area Using Mobile Terrestrial Laser Scanners: Should Rows be Scanned On-the-Go or Discontinuously Sampled?

PubMed Central

del-Moral-Martínez, Ignacio; Rosell-Polo, Joan R.; Company, Joaquim; Sanz, Ricardo; Escolà, Alexandre; Masip, Joan; Martínez-Casasnovas, José A.; Arnó, Jaume

2016-01-01

The leaf area index (LAI) is defined as the one-side leaf area per unit ground area, and is probably the most widely used index to characterize grapevine vigor. However, LAI varies spatially within vineyard plots. Mapping and quantifying this variability is very important for improving management decisions and agricultural practices. In this study, a mobile terrestrial laser scanner (MTLS) was used to map the LAI of a vineyard, and then to examine how different scanning methods (on-the-go or discontinuous systematic sampling) may affect the reliability of the resulting raster maps. The use of the MTLS allows calculating the enveloping vegetative area of the canopy, which is the sum of the leaf wall areas for both sides of the row (excluding gaps) and the projected upper area. Obtaining the enveloping areas requires scanning from both sides one meter length section along the row at each systematic sampling point. By converting the enveloping areas into LAI values, a raster map of the latter can be obtained by spatial interpolation (kriging). However, the user can opt for scanning on-the-go in a continuous way and compute 1-m LAI values along the rows, or instead, perform the scanning at discontinuous systematic sampling within the plot. An analysis of correlation between maps indicated that MTLS can be used discontinuously in specific sampling sections separated by up to 15 m along the rows. This capability significantly reduces the amount of data to be acquired at field level, the data storage capacity and the processing power of computers. PMID:26797618

Mapping Vineyard Leaf Area Using Mobile Terrestrial Laser Scanners: Should Rows be Scanned On-the-Go or Discontinuously Sampled?

PubMed

del-Moral-Martínez, Ignacio; Rosell-Polo, Joan R; Company, Joaquim; Sanz, Ricardo; Escolà, Alexandre; Masip, Joan; Martínez-Casasnovas, José A; Arnó, Jaume

2016-01-19

The leaf area index (LAI) is defined as the one-side leaf area per unit ground area, and is probably the most widely used index to characterize grapevine vigor. However, LAI varies spatially within vineyard plots. Mapping and quantifying this variability is very important for improving management decisions and agricultural practices. In this study, a mobile terrestrial laser scanner (MTLS) was used to map the LAI of a vineyard, and then to examine how different scanning methods (on-the-go or discontinuous systematic sampling) may affect the reliability of the resulting raster maps. The use of the MTLS allows calculating the enveloping vegetative area of the canopy, which is the sum of the leaf wall areas for both sides of the row (excluding gaps) and the projected upper area. Obtaining the enveloping areas requires scanning from both sides one meter length section along the row at each systematic sampling point. By converting the enveloping areas into LAI values, a raster map of the latter can be obtained by spatial interpolation (kriging). However, the user can opt for scanning on-the-go in a continuous way and compute 1-m LAI values along the rows, or instead, perform the scanning at discontinuous systematic sampling within the plot. An analysis of correlation between maps indicated that MTLS can be used discontinuously in specific sampling sections separated by up to 15 m along the rows. This capability significantly reduces the amount of data to be acquired at field level, the data storage capacity and the processing power of computers.

Optimal interpolation analysis of leaf area index using MODIS data

USGS Publications Warehouse

Gu, Yingxin; Belair, Stephane; Mahfouf, Jean-Francois; Deblonde, Godelieve

2006-01-01

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI analysis is an optimal combination of the MODIS observations and derived climatology, depending on their associated errors σo and σc. The “best estimate” LAI is derived from a simple three-point smoothing technique combined with a selection of maximum LAI (after data quality control) values to ensure a higher quality. The LAI climatology is a time smoothed mean value of the “best estimate” LAI during the years of 2002–2004. The observation error is obtained by comparing the MODIS observed LAI with the “best estimate” of the LAI, and the climatological error is obtained by comparing the “best estimate” of LAI with the climatological LAI value. The LAI analysis is the result of a weighting between these two errors. Demonstration of the method described in this paper is presented for the 15-km grid of Meteorological Service of Canada (MSC)'s regional version of the numerical weather prediction model. The final LAI analyses have a relatively smooth temporal evolution, which makes them more appropriate for environmental prediction than the original MODIS LAI observation data. They are also more realistic than the LAI data currently used operationally at the MSC which is based on land-cover databases.

Monthly leaf area index estimates from point-in-time measurements and needle phenology for Pinus taeda

Treesearch

D.A. Sampson; T.J. Albaugh; Kurt H. Johnsen; H.L. Allen; Stanley J. Zarnoch

2003-01-01

Abstract: Leaf area index (LAI) of loblolly pine (Pinus taeda L.) trees of the southern United States varies almost twofold interannually; loblolly pine, essentially, carries two foliage cohorts at peak LAI (September) and one at minimum (March–April). Herein, we present an approach that may be site invariant to estimate monthly...

Estimation of leaf area index and foliage clumping in deciduous forests using digital photography

NASA Astrophysics Data System (ADS)

Chianucci, Francesco; Cutini, Andrea

2013-04-01

Rapid, reliable and meaningful estimates of leaf area index (LAI) are essential to the characterization of forest ecosystems. In this contribution the accuracy of both fisheye and non-fisheye digital photography for the estimation of forest leaf area in deciduous stands was evaluated. We compared digital hemispherical photography (DHP), the most widely used technique that measures the gap fraction at multiple zenith angles, with methods that measure the gap fraction at a single zenith angle, namely 57.5 degree photography and cover photography (DCP). Comparison with other different gap fraction methods used to calculate LAI such as canopy transmittance measurements from AccuPAR ceptometer and LAI- 2000 Plant Canopy Analyzer (PCA) were also performed. LAI estimated from all these indirect methods were compared with direct measurements obtained by litter traps (LAILT). We applied these methods in 10 deciduous stands of Quercus cerris, Castanea sativa and Fagus sylvatica, the most common deciduous species in Italy, where LAILT ranged from 3.9 to 7.3. DHP and DCP provided good indirect estimates of LAILT, and outperformed the other indirect methods. The DCP method provided estimates of crown porosity, crown cover, foliage cover and the clumping index at the zenith, but required assumptions about the light extinction coefficient at the zenith (k), to accurately estimate LAI. Cover photography provided good indirect estimates of LAI assuming a spherical leaf angle distribution, even though k appeared to decrease as LAI increased, thus affecting the accuracy of LAI estimates in DCP. In contrast, the accuracy of LAI estimates in DHP appeared insensitive to LAILT values, but the method was sensitive to photographic exposure, gamma-correction and was more time-consuming than DCP. Foliage clumping was estimated from all the photographic methods by analyzing either gap size distribution (DCP) or gap fraction distribution (DHP). Foliage clumping was also calculated from PCA and

Estimation of Canopy Sunlit Fraction of Leaf Area from Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Yang, B.; Knyazikhin, Y.; Yan, K.; Chen, C.; Park, T.; CHOI, S.; Mottus, M.; Rautiainen, M.; Stenberg, P.; Myneni, R.; Yan, L.

2015-12-01

The sunlit fraction of leaf area (SFLA) defined as the fraction of the total hemisurface leaf area illuminated by the direct solar beam is a key structural variable in many global models of climate, hydrology, biogeochemistry and ecology. SFLAI is expected to be a standard product from the Earth Polychromatic Imaging Camera (EPIC) on board the joint NOAA, NASA and US Air Force Deep Space Climate Observatory (DSCOVR) mission, which was successfully launched from Cape Canaveral, Florida on February 11, 2015. The DSCOVR EPIC sensor orbiting the Sun-Earth Lagrange L1 point provides multispectral measurements of the radiation reflected by Earth in retro-illumination directions. This poster discusses a methodology for estimating the SFLA using LAI-2000 Canopy Analyzer, which is expected to underlie the strategy for validation of the DSCOVR EPIC land surface products. LAI-2000 data collected over 18 coniferous and broadleaf sites in Hyytiälä, Central Finland, were used to estimate the SFLA. Field data on canopy geometry were used to simulate selected sites. Their SFLAI was calculated using a Monte Carlo (MC) technique. LAI-2000 estimates of SFLA showed a very good agreement with MC results, suggesting validity of the proposed approach.

Leaf Area Index Estimation Using Chinese GF-1 Wide Field View Data in an Agriculture Region.

PubMed

Wei, Xiangqin; Gu, Xingfa; Meng, Qingyan; Yu, Tao; Zhou, Xiang; Wei, Zheng; Jia, Kun; Wang, Chunmei

2017-07-08

Leaf area index (LAI) is an important vegetation parameter that characterizes leaf density and canopy structure, and plays an important role in global change study, land surface process simulation and agriculture monitoring. The wide field view (WFV) sensor on board the Chinese GF-1 satellite can acquire multi-spectral data with decametric spatial resolution, high temporal resolution and wide coverage, which are valuable data sources for dynamic monitoring of LAI. Therefore, an automatic LAI estimation algorithm for GF-1 WFV data was developed based on the radiative transfer model and LAI estimation accuracy of the developed algorithm was assessed in an agriculture region with maize as the dominated crop type. The radiative transfer model was firstly used to simulate the physical relationship between canopy reflectance and LAI under different soil and vegetation conditions, and then the training sample dataset was formed. Then, neural networks (NNs) were used to develop the LAI estimation algorithm using the training sample dataset. Green, red and near-infrared band reflectances of GF-1 WFV data were used as the input variables of the NNs, as well as the corresponding LAI was the output variable. The validation results using field LAI measurements in the agriculture region indicated that the LAI estimation algorithm could achieve satisfactory results (such as R² = 0.818, RMSE = 0.50). In addition, the developed LAI estimation algorithm had potential to operationally generate LAI datasets using GF-1 WFV land surface reflectance data, which could provide high spatial and temporal resolution LAI data for agriculture, ecosystem and environmental management researches.

Leaf area index uncertainty estimates for model-data fusion applications

Treesearch

Andrew D. Richardson; D. Bryan Dail; D.Y. Hollinger

2011-01-01

Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model-data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux...

Towards an improved LAI collection protocol via simulated field-based PAR sensing

DOE PAGES

Yao, Wei; Van Leeuwen, Martin; Romanczyk, Paul; ...

2016-07-14

In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While photosynthetically-active radiation (PAR) sensors have been validated for measuring crop LAI, there is limited literature on the efficacy of PAR-based LAI measurement in the forest environment. This study (i) validates PAR-based LAI measurement in forest environments, and (ii) proposes a suitable collection protocol, which balances efficiency with measurement variation, e.g., due to sun flecks and various-sized canopymore » gaps. A synthetic PAR sensor model was developed in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and used to validate LAI measurement based on first-principles and explicitly-known leaf geometry. Simulated collection parameters were adjusted to empirically identify optimal collection protocols. Furthermore, these collection protocols were then validated in the field by correlating PAR-based LAI measurement to the normalized difference vegetation index (NDVI) extracted from the “classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) data (R 2 was 0.61). The results indicate that our proposed collecting protocol is suitable for measuring the LAI of sparse forest (LAI < 3–5 ( m 2/m 2)).« less

Comparing LAI estimates of corn and soybean from vegetation indices of multi-resolution satellite images

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal ...

Three Different Methods of Estimating LAI in a Small Watershed

NASA Astrophysics Data System (ADS)

Speckman, H. N.; Ewers, B. E.; Beverly, D.

2015-12-01

Leaf area index (LAI) is a critical input of models that improve predictive understanding of ecology, hydrology, and climate change. Multiple techniques exist to quantify LAI, most of which are labor intensive, and all often fail to converge on similar estimates. . Recent large-scale bark beetle induced mortality greatly altered LAI, which is now dominated by younger and more metabolically active trees compared to the pre-beetle forest. Tree mortality increases error in optical LAI estimates due to the lack of differentiation between live and dead branches in dense canopy. Our study aims to quantify LAI using three different LAI methods, and then to compare the techniques to each other and topographic drivers to develop an effective predictive model of LAI. This study focuses on quantifying LAI within a small (~120 ha) beetle infested watershed in Wyoming's Snowy Range Mountains. The first technique estimated LAI using in-situ hemispherical canopy photographs that were then analyzed with Hemisfer software. The second LAI estimation technique was use of the Kaufmann 1982 allometrerics from forest inventories conducted throughout the watershed, accounting for stand basal area, species composition, and the extent of bark beetle driven mortality. The final technique used airborne light detection and ranging (LIDAR) first DMS returns, which were used to estimating canopy heights and crown area. LIDAR final returns provided topographical information and were then ground-truthed during forest inventories. Once data was collected, a fractural analysis was conducted comparing the three methods. Species composition was driven by slope position and elevation Ultimately the three different techniques provided very different estimations of LAI, but each had their advantage: estimates from hemisphere photos were well correlated with SWE and snow depth measurements, forest inventories provided insight into stand health and composition, and LIDAR were able to quickly and

Estimation of big sagebrush leaf area index with terrestrial laser scanning

USDA-ARS?s Scientific Manuscript database

Accurate monitoring and quantification of the structure and function of semiarid ecosystems is necessary to improve carbon and water flux models that help describe how these systems will respond in the future. The leaf area index (LAI, m2 m-2) is an important indicator of energy, water, and carbon e...

Evaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests

NASA Astrophysics Data System (ADS)

Wang, Rong; Chen, Jing M.; Liu, Zhili; Arain, Altaf

2017-08-01

Seasonal variations of leaf area index (LAI) have crucial controls on the interactions between the land surface and the atmosphere. Over the past decades, a number of remote sensing (RS) LAI products have been developed at both global and regional scales for various applications. These products are so far only validated using ground LAI data acquired mostly in the middle of the growing season. The accuracy of the seasonal LAI variation in these products remains unknown and there are few ground data available for this purpose. We performed regular LAI measurements over a whole year at five coniferous sites using two methods: (1) an optical method with LAI-2000 and TRAC; (2) a direct method through needle elongation monitoring and litterfall collection. We compared seasonal trajectory of LAI from remote sensing (RS LAI) with that from a direct method (direct LAI). RS LAI agrees very well with direct LAI from the onset of needle growth to the seasonal peak (R2 = 0.94, RMSE = 0.44), whereas RS LAI declines earlier and faster than direct LAI from the seasonal peak to the completion of needle fall. To investigate the possible reasons for the discrepancy, the MERIS Terrestrial Chlorophyll Index (MTCI) was compared with RS LAI. Meanwhile, phenological metrics, i.e. the start of growing season (SOS) and the end of growing season (EOS), were extracted from direct LAI, RS LAI and MTCI time series. SOS from RS LAI is later than that from direct LAI by 9.3 ± 4.0 days but earlier than that from MTCI by 2.6 ± 1.9 days. On the contrary, for EOS, RS LAI is later than MTCI by 3.3 ± 8.4 days and much earlier than direct LAI by 30.8 ± 7.2 days. Our results suggest that the seasonal trajectory of RS LAI well captures canopy structural information from the onset of needle growth to the seasonal peak, but is greatly influenced by the decrease in leaf chlorophyll content, as indicated by MTCI, from the seasonal peak to the completion of needle fall. These findings have significant

Investigating the Relationship Between Liquid Water and Leaf Area in Clonal Populus

NASA Technical Reports Server (NTRS)

Roberts, Dar; Brown, K.; Green, R.; Ustin, S.; Hinckley, T.

1998-01-01

Leaf Area Index (LAI) is one of the most commonly employed biophysical parameters used to characterize vegetation canopies and scale leaf physiological processes to larger scales. For example, LAI is a critical parameter used in regional scale estimates of evapotranspiration, photosynthesis, primary productivity, and carbon cycling (Running et al., 1989; Dorman and Sellers, 1989; Potter et al., 1993). LAI is typically estimated using ratio-based techniques, such as the Normalized Difference Vegetation Index (NDVI: e.g. Tucker 1979; Asrar et al., 1989; Sellers 1985, 1987). The physical basis behind this relationship depends on the high spectral contrast between scattered near-infrared (NIR) and absorbed red radiation in canopies. As the number of leaves present in a canopy increases over a unit area, NIR reflectance increases, while red reflectance decreases, resulting in an increase in the ratio. Through time series and image compositing, NDVI provides an additional temporal measure of how these parameters change, providing a means to monitor fluxes and productivity (Tucker et al., 1983). NDVI, while highly successful for agriculture and grassland ecosystems has been found to be less successful in evergreen chaparral and forested ecosystems (Badhwar et al., 1986; Gamon et al., 1993; Hall et al., 1995). Typically, the relationship between NDVI and LAI becomes progressively more asymptotic at LAI values above three (Sellers, 1985), although linear relationships have been observed in conifers at LAis as high as 13 (Spanner et al., 1990). In this paper, we explore an alternative approach for estimating LAI for remotely sensed data from AVIRIS based on estimates of canopy liquid water. Our primary objective is to test the hypothesis that the depth of the liquid water bands expressed in canopy reflectance spectra at 960, 1200, 1400 and 1900 nm increases with increasing LAI in canopies. This study builds from work by Roberts et al. (1997), in which liquid water was shown

Linking in situ LAI and fine resolution remote sensing data to map reference LAI over cropland and grassland using geostatistical regression method

NASA Astrophysics Data System (ADS)

He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua

2016-08-01

Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.

Determining the K coefficient to leaf area index estimations in a tropical dry forest

NASA Astrophysics Data System (ADS)

Magalhães, Sarah Freitas; Calvo-Rodriguez, Sofia; do Espírito Santo, Mário Marcos; Sánchez Azofeifa, Gerardo Arturo

2018-03-01

Vegetation indices are useful tools to remotely estimate several important parameters related to ecosystem functioning. However, improving and validating estimations for a wide range of vegetation types are necessary. In this study, we provide a methodology for the estimation of the leaf area index (LAI) in a tropical dry forest (TDF) using the light diffusion through the canopy as a function of the successional stage. For this purpose, we estimated the K coefficient, a parameter that relates the normalized difference vegetation index (NDVI) to LAI, based on photosynthetically active radiation (PAR) and solar radiation. The study was conducted in the Mata Seca State Park, in southeastern Brazil, from 2012 to 2013. We defined four successional stages (very early, early, intermediate, and late) and established one optical phenology tower at one plot of 20 × 20 m per stage. Towers measured the incoming and reflected solar radiation and PAR for NDVI calculation. For each plot, we established 24 points for LAI sampling through hemispherical photographs. Because leaf cover is highly seasonal in TDFs, we determined ΔK (leaf growth phase) and K max (leaf maturity phase). We detected a strong correlation between NDVI and LAI, which is necessary for a reliable determination of the K coefficient. Both NDVI and LAI varied significantly between successional stages, indicating sensitivity to structural changes in forest regeneration. Furthermore, the K values differed between successional stages and correlated significantly with other environmental variables such as air temperature and humidity, fraction of absorbed PAR, and soil moisture. Thus, we established a model based on spectral properties of the vegetation coupled with biophysical characteristics in a TDF that makes possible to estimate LAI from NDVI values. The application of the K coefficient can improve remote estimations of forest primary productivity and gases and energy exchanges between vegetation and atmosphere

Retrieval of LAI and leaf chlorophyll content from remote sensing data by agronomy mechanism knowledge to solve the ill-posed inverse problem

NASA Astrophysics Data System (ADS)

Li, Zhenhai; Nie, Chenwei; Yang, Guijun; Xu, Xingang; Jin, Xiuliang; Gu, Xiaohe

2014-10-01

Leaf area index (LAI) and LCC, as the two most important crop growth variables, are major considerations in management decisions, agricultural planning and policy making. Estimation of canopy biophysical variables from remote sensing data was investigated using a radiative transfer model. However, the ill-posed problem is unavoidable for the unique solution of the inverse problem and the uncertainty of measurements and model assumptions. This study focused on the use of agronomy mechanism knowledge to restrict and remove the ill-posed inversion results. For this purpose, the inversion results obtained using the PROSAIL model alone (NAMK) and linked with agronomic mechanism knowledge (AMK) were compared. The results showed that AMK did not significantly improve the accuracy of LAI inversion. LAI was estimated with high accuracy, and there was no significant improvement after considering AMK. The validation results of the determination coefficient (R2) and the corresponding root mean square error (RMSE) between measured LAI and estimated LAI were 0.635 and 1.022 for NAMK, and 0.637 and 0.999 for AMK, respectively. LCC estimation was significantly improved with agronomy mechanism knowledge; the R2 and RMSE values were 0.377 and 14.495 μg cm-2 for NAMK, and 0.503 and 10.661 μg cm-2 for AMK, respectively. Results of the comparison demonstrated the need for agronomy mechanism knowledge in radiative transfer model inversion.

Leaf area index, biomass carbon and growth rate of radiata pine genetic types and relationships with LiDAR

Treesearch

Peter N. Beets; Stephen Reutebuch; Mark O. Kimberley; Graeme R. Oliver; Stephen H. Pearce; Robert J. McGaughey

2011-01-01

Relationships between discrete-return light detection and ranging (LiDAR) data and radiata pine leaf area index (LAI), stem volume, above ground carbon, and carbon sequestration were developed using 10 plots with directly measured biomass and leaf area data, and 36 plots with modelled carbon data. The plots included a range of genetic types established on north- and...

BOREAS RSS-7 Landsat TM LAI IMages of the SSA and NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team used Landsat Thematic Mapper (TM) images processed at CCRS to produce images of Leaf Area Index (LAI) for the BOREAS study areas. Two images acquired on 06-Jun and 09-Aug-1991 were used for the SSA, and one image acquired on 09-Jun-1994 was used for the NSA. The LAI images are based on ground measurements and Landsat TM Reduced Simple Ratio (RSR) images. The data are stored in binary image-format files.

Collection of LAI and FPAR Data Over The Terra Core Sites

NASA Technical Reports Server (NTRS)

Myneni, Ranga B.; Knjazihhin, J.; Tian, Y.; Wang, Y.

2001-01-01

The objective of our effort was to collect and archive data on LAI (leaf area index) and FPAR (Fraction of Photosynthetically active Radiation absorbed by vegetation) at the EOS Core validation sites as well as to validate and evaluate global fields of LAI and FPAR derived from atmospherically corrected MODIS (Moderate Resolution Imaging Spectrometer) surface reflectance data by comparing these fields with the EOS Core validation data set. The above has been accomplished by: (a) the participation in selected field campaigns within the EOS Validation Program; (b) the processing of the collected data so that suitable comparison between field measurements and the MODIS LAI/FPAR fields can be made; (c) the comparison of the MODAS LAI/FRAM fields with the EOS Terra Core validation data set.

Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions

NASA Astrophysics Data System (ADS)

Xie, Qiaoyun; Huang, Wenjiang; Dash, Jadunandan; Song, Xiaoyu; Huang, Linsheng; Zhao, Jinling; Wang, Renhong

2015-12-01

Leaf area index (LAI) is an important indicator for monitoring crop growth conditions and forecasting grain yield. Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques. Spectral vegetation indices, mathematical combination of reflectance bands, are widely used for LAI estimation due to their computational simplicity and their applications ranged from the leaf scale to the entire globe. However, in many cases, their applicability is limited to specific vegetation types or local conditions due to species specific nature of the relationship used to transfer the vegetation indices to LAI. The overall objective of this study is to investigate the most suitable vegetation index for estimating winter wheat LAI under eight different types of fertilizer and irrigation conditions. Regression models were used to estimate LAI using hyperspectral reflectance data from the Pushbroom Hyperspectral Imager (PHI) and in-situ measurements. Our results showed that, among six vegetation indices investigated, the modified soil-adjusted vegetation index (MSAVI) and the normalized difference vegetation index (NDVI) exhibited strong and significant relationships with LAI, and thus were sensitive across different nitrogen and water treatments. The modified triangular vegetation index (MTVI2) confirmed its potential on crop LAI estimation, although second to MSAVI and NDVI in our study. The enhanced vegetation index (EVI) showed moderate performance. However, the ratio vegetation index (RVI) and the modified simple ratio index (MSR) predicted the least accurate estimations of LAI, exposing the simple band ratio index's weakness under different treatment conditions. The results support the use of vegetation indices for a quick and effective LAI mapping procedure that is suitable for winter wheat under different management practices.

A LAI inversion algorithm based on the unified model of canopy bidirectional reflectance distribution function for the Heihe River Basin

NASA Astrophysics Data System (ADS)

Ma, B.; Li, J.; Fan, W.; Ren, H.; Xu, X.

2017-12-01

Leaf area index (LAI) is one of the important parameters of vegetation canopy structure, which can represent the growth condition of vegetation effectively. The accuracy, availability and timeliness of LAI data can be improved greatly, which is of great importance to vegetation-related research, such as the study of atmospheric, land surface and hydrological processes to obtain LAI by remote sensing method. Heihe River Basin is the inland river basin in northwest China. There are various types of vegetation and all kinds of terrain conditions in the basin, so it is helpful for testing the accuracy of the model under the complex surface and evaluating the correctness of the model to study LAI in this area. On the other hand, located in west arid area of China, the ecological environment of Heihe Basin is fragile, LAI is an important parameter to represent the vegetation growth condition, and can help us understand the status of vegetation in the Heihe River Basin. Different from the previous LAI inversion models, the BRDF (bidirectional reflectance distribution function) unified model can be applied for both continuous vegetation and discrete vegetation, it is appropriate to the complex vegetation distribution. LAI is the key input parameter of the model. We establish the inversion algorithm that can exactly retrieve LAI using remote sensing image based on the unified model. First, we determine the vegetation type through the vegetation classification map to obtain the corresponding G function, leaf and surface reflectivity. Then, we need to determine the leaf area index (LAI), the aggregation index (ζ) and the sky scattered light ratio (β) range and the value of the interval, entering all the parameters into the model to calculate the corresponding reflectivity ρ and establish the lookup table of different vegetation. Finally, we can invert LAI on the basis of the established lookup table. The principle of inversion is least squares method. We have produced 1 km

[Quantitative relationships between hyper-spectral vegetation indices and leaf area index of rice].

PubMed

Tian, Yong-Chao; Yang, Jie; Yao, Xia; Zhu, Yan; Cao, Wei-Xing

2009-07-01

Based on field experiments with different rice varieties under different nitrogen application levels, the quantitative relationships of rice leaf area index (LAI) with canopy hyper-spectral parameters at different growth stages were analyzed. Rice LAI had good relationships with several hyper-spectral vegetation indices, the correlation coefficient being the highest with DI (difference index), followed by with RI (ratio index), and NI (normalized index), based on the spectral reflectance or the first derivative spectra. The two best spectral indices for estimating LAI were the difference index DI (854, 760) (based on two spectral bands of 850 nm and 760 nm) and the difference index DI (D676, D778) (based on two first derivative bands of 676 nm and 778 nm). In general, the hyper-spectral vegetation indices based on spectral reflectance performed better than the spectral indices based on the first derivative spectra. The tests with independent dataset suggested that the rice LAI monitoring models with difference index DI (854,760) as the variable could give an accurate LAI estimation, being available for estimation of rice LAI.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more

Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurments of height and crown dimensions

Treesearch

Scott D. Roberts; Thomas J. Dean; David L. Evans; John W. McCombs; Richard L. Harrington; Partick A. Glass

2005-01-01

Accurate estimates of leaf area index (LAI) could provide useful information to forest managers, but due to difficulties in measurement, leaf area is rarely used in decision-making. A reliable approach to remotely estimating LA1 would greatly facilitate its use in forest management. This study investigated the potential for using small-footprint iDAR, a laser-based...

Development of a global LAI estimation algorithm for JAXA's new earth observation satellite sensor, GCOM-C/SGLI

NASA Astrophysics Data System (ADS)

Ono, Y.; Murakami, H.; Kobayashi, H.; Nasahara, K. N.; Kajiwara, K.; Honda, Y.

2014-12-01

Leaf Area Index (LAI) is defined as the one-side green leaf area per unit ground surface area. Global LAI products, such as MOD15 (Terra&Aqua/MODIS) and CYCLOPES (SPOT/VEGETATION) are used for many global terrestrial carbon models. Japan Aerospace eXploration Agency (JAXA) is planning to launch GCOM-C (Global Change Observation Mission-Climate) which carries SGLI (Second-generation GLobal Imager) in the Japanese Fiscal Year 2017. SGLI has the features, such as 17-channel from near ultraviolet to thermal infrared, 250-m spatial resolution, polarization, and multi-angle (nadir and ±45-deg. along-track slant) observation. In the GCOM-C/SGLI land science team, LAI is scheduled to be generated from GCOM-C/SGLI observation data as a standard product (daily 250-m). In extisting algorithms, LAI is estimated by the reverse analysis of vegetation radiative transfer models (RTMs) using multi-spectral and mono-angle observation data. Here, understory layer in vegetation RTMs is assumed by plane parallel (green leaves + soil) which set up arbitrary understroy LAI. However, actual understory consists of various elements, such as green leaves, dead leaves, branches, soil, and snow. Therefore, if understory in vegetation RTMs differs from reality, it will cause an error of LAI to estimate. This report describes an algorithm which estimates LAI in consideration of the influence of understory using GCOM-C/SGLI multi-spectral and multi-angle observation data.

Spatial and Temporal Dynamics of the Leaf Area Index of the Caatinga Biome

NASA Astrophysics Data System (ADS)

Alves Rodrigues Pinheiro, Everton; de Jong van Lier, Quirijn; Metselaar, Klaas

2015-04-01

Leaf Area Index (LAI) is an important characteristic of ecosystems with a prominent role in processes such as transpiration, photosynthesis and interception. The Caatinga biome is a unique semiarid ecosystem ocurring in a specific region of Brazil. An important main feature of this biome is the leaf shedding and regenerative capacity of its species. The aim of this study was to quantify both spatial and temporal dynamics of the LAI of the Caatinga biome in the Aiuaba Experimental Basin, an integrally-preserved Caatinga reserve, coordinates 6°42'S; 40°17'W. The research site (12 km2) was divided into three main Soil and Vegatation Associations (SVA). For each SVA the soil type and root depth are respectively, Acrisol -0.8 m, Luvisol - 0.6 m and Regosol - 0.4 m. The LAI was estimated by SEBAL algorithm applied to eleven satellite images from Landsat 5. The values of LAI estimated by SEBAL were correlated to the mean soil water content of the 15 days previous to the satellite image date. Eight images were used to generate a simple regression model, yielding a range of coefficient of determination from 0.89 to 0.92. Three other images were used to validate the equations. The Nash-Sutcliffe efficiency coefficient ranged from 0.76 to 0.94. Using the validated correlations, the LAI was calculated over the time for each of the three SVA, from 2004 to 2012. For SVA1, SVA2 and SVA3, the avarage values of LAI during the rainy season were 0.97, 1.12 and 1.07, respectively. During the dry season, the mean values were 0.15 for SVA1 and 0.11 for SVA2 and SVA3. The vegetation showed abrupt LAI changes, and the average previous 15 days soil water content was a good indicator for this. The study has shown that the maximum LAI was relatively stable over the years, occurring between March and April. The spatial behavior of LAI appeared to be similar, independently of the soil type and root depth.

First direct landscape-scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity

Treesearch

David B. Clark; Paulo C. Olivas; Steven F. Oberbauer; Deborah A. Clark; Michael G. Ryan

2008-01-01

Leaf Area Index (leaf area per unit ground area, LAI) is a key driver of forest productivity but has never previously been measured directly at the landscape scale in tropical rain forest (TRF). We used a modular tower and stratified random sampling to harvest all foliage from forest floor to canopy top in 55 vertical transects (4.6 m2) across 500 ha of old growth in...

Estimation of vegetation parameters such as Leaf Area Index from polarimetric SAR data

NASA Astrophysics Data System (ADS)

Hetz, Marina; Blumberg, Dan G.; Rotman, Stanley R.

2010-05-01

This work presents the analysis of the capability to use the radar backscatter coefficient in semi-arid zones to estimate the vegetation crown in terms of Leaf Area Index (LAI). The research area is characterized by the presence of a pine forest with shrubs as an underlying vegetation layer (understory), olive trees, natural grove areas and eucalyptus trees. The research area was imaged by an airborne RADAR system in L-band during February 2009. The imagery includes multi-look radar images. All the images were fully polarized i.e., HH, VV, HV polarizations. For this research we used the central azimuth angle (113° ). We measured LAI using the ?T Sun Scan Canopy Analysis System. Verification was done by analytic calculations and digital methods for the leaf's and needle's surface area. In addition, we estimated the radar extinction coefficient of the vegetation volume by comparing point calibration targets (trihedral corner reflectors with 150cm side length) within and without the canopy. The radar extinction in co- polarized images was ~26dB and ~24dB for pines and olives respectively, compared to the same calibration target outside the vegetation. We used smaller trihedral corner reflectors (41cm side length) and covered them with vegetation to measure the correlation between vegetation density, LAI and radar backscatter coefficient for pines and olives under known conditions. An inverse correlation between the radar backscatter coefficient of the trihedral corner reflectors covered by olive branches and the LAI of those branches was observed. The correlation between LAI and the optical transmittance was derived using the Beer-Lambert law. In addition, comparing this law's principle to the principle of the radar backscatter coefficient production, we derived the equation that connects between the radar backscatter coefficient and LAI. After extracting the radar backscatter coefficient of forested areas, all the vegetation parameters were used as inputs for the

Automated In-Situ Laser Scanner for Monitoring Forest Leaf Area Index

PubMed Central

Culvenor, Darius S.; Newnham, Glenn J.; Mellor, Andrew; Sims, Neil C.; Haywood, Andrew

2014-01-01

An automated laser rangefinding instrument was developed to characterize overstorey and understorey vegetation dynamics over time. Design criteria were based on information needs within the statewide forest monitoring program in Victoria, Australia. The ground-based monitoring instrument captures the key vegetation structural information needed to overcome ambiguity in the estimation of forest Leaf Area Index (LAI) from satellite sensors. The scanning lidar instrument was developed primarily from low cost, commercially accessible components. While the 635 nm wavelength lidar is not ideally suited to vegetation studies, there was an acceptable trade-off between cost and performance. Tests demonstrated reliable range estimates to live foliage up to a distance of 60 m during night-time operation. Given the instrument's scan angle of 57.5 degrees zenith, the instrument is an effective tool for monitoring LAI in forest canopies up to a height of 30 m. An 18 month field trial of three co-located instruments showed consistent seasonal trends and mean LAI of between 1.32 to 1.56 and a temporal LAI variation of 8 to 17% relative to the mean. PMID:25196006

A New Global LAI Product and Its Use for Terrestrial Carbon Cycle Estimation

NASA Astrophysics Data System (ADS)

Chen, J. M.; Liu, R.; Ju, W.; Liu, Y.

2014-12-01

For improving the estimation of the spatio-temporal dynamics of the terrestrial carbon cycle, a new time series of the leaf area index (LAI) is generated for the global land surface at 8 km resolution from 1981 to 2012 by combining AVHRR and MODIS satellite data. This product differs from existing LAI products in the following two aspects: (1) the non-random spatial distribution of leaves with the canopy is considered, and (2) the seasonal variation of the vegetation background is included. The non-randomness of the leaf spatial distribution in the canopy is considered using the second vegetation structural parameter named clumping index (CI), which quantifies the deviation of the leaf spatial distribution from the random case. Using the MODIS Bidirectional Reflectance Distribution Function product, a global map of CI is produced at 500 m resolution. In our LAI algorithm, CI is used to convert the effective LAI obtained from mono-angle remote sensing into the true LAI, otherwise LAI would be considerably underestimated. The vegetation background is soil in crop, grass and shrub but includes soil, grass, moss, and litter in forests. Through processing a large volume of MISR data from 2000 to 2010, monthly red and near-infrared reflectances of the vegetation background is mapped globally at 1 km resolution. This new LAI product has been validated extensively using ground-based LAI measurements distributed globally. In carbon cycle modeling, the use of CI in addition to LAI allows for accurate separation of sunlit and shaded leaves as an important step in terrestrial photosynthesis and respiration modeling. Carbon flux measurements over 100 sites over the globe are used to validate an ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS). The validated model is run globally at 8 km resolution for the period from 1981 to 2012 using the LAI product and other spatial datasets. The modeled results suggest that changes in vegetation structure as quantified

Assimilation of Remotely Sensed Leaf Area Index into the Community Land Model with Explicit Carbon and Nitrogen Components using Data Assimilation Research Testbed

NASA Astrophysics Data System (ADS)

Ling, X.; Fu, C.; Yang, Z. L.; Guo, W.

2017-12-01

Information of the spatial and temporal patterns of leaf area index (LAI) is crucial to understand the exchanges of momentum, carbon, energy, and water between the terrestrial ecosystem and the atmosphere, while both in-situ observation and model simulation usually show distinct deficiency in terms of LAI coverage and value. Land data assimilation, combined with observation and simulation together, is a promising way to provide variable estimation. The Data Assimilation Research Testbed (DART) developed and maintained by the National Centre for Atmospheric Research (NCAR) provides a powerful tool to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to better understanding of all three. Here we systematically investigated the effects of data assimilation on improving LAI simulation based on NCAR Community Land Model with the prognostic carbon-nitrogen option (CLM4CN) linked with DART using the deterministic Ensemble Adjustment Kalman Filter (EAKF). Random 40-member atmospheric forcing was used to drive the CLM4CN with or without LAI assimilation. The Global Land Surface Satellite LAI data (GLASS LAI) LAI is assimilated into the CLM4CN at a frequency of 8 days, and LAI (and leaf carbon / nitrogen) are adjusted at each time step. The results show that assimilating remotely sensed LAI into the CLM4CN is an effective method for improving model performance. In detail, the CLM4-CN simulated LAI systematically overestimates global LAI, especially in low latitude with the largest bias of 5 m2/m2. While if updating both LAI and leaf carbon and leaf nitrogen simultaneously during assimilation, the analyzed LAI can be corrected, especially in low latitude regions with the bias controlled around ±1 m2/m2. Analyzed LAI could also represent the seasonal variation except for the Southern Temperate (23°S-90°S). The obviously improved regions located in the center of Africa, Amazon, the South of Eurasia, the northeast of

Estimates of leaf area index from spectral reflectance of wheat under different cultural practices and solar angle

NASA Technical Reports Server (NTRS)

Asrar, G.; Kanemasu, E. T.; Yoshida, M.

1985-01-01

The influence of management practices and solar illumination angle on the leaf area index (LAI) was estimated from measurements of wheat canopy reflectance evaluated by two methods, a regression formula and an indirect technique. The date of planting and the time of irrigation in relation to the stage of plant growth were found to have significant effects on the development of leaves in spring wheat. A reduction in soil moisture adversely affected both the duration and magnitude of the maximum LAI for late planting dates. In general, water stress during vegetative stages resulted in a reduction in maximum LAI, while water stress during the reproductive period shortened the duration of green LAI in spring wheat. Canopy geometry and solar angle also affected the spectral properties of the canopies, and hence the estimated LAI. Increase in solar zenith angles resulted in a general increase in estimated LAI obtained from both methods.

Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index

NASA Astrophysics Data System (ADS)

Chen, Jing M.; Cihlar, Josef

1995-09-01

Optical instruments currently available for measuring the leaf-area index (LAI) of a plant canopy all utilize only the canopy gap-fraction information. These instruments include the Li-Cor LAI-2000 Plant Canopy Analyzer, Decagon, and Demon. The advantages of utilizing both the canopy gap-fraction and gap-size information are shown. For the purpose of measuring the canopy gap size, a prototype sunfleck-LAI instrument named Tracing Radiation and Architecture of Canopies (TRAC), has been developed and tested in two pure conifer plantations, red pine (Pinus resinosa Ait.) and jack pine (Pinus banksiana Lamb). A new gap-size-analysis theory is presented to quantify the effect of canopy architecture on optical measurements of LAI based on the gap-fraction principle. The theory is an improvement on that of Lang and Xiang [Agric. For. Meteorol. 37, 229 (1986)]. In principle, this theory can be used for any heterogeneous canopies.

Relationships between stem diameter, sapwood area, leaf area and transpiration in a young mountain ash forest.

PubMed

Vertessy, R A; Benyon, R G; O'Sullivan, S K; Gribben, P R

1995-09-01

We examined relationships between stem diameter, sapwood area, leaf area and transpiration in a 15-year-old mountain ash (Eucalyptus regnans F. Muell.) forest containing silver wattle (Acacia dealbata Link.) as a suppressed overstory species and mountain hickory (Acacia frigescens J.H. Willis) as an understory species. Stem diameter explained 93% of the variation in leaf area, 96% of the variation in sapwood area and 88% of the variation in mean daily spring transpiration in 19 mountain ash trees. In seven silver wattle trees, stem diameter explained 87% of the variation in sapwood area but was a poor predictor of the other variables. When transpiration measurements from individual trees were scaled up to a plot basis, using stem diameter values for 164 mountain ash trees and 124 silver wattle trees, mean daily spring transpiration rates of the two species were 2.3 and 0.6 mm day(-1), respectively. The leaf area index of the plot was estimated directly by destructive sampling, and indirectly with an LAI-2000 plant canopy analyzer and by hemispherical canopy photography. All three methods gave similar results.

Application of a new leaf area index algorithm to China's landmass using MODIS data for carbon cycle research.

PubMed

Liu, R; Chen, J M; Liu, J; Deng, F; Sun, R

2007-11-01

An operational system was developed for mapping the leaf area index (LAI) for carbon cycle models from the moderate resolution imaging spectroradiometer (MODIS) data. The LAI retrieval algorithm is based on Deng et al. [2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44, 2219-2229], which uses the 4-scale radiative transfer model [Chen, J.M., Leblancs, 1997. A 4-scale bidirectional reflection model based on canopy architecture. IEEE Transactions on Geoscience and Remote Sensing, 35, 1316-1337] to simulate the relationship of LAI with vegetated surface reflectance measured from space for various spectral bands and solar and view angles. This algorithm has been integrated to the MODISoft platform, a software system designed for processing MODIS data, to generate 250 m, 500 m and 1 km resolution LAI products covering all of China from MODIS MOD02 or MOD09 products. The multi-temporal interpolation method was implemented to remove the residual cloud and other noise in the final LAI product so that it can be directly used in carbon models without further processing. The retrieval uncertainties from land cover data were evaluated using five different data sets available in China. The results showed that mean LAI discrepancies can reach 27%. The current product was also compared with the NASA MODIS MOD15 LAI product to determine the agreement and disagreement of two different product series. LAI values in the MODIS product were found to be 21% larger than those in the new product. These LAI products were compared against ground TRAC measurements in forests in Qilian Mountain and Changbaishan. On average, the new LAI product agrees with the field measurement in Changbaishan within 2%, but the MODIS product is positively biased by about 20%. In Qilian Mountain, where forests are sparse, the new product is lower than field measurements by about 38%, while the MODIS product is larger by about 65%.

Estimating Leaf Area Index in Southeast Alaska: A Comparison of Two Techniques

PubMed Central

Eckrich, Carolyn A.; Flaherty, Elizabeth A.; Ben-David, Merav

2013-01-01

The relationship between canopy structure and light transmission to the forest floor is of particular interest for studying the effects of succession, timber harvest, and silviculture prescriptions on understory plants and trees. Indirect measurements of leaf area index (LAI) estimated using gap fraction analysis with linear and hemispheric sensors have been commonly used to assess radiation interception by the canopy, although the two methods often yield inconsistent results. We compared simultaneously obtained measurements of LAI from a linear ceptometer and digital hemispheric photography in 21 forest stands on Prince of Wales Island, Alaska. We assessed the relationship between these estimates and allometric LAI based on tree diameter at breast height (LAIDBH). LAI values measured at 79 stations in thinned, un-thinned controls, old-growth and clearcut stands were highly correlated between the linear sensor (AccuPAR) and hemispheric photography, but the latter was more negatively biased compared to LAIDBH. In contrast, AccuPAR values were more similar to LAIDBH in all stands with basal area less than 30 m2ha−1. Values produced by integrating hemispheric photographs over the zenith angles 0–75° (Ring 5) were highly correlated with those integrated over the zenith angles 0–60° (Ring 4), although the discrepancies between the two measures were significant. On average, the AccuPAR estimates were 53% higher than those derived from Ring 5, with most of the differences in closed canopy stands (unthinned controls and old-growth) and less so in clearcuts. Following typical patterns of canopy closure, AccuPAR LAI values were higher in dense control stands than in old-growth, whereas the opposite was derived from Ring 5 analyses. Based on our results we advocate the preferential use of linear sensors where canopy openness is low, canopies are tall, and leaf distributions are clumped and angles are variable, as is common in the conifer forests of coastal Alaska

Relationships of Leaf Area Index and NDVI for 12 Brassica Cultivars in Northeastern Montana

NASA Astrophysics Data System (ADS)

Jabro, Jay; Allen, Brett; Long, Dan; Isbell, Terry; Gesch, Russ; Brown, Jack; Hatfield, Jerry; Archer, David; Oblath, Emily; Vigil, Merle; Kiniry, Jim; Hunter, Kimberly; Shonnard, David

2017-04-01

To our knowledge, there is limited information on the relationship of the normalized difference vegetation index (NDVI) and leaf area index (LAI) in spring Brassica oilseed crops. The 2014 results of NDVI and LAI of 12 spring varieties of oilseed crops were measured in a field study conducted in Sidney, Montana, USA under dryland conditions. These 12 varieties were grouped under six species (B. napus, B. rapa, B. juncea, B. carinata, Sinapis alba, and Camelina sativa). The NDVI and LAI were measured weekly throughout the growing season. The NDVI was continually measured at one sample per second across the whole plot using a Crop Circle ACS-470 active crop canopy sensor. The LAI was measured at two locations at 12 samples per plot using an AccuPar model LP-80 Ceptometer. Treatments were replicated four times in a randomized complete block design in plots of 3 m×9 m. Temporal dynamics of NDVI and LAI in various growth stages of 12 varieties were evaluated throughout the growing season. Significant relationships and models between NDVI and LAI were obtained when 12 varieties were grouped under six species.

The effect of year-to-year variability of leaf area index on Variable Infiltration Capacity model performance and simulation of runoff

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2015-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrological model performance and the simulation of runoff using the Variable Infiltration Capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) leaf area index dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the deviation of the simulated monthly runoff using the observed monthly LAI from simulated runoff using long-term mean monthly LAI was computed. The VIC model predicted monthly runoff in the selected sub-catchments with model efficiencies ranging from 61.5% to 95.9% during calibration (1982-1997) and 59% to 92.4% during validation (1998-2012). Our results suggest systematic improvements, from 4% to 25% in Nash-Sutcliffe efficiency, in sparsely forested sub-catchments when the VIC model was calibrated with observed monthly LAI instead of long-term mean monthly LAI. There was limited systematic improvement in tree dominated sub-catchments. The results also suggest that the model overestimation or underestimation of runoff during wet and dry periods can be reduced to 25 mm and 35 mm respectively by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

Combined Study of Snow Depth Determination and Winter Leaf Area Index Retrieval by Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Jenicek, Michal

2017-04-01

A rapid and robust approach using Unmanned Aerial Vehicle (UAV) digital photogrammetry was performed for evaluating snow accumulation over different small localities (e.g. disturbed forest and open area) and for indirect field measurements of Leaf Area Index (LAI) of coniferous forest within the Šumava National Park, Czech Republic. The approach was used to reveal impacts related to changes in forest and snowpack and to determine winter effective LAI for monitoring the impact of forest canopy metrics on snow accumulation. Due to the advancement of the technique, snow depth and volumetric changes of snow depth over these selected study areas were estimated at high spatial resolution (1 cm) by subtracting a snow-free digital elevation model (DEM) from a snow-covered DEM. Both, downward-looking UAV images and upward-looking digital hemispherical photography (DHP), and additional widely used LAI-2200 canopy analyser measurements were applied to determine the winter LAI, controlling interception and transmitting radiation. For the performance of downward-looking UAV images the snow background instead of the sky fraction was used. The reliability of UAV-based LAI retrieval was tested by taking an independent data set during the snow cover mapping campaigns. The results showed the potential of digital photogrammetry for snow depth mapping and LAI determination by UAV techniques. The average difference obtained between ground-based and UAV-based measurements of snow depth was 7.1 cm with higher values obtained by UAV. The SD of 22 cm for the open area seemed competitive with the typical precision of point measurements. In contrast, the average difference in disturbed forest area was 25 cm with lower values obtained by UAV and a SD of 36 cm, which is in agreement with other studies. The UAV-based LAI measurements revealed the lowest effective LAI values and the plant canopy analyser LAI-2200 the highest effective LAI values. The biggest bias of effective LAI was observed

Look-up-table approach for leaf area index retrieval from remotely sensed data based on scale information

NASA Astrophysics Data System (ADS)

Zhu, Xiaohua; Li, Chuanrong; Tang, Lingli

2018-03-01

Leaf area index (LAI) is a key structural characteristic of vegetation and plays a significant role in global change research. Several methods and remotely sensed data have been evaluated for LAI estimation. This study aimed to evaluate the suitability of the look-up-table (LUT) approach for crop LAI retrieval from Satellite Pour l'Observation de la Terre (SPOT)-5 data and establish an LUT approach for LAI inversion based on scale information. The LAI inversion result was validated by in situ LAI measurements, indicating that the LUT generated based on the PROSAIL (PROSPECT+SAIL: properties spectra + scattering by arbitrarily inclined leaves) model was suitable for crop LAI estimation, with a root mean square error (RMSE) of ˜0.31m2 / m2 and determination coefficient (R2) of 0.65. The scale effect of crop LAI was analyzed based on Taylor expansion theory, indicating that when the SPOT data aggregated by 200 × 200 pixel, the relative error is significant with 13.7%. Finally, an LUT method integrated with scale information was proposed in this article, improving the inversion accuracy with RMSE of 0.20 m2 / m2 and R2 of 0.83.

Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography

PubMed Central

Zhao, Dehua; Xie, Dong; Zhou, Hengjie; Jiang, Hao; An, Shuqing

2012-01-01

Non-destructive estimation using digital cameras is a common approach for estimating leaf area index (LAI) of terrestrial vegetation. However, no attempt has been made so far to develop non-destructive approaches to LAI estimation for aquatic vegetation. Using the submerged plant species Potamogeton malainus, the objective of this study was to determine whether the gap fraction derived from vertical photographs could be used to estimate LAI of aquatic vegetation. Our results suggested that upward-oriented photographs taken from beneath the water surface were more suitable for distinguishing vegetation from other objects than were downward-oriented photographs taken from above the water surface. Exposure settings had a substantial influence on the identification of vegetation in upward-oriented photographs. Automatic exposure performed nearly as well as the optimal trial exposure, making it a good choice for operational convenience. Similar to terrestrial vegetation, our results suggested that photographs taken for the purpose of distinguishing gap fraction in aquatic vegetation should be taken under diffuse light conditions. Significant logarithmic relationships were observed between the vertical gap fraction derived from upward-oriented photographs and plant area index (PAI) and LAI derived from destructive harvesting. The model we developed to depict the relationship between PAI and gap fraction was similar to the modified theoretical Poisson model, with coefficients of 1.82 and 1.90 for our model and the theoretical model, respectively. This suggests that vertical upward-oriented photographs taken from below the water surface are a feasible alternative to destructive harvesting for estimating PAI and LAI for the submerged aquatic plant Potamogeton malainus. PMID:23226557

Quantifying seasonal variation of leaf area index using near-infrared digital camera in a rice paddy

NASA Astrophysics Data System (ADS)

Hwang, Y.; Ryu, Y.; Kim, J.

2017-12-01

Digital camera has been widely used to quantify leaf area index (LAI). Numerous simple and automatic methods have been proposed to improve the digital camera based LAI estimates. However, most studies in rice paddy relied on arbitrary thresholds or complex radiative transfer models to make binary images. Moreover, only a few study reported continuous, automatic observation of LAI over the season in rice paddy. The objective of this study is to quantify seasonal variations of LAI using raw near-infrared (NIR) images coupled with a histogram shape-based algorithm in a rice paddy. As vegetation highly reflects the NIR light, we installed NIR digital camera 1.8 m above the ground surface and acquired unsaturated raw format images at one-hour intervals between 15 to 80 º solar zenith angles over the entire growing season in 2016 (from May to September). We applied a sub-pixel classification combined with light scattering correction method. Finally, to confirm the accuracy of the quantified LAI, we also conducted direct (destructive sampling) and indirect (LAI-2200) manual observations of LAI once per ten days on average. Preliminary results show that NIR derived LAI agreed well with in-situ observations but divergence tended to appear once rice canopy is fully developed. The continuous monitoring of LAI in rice paddy will help to understand carbon and water fluxes better and evaluate satellite based LAI products.

Retrieval of Winter Wheat Leaf Area Index from Chinese GF-1 Satellite Data Using the PROSAIL Model.

PubMed

Li, He; Liu, Gaohuan; Liu, Qingsheng; Chen, Zhongxin; Huang, Chong

2018-04-06

Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most established methods for estimating crop LAI. In this study, a look-up table (LUT) based on the PROSAIL RTM was first used to estimate winter wheat LAI from GF-1 data, which accounted for some available prior knowledge relating to the distribution of winter wheat characteristics. Next, the effects of 15 LAI-LUT strategies with reflectance bands and 10 LAI-LUT strategies with vegetation indexes on the accuracy of the winter wheat LAI retrieval with different phenological stages were evaluated against in situ LAI measurements. The results showed that the LUT strategies of LAI-GNDVI were optimal and had the highest accuracy with a root mean squared error (RMSE) value of 0.34, and a coefficient of determination (R²) of 0.61 during the elongation stages, and the LUT strategies of LAI-Green were optimal with a RMSE of 0.74, and R² of 0.20 during the grain-filling stages. The results demonstrated that the PROSAIL RTM had great potential in winter wheat LAI inversion with GF-1 satellite data and the performance could be improved by selecting the appropriate LUT inversion strategies in different growth periods.

Inconsistencies of interannual variability and trends in long-term satellite leaf area index products.

PubMed

Jiang, Chongya; Ryu, Youngryel; Fang, Hongliang; Myneni, Ranga; Claverie, Martin; Zhu, Zaichun

2017-10-01

Understanding the long-term performance of global satellite leaf area index (LAI) products is important for global change research. However, few effort has been devoted to evaluating the long-term time-series consistencies of LAI products. This study compared four long-term LAI products (GLASS, GLOBMAP, LAI3g, and TCDR) in terms of trends, interannual variabilities, and uncertainty variations from 1982 through 2011. This study also used four ancillary LAI products (GEOV1, MERIS, MODIS C5, and MODIS C6) from 2003 through 2011 to help clarify the performances of the four long-term LAI products. In general, there were marked discrepancies between the four long-term LAI products. During the pre-MODIS period (1982-1999), both linear trends and interannual variabilities of global mean LAI followed the order GLASS>LAI3g>TCDR>GLOBMAP. The GLASS linear trend and interannual variability were almost 4.5 times those of GLOBMAP. During the overlap period (2003-2011), GLASS and GLOBMAP exhibited a decreasing trend, TCDR no trend, and LAI3g an increasing trend. GEOV1, MERIS, and MODIS C6 also exhibited an increasing trend, but to a much smaller extent than that from LAI3g. During both periods, the R 2 of detrended anomalies between the four long-term LAI products was smaller than 0.4 for most regions. Interannual variabilities of the four long-term LAI products were considerably different over the two periods, and the differences followed the order GLASS>LAI3g>TCDR>GLOBMAP. Uncertainty variations quantified by a collocation error model followed the same order. Our results indicate that the four long-term LAI products were neither intraconsistent over time nor interconsistent with each other. These inconsistencies may be due to NOAA satellite orbit changes and MODIS sensor degradation. Caution should be used in the interpretation of global changes derived from the four long-term LAI products. © 2017 John Wiley & Sons Ltd.

Large-scale Estimates of Leaf Area Index from Active Remote Sensing Laser Altimetry

NASA Astrophysics Data System (ADS)

Hopkinson, C.; Mahoney, C.

2016-12-01

Leaf area index (LAI) is a key parameter that describes the spatial distribution of foliage within forest canopies which in turn control numerous relationships between the ground, canopy, and atmosphere. The retrieval of LAI has demonstrated success by in-situ (digital) hemispherical photography (DHP) and airborne laser scanning (ALS) data; however, field and ALS acquisitions are often spatially limited (100's km2) and costly. Large-scale (>1000's km2) retrievals have been demonstrated by optical sensors, however, accuracies remain uncertain due to the sensor's inability to penetrate the canopy. The spaceborne Geoscience Laser Altimeter System (GLAS) provides a possible solution in retrieving large-scale derivations whilst simultaneously penetrating the canopy. LAI retrieved by multiple DHP from 6 Australian sites, representing a cross-section of Australian ecosystems, were employed to model ALS LAI, which in turn were used to infer LAI from GLAS data at 5 other sites. An optimally filtered GLAS dataset was then employed in conjunction with a host of supplementary data to build a Random Forest (RF) model to infer predictions (and uncertainties) of LAI at a 250 m resolution across the forested regions of Australia. Predictions were validated against ALS-based LAI from 20 sites (R2=0.64, RMSE=1.1 m2m-2); MODIS-based LAI were also assessed against these sites (R2=0.30, RMSE=1.78 m2m-2) to demonstrate the strength of GLAS-based predictions. The large-scale nature of current predictions was also leveraged to demonstrate large-scale relationships of LAI with other environmental characteristics, such as: canopy height, elevation, and slope. The need for such wide-scale quantification of LAI is key in the assessment and modification of forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network, in fulfilling their government issued mandates.

An evaluation of MODIS 250-m data for green LAI estimation in crops

NASA Astrophysics Data System (ADS)

Gitelson, Anatoly A.; Wardlow, Brian D.; Keydan, Galina P.; Leavitt, Bryan

2007-10-01

Green leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse applications. Remotely sensed data provide considerable potential for estimating LAI at local, regional, and global scales. The goal of this study was to retrieve green LAI from MODIS 250-m vegetation index (VI) data for irrigated and rainfed maize and soybeans. The performance of both MODIS-derived NDVI and Wide Dynamic Range Vegetation Index (WDRVI) were evaluated across three growing seasons (2002 through 2004) over a wide range of LAI and also compared to the performance of NDVI and WDRVI derived from reflectance data collected at close-range across the same field locations. The NDVI vs. LAI relationship showed asymptotic behavior with a sharp decrease in the sensitivity of the NDVI to LAI exceeding 2 m2/m2 for both crops. WDRVI vs. LAI relation was linear across the entire range of LAI variation with determination coefficients above 0.93. Importantly, the coefficients of the close-range WDRVI vs. LAI equation and the MODIS-retrieved WDRVI vs. LAI equation were very close. The WDRVI was found to be capable of accurately estimating LAI across a much greater LAI range than the NDVI and can be used for assessing even slight variations in LAI, which are indicative of the early stages of plant stress. These results demonstrate the new possibilities for analyzing the spatio-temporal variation of the LAI of crops using multi-temporal MODIS 250-m imagery.

Monitoring boreal forest leaf area index across a Siberian burn chronosequence: a MODIS validation study

USGS Publications Warehouse

Cheng, X.; Vierling, Lee; Deering, D.; Conley, A.

2005-01-01

Landscapes containing differing amounts of ecological disturbance provide an excellent opportunity to validate and better understand the emerging Moderate Resolution Imaging Spectrometer (MODIS) vegetation products. Four sites, including 1‐year post‐fire coniferous, 13‐year post‐fire deciduous, 24‐year post‐fire deciduous, and >100 year old post‐fire coniferous forests, were selected to serve as a post‐fire chronosequence in the central Siberian region of Krasnoyarsk (57.3°N, 91.6°E) with which to study the MODIS leaf area index (LAI) and vegetation index (VI) products. The collection 4 MODIS LAI product correctly represented the summer site phenologies, but significantly underestimated the LAI value of the >100 year old coniferous forest during the November to April time period. Landsat 7‐derived enhanced vegetation index (EVI) performed better than normalized difference vegetation index (NDVI) to separate the deciduous and conifer forests, and both indices contained significant correlation with field‐derived LAI values at coniferous forest sites (r 2 = 0.61 and r 2 = 0.69, respectively). The reduced simple ratio (RSR) markedly improved LAI prediction from satellite measurements (r 2 = 0.89) relative to NDVI and EVI. LAI estimates derived from ETM+ images were scaled up to evaluate the 1 km resolution MODIS LAI product; from this analysis MODIS LAI overestimated values in the low LAI deciduous forests (where LAI<5) and underestimated values in the high LAI conifer forests (where LAI>6). Our results indicate that further research on the MODIS LAI product is warranted to better understand and improve remote LAI quantification in disturbed forest landscapes over the course of the year.

Satellite based remote sensing technique as a tool for real time monitoring of leaf retention in natural rubber plantations affected by abnormal leaf fall disease

NASA Astrophysics Data System (ADS)

Pradeep, B.; Meti, S.; James, J.

2014-11-01

Most parts of the traditional natural rubber growing regions of India, extending from Kanyakumari district of Tamil Nadu in the South to Kasaragod district of Kerala in the North received excess and prolonged rains during 2013. This led to severe incidence of Abnormal Leaf Fall (ALF) disease caused by the fungus, Phytophthora sp. The present study demonstrated the first time use of satellite remote sensing technique to monitor ALF disease by estimating Leaf Area Index (LAI) in natural rubber holdings in near real time. Leaf retention was monitored in between April and December 2012 and 2013 by estimating LAI using MODIS 15A2 product covering rubber holdings spread across all districts in the traditional rubber growing region of the country that was mapped using Resourcesat LISS III 2012 and 2013 data. It was found that as the monsoon advanced, LAI decreased substantially in both years, but the reduction was much more substantial and prolonged in many districts during 2013 than 2012 reflecting increased leaf fall due to ALF disease in 2013. The decline was more pronounced in central and northern Kerala than in the South. Kanyakumari district of Tamil Nadu is generally known to be free from ALF disease, but there was considerable leaf loss due to ALF in June 2012 and June and July 2013 even as the monsoon was unusually severe in 2013. Weighted mean LAI during for the entire period of April to December was estimated as a weighted average of LAI and per cent of total area under rubber in each district in the study area for the two years. This was markedly less in 2013 than 2012. The implications of poor leaf retention for biomass production (net primary productivity), carbon sequestration and rubber yield are discussed.

Relationship between aerodynamic roughness length and bulk sedge leaf area index in a mixed-species boreal mire complex

NASA Astrophysics Data System (ADS)

Alekseychik, P. K.; Korrensalo, A.; Mammarella, I.; Vesala, T.; Tuittila, E.-S.

2017-06-01

Leaf area index (LAI) is an important parameter in natural ecosystems, representing the seasonal development of vegetation and photosynthetic potential. However, direct measurement techniques require labor-intensive field campaigns that are usually limited in time, while remote sensing approaches often do not yield reliable estimates. Here we propose that the bulk LAI of sedges (LAIs) can be estimated alternatively from a micrometeorological parameter, the aerodynamic roughness length for momentum (z0). z0 can be readily calculated from high-response turbulence and other meteorological data, typically measured continuously and routinely available at ecosystem research sites. The regressions of LAI versus z0 were obtained using the data from two Finnish natural sites representative of boreal fen and bog ecosystems. LAIs was found to be well correlated with z0 and sedge canopy height. Superior method performance was demonstrated in the fen ecosystem where the sedges make a bigger contribution to overall surface roughness than in bogs.

Leaf area index retrieval using Hyperion EO-1 data-based vegetation indices in Himalayan forest system

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Singh, Sarnam

2016-04-01

Present Study is being taken to retrieve Leaf Area Indexn(LAI) in Himalayan forest system using vegetation indices developed from Hyperion EO-1 hyperspectral data. Hemispherical photograph were captured in the month of March and April, 2012 at 40 locations, covering moist tropical Sal forest, subtropical Bauhinia and pine forest and temperate Oak forest and analysed using an open source GLA software. LAI in the study region was ranging in between 0.076 m2/m2 to 6.00 m2/m2. These LAI values were used to develop spectral models with the FLAASH corrected Hyperion measurements.Normalized difference vegetation index (NDVI) was used taking spectral reflectance values of all the possible combinations of 170 atmospherically corrected channels. The R2 was ranging from lowest 0.0 to highest 0.837 for the band combinations of spectral region 640 nm and 670 nm. The spectral model obtained was, spectral reflectance (y) = 0.02x LAI(x) - 0.0407.

Estimation of leaf area index using WorldView-2 and Aster satellite image: a case study from Turkey.

PubMed

Günlü, Alkan; Keleş, Sedat; Ercanlı, İlker; Şenyurt, Muammer

2017-10-04

The objective of this study is to estimate the leaf area index (LAI) of a forest ecosystem using two different satellite images, WorldView-2 and Aster. For this purpose, 108 sample plots were taken from pure Crimean pine forest stands of Yenice Forest Management Planning Unit in Ilgaz Forest Management Enterprise, Turkey. Each sample plot was imaged with hemispherical photographs with a fish-eye camera to determine the LAI. These photographs were analyzed with the help of Hemisfer Hemiview software program, and thus, the LAI of each sample plot was estimated. Furthermore, multiple regression analysis method was used to model the statistical relationships between the LAI values and band spectral reflection values and some vegetation indices (Vis) obtained from satellite images. The results show that the high-resolution WorldView-2 satellite image is better than the medium-resolution Aster satellite image in predicting the LAI. It was also seen that the results obtained by using the VIs are better than the bands when the LAI value is predicted with satellite images.

Relation of MODIS EVI and LAI across time, vegetation types and hydrological regimes

NASA Astrophysics Data System (ADS)

Alexandridis, Thomas; Ovakoglou, George

2015-04-01

Estimation of the Leaf Area Index (LAI) of a landscape is considered important to describe the ecosystems activity and is used as an important input parameter in hydrological and biogeochemical models related to water and carbon cycle, desertification risk, etc. The measurement of LAI in the field is a laborious and costly process and is mainly done by indirect methods, such as hemispherical photographs that are processed by specialized software. For this reason there have been several attempts to estimate LAI with multispectral satellite images, using theoretical biomass development models, or empirical equations using vegetation indices and land cover maps. The aim of this work is to study the relation of MODIS EVI and LAI across time, vegetation type, and hydrological regime. This was achieved by studying 120 maps of EVI and LAI which cover a hydrological year and five hydrologically diverse areas: river Nestos in Greece, Queimados catchment in Brazil, Rijnland catchment in The Netherlands, river Tamega in Portugal, and river Umbeluzi in Mozambique. The following Terra MODIS composite datasets were downloaded for the hydrological year 2012-2013: MOD13A2 "Vegetation Indices" and MCD15A2 "LAI and FPAR", as well as the equivalent quality information layers (QA). All the pixels that fall in a vegetation land cover (according to the MERIS GLOBCOVER map) were sampled for the analysis, with the exception of those that fell at the border between two vegetation or other land cover categories, to avoid the influence of mixed pixels. Using linear regression analysis, the relationship between EVI and LAI was identified per date, vegetation type and study area. Results show that vegetation type has the highest influence in the variation of the relationship between EVI and LAI in each study area. The coefficient of determination (R2) is high and statistically significant (ranging from 0.41 to 0.83 in 90% of the cases). When plotting the EVI factor from the regression equation

Retrieval of Winter Wheat Leaf Area Index from Chinese GF-1 Satellite Data Using the PROSAIL Model

PubMed Central

Li, He; Liu, Gaohuan; Liu, Qingsheng; Chen, Zhongxin; Huang, Chong

2018-01-01

Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most established methods for estimating crop LAI. In this study, a look-up table (LUT) based on the PROSAIL RTM was first used to estimate winter wheat LAI from GF-1 data, which accounted for some available prior knowledge relating to the distribution of winter wheat characteristics. Next, the effects of 15 LAI-LUT strategies with reflectance bands and 10 LAI-LUT strategies with vegetation indexes on the accuracy of the winter wheat LAI retrieval with different phenological stages were evaluated against in situ LAI measurements. The results showed that the LUT strategies of LAI-GNDVI were optimal and had the highest accuracy with a root mean squared error (RMSE) value of 0.34, and a coefficient of determination (R2) of 0.61 during the elongation stages, and the LUT strategies of LAI-Green were optimal with a RMSE of 0.74, and R2 of 0.20 during the grain-filling stages. The results demonstrated that the PROSAIL RTM had great potential in winter wheat LAI inversion with GF-1 satellite data and the performance could be improved by selecting the appropriate LUT inversion strategies in different growth periods. PMID:29642395

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

NASA Astrophysics Data System (ADS)

Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

2015-02-01

Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance

Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong; Hashimoto, Hirofumi; Milesi, Cristina; Michaelis, Andrew; Wang, Weile; Votava, Petr; Samanta, Arindam; Melton, Forrest;

Simulated and Inferred LAI, NPP, and Biomes in North America Since the Last Glacial Maximum.

NASA Astrophysics Data System (ADS)

Zajac, L. M.; Williams, J. W.; Kaplan, J.

2004-12-01

Vegetation structure and productivity are sensitive to climate change and are an important source of feedbacks to the climate system. Here we employ multiple lines of evidence to reconstruct variations in leaf area index (LAI), net primary productivity (NPP), and biomes. LAI determines the total canopy surface area available for light interception, gas exchange, and water loss, and NPP, the increase in plant carbon per unit area, measures the flux of carbon into the terrestrial biosphere. BIOME4, an equilibrium biogeography and biogeochemistry vegetation model, is used to simulate LAI, NPP, and biome distributions in North America for the past 21,000 years at 1,000-year time-steps. BIOME4 was coupled asynchronously to the Hadley Center Unified Model with a mixed-layer ocean model forced by variations in orbital boundary conditions, physiography, and atmospheric CO2 concentration (Kaplan et al. 2002). BIOME4 models LAI as a trade-off between maximizing light interception and minimizing water loss and assigns the LAI that maximizes NPP. Past LAI's and biomes, independently estimated from fossil pollen assemblages using the modern analogue technique, are compared to model results. In unglaciated eastern North America, canopy closure of the full-glacial conifer forests and woodlands in response to ameliorating climatic conditions resulted in a 80% increase in LAI's between 21 ka and 11 ka. After 8 ka, large areas of tundra and forest-tundra developed in deglaciated regions. The BIOME4 simulations show good agreement with the LAI's and biome distribution inferred from fossil pollen records. Sensitivity analyses with BIOME4 indicate that both climate and CO2 played important roles in regulating vegetation structure and productivity.

Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

NASA Astrophysics Data System (ADS)

Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

2016-09-01

Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

A better way of representing stem area index in two-big-leaf models: the application and impact on canopy integration of leaf nitrogen content

NASA Astrophysics Data System (ADS)

Chen, M.; Butler, E. E.; Wythers, K. R.; Kattge, J.; Ricciuto, D. M.; Thornton, P. E.; Atkin, O. K.; Flores-Moreno, H.; Reich, P. B.

2017-12-01

In order to better estimate the carbon budget of the globe, accurately simulating gross primary productivity (GPP) in earth system models is critical. When upscaling leaf level photosynthesis to the canopy, climate models uses different big-leaf schemes. About half of the state-of-the-art earth system models use a "two-big-leaf" scheme that partitions canopies into direct and diffusively illuminated fractions to reduce high bias of GPP simulated by one-big-leaf models. Some two-big-leaf models, such as ACME (identical in this respect to CLM 4.5) add leaf area index (LAI) and stem area index (SAI) together when calculating canopy radiation transfer. This treatment, however, will result in higher fraction of sunlit leaves. It will also lead to an artificial overestimation of canopy nitrogen content. Here we introduce a new algorithm of simulating SAI in a two-big-leaf model. The new algorithm reduced the sunlit leave fraction of the canopy and conserved the nitrogen content from leaf to canopy level. The lower fraction of sunlit leaves reduced global GPP especially in tropical area. Compared to the default model, for the past 100 years (1909-2009), the averaged global annual GPP is lowered by 4.11 PgC year-1 using this new algorithm.

Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

2016-01-01

Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

2016-10-01

Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

New Features of the Collection 4 MODIS LAI and FPAR Product

NASA Astrophysics Data System (ADS)

Bin, T.; Yang, W.; Dong, H.; Shabanov, N.; Knyazikhin, Y.; Myneni, R.

2003-12-01

An algorithm based on physics of radiative transfer in vegetation canopies for the retrieval of vegetation green leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) from MODIS surface reflectance data was developed, prototyped and is in operational production at NASA computing facilities since June 2000. This poster highlights recent changes in the operational MODIS LAI and FPAR algorithm introduced for collection 4 data reprocessing. The changes to the algorithm are targeted to improve agreement of retrieved LAI and FPAR with corresponding field measurements, improve consistency of Quality Control (QC) definitions and miscellaneous bug fixes as summarized below. * Improvement of LUTs for the main and back-up algorithms for biomes 1 and 3. Benefits: a) increase in quality of retrievals; b) non-physical peaks in the global LAI distribution have been removed; c) improved agreement with field measurements * Improved QA scheme. Benefits: a) consistency between MODLAND and SCF quality flags has been achieved; b)ambiguity in QA has been resolved * New 8-day compositing scheme. Benefits: a) compositing over best quality retrievals, instead of all retrievals; b) lowers LAI values, decreases saturation and number of pixels generated by the back-up * At-launch static IGBP land cover, input to the LAI/FPAR algorithm, was replaced with the MODIS land cover map. Benefits: a) crosswalking of 17 classes IGBP scheme to 6-biome LC has been eliminated; b) uncertainties in the MODIS LAI/FPAR product due to uncertainties in land cover map have been reduced

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Tan, Bin; Hu, Jiannan; Huang, Dong; Yang, Wenze; Zhang, Ping; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2005-01-01

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data

PubMed Central

Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

2017-01-01

Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size. PMID:28045443

Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data.

PubMed

Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

2017-01-01

Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size.

The seasonality of AVHRR data of temperate coniferous forests - Relationship with leaf area index

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

1990-01-01

The relationship between the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) and coniferous forest leaf area index (LAI) over the western United States is examined. AVHRR data from the NOAA-9 satellite were acquired of the western U.S. from March 1986 to November 1987 and monthly maximum value composites of AVHRR NDVI were calculated for 19 coniferous forest stands in Oregon, Washington, Montana, and California. It is concluded that the relationships under investigation vary according to seasonal changes in surface reflectance based on key biotic and abiotic controls including phenological changes in LAI caused by seasonal temperature and precipitation variations, the proportions of surface cover types contributing to the overall reflectance, and effects resulting from large variations in the solar zenith angle.

Improving the frequency of high spatial resolution leaf area index maps using Landsat OLI and Sentinel-2 MSI

NASA Astrophysics Data System (ADS)

Li, S.; Ganguly, S.; Dungan, J. L.; Zhang, G.; Ju, J.; Claverie, M.

2015-12-01

The European Space Agency's Sentinel-2 mission successfully launched the first of two satellites in June, 2015. Sentinel 2A's MSI instrument is now providing optical data similar to Landsat 8's OLI imagery and, with its global repeat of 10 days, has the potential to increase the availability of 30m resolution high level products such as leaf area index (LAI). Prior to the launch of S-2A, we simulated MSI imagery using EO-1 Hyperion data and estimated green LAI using an algorithm based on canopy spectral invariants theory. Comparison of the resulting LAI maps resulting from the simulated MSI and corresponding maps derived from OLI data showed a RMSE of 0.1875. Uncertainty bounds on actual MSI data promise to be narrower because of the superior signal-to-noise ratio of MSI. A workflow for the production of LAI and other high level products including data ingest, BRDF correction, cloud masking and atmospheric correction is being developed using the NASA Earth Exchange (NEX) and will improve the capability to examine seasonal changes in canopy LAI.

Applying the concept of ecohydrological equilibrium to predict steady-state leaf area index for Australian ecosystems

NASA Astrophysics Data System (ADS)

Yang, J.; Medlyn, B.; De Kauwe, M. G.; Duursma, R.

2017-12-01

Leaf Area Index (LAI) is a key variable in modelling terrestrial vegetation, because it has a major impact on carbon, water and energy fluxes. However, LAI is difficult to predict: several recent intercomparisons have shown that modelled LAI differs significantly among models, and between models and satellite-derived estimates. Empirical studies show that long-term mean LAI is strongly related to mean annual precipitation. This observation is predicted by the theory of ecohydrological equilibrium, which provides a promising alternative means to predict steady-state LAI. We implemented this theory in a simple optimisation model. We hypothesized that, when water availability is limited, plants should adjust long-term LAI and stomatal behavior (g1) to maximize net canopy carbon export, under the constraint that canopy transpiration is a fixed fraction of total precipitation. We evaluated the predicted LAI (Lopt) for Australia against ground-based observations of LAI at 135 sites, and continental-scale satellite-derived estimates. For the site-level data, the RMSE of predicted Lopt was 0.14 m2 m-2, which was similar to the RMSE of a comparison of the data against nine-year mean satellite-derived LAI at those sites. Continentally, Lopt had a R2 of over 70% when compared to satellite-derived LAI, which is comparable to the R2 obtained when different satellite products are compared against each other. The predicted response of Lopt to the increase in atmospheric CO2 over the last 30 years also agreed with the estimate based on satellite-derivatives. Our results indicate that long-term equilibrium LAI can be successfully predicted from a simple application of ecohydrological theory. We suggest that this theory could be usefully incorporated into terrestrial vegetation models to improve their predictions of LAI.

Evaluation and Validation of Updated MODIS C6 and VIIRS LAI/FPAR

NASA Astrophysics Data System (ADS)

Yan, K.; Park, T.; Chen, C.; Yang, B.; Yan, G.; Knyazikhin, Y.; Myneni, R. B.; CHOI, S.

2015-12-01

Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (0.4-0.7 μm) absorbed by vegetation (FPAR) play a key role in characterizing vegetation canopy functioning and energy absorption capacity. With radiative transfer realization, MODIS onboard NASA EOS Terra and Aqua satellites has provided globally continuous LAI/FPAR since 2000 and continuously updated the products with better quality. And NPP VIIRS shows the measurement capability to extend high-quality LAI/FPAR time series data records as a successor of MODIS. The primary objectives of this study are 1) to evaluate and validate newly updated MODIS Collection 6 (C6) LAI/FPAR product which has finer resolution (500m) and improved biome type input, and 2) to examine and adjust VIIRS LAI/FPAR algorithm for continuity with MODIS'. For MODIS C6 investigation, we basically measure the spatial coverage (i.e., main radiative transfer algorithm execution), continuity and consistency with Collection 5 (C5), and accuracy with field measured LAI/FPAR. And we also validate C6 LAI/FPAR via comparing other possible global LAI/FPAR products (e.g., GLASS and CYCLOPES) and capturing co-varying seasonal signatures with climatic variables (e.g., temperature and precipitation). For VIIRS evaluation and adjustment, we first quantify possible difference between C5 and MODIS heritage based VIIRS LAI/FPAR. Then based on the radiative transfer theory of canopy spectral invariants, we find VIIRS- and biome-specific configurable parameters (single scattering albedo and uncertainty). These two practices for MODIS C6 and VIIRS LAI/FPAR products clearly suggest that (a) MODIS C6 has better coverage and accuracy than C5, (b) C6 shows consistent spatiotemporal pattern with C5, (c) VIIRS has the potential for producing MODIS-like global LAI/FPAR Earth System Data Records.

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

USDA-ARS?s Scientific Manuscript database

The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

Monitoring and mapping leaf area index of rubber and oil palm in small watershed area

NASA Astrophysics Data System (ADS)

Rusli, N.; Majid, M. R.

2014-02-01

Existing conventional methods to determine LAI are tedious and time consuming for implementation in small or large areas. Thus, raster LAI data which are available free were downloaded for 4697.60 km2 of Sungai Muar watershed area in Johor. The aim of this study is to monitor and map LAI changes of rubber and oil palm throughout the years from 2002 to 2008. Raster datasets of LAI value were obtained from the National Aeronautics and Space Administration (NASA) website of available years from 2002 to year 2008. These data, were mosaicked and subset utilizing ERDAS Imagine 9.2. Next, the LAI raster dataset was multiplied by a scale factor of 0.1 to derive the final LAI value. Afterwards, to determine LAI values of rubber and oil palms, the boundaries of each crop from land cover data of the years 2002, 2006 and 2008 were exploited to overlay with LAI raster dataset. A total of 5000 sample points were generated utilizing the Hawths Tool (extension in ARcGIS 9.2) within these boundaries area and utilized for extracting LAI value of oil palm and rubber. In integration, a wide range of literature review was conducted as a guideline to derive LAI value of oil palm and rubber which range from 0 to 6. The results show, an overall mean LAI value from year 2002 to 2008 as decremented from 4.12 to 2.5 due to land cover transition within these years. In 2002, the mean LAI value of rubber and oil palm is 2.65 and 2.53 respectively. Meanwhile in 2006, the mean LAI value for rubber and oil palm is 2.54 and 2.82 respectively. In 2008, the mean LAI value for both crops is 0.85 for rubber and 1.04 for oil palm. In conclusion, apart from the original function of LAI which is related to the growth and metabolism of vegetation, the changes of LAI values from year 2002 to 2008 also capable to explain the process of land cover changes in a watershed area.

Analysis on Difference of Forest Phenology Extracted from EVI and LAI Based on PhenoCams

NASA Astrophysics Data System (ADS)

Wang, C.; Jing, L.; Qinhuo, L.

2017-12-01

Land surface phenology can make up for the deficiency of field observation with advantages of capturing the continuous expression of phenology on a large scale. However, there are some variability in phenological metrics derived from different satellite time-series data of vegetation parameters. This paper aims at assessing the difference of phenology information extracted from EVI and LAI time series. To achieve this, some web-camera sites were selected to analyze the characteristics between MODIS-EVI and MODIS-LAI time series from 2010 to 2014 for different forest types, including evergreen coniferous forest, evergreen broadleaf forest, deciduous coniferous forest and deciduous broadleaf forest. At the same time, satellite-based phenological metrics were extracted by the Logistics algorithm and compared with camera-based phenological metrics. Results show that the SOS and EOS that are extracted from LAI are close to bud burst and leaf defoliation respectively, while the SOS and EOS that are extracted from EVI is close to leaf unfolding and leaf coloring respectively. Thus the SOS that is extracted from LAI is earlier than that from EVI, while the EOS that is extracted from LAI is later than that from EVI at deciduous forest sites. Although the seasonal variation characteristics of evergreen forests are not apparent, significant discrepancies exist in LAI time series and EVI time series. In addition, Satellite- and camera-based phenological metrics agree well generally, but EVI has higher correlation with the camera-based canopy greenness (green chromatic coordinate, gcc) than LAI.

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates

Extracting leaf area index using viewing geometry effects-A new perspective on high-resolution unmanned aerial system photography

NASA Astrophysics Data System (ADS)

Roth, Lukas; Aasen, Helge; Walter, Achim; Liebisch, Frank

2018-07-01

Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI prediction accuracy was comparable with the one of a gap fraction-based handheld device (R2 of 0.92 , RMSE of 0.42 m 2m-2) and correlated well with destructive LAI measurements (R2 of 0.89 , RMSE of 0.41 m2 m-2). These results indicate that, if respecting the range (LAI ≤ 3) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 2; Implementation, Analysis and Validation

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Samanta, Arindam; Schull, Mitchell A.; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramajrushna R,; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

Assimilation of LAI time-series in crop production models

NASA Astrophysics Data System (ADS)

Kooistra, Lammert; Rijk, Bert; Nannes, Louis

2014-05-01

Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor

Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

PubMed

Smettem, Keith R J; Waring, Richard H; Callow, John N; Wilson, Melissa; Mu, Qiaozhen

2013-08-01

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes. © 2013 John Wiley & Sons Ltd.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species.

PubMed

Gilardelli, Carlo; Orlando, Francesca; Movedi, Ermes; Confalonieri, Roberto

2018-03-29

Digital hemispherical photography (DHP) has been widely used to estimate leaf area index (LAI) in forestry. Despite the advancement in the processing of hemispherical images with dedicated tools, several steps are still manual and thus easily affected by user's experience and sensibility. The purpose of this study was to quantify the impact of user's subjectivity on DHP LAI estimates for broad-leaved woody canopies using the software Can-Eye. Following the ISO 5725 protocol, we quantified the repeatability and reproducibility of the method, thus defining its precision for a wide range of broad-leaved canopies markedly differing for their structure. To get a complete evaluation of the method accuracy, we also quantified its trueness using artificial canopy images with known canopy cover. Moreover, the effect of the segmentation method was analysed. The best results for precision (restrained limits of repeatability and reproducibility) were obtained for high LAI values (>5) with limits corresponding to a variation of 22% in the estimated LAI values. Poorer results were obtained for medium and low LAI values, with a variation of the estimated LAI values that exceeded the 40%. Regardless of the LAI range explored, satisfactory results were achieved for trees in row-structured plantations (limits almost equal to the 30% of the estimated LAI). Satisfactory results were achieved for trueness, regardless of the canopy structure. The paired t -test revealed that the effect of the segmentation method on LAI estimates was significant. Despite a non-negligible user effect, the accuracy metrics for DHP are consistent with those determined for other indirect methods for LAI estimates, confirming the overall reliability of DHP in broad-leaved woody canopies.

Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species

PubMed Central

Gilardelli, Carlo; Orlando, Francesca; Movedi, Ermes; Confalonieri, Roberto

2018-01-01

Digital hemispherical photography (DHP) has been widely used to estimate leaf area index (LAI) in forestry. Despite the advancement in the processing of hemispherical images with dedicated tools, several steps are still manual and thus easily affected by user’s experience and sensibility. The purpose of this study was to quantify the impact of user’s subjectivity on DHP LAI estimates for broad-leaved woody canopies using the software Can-Eye. Following the ISO 5725 protocol, we quantified the repeatability and reproducibility of the method, thus defining its precision for a wide range of broad-leaved canopies markedly differing for their structure. To get a complete evaluation of the method accuracy, we also quantified its trueness using artificial canopy images with known canopy cover. Moreover, the effect of the segmentation method was analysed. The best results for precision (restrained limits of repeatability and reproducibility) were obtained for high LAI values (>5) with limits corresponding to a variation of 22% in the estimated LAI values. Poorer results were obtained for medium and low LAI values, with a variation of the estimated LAI values that exceeded the 40%. Regardless of the LAI range explored, satisfactory results were achieved for trees in row-structured plantations (limits almost equal to the 30% of the estimated LAI). Satisfactory results were achieved for trueness, regardless of the canopy structure. The paired t-test revealed that the effect of the segmentation method on LAI estimates was significant. Despite a non-negligible user effect, the accuracy metrics for DHP are consistent with those determined for other indirect methods for LAI estimates, confirming the overall reliability of DHP in broad-leaved woody canopies. PMID:29596376

Evaluating Hyperspectral Vegetation Indices for Leaf Area Index Estimation of Oryza sativa L. at Diverse Phenological Stages

PubMed Central

Din, Mairaj; Zheng, Wen; Rashid, Muhammad; Wang, Shanqin; Shi, Zhihua

2017-01-01

Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measurements were carried out over 2 years (2015 and 2016) in Meichuan, Hubei, China. Different N fertilization, 0, 45, 82, 127, 165, 210, 247, and 292 kg ha-1, were applied to generate various scales of VIs and LAI values. Regression models were used to perform quantitative analyses between spectral VIs and LAI measured under different phenological stages. In addition, the coefficient of determination and RMSE were employed to evaluate these models. Among the nine VIs, the ratio vegetation index, normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), modified triangular vegetation index (MTVI2) and exhibited strong and significant relationships with the LAI estimation at different phenological stages. The enhanced vegetation index performed moderately. However, the green normalized vegetation index and blue normalized vegetation index confirmed that there is potential for crop LAI estimation at early phenological stages; the soil-adjusted vegetation index and optimized soil-adjusted vegetation index were more related to the soil optical properties, which were predicted to be the least accurate for LAI estimation. The noise equivalent accounted for the sensitivity of the VIs and MSAVI, MTVI2, and NDVI for the LAI estimation at phenological stages. The results note that LAI at different crop phenological stages has a significant influence on the potential of hyperspectral derived VIs under different N management practices. PMID:28588596

Evaluation and Intercomparison of MODIS and GEOV1 Global Leaf Area Index Products over Four Sites in North China

PubMed Central

Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping

2015-01-01

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + Aqua MODIS and Terra MODIS LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509

Leaf Area Index Estimation in Vineyards from Uav Hyperspectral Data, 2d Image Mosaics and 3d Canopy Surface Models

NASA Astrophysics Data System (ADS)

Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.

2015-08-01

The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.

An enhanced approach for the use of satellite-derived leaf area index values in dry deposition modeling in the Athabasca oil sands region.

PubMed

Davies, Mervyn; Cho, Sunny; Spink, David; Pauls, Ron; Desilets, Michael; Shen, Yan; Bajwa, Kanwardeep; Person, Reid

2016-12-15

In the Athabasca oil sands region (AOSR) of Northern Alberta, the dry deposition of sulphur and nitrogen compounds represents a major fraction of total (wet plus dry) deposition due to oil sands emissions. The leaf area index (LAI) is a critical parameter that affects the dry deposition of these gaseous and particulate compounds to the surrounding boreal forest canopy. For this study, LAI values based on Moderate Resolution Imaging Spectroradiometer satellite imagery were obtained and compared to ground-based measurements, and two limitations with the satellite data were identified. The satellite LAI data firstly represents one-sided LAI values that do not account for the enhanced LAI associated with needle leaf geometry, and secondly, underestimates LAI in winter-time northern latitude regions. An approach for adjusting satellite LAI values for different boreal forest cover types, as a function of time of year, was developed to produce more representative LAI values that can be used by air quality sulphur and nitrogen deposition models. The application of the approach increases the AOSR average LAI for January from 0.19 to 1.40, which represents an increase of 637%. Based on the application of the CALMET/CALPUFF model system, this increases the predicted regional average dry deposition of sulphur and nitrogen compounds for January by factors of 1.40 to 1.30, respectively. The corresponding AOSR average LAI for July increased from 2.8 to 4.0, which represents an increase of 43%. This increases the predicted regional average dry deposition of sulphur and nitrogen compounds for July by factors of 1.28 to 1.22, respectively. These findings reinforce the importance of the LAI metric for predicting the dry deposition of sulphur and nitrogen compounds. While satellite data can provide enhanced spatial and temporal resolution, adjustments are identified to overcome associated limitations. This work is considered to have application for other deposition model studies where

Measuring Effective Leaf Area Index, Foliage Profile, and Stand Height in New England Forest Stands Using a Full-Waveform Ground-Based Lidar

NASA Technical Reports Server (NTRS)

Zhao, Feng; Yang, Xiaoyuan; Schull, Mithcell A.; Roman-Colon, Miguel O.; Yao, Tian; Wang, Zhuosen; Zhang, Qingling; Jupp, David L. B.; Lovell, Jenny L.; Culvenor, Darius;

Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Saatchi, S. S.; Shugart, H. H.; Wshington-Allen, R. A.

2007-05-01

Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, p <0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 +0.074*radarsat+1.56*SR, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.

Practical field methods of estimating canopy cover, PAR, and LAI in Michigan Oak and pine stands

Treesearch

David S. Buckley; J.G. Isebrands; Terry L. Sharik

1999-01-01

With the increased use of variables such as canopy cover photosynthetically active radiation (PAR) and overstory leaf area index (LAI) in forestry research, relationships between these variables and traditional forestry variables must be defined before recommended levels of these research variables can be achieved by forestry practitioners on the ground. We measured...

Leaf and fine root carbon stocks and turnover are coupled across Arctic ecosystems.

PubMed

Sloan, Victoria L; Fletcher, Benjamin J; Press, Malcolm C; Williams, Mathew; Phoenix, Gareth K

2013-12-01

Estimates of vegetation carbon pools and their turnover rates are central to understanding and modelling ecosystem responses to climate change and their feedbacks to climate. In the Arctic, a region containing globally important stores of soil carbon, and where the most rapid climate change is expected over the coming century, plant communities have on average sixfold more biomass below ground than above ground, but knowledge of the root carbon pool sizes and turnover rates is limited. Here, we show that across eight plant communities, there is a significant positive relationship between leaf and fine root turnover rates (r(2) = 0.68, P < 0.05), and that the turnover rates of both leaf (r(2) = 0.63, P < 0.05) and fine root (r(2) = 0.55, P < 0.05) pools are strongly correlated with leaf area index (LAI, leaf area per unit ground area). This coupling of root and leaf dynamics supports the theory of a whole-plant economics spectrum. We also show that the size of the fine root carbon pool initially increases linearly with increasing LAI, and then levels off at LAI = 1 m(2) m(-2), suggesting a functional balance between investment in leaves and fine roots at the whole community scale. These ecological relationships not only demonstrate close links between above and below-ground plant carbon dynamics but also allow plant carbon pool sizes and their turnover rates to be predicted from the single readily quantifiable (and remotely sensed) parameter of LAI, including the possibility of estimating root data from satellites. © 2013 John Wiley & Sons Ltd.

Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna.

Treesearch

William A. Hoffmann; Edson Rangel da Silva; Gustavo C. Machado; Sandra Bucci; Fabian G. Scholz; Guillermo Goldstein; Frederick C. Meinzer

2005-01-01

Interactions between trees and grasses that influence leaf area index (LAI) have important consequences for savanna ecosystem processes through their controls on water, carbon, and energy fluxes as well as fire regimes. We measured LAI, of the groundlayer (herbaceous and woody plants 1-m tall), in the Brazilian...

LAI (in situ, simulated, Landsat-derived, and MODIS): A comparison within an Oak-Hickory Forest Complex in southwestern Virginia, USA.

EPA Science Inventory

The United States Environmental Protection Agency’s Environmental Sciences and Atmospheric Modeling Analysis Divisions are investigating the viability of simulated (i.e., ‘modeled’) leaf area index (LAI) inputs into various regional and local scale air quality models. Satellite L...

MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere.

Treesearch

Warren B. Cohen; Thomas K. Maiersperger; David P. Turner; William D. Ritts; Dirk Pflugmacher; Robert E. Kennedy; Alan Kirschbaum; Steven W. Running; Marcos Costa; Stith T. Gower

2006-01-01

Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS...

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Temporal Stability of the NDVI-LAI Relationship in a Napa Valley Vineyard

NASA Technical Reports Server (NTRS)

Johnson, L. F.

2003-01-01

Remotely sensed normalized difference vegetation index (NDVI) values, derived from high-resolution satellite images, were compared with ground measurements of vineyard leaf area index (LAI) periodically during the 2001 growing season. The two variables were strongly related at six ground calibration sites on each of four occasions (r squared = 0.91 to 0.98). Linear regression equations relating the two variables did not significantly differ by observation date, and a single equation accounted for 92 percent of the variance in the combined dataset. Temporal stability of the relationship opens the possibility of transforming NDVI maps to LAI in the absence of repeated ground calibration fieldwork. In order to take advantage of this circumstance, however, steps should be taken to assure temporal consistency in spectral data values comprising the NDVI.

Retrieval of Vertical LAI Profiles Over Tropical Rain Forests using Waveform Lidar at La Selva, Costa Rica

NASA Technical Reports Server (NTRS)

Tang, Hao; Dubayah, Ralph; Swatantra, Anu; Hofton, Michelle; Sheldon, Sage; Clark, David B.; Blair, Bryan

2012-01-01

This study explores the potential of waveform lidar in mapping the vertical and spatial distributions of leaf area index (LAI) over the tropical rain forest of La Selva Biological Station in Costa Rica. Vertical profiles of LAI were derived at 0.3 m height intervals from the Laser Vegetation Imaging Sensor (LVIS) data using the Geometric Optical and Radiative Transfer (GORT) model. Cumulative LAI profiles obtained from LVIS were validated with data from 55 ground to canopy vertical transects using a modular field tower to destructively sample all vegetation. Our results showed moderate agreement between lidar and field derived LAI (r2=0.42, RMSE=1.91, bias=-0.32), which further improved when differences between lidar and tower footprint scales (r2=0.50, RMSE=1.79, bias=0.27) and distance of field tower from lidar footprint center (r2=0.63, RMSE=1.36, bias=0.0) were accounted for. Next, we mapped the spatial distribution of total LAI across the landscape and analyzed LAI variations over different land cover types. Mean values of total LAI were 1.74, 5.20, 5.41 and 5.62 over open pasture, secondary forests, regeneration forests after selective-logging and old-growth forests respectively. Lastly, we evaluated the sensitivities of our LAI retrieval model to variations in canopy/ground reflectance ratio and to waveform noise such as induced by topographic slopes. We found for both, that the effects were not significant for moderate LAI values (about 4). However model derivations of LAI might be inaccurate in areas of high-slope and high LAI (about 8) if ground return energies are low. This research suggests that large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the high LAI levels in tropical rain forests and may be a useful tool for understanding the light transmittance within these canopies.

Leaf area and structural changes after thinning in even-aged Picea rubens and Abies balsamea stands in Maine, USA

Treesearch

R. Justin DeRose; Robert S. Seymour

2012-01-01

We tested the hypothesis that changes in leaf area index (LAIm2 m-2) and mean stand diameter following thinning are due to thinning type and residual density. The ratios of pre- to postthinning diameter and LAI were used to assess structural changes between replicated crown, dominant, and low thinning treatments to 33% and 50% residual density in even-aged Picea rubens...

Do the energy fluxes and surface conductance of boreal coniferous forests in Europe scale with leaf area?

PubMed

Launiainen, Samuli; Katul, Gabriel G; Kolari, Pasi; Lindroth, Anders; Lohila, Annalea; Aurela, Mika; Varlagin, Andrej; Grelle, Achim; Vesala, Timo

2016-12-01

Earth observing systems are now routinely used to infer leaf area index (LAI) given its significance in spatial aggregation of land surface fluxes. Whether LAI is an appropriate scaling parameter for daytime growing season energy budget, surface conductance (G s ), water- and light-use efficiency and surface-atmosphere coupling of European boreal coniferous forests was explored using eddy-covariance (EC) energy and CO 2 fluxes. The observed scaling relations were then explained using a biophysical multilayer soil-vegetation-atmosphere transfer model as well as by a bulk G s representation. The LAI variations significantly alter radiation regime, within-canopy microclimate, sink/source distributions of CO 2 , H 2 O and heat, and forest floor fluxes. The contribution of forest floor to ecosystem-scale energy exchange is shown to decrease asymptotically with increased LAI, as expected. Compared with other energy budget components, dry-canopy evapotranspiration (ET) was reasonably 'conservative' over the studied LAI range 0.5-7.0 m 2 m -2 . Both ET and G s experienced a minimum in the LAI range 1-2 m 2 m -2 caused by opposing nonproportional response of stomatally controlled transpiration and 'free' forest floor evaporation to changes in canopy density. The young forests had strongest coupling with the atmosphere while stomatal control of energy partitioning was strongest in relatively sparse (LAI ~2 m 2 m -2 ) pine stands growing on mineral soils. The data analysis and model results suggest that LAI may be an effective scaling parameter for net radiation and its partitioning but only in sparse stands (LAI <3 m 2 m -2 ). This finding emphasizes the significance of stand-replacing disturbances on the controls of surface energy exchange. In denser forests, any LAI dependency varies with physiological traits such as light-saturated water-use efficiency. The results suggest that incorporating species traits and site conditions are necessary when LAI is used in

Satellite derived estimates of forest leaf area index in South-west Western Australia are not tightly coupled to inter-annual variations in rainfall: implications for groundwater decline in a drying climate.

NASA Astrophysics Data System (ADS)

Smettem, Keith; Waring, Richard; Callow, Nik; Wilson, Melissa; Mu, Qiaozhen

2013-04-01

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. Ecological optimality proposes that the long term average canopy size of undisturbed perennial vegetation is tightly coupled to climate. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study we analysed satellite-derived estimates of monthly LAI across forested coastal catchments of South-west Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, inter-annual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long term decline in areal average underground water storage storage and diminished summer flows, with a trend towards more ephemeral flow regimes.

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

USDA-ARS?s Scientific Manuscript database

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and funct...

[Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].

PubMed

Han, Zhao-ying; Zhu, Xi-cun; Fang, Xian-yi; Wang, Zhuo-yuan; Wang, Ling; Zhao, Geng-Xing; Jiang, Yuan-mao

2016-03-01

Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation. The Red Fuji apple trees of full bearing fruit are the researching objects. Ninety apple trees canopies spectral reflectance and LAI values were measured by the ASD Fieldspec3 spectrometer and LAI-2200 in thirty orchards in constant two years in Qixia research area of Shandong Province. The optimal vegetation indices were selected by the method of correlation analysis of the original spectral reflectance and vegetation indices. The models of predicting the LAI were built with the multivariate regression analysis method of support vector machine (SVM) and random forest (RF). The new vegetation indices, GNDVI527, ND-VI676, RVI682, FD-NVI656 and GRVI517 and the previous two main vegetation indices, NDVI670 and NDVI705, are in accordance with LAI. In the RF regression model, the calibration set decision coefficient C-R2 of 0.920 and validation set decision coefficient V-R2 of 0.889 are higher than the SVM regression model by 0.045 and 0.033 respectively. The root mean square error of calibration set C-RMSE of 0.249, the root mean square error validation set V-RMSE of 0.236 are lower than that of the SVM regression model by 0.054 and 0.058 respectively. Relative analysis of calibrating error C-RPD and relative analysis of validation set V-RPD reached 3.363 and 2.520, 0.598 and 0.262, respectively, which were higher than the SVM regression model. The measured and predicted the scatterplot trend line slope of the calibration set and validation set C-S and V-S are close to 1. The estimation result of RF regression model is better than that of the SVM. RF regression model can be used to estimate the LAI of red Fuji apple trees in full fruit period.

Leaf-IT: An Android application for measuring leaf area.

PubMed

Schrader, Julian; Pillar, Giso; Kreft, Holger

2017-11-01

The use of plant functional traits has become increasingly popular in ecological studies because plant functional traits help to understand key ecological processes in plant species and communities. This also includes changes in diversity, inter- and intraspecific interactions, and relationships of species at different spatiotemporal scales. Leaf traits are among the most important traits as they describe key dimensions of a plant's life history strategy. Further, leaf area is a key parameter with relevance for other traits such as specific leaf area, which in turn correlates with leaf chemical composition, photosynthetic rate, leaf longevity, and carbon investment. Measuring leaf area usually involves the use of scanners and commercial software and can be difficult under field conditions. We present Leaf-IT, a new smartphone application for measuring leaf area and other trait-related areas. Leaf-IT is free, designed for scientific purposes, and runs on Android 4 or higher. We tested the precision and accuracy using objects with standardized area and compared the area measurements of real leaves with the well-established, commercial software WinFOLIA using the Altman-Bland method. Area measurements of standardized objects show that Leaf-IT measures area with high accuracy and precision. Area measurements with Leaf-IT of real leaves are comparable to those of WinFOLIA. Leaf-IT is an easy-to-use application running on a wide range of smartphones. That increases the portability and use of Leaf-IT and makes it possible to measure leaf area under field conditions typical for remote locations. Its high accuracy and precision are similar to WinFOLIA. Currently, its main limitation is margin detection of damaged leaves or complex leaf morphologies.

A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes

NASA Astrophysics Data System (ADS)

Montane, F.; Fox, A. M.; Arellano, A. F.; Alexander, M. R.; Moore, D. J.

2016-12-01

Carbon (C) allocation to different plant tissues (leaves, stem and roots) remains a central challenge for understanding the global C cycle, as it determines C residence time. We used a diverse set of observations (AmeriFlux eddy covariance towers, biomass estimates from tree-ring data, and Leaf Area Index measurements) to compare C fluxes, pools, and Leaf Area Index (LAI) data with the Community Land Model (CLM). We ran CLM for seven temperate forests in North America (including evergreen and deciduous sites) between 1980 and 2013 using different C allocation schemes: i) standard C allocation scheme in CLM, which allocates C to the stem and leaves as a dynamic function of annual net primary productivity (NPP); ii) two fixed C allocation schemes, one representative of evergreen and the other one of deciduous forests, based on Luyssaert et al. 2007; iii) an alternative C allocation scheme, which allocated C to stem and leaves, and to stem and coarse roots, as a dynamic function of annual NPP, based on Litton et al. 2007. At our sites CLM usually overestimated gross primary production and ecosystem respiration, and underestimated net ecosystem exchange. Initial aboveground biomass in 1980 was largely overestimated for deciduous forests, whereas aboveground biomass accumulation between 1980 and 2011 was highly underestimated for both evergreen and deciduous sites due to the lower turnover rate in the sites than the one used in the model. CLM overestimated LAI in both evergreen and deciduous sites because the Leaf C-LAI relationship in the model did not match the observed Leaf C-LAI relationship in our sites. Although the different C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, one of the alternative C allocation schemes used (iii) gave more realistic stem C/leaf C ratios, and highly reduced the overestimation of initial

Quantifying forest LAI succession in sub-tropical forests using time-series of Landsat data, 1987 -2015

NASA Astrophysics Data System (ADS)

Wu, Q.; Song, J.; Wang, J.; Chen, S.; Yu, B.; Liao, L.

2016-12-01

Monitoring the dynamics of leaf area index (LAI) throughout the life-cycle of forests (from seeding to maturity) is vital for simulating forest growth and quantifying carbon sequestration. However, all current global LAI produts show extremely low accuracy in forests and the coarse spatial resolution(nearly 1-km) mismatch with the spatial scale of forest inventory plots (nearly 26m*26m). To date, several studies have explored the possibility of satellite data to classify forest succession or predict stand age. And a few studies have explored the potential of using long term Landsat data to monitor the growing trend of forests, but no studies have quantified the inter-annual and intra-annual LAI dynamics along with forest succession. Vegetation indexes are not perfect variables in quantifying forest foliage dynamics. Hallet (1995) suggested remote sensing of biophysical characteristics should shift away from direct inference from vegetation indices toward more physically based algorithms. This work intends to be a pioneer example for improving the accuracy of forests LAI and providing temporal-spatial matching LAI datasets for monitoring forest processes. We integrates the Geometric-Optical and Radiative Transfer (GORT) model with the Physiological Principles Predicting Growth (3-PG) model to improve the estimation of the forest canopy LAI dynamics. Reflectance time-series data from 1987 to 2015 were collected and preprocessed for forests in southern China, using all available Landsat data (with <80% cloud). Effective LAI and true LAI were field measured to validate our results using various instruments, including digital hemispheric photographs (DHP), LAI-2000 Plant Canopy Analyzer (LI-COR), and Tracing radiation and Architecture of Canopies (TRAC). Results show that the relationship between spectral metrics of satellite images and forest LAI is clear in early stages before maturity. 3-PG provide accurate inter-annual trend of forest LAI, while satellite images

Architecture of the Black Moshannon forest canopy measured by hemispherical photographs and a LI-COR LAI-2000 sensor

Treesearch

Y. S. Wang; J. Welles; D. R. Miller; D. E. Anderson; G. Heisler; M. McManus

1991-01-01

Non-destructive measurements of light penetration were made at 10 heights in the canopy on twelve different sites in the PA oak forest where the Blackmo 88 spray-micrometeorological experiment was conducted. Vertical profiles of Leaf Area Index, LAI, were calculated from these measurements, and the data were used to define the spatial variability of the forest canopy...

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index

PubMed Central

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-01-01

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data. PMID:27879906

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index.

PubMed

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-06-06

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data.

Assessing soybean leaf area and leaf biomass by spectral measurements

NASA Technical Reports Server (NTRS)

Holben, B. N.; Tucker, C. J.; Fan, C. J.

1979-01-01

Red and photographic infrared spectral radiances were correlated with soybean total leaf area index, green leaf area index, chlorotic leaf area index, green leaf biomass, chlorotic leaf biomass, and total biomass. The most significant correlations were found to exist between the IR/red radiance ratio data and green leaf area index and/or green leaf biomass (r squared equals 0.85 and 0.86, respectively). These findings demonstrate that remote sensing data can supply information basic to soybean canopy growth, development, and status by nondestructive determination of the green leaf area or green leaf biomass.

Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest

NASA Astrophysics Data System (ADS)

Tian, Jinyan; Wang, Le; Li, Xiaojuan; Gong, Huili; Shi, Chen; Zhong, Ruofei; Liu, Xiaomeng

2017-09-01

Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has been reported in several studies. However, in most forests, the challenges associated with the interference from a complex background and a variety of vegetation species have hindered research using UAV images. To the best of our knowledge, very few studies have mapped the forest LAI with a UAV image. In addition, the drawbacks and advantages of estimating the forest LAI with UAV and satellite images at high spatial resolution remain a knowledge gap in existing literature. Therefore, this paper aims to map LAI in a mangrove forest with a complex background and a variety of vegetation species using a UAV image and compare it with a WorldView-2 image (WV2). In this study, three representative NDVIs, average NDVI (AvNDVI), vegetated specific NDVI (VsNDVI), and scaled NDVI (ScNDVI), were acquired with UAV and WV2 to predict the plot level (10 × 10 m) LAI. The results showed that AvNDVI achieved the highest accuracy for WV2 (R2 = 0.778, RMSE = 0.424), whereas ScNDVI obtained the optimal accuracy for UAV (R2 = 0.817, RMSE = 0.423). In addition, an overall comparison results of the WV2 and UAV derived LAIs indicated that UAV obtained a better accuracy than WV2 in the plots that were covered with homogeneous mangrove species or in the low LAI plots, which was because UAV can effectively eliminate the influence from the background and the vegetation species owing to its high spatial resolution. However, WV2 obtained a slightly higher accuracy than UAV in the plots covered with a variety of mangrove species, which was because the UAV sensor provides a negative spectral response function(SRF) than WV2 in terms of the mangrove LAI estimation.

VIS and NIR land surface albedo sensitivity of the Ent Terrestrial Biosphere Model to forcing leaf area index

NASA Astrophysics Data System (ADS)

Montes, C.; Kiang, N. Y.; Ni-Meister, W.; Yang, W.; Schaaf, C.; Aleinov, I. D.; Jonas, J.; Zhao, F. A.; Yao, T.; Wang, Z.; Sun, Q.; Carrer, D.

2016-12-01

Land surface albedo is a major controlling factor in vegetation-atmosphere transfers, modifying the components of the energy budget, the ecosystem productivity and patterns of regional and global climate. General Circulation Models (GCMs) are coupled to Dynamic Global Vegetation Models (DGVMs) to solve vegetation albedo by using simple schemes prescribing albedo based on vegetation classification, and approximations of canopy radiation transport for multiple plant functional types (PFTs). In this work, we aim at evaluating the sensitivity of the NASA Ent Terrestrial Biosphere Model (TBM), a demographic DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM, in estimating VIS and NIR surface albedo by using variable forcing leaf area index (LAI). The Ent TBM utilizes a new Global Vegetation Structure Dataset (GVSD) to account for geographically varying vegetation tree heights and densities, as boundary conditions to the gap-probability based Analytical Clumped Two-Stream (ACTS) canopy radiative transfer scheme (Ni-Meister et al., 2010). Land surface and vegetation characteristics for the Ent GVSD are obtained from a number of earth observation platforms and algorithms, including the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and plant functional types (PFTs) (Friedl et al., 2010), soil albedo derived from MODIS (Carrer et al., 2014), and vegetation height from the Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice, Cloud, and land Elevation Satellite) (Simard et al., 2011; Tang et al., 2014). Three LAI products are used as input to ACTS/Ent TBM: MODIS MOD15A2H product (Yang et al., 2006), Beijing Normal University LAI (Yuan et al., 2011), and Global Data Sets of Vegetation (LAI3g) (Zhu et al. 2013). The sensitivity of the Ent TBM VIS and NIR albedo to the three LAI products is assessed, compared against the previous GISS GCM vegetation classification and prescribed Lambertian albedoes (Matthews, 1984), and against

A Study toward the Evaluation of ALOS Images for LAI Estimation in Rice Fields

NASA Astrophysics Data System (ADS)

Sharifi Hashjin, Sh.; Darvishzadeh, R.; Khandan, R.

2013-10-01

For expanding and managing agricultural sources, satellite data have a key role in determining required information about different factors in plants Including Leaf Area Index (LAI).This paper has studied the potential of spectral indices in estimating rice canopy LAI in Amol city as one of the main sources of rice production in Iran. Due to its importance in provision of food and calorie of a major portion of population, rice product was chosen for study. A field campaign was conducted when rice was in the max growth stage (late of June). Also, two satellite images from ALOS-AVNIR-2 were used (simultaneous with conducted field works) to extract and determine vegetation indices. Then the Regression between measured data and vegetation indices, derived from combination of different bands, was evaluated and after that suitable vegetation indices were realized. Finally, statistics and calculations for introduction of a suitable model were presented. After examination of models, the results showed that RDVI and SAVI2, by determination coefficient and RMSE of 0.12-0.59 and 0.24-0.62, have more accuracy in LAI estimation. Results of present study demonstrated the potential of ALOS images, for LAI estimation and their significant role in monitoring and managing the rice plant.

Effects of Controlled-Release Fertilizer on Leaf Area Index and Fruit Yield in High-Density Soilless Tomato Culture Using Low Node-Order Pinching

PubMed Central

Kinoshita, Takafumi; Yano, Takayoshi; Sugiura, Makoto; Nagasaki, Yuji

2014-01-01

To further development of a simplified fertigation system using controlled-release fertilizers (CRF), we investigated the effects of differing levels of fertilizers and plant density on leaf area index (LAI), fruit yields, and nutrient use in soilless tomato cultures with low node-order pinching and high plant density during spring-summer (SS), summer-fall (SF), and fall-winter (FW) seasons. Plants were treated with 1 of 3 levels of CRF in a closed system, or with liquid fertilizer (LF) with constant electrical conductivity (EC) in a drip-draining system. Two plant densities were examined for each fertilizer treatment. In CRF treatments, LAI at pinching increased linearly with increasing nutrient supply for all cropping seasons. In SS, both light interception by plant canopy at pinching and total marketable fruit yield increased linearly with increasing LAI up to 6 m2·m−2; the maximization point was not reached for any of the treatments. In FW, both light interception and yield were maximized at an LAI of approximately 4. These results suggest that maximizing the LAI in SS and FW to the saturation point for light interception is important for increasing yield. In SF, however, the yield maximized at an LAI of approximately 3, although the light interception linearly increased with increasing LAI, up to 4.5. According to our results, the optimal LAI at pinching may be 6 in SS, 3 in SF, and 4 in FW. In comparing LAI values with similar fruit yield, we found that nutrient supply was 32−46% lower with the CRF method than with LF. In conclusion, CRF application in a closed system enables growers to achieve a desirable LAI to maximize fruit yield with a regulated amount of nutrient supply per unit area. Further, the CRF method greatly reduced nutrient use without decreasing fruit yield at similar LAIs, as compared to the LF method. PMID:25402478

Spatial variation and seasonal dynamics of leaf-area index in the arctic tundra-implications for linking ground observations and satellite images

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Räsänen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika

2017-09-01

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Sources of Uncertainty in the Prediction of LAI / fPAR from MODIS

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Ganapol, Barry D.; Brass, James A. (Technical Monitor)

2002-01-01

To explicate the sources of uncertainty in the prediction of biophysical variables over space, consider the general equation: where z is a variable with values on some nominal, ordinal, interval or ratio scale; y is a vector of input variables; u is the spatial support of y and z ; x and u are the spatial locations of y and z , respectively; f is a model and B is the vector of the parameters of this model. Any y or z has a value and a spatial extent which is called its support. Viewed in this way, categories of uncertainty are from variable (e.g. measurement), parameter, positional. support and model (e.g. structural) sources. The prediction of Leaf Area Index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) are examples of z variables predicted using model(s) as a function of y variables and spatially constant parameters. The MOD15 algorithm is an example of f, called f(sub 1), with parameters including those defined by one of six biome types and solar and view angles. The Leaf Canopy Model (LCM)2, a nested model that combines leaf radiative transfer with a full canopy reflectance model through the phase function, is a simpler though similar radiative transfer approach to f(sub 1). In a previous study, MOD15 and LCM2 gave similar results for the broadleaf forest biome. Differences between these two models can be used to consider the structural uncertainty in prediction results. In an effort to quantify each of the five sources of uncertainty and rank their relative importance for the LAI/fPAR prediction problem, we used recent data for an EOS Core Validation Site in the broadleaf biome with coincident surface reflectance, vegetation index, fPAR and LAI products from the Moderate Resolution Imaging Spectrometer (MODIS). Uncertainty due to support on the input reflectance variable was characterized using Landsat ETM+ data. Input uncertainties were propagated through the LCM2 model and compared with published uncertainties from the MOD15

Directional effects on NDVI and LAI retrievals from MODIS: A case study in Brazil with soybean

NASA Astrophysics Data System (ADS)

Breunig, Fábio Marcelo; Galvão, Lênio Soares; Formaggio, Antônio Roberto; Epiphanio, José Carlos Neves

2011-02-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is largely used to estimate Leaf Area Index (LAI) using radiative transfer modeling (the "main" algorithm). When this algorithm fails for a pixel, which frequently occurs over Brazilian soybean areas, an empirical model (the "backup" algorithm) based on the relationship between the Normalized Difference Vegetation Index (NDVI) and LAI is utilized. The objective of this study is to evaluate directional effects on NDVI and subsequent LAI estimates using global (biome 3) and local empirical models, as a function of the soybean development in two growing seasons (2004-2005 and 2005-2006). The local model was derived from the pixels that had LAI values retrieved from the main algorithm. In order to keep the reproductive stage for a given cultivar as a constant factor while varying the viewing geometry, pairs of MODIS images acquired in close dates from opposite directions (backscattering and forward scattering) were selected. Linear regression relationships between the NDVI values calculated from these two directions were evaluated for different view angles (0-25°; 25-45°; 45-60°) and development stages (<45; 45-90; >90 days after planting). Impacts on LAI retrievals were analyzed. Results showed higher reflectance values in backscattering direction due to the predominance of sunlit soybean canopy components towards the sensor and higher NDVI values in forward scattering direction due to stronger shadow effects in the red waveband. NDVI differences between the two directions were statistically significant for view angles larger than 25°. The main algorithm for LAI estimation failed in the two growing seasons with gradual crop development. As a result, up to 94% of the pixels had LAI values calculated from the backup algorithm at the peak of canopy closure. Most of the pixels selected to compose the 8-day MODIS LAI product came from the forward scattering view because it displayed larger LAI values than the

Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2014-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982-1997) and 59 to 92.4% during validation (1998-2012). Our results suggest systematic improvements from 4 to 25% in the Nash-Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area.

PubMed

Easlon, Hsien Ming; Bloom, Arnold J

2014-07-01

Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. • Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. • Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images.

Validation and Temporal Analysis of Lai and Fapar Products Derived from Medium Resolution Sensor

NASA Astrophysics Data System (ADS)

Claverie, M.; Vermote, E. F.; Baret, F.; Weiss, M.; Hagolle, O.; Demarez, V.

2012-12-01

Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been defined as Essential Climate Variables. Many Earth surface monitoring applications are based on global estimation combined with a relatively high frequency. The medium spatial resolution sensors (MRS), such as SPOT-VGT, MODIS or MERIS, have been widely used to provide land surface products (mainly LAI and FAPAR) to the scientific community. These products require quality assessment and consistency. However, due to consistency of the ground measurements spatial sampling, the medium resolution is not appropriate for direct validation with in situ measurements sampling. It is thus more adequate to use high spatial resolution sensors which can integrate the spatial variability. The recent availability of combined high spatial (8 m) and temporal resolutions (daily) Formosat-2 data allows to evaluate the accuracy and the temporal consistency of medium resolution sensors products. In this study, we proposed to validate MRS products over a cropland area and to analyze their spatial and temporal consistency. As a matter of fact, this study belongs to the Stage 2 of the validation, as defined by the Land Product Validation sub-group of the Earth Observation Satellites. Reference maps, derived from the aggregation of Formosat-2 data (acquired during the 2006-2010 period over croplands in southwest of France), were compared with (i) two existing global biophysical variables products (GEOV1/VGT and MODIS-15 coll. 5), and (ii) a new product (MODdaily) derived from the inversion of PROSAIL radiative transfer model (EMMAH, INRA Avignon) applied on MODIS BRDF-corrected daily reflectance. Their uncertainty was calculated with 105 LAI and FAPAR reference maps, which uncertainties (22 % for LAI and 12% for FAPAR) were evaluated with in situ measurements performed over maize, sunflower and soybean. Inter-comparison of coarse resolution (0.05°) products showed that LAI and FAPAR have

Assimilating leaf area index of three typical types of subtropical forest in China from MODIS time series data based on the integrated ensemble Kalman filter and PROSAIL model

NASA Astrophysics Data System (ADS)

Li, Xuejian; Mao, Fangjie; Du, Huaqiang; Zhou, Guomo; Xu, Xiaojun; Han, Ning; Sun, Shaobo; Gao, Guolong; Chen, Liang

2017-04-01

Subtropical forest ecosystems play essential roles in the global carbon cycle and in carbon sequestration functions, which challenge the traditional understanding of the main functional areas of carbon sequestration in the temperate forests of Europe and America. The leaf area index (LAI) is an important biological parameter in the spatiotemporal simulation of the carbon cycle, and it has considerable significance in carbon cycle research. Dynamic retrieval based on remote sensing data is an important method with which to obtain large-scale high-accuracy assessments of LAI. This study developed an algorithm for assimilating LAI dynamics based on an integrated ensemble Kalman filter using MODIS LAI data, MODIS reflectance data, and canopy reflectance data modeled by PROSAIL, for three typical types of subtropical forest (Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest) in China during 2014-2015. There were some errors of assimilation in winter, because of the bad data quality of the MODIS product. Overall, the assimilated LAI well matched the observed LAI, with R2 of 0.82, 0.93, and 0.87, RMSE of 0.73, 0.49, and 0.42, and aBIAS of 0.50, 0.23, and 0.03 for Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest, respectively. The algorithm greatly decreased the uncertainty of the MODIS LAI in the growing season and it improved the accuracy of the MODIS LAI. The advantage of the algorithm is its use of biophysical parameters (e.g., measured LAI) in the LAI assimilation, which makes it possible to assimilate long-term MODIS LAI time series data, and to provide high-accuracy LAI data for the study of carbon cycle characteristics in subtropical forest ecosystems.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Improved estimation of leaf area index and leaf chlorophyll content of a potato crop using multi-angle spectral data - potential of unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Roosjen, Peter P. J.; Brede, Benjamin; Suomalainen, Juha M.; Bartholomeus, Harm M.; Kooistra, Lammert; Clevers, Jan G. P. W.

2018-04-01

In addition to single-angle reflectance data, multi-angular observations can be used as an additional information source for the retrieval of properties of an observed target surface. In this paper, we studied the potential of multi-angular reflectance data for the improvement of leaf area index (LAI) and leaf chlorophyll content (LCC) estimation by numerical inversion of the PROSAIL model. The potential for improvement of LAI and LCC was evaluated for both measured data and simulated data. The measured data was collected on 19 July 2016 by a frame-camera mounted on an unmanned aerial vehicle (UAV) over a potato field, where eight experimental plots of 30 × 30 m were designed with different fertilization levels. Dozens of viewing angles, covering the hemisphere up to around 30° from nadir, were obtained by a large forward and sideways overlap of collected images. Simultaneously to the UAV flight, in situ measurements of LAI and LCC were performed. Inversion of the PROSAIL model was done based on nadir data and based on multi-angular data collected by the UAV. Inversion based on the multi-angular data performed slightly better than inversion based on nadir data, indicated by the decrease in RMSE from 0.70 to 0.65 m2/m2 for the estimation of LAI, and from 17.35 to 17.29 μg/cm2 for the estimation of LCC, when nadir data were used and when multi-angular data were used, respectively. In addition to inversions based on measured data, we simulated several datasets at different multi-angular configurations and compared the accuracy of the inversions of these datasets with the inversion based on data simulated at nadir position. In general, the results based on simulated (synthetic) data indicated that when more viewing angles, more well distributed viewing angles, and viewing angles up to larger zenith angles were available for inversion, the most accurate estimations were obtained. Interestingly, when using spectra simulated at multi-angular sampling configurations as

Impacts of including forest understory brightness and foliage clumping information from multiangular measurements on leaf area index mapping over North America

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing M.; Alikas, Krista; Deng, Feng

2010-09-01

A new leaf area index (LAI) data set in 10 day intervals with consideration of the understory reflectance and foliage clumping effects over North America for 1 year is developed. The data set brings effectively together measurements from multiple sensors with complementary capabilities (SPOT-VEGETATION, Multiangle Imaging Spectroradiometer, POLDER). First, the temporal consistency analysis indicated the new product is on par with other available LAI data sets currently used by the community. Second, with the removal of the background (understory in forests, moss, litter, and soil) effect on the forest overstory LAI retrieval, slightly different LAI reductions were found between needleleaf and broadleaf forests. This is caused by the more clumped nature of needleleaf forests, especially at higher LAI values, which allows more light to penetrate through the overstory canopy, making the understory more visible for equal LAI as compared to broadleaf forests. This is found over a representative set of 105 CEOS Benchmark Land Multisite Analysis and Intercomparison of Products sites in North America used for indirect validation. Third, the data set was directly validated and compared with Moderate Resolution Imaging Spectroradiometer Collection 5 LAI product using results from the BigFoot project for available forest test sites. This study demonstrates that the fusion of data inputs between multiple sensors can indeed lead to improved products and that multiangle remote sensing can help us to address effectively the issues (separating the signal from the understory and overstory, foliage clumping) that could not be solved via the means of the conventional mono-angle remote sensing.

[Green space vegetation quantity in workshop area of Wuhan Iron and Steel Company].

PubMed

Chen, Fang; Zhou, Zhixiang; Wang, Pengcheng; Li, Haifang; Zhong, Yingfei

2006-04-01

Aimed at the complex community structure and higher fragmentation of urban green space, and based on the investigation of synusia structure and its coverage, this paper studied the vegetation quantity of ornamental green space in the workshop area of Wuhan Iron and Steel Company, with the help of GIS. The results showed that different life forms of ornamental plants in this area had a greater difference in their single leaf area and leaf area index (LAI), and the LAI was not only depended on single leaf area, but also governed by the shape of tree crown and the intensive degree of branches and leaves. The total vegetation quantity was 1 694.2 hm2, with the average LAI being 7.75, and the vegetation quantity of arbor-shrub-herb and arbor-shrub communities accounted for 79.7% and 92.3% of the total, respectively, reflecting that the green space structure was dominated by arbor species and by arbor-shrub-herb and arbor-shrub community types. Single layer-structured lawn had a less percentage, while the vegetation quantity of herb synusia accounted for 22.9% of the total, suggesting an afforestation characteristic of "making use of every bit of space" in the workshop area. The vegetation quantity of urban ornamental green space depended on the area of green space, its synusia structure, and the LAI and coverage of ornamental plants. In enlarging urban green space, ornamental plant species with high LAI should be selected, and community structure should be improved to have a higher vegetation quantity in urban area. To quantify the vegetation quantity of urban ornamental green space more accurately, synusia should be taken as the unit to measure the LAI of typical species, and the synusia structure and its coverage of different community types should be investigated with the help of remote sensing images and GIS.

Effects of leaf area index on the coupling between water table, land surface energy fluxes, and planetary boundary layer at the regional scale

NASA Astrophysics Data System (ADS)

Lu, Y.; Rihani, J.; Langensiepen, M.; Simmer, C.

2013-12-01

Vegetation plays an important role in the exchange of moisture and energy at the land surface. Previous studies indicate that vegetation increases the complexity of the feedbacks between the atmosphere and subsurface through processes such as interception, root water uptake, leaf surface evaporation, and transpiration. Vegetation cover can affect not only the interaction between water table depth and energy fluxes, but also the development of the planetary boundary layer. Leaf Area Index (LAI) is shown to be a major factor influencing these interactions. In this work, we investigate the sensitivity of water table, surface energy fluxes, and atmospheric boundary layer interactions to LAI as a model input. We particularly focus on the role LAI plays on the location and extent of transition zones of strongest coupling and how this role changes over seasonal timescales for a real catchment. The Terrestrial System Modelling Platform (TerrSysMP), developed within the Transregional Collaborative Research Centre 32 (TR32), is used in this study. TerrSysMP consists of the variably saturated groundwater model ParFlow, the land surface model Community Land Model (CLM), and the regional climate and weather forecast model COSMO (COnsortium for Small-scale Modeling). The sensitivity analysis is performed over a range of LAI values for different vegetation types as extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset for the Rur catchment in Germany. In the first part of this work, effects of vegetation structure on land surface energy fluxes and their connection to water table dynamics are studied using the stand-alone CLM and the coupled subsurface-surface components of TerrSysMP (ParFlow-CLM), respectively. The interconnection between LAI and transition zones of strongest coupling are investigated and analyzed through a subsequent set of subsurface-surface-atmosphere coupled simulations implementing the full TerrSysMP model system.

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

NASA Technical Reports Server (NTRS)

Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2006-01-01

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

Leaf area dynamics of conifer forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Margolis, H.; Oren, R.; Whitehead, D.

1995-07-01

Estimating the surface area of foliage supported by a coniferous forest canopy is critical for modeling its biological properties. Leaf area represents the surface area available for the interception of energy, the absorption of carbon dioxide, and the diffusion of water from the leaf to the atmosphere. The concept of leaf area is pertinent to the physiological and ecological dynamics of conifers at a wide range of spatial scales, from individual leaves to entire biomes. In fact, the leaf area of vegetation at a global level can be thought of as a carbon-absorbing, water-emitting membrane of variable thickness, which canmore » have an important influence on the dynamics and chemistry of the Earth`s atmosphere over both the short and the long term. Unless otherwise specified, references to leaf area herein refer to projected leaf area, i.e., the vertical projection of needles placed on a flat plane. Total leaf surface area is generally from 2.0 to 3.14 times that of projected leaf area for conifers. It has recently been suggested that hemisurface leaf area, i.e., one-half of the total surface area of a leaf, a more useful basis for expressing leaf area than is projected area. This chapter is concerned with the dynamics of coniferous forest leaf area at different spatial and temporal scales. In the first part, we consider various hypotheses related to the control of leaf area development, ranging from simple allometric relations with tree size to more complex mechanistic models that consider the movement of water and nutrients to tree canopies. In the second part, we consider various aspects of leaf area dynamics at varying spatial and temporal scales, including responses to perturbation, seasonal dynamics, genetic variation in crown architecture, the responses to silvicultural treatments, the causes and consequences of senescence, and the direct measurement of coniferous leaf area at large spatial scales using remote sensing.« less

A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

NASA Astrophysics Data System (ADS)

Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

2017-12-01

Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

Evaluation of the observation operator Jacobian for leaf area index data assimilation with an extended Kalman filter

NASA Astrophysics Data System (ADS)

Rüdiger, Christoph; Albergel, CléMent; Mahfouf, Jean-FrançOis; Calvet, Jean-Christophe; Walker, Jeffrey P.

2010-05-01

To quantify carbon and water fluxes between the vegetation and the atmosphere in a consistent manner, land surface models now include interactive vegetation components. These models treat the vegetation biomass as a prognostic model state, allowing the model to dynamically adapt the vegetation states to environmental conditions. However, it is expected that the prediction skill of such models can be greatly increased by assimilating biophysical observations such as leaf area index (LAI). The Jacobian of the observation operator, a central aspect of data assimilation methods such as the extended Kalman filter (EKF) and the variational assimilation methods, provides the required linear relationship between the observation and the model states. In this paper, the Jacobian required for assimilating LAI into the Interaction between the Soil, Biosphere and Atmosphere-A-gs land surface model using the EKF is studied. In particular, sensitivity experiments were undertaken on the size of the initial perturbation for estimating the Jacobian and on the length of the time window between initial state and available observation. It was found that small perturbations (0.1% of the state) typically lead to accurate estimates of the Jacobian. While other studies have shown that the assimilation of LAI with 10 day assimilation windows is possible, 1 day assimilation intervals can be chosen to comply with numerical weather prediction requirements. Moreover, the seasonal dependence of the Jacobian revealed contrasted groups of Jacobian values due to environmental factors. Further analyses showed the Jacobian values to vary as a function of the LAI itself, which has important implications for its assimilation in different seasons, as the size of the LAI increments will subsequently vary due to the variability of the Jacobian.

The prediction of leaf area index from forest polygons decomposed through the integration of remote sensing, GIS, UNIX, and C

NASA Astrophysics Data System (ADS)

Wulder, M. A.

1998-03-01

Forest stand data are normally stored in a geographic information system (GIS) on the basis of areas of similar species combinations. Polygons are created based upon species assemblages and given labels relating the percentage of areal coverage by each significant species type within the specified area. As a result, estimation of leaf area index (LAI) from the digital numbers found within GIS-stored polygons lack accuracy as the predictive equations for LAI are normally developed for individual species, not species assemblages. A Landsat TM image was acquired to enable a classification which allows for the decomposition of forest-stand polygons into greater species detail. Knowledge of the actual internal composition of the stand polygons provides for computation of LAI values based upon the appropriate predictive equation resulting in higher accuracy of these estimates. To accomplish this goal it was necessary to extract, for each cover type in each polygon, descriptive values to represent the digital numbers located in that portion of the polygon. The classified image dictates the species composition of the various portions of the polygon and within these areas the raster pixel values are tabulated and averaged. Due to a lack of existing software tools to assess the raster values occurring within GIS polygons a combination of remote sensing, GIS, UNIX, and specifically coded C programs were necessary. Such tools are frequently used by the spatial analyst and indicate the complexity of what may appear to be a straight-forward spatial analysis problem.

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

NASA Technical Reports Server (NTRS)

Peduzzi, Alicia; Wynne, Randolph Hamilton; Thomas, Valerie A.; Nelson, Ross F.; Reis, James J.; Sanford, Mark

2012-01-01

The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m) in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric), five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks) as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R2 to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors), when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest

DOE PAGES

Yang, Hualei; Yang, Xi; Heskel, Mary; ...

2017-04-28

Changes in plant phenology affect the carbon flux of terrestrial forest ecosystems due to the link between the growing season length and vegetation productivity. Digital camera imagery, which can be acquired frequently, has been used to monitor seasonal and annual changes in forest canopy phenology and track critical phenological events. However, quantitative assessment of the structural and biochemical controls of the phenological patterns in camera images has rarely been done. In this study, we used an NDVI (Normalized Difference Vegetation Index) camera to monitor daily variations of vegetation reflectance at visible and near-infrared (NIR) bands with high spatial and temporalmore » resolutions, and found that the infrared camera based NDVI (camera-NDVI) agreed well with the leaf expansion process that was measured by independent manual observations at Harvard Forest, Massachusetts, USA. We also measured the seasonality of canopy structural (leaf area index, LAI) and biochemical properties (leaf chlorophyll and nitrogen content). Here we found significant linear relationships between camera-NDVI and leaf chlorophyll concentration, and between camera-NDVI and leaf nitrogen content, though weaker relationships between camera-NDVI and LAI. Therefore, we recommend ground-based camera-NDVI as a powerful tool for long-term, near surface observations to monitor canopy development and to estimate leaf chlorophyll, nitrogen status, and LAI.« less

Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Hualei; Yang, Xi; Heskel, Mary

Changes in plant phenology affect the carbon flux of terrestrial forest ecosystems due to the link between the growing season length and vegetation productivity. Digital camera imagery, which can be acquired frequently, has been used to monitor seasonal and annual changes in forest canopy phenology and track critical phenological events. However, quantitative assessment of the structural and biochemical controls of the phenological patterns in camera images has rarely been done. In this study, we used an NDVI (Normalized Difference Vegetation Index) camera to monitor daily variations of vegetation reflectance at visible and near-infrared (NIR) bands with high spatial and temporalmore » resolutions, and found that the infrared camera based NDVI (camera-NDVI) agreed well with the leaf expansion process that was measured by independent manual observations at Harvard Forest, Massachusetts, USA. We also measured the seasonality of canopy structural (leaf area index, LAI) and biochemical properties (leaf chlorophyll and nitrogen content). Here we found significant linear relationships between camera-NDVI and leaf chlorophyll concentration, and between camera-NDVI and leaf nitrogen content, though weaker relationships between camera-NDVI and LAI. Therefore, we recommend ground-based camera-NDVI as a powerful tool for long-term, near surface observations to monitor canopy development and to estimate leaf chlorophyll, nitrogen status, and LAI.« less

Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest.

PubMed

Yang, Hualei; Yang, Xi; Heskel, Mary; Sun, Shucun; Tang, Jianwu

2017-04-28

Changes in plant phenology affect the carbon flux of terrestrial forest ecosystems due to the link between the growing season length and vegetation productivity. Digital camera imagery, which can be acquired frequently, has been used to monitor seasonal and annual changes in forest canopy phenology and track critical phenological events. However, quantitative assessment of the structural and biochemical controls of the phenological patterns in camera images has rarely been done. In this study, we used an NDVI (Normalized Difference Vegetation Index) camera to monitor daily variations of vegetation reflectance at visible and near-infrared (NIR) bands with high spatial and temporal resolutions, and found that the infrared camera based NDVI (camera-NDVI) agreed well with the leaf expansion process that was measured by independent manual observations at Harvard Forest, Massachusetts, USA. We also measured the seasonality of canopy structural (leaf area index, LAI) and biochemical properties (leaf chlorophyll and nitrogen content). We found significant linear relationships between camera-NDVI and leaf chlorophyll concentration, and between camera-NDVI and leaf nitrogen content, though weaker relationships between camera-NDVI and LAI. Therefore, we recommend ground-based camera-NDVI as a powerful tool for long-term, near surface observations to monitor canopy development and to estimate leaf chlorophyll, nitrogen status, and LAI.

Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

DOE PAGES

Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; ...

2014-12-02

Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of themore » CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely

Estimating gross primary productivity of a tropical forest ecosystem over north-east India using LAI and meteorological variables

NASA Astrophysics Data System (ADS)

Deb Burman, Pramit Kumar; Sarma, Dipankar; Williams, Mathew; Karipot, Anandakumar; Chakraborty, Supriyo

2017-10-01

Tropical forests act as a major sink of atmospheric carbon dioxide, and store large amounts of carbon in biomass. India is a tropical country with regions of dense vegetation and high biodiversity. However due to the paucity of observations, the carbon sequestration potential of these forests could not be assessed in detail so far. To address this gap, several flux towers were erected over different ecosystems in India by Indian Institute of Tropical Meteorology as part of the MetFlux India project funded by MoES (Ministry of Earth Sciences, Government of India). A 50 m tall tower was set up over a semi-evergreen moist deciduous forest named Kaziranga National Park in north-eastern part of India which houses a significant stretch of local forest cover. Climatically this region is identified to be humid sub-tropical. Here we report first generation of the in situ meteorological observations and leaf area index (LAI) measurements from this site. LAI obtained from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) is compared with the in situ measured LAI. We use these in situ measurements to calculate the total gross photosynthesis (or gross primary productivity, GPP) of the forest using a calibrated model. LAI and GPP show prominent seasonal variation. LAI ranges between 0.75 in winter to 3.25 in summer. Annual GPP is estimated to be 2.11 kg C m^{-2} year^{-1}.

Photon Recollision Probability: a Useful Concept for Cross Scale Consistency Check between Leaf Area Index and Foliage Clumping Products

NASA Astrophysics Data System (ADS)

Pisek, J.

2017-12-01

Clumping index (CI) is the measure of foliage aggregation relative to a random distribution of leaves in space. CI is an important factor for the correct quantification of true leaf area index (LAI). Global and regional scale CI maps have been generated from various multi-angle sensors based on an empirical relationship with the normalized difference between hotspot and darkspot (NDHD) index (Chen et al., 2005). Ryu et al. (2011) suggested that accurate calculation of radiative transfer in a canopy, important for controlling gross primary productivity (GPP) and evapotranspiration (ET) (Baldocchi and Harley, 1995), should be possible by integrating CI with incoming solar irradiance and LAI from MODIS land and atmosphere products. It should be noted that MODIS LAI/FPAR product uses internal non-empirical, stochastic equations for parameterization of foliage clumping. This raises a question if integration of the MODIS LAI product with empirically-based CI maps does not introduce any inconsistencies. Here, the consistency is examined independently through the `recollision probability theory' or `p-theory' (Knyazikhin et al., 1998) along with raw LAI-2000/2200 Plant Canopy Analyzer (PCA) data from > 30 sites, surveyed across a range of vegetation types. The theory predicts that the amount of radiation scattered by a canopy should depend only on the wavelength and the spectrally invariant canopy structural parameter p. The parameter p is linked to the foliage clumping (Stenberg et al., 2016). Results indicate that integration of the MODIS LAI product with empirically-based CI maps is feasible. Importantly, for the first time it is shown that it is possible to obtain p values for any location solely from Earth Observation data. This is very relevant for future applications of photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

Estimation of Spatial Trends in LAI in Heterogeneous Semi-arid Ecosystems using Full Waveform Lidar

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Ilangakoon, N.; Spaete, L.; Dashti, H.

2017-12-01

Leaf area index (LAI) is a key structural trait that is defined by the plant functional type (PFT) and controlled by prevailing climate- and human-driven ecosystem stresses. Estimates of LAI using remote sensing techniques are limited by the uncertainties of vegetation inter and intra-gap fraction estimates; this is especially the case in sparse, low stature vegetated ecosystems. Small footprint full waveform lidar digitizes the total amount of return energy with the direction information as a near continuous waveform at a high vertical resolution (1 ns). Thus waveform lidar provides additional data matrices to capture vegetation gaps as well as PFTs that can be used to constrain the uncertainties of LAI estimates. In this study, we calculated a radiometrically calibrated full waveform parameter called backscatter cross section, along with other data matrices from the waveform to estimate vegetation gaps across plots (10 m x 10 m) in a semi-arid ecosystem in the western US. The LAI was then estimated using empirical relationships with directional gap fraction. Full waveform-derived gap fraction based LAI showed a high correlation with field observed shrub LAI (R2 = 0.66, RMSE = 0.24) compared to discrete return lidar based LAI (R2 = 0.01, RMSE = 0.5). The data matrices derived from full waveform lidar classified a number of deciduous and evergreen tree species, shrub species, and bare ground with an overall accuracy of 89% at 10 m. A similar analysis was performed at 1m with overall accuracy of 80%. The next step is to use these relationships to map the PFTs LAI at 10 m spatial scale across the larger study regions. The results show the exciting potential of full waveform lidar to identify plant functional types and LAI in low-stature vegetation dominated semi-arid ecosystems, an ecosystem in which many other remote sensing techniques fail. These results can be used to assess ecosystem state, habitat suitability as well as to constrain model uncertainties in

A methodology to estimate representativeness of LAI station observation for validation: a case study with Chinese Ecosystem Research Network (CERN) in situ data

NASA Astrophysics Data System (ADS)

Xu, Baodong; Li, Jing; Liu, Qinhuo; Zeng, Yelu; Yin, Gaofei

2014-11-01

Leaf Area Index (LAI) is known as a key vegetation biophysical variable. To effectively use remote sensing LAI products in various disciplines, it is critical to understand the accuracy of them. The common method for the validation of LAI products is firstly establish the empirical relationship between the field data and high-resolution imagery, to derive LAI maps, then aggregate high-resolution LAI maps to match moderate-resolution LAI products. This method is just suited for the small region, and its frequencies of measurement are limited. Therefore, the continuous observing LAI datasets from ground station network are important for the validation of multi-temporal LAI products. However, due to the scale mismatch between the point observation in the ground station and the pixel observation, the direct comparison will bring the scale error. Thus it is needed to evaluate the representativeness of ground station measurement within pixel scale of products for the reasonable validation. In this paper, a case study with Chinese Ecosystem Research Network (CERN) in situ data was taken to introduce a methodology to estimate representativeness of LAI station observation for validating LAI products. We first analyzed the indicators to evaluate the observation representativeness, and then graded the station measurement data. Finally, the LAI measurement data which can represent the pixel scale was used to validate the MODIS, GLASS and GEOV1 LAI products. The result shows that the best agreement is reached between the GLASS and GEOV1, while the lowest uncertainty is achieved by GEOV1 followed by GLASS and MODIS. We conclude that the ground station measurement data can validate multi-temporal LAI products objectively based on the evaluation indicators of station observation representativeness, which can also improve the reliability for the validation of remote sensing products.

Worldwide Historical Estimates of Leaf Area Index, 1932-2000

NASA Technical Reports Server (NTRS)

Scurlock, J. M. O.; Asner, G. P.; Gower, S. T.

2001-01-01

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 and other vegetation parameters. The LA1 data are linked to a bibliography of over 300 originalsource references.This report documents the development of this data set, its contents, and its availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which were collected using a wide range of methodologies and assumptions that may not allow comparisons among sites.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

ASSESSMENT OF MODIS LAI (W4) IN LOBLOLLY PINE (P. TAEDA) FOREST TYPE, APPOMATTOX, VIRGINIA

EPA Science Inventory

The United States Environmental Protection Agency initiated MODIS MODI5A2LAI validation research (2002) in the evergreen needle leaf biome, as defined in the MOD12 classification, in a regional study located in the southeastern United States.

Spatial Upscaling of Long-term In Situ LAI Measurements from Global Network Sites for Validation of Remotely Sensed Products

NASA Astrophysics Data System (ADS)

Xu, B.; Jing, L.; Qinhuo, L.; Zeng, Y.; Yin, G.; Fan, W.; Zhao, J.

2015-12-01

Leaf area index (LAI) is a key parameter in terrestrial ecosystem models, and a series of global LAI products have been derived from satellite data. To effectively apply these LAI products, it is necessary to evaluate their accuracy reasonablely. The long-term LAI measurements from the global network sites are an important supplement to the product validation dataset. However, the spatial scale mismatch between the site measurement and the pixel grid hinders the utilization of these measurements in LAI product validation. In this study, a pragmatic approach based on the Bayesian linear regression between long-term LAI measurements and high-resolution images is presented for upscaling the point-scale measurements to the pixel-scale. The algorithm was evaluated using high-resolution LAI reference maps provided by the VALERI project at the Järvselja site and was implemented to upscale the long-term LAI measurements at the global network sites. Results indicate that the spatial scaling algorithm can reduce the root mean square error (RMSE) from 0.42 before upscaling to 0.21 after upscaling compared with the aggregated LAI reference maps at the pixel-scale. Meanwhile, the algorithm shows better reliability and robustness than the ordinary least square (OLS) method for upscaling some LAI measurements acquired at specific dates without high-resolution images. The upscaled LAI measurements were employed to validate three global LAI products, including MODIS, GLASS and GEOV1. Results indicate that (i) GLASS and GEOV1 show consistent temporal profiles over most sites, while MODIS exhibits temporal instability over a few forest sites. The RMSE of seasonality between products and upscaled LAI measurement is 0.25-1.72 for MODIS, 0.17-1.29 for GLASS and 0.36-1.35 for GEOV1 along with different sites. (ii) The uncertainty for products varies over different months. The lowest and highest uncertainty for MODIS are 0.67 in March and 1.53 in August, for GLASS are 0.67 in November

The Sentinel-2 MSI Can Increase the Temporal Resolution of 30m Satellite-Derived LAI Estimates

NASA Astrophysics Data System (ADS)

Dungan, J. L.; Li, S.; Ganguly, S.; Wang, W.; Nemani, R. R.; Ju, J.; Claverie, M.; Masek, J. G.

2016-12-01

The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored.

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

NASA Technical Reports Server (NTRS)

Huemmrich, Karl F.

2013-01-01

The leaf inclination angle distribution (LAD) is an important characteristic of vegetation canopy structure affecting light interception within the canopy. However, LADs are difficult and time consuming to measure. To examine possible global patterns of LAD and their implications in remote sensing, a model was developed to predict leaf angles within canopies. Canopies were simulated using the SAIL radiative transfer model combined with a simple photosynthesis model. This model calculated leaf inclination angles for horizontal layers of leaves within the canopy by choosing the leaf inclination angle that maximized production over a day in each layer. LADs were calculated for five latitude bands for spring and summer solar declinations. Three distinct LAD types emerged: tropical, boreal, and an intermediate temperate distribution. In tropical LAD, the upper layers have a leaf angle around 35 with the lower layers having horizontal inclination angles. While the boreal LAD has vertical leaf inclination angles throughout the canopy. The latitude bands where each LAD type occurred changed with the seasons. The different LADs affected the fraction of absorbed photosynthetically active radiation (fAPAR) and Normalized Difference Vegetation Index (NDVI) with similar relationships between fAPAR and leaf area index (LAI), but different relationships between NDVI and LAI for the different LAD types. These differences resulted in significantly different relationships between NDVI and fAPAR for each LAD type. Since leaf inclination angles affect light interception, variations in LAD also affect the estimation of leaf area based on transmittance of light or lidar returns.

Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

NASA Astrophysics Data System (ADS)

Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

2013-04-01

Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the

Chronological Sequence of Leaf Phenology, Xylem and Phloem Formation and Sap Flow of Quercus pubescens from Abandoned Karst Grasslands

PubMed Central

Lavrič, Martina; Eler, Klemen; Ferlan, Mitja; Vodnik, Dominik; Gričar, Jožica

2017-01-01

Intra-annual variations in leaf development, radial growth, including the phloem part, and sap flow have rarely been studied in deciduous trees from drought-prone environments. In order to understand better the chronological order and temporal course of these processes, we monitored leaf phenology, xylem and phloem formation and sap flow in Quercus pubescens from abandoned karst grasslands in Slovenia during the growing season of 2014. We found that the initial earlywood vessel formation started before bud opening at the beginning of April. Buds started to open in the second half of April and full leaf unfolding occurred by the end of May. LAI values increased correspondingly with leaf development. About 28% of xylem and 22% of phloem annual increment were formed by the time of bud break. Initial earlywood vessels were fully lignified and ready for water transport, indicating that they are essential to provide hydraulic conductivity for axial water flow during leaf development. Sap flow became active and increasing contemporarily with leaf development and LAI values. Similar early spring patterns of xylem sap flow and LAI denoted that water transport in oaks broadly followed canopy leaf area development. In the initial 3 weeks of radial growth, phloem growth preceded that of xylem, indicating its priority over xylem at the beginning of the growing season. This may be related to the fact that after bud break, the developing foliage is a very large sink for carbohydrates but, at the same time, represents a small transpirational area. Whether the interdependence of the chronological sequence of the studied processes is fixed in Q. pubescens needs to be confirmed with more data and several years of analyses, although the ‘correct sequence’ of processes is essential for synchronized plant performance and response to environmental stress. PMID:28321232

Assimilation of Leaf Area Index and Soil Wetness Index into the ISBA-A-gs land surface model over France

NASA Astrophysics Data System (ADS)

Barbu, A. L.; Calvet, J.-C.; Lafont, S.

2012-04-01

The development of a Land Data Assimilation System (LDAS) dedicated to carbon and water cycles is considered as a key aspect for monitoring activities of terrestrial carbon fluxes. It allows the assimilation of biophysical products in order to reduce the bias between the model simulations and the observations and have a positive impact on carbon and water fluxes. This work shows the benefits of data assimilation of Earth observations for the monitoring of vegetation status and carbon fluxes, in the framework of the GEOLAND2 project, co-funded by the European Commission within the GMES initiative in FP7. In this study, the SURFEX modelling platform developed at Meteo-France is used for describing the continental vegetation state, surface fluxes and soil moisture. It consists of the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The vegetation biomass and Leaf Area Index (LAI) evolve dynamically in response to weather and climate conditions. The ECOCLIMAP database provides detailed information about the land cover at a resolution of 1 km. Over the France domain, the most present ecosystem types are grasslands (32%), C3 crop lands (24%), deciduous forest (20%), bare soil (11%), and C4 crop lands (8%).The model also includes a representation of the soil moisture stress with two different types of drought responses for herbaceous vegetation and forests. A version of the Extended Kalman Filter (EKF) scheme is developed for the joint assimilation of satellite-derived surface soil moisture from ASCAT-25 km product, namely Soil Wetness Index (SWI-01) developed by TU-Wien, and remote sensing LAI product provided by GEOLAND2. The GEOLAND2 LAI product is derived from CYCLOPES V3.1 and MODIS collection 5 data. It is more consistent with an effective LAI for low LAI and close to the actual LAI for high values. The assimilation experiment was conducted across France at a spatial resolution of 8 km. The study period ranges from July 2007 to December

Effects of grazing on leaf area index, fractional cover and evapotranspiration by a desert phreatophyte community at a former uranium mill site on the Colorado Plateau.

PubMed

Bresloff, Cynthia J; Nguyen, Uyen; Glenn, Edward P; Waugh, Jody; Nagler, Pamela L

2013-01-15

This study employed ground and remote sensing methods to monitor the effects of grazing on leaf area index (LAI), fractional cover (f(c)) and evapotranspiration (ET) of a desert phreatophyte community over an 11 year period at a former uranium mill site on the Colorado Plateau, U.S. Nitrate, ammonium and sulfate are migrating away from the mill site in a shallow alluvial aquifer. The phreatophyte community, consisting of Atriplex canescens (ATCA) and Sarcobatus vermiculatus (SAVE) shrubs, intercepts groundwater and could potentially slow the movement of the contaminant plume through evapotranspiration (ET). However, the site has been heavily grazed by livestock, reducing plant cover and LAI. We used livestock exclosures and revegetation plots to determine the effects of grazing on LAI, f(c) and ET, then projected the findings over the whole site using multi-platform remote sensing methods. We show that ET is approximately equal to annual precipitation at the site, but when ATCA and SAVE are protected from grazing they can develop high f(c) and LAI values, and ET can exceed annual precipitation, with the excess coming from groundwater discharge. Therefore, control of grazing could be an effective method to slow migration of contaminants at this and similar sites in the western U.S. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effects of grazing on leaf area index, fractional cover and evapotranspiration by a desert phreatophyte community at a former uranium mill site on the Colorado Plateau

USGS Publications Warehouse

Bresloff, Cynthia J.; Nguyen, Uyen; Glenn, Edward P.; Waugh, Jody; Nagler, Pamela L.

2013-01-01

This study employed ground and remote sensing methods to monitor the effects of grazing on leaf area index (LAI), fractional cover (fc) and evapotranspiration (ET) of a desert phreatophyte community over an 11 year period at a former uranium mill site on the Colorado Plateau, U.S. Nitrate, ammonium and sulfate are migrating away from the mill site in a shallow alluvial aquifer. The phreatophyte community, consisting of Atriplex canescens (ATCA) and Sarcobatus vermiculatus (SAVE) shrubs, intercepts groundwater and could potentially slow the movement of the contaminant plume through evapotranspiration (ET). However, the site has been heavily grazed by livestock, reducing plant cover and LAI. We used livestock exclosures and revegetation plots to determine the effects of grazing on LAI, fc and ET, then projected the findings over the whole site using multi-platform remote sensing methods. We show that ET is approximately equal to annual precipitation at the site, but when ATCA and SAVE are protected from grazing they can develop high fc and LAI values, and ET can exceed annual precipitation, with the excess coming from groundwater discharge. Therefore, control of grazing could be an effective method to slow migration of contaminants at this and similar sites in the western U.S.

Optimal balance of water use efficiency and leaf construction cost with a link to the drought threshold of the desert steppe ecotone in northern China.

PubMed

Wei, Haixia; Luo, Tianxiang; Wu, Bo

2016-09-01

In arid environments, a high nitrogen content per leaf area (Narea) induced by drought can enhance water use efficiency (WUE) of photosynthesis, but may also lead to high leaf construction cost (CC). Our aim was to investigate how maximizing Narea could balance WUE and CC in an arid-adapted, widespread species along a rainfall gradient, and how such a process may be related to the drought threshold of the desert-steppe ecotone in northern China. Along rainfall gradients with a moisture index (MI) of 0·17-0·41 in northern China and the northern Tibetan Plateau, we measured leaf traits and stand variables including specific leaf area (SLA), nitrogen content relative to leaf mass and area (Nmass, Narea) and construction cost (CCmass, CCarea), δ(13)C (indicator of WUE), leaf area index (LAI) and foliage N-pool across populations of Artemisia ordosica In samples from northern China, a continuous increase of Narea with decreasing MI was achieved by a higher Nmass and constant SLA (reduced LAI and constant N-pool) in high-rainfall areas (MI > 0·29), but by a lower SLA and Nmass (reduced LAI and N-pool) in low-rainfall areas (MI ≤ 0·29). While δ(13)C, CCmass and CCarea continuously increased with decreasing MI, the low-rainfall group had higher Narea and δ(13)C at a given CCarea, compared with the high-rainfall group. Similar patterns were also found in additional data for the same species in the northern Tibetan Plateau. The observed drought threshold where MI = 0·29 corresponded well to the zonal boundary between typical and desert steppes in northern China. Our data indicated that below a climatic drought threshold, drought-resistant plants tend to maximize their intrinsic WUE through increased Narea at a given CCarea, which suggests a linkage between leaf functional traits and arid vegetation zonation. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please

Optimal balance of water use efficiency and leaf construction cost with a link to the drought threshold of the desert steppe ecotone in northern China

PubMed Central

Wei, Haixia; Luo, Tianxiang; Wu, Bo

2016-01-01

Background and Aims In arid environments, a high nitrogen content per leaf area (Narea) induced by drought can enhance water use efficiency (WUE) of photosynthesis, but may also lead to high leaf construction cost (CC). Our aim was to investigate how maximizing Narea could balance WUE and CC in an arid-adapted, widespread species along a rainfall gradient, and how such a process may be related to the drought threshold of the desert–steppe ecotone in northern China. Methods Along rainfall gradients with a moisture index (MI) of 0·17–0·41 in northern China and the northern Tibetan Plateau, we measured leaf traits and stand variables including specific leaf area (SLA), nitrogen content relative to leaf mass and area (Nmass, Narea) and construction cost (CCmass, CCarea), δ13C (indicator of WUE), leaf area index (LAI) and foliage N-pool across populations of Artemisia ordosica. Key Results In samples from northern China, a continuous increase of Narea with decreasing MI was achieved by a higher Nmass and constant SLA (reduced LAI and constant N-pool) in high-rainfall areas (MI > 0·29), but by a lower SLA and Nmass (reduced LAI and N-pool) in low-rainfall areas (MI ≤ 0·29). While δ13C, CCmass and CCarea continuously increased with decreasing MI, the low-rainfall group had higher Narea and δ13C at a given CCarea, compared with the high-rainfall group. Similar patterns were also found in additional data for the same species in the northern Tibetan Plateau. The observed drought threshold where MI = 0·29 corresponded well to the zonal boundary between typical and desert steppes in northern China. Conclusions Our data indicated that below a climatic drought threshold, drought-resistant plants tend to maximize their intrinsic WUE through increased Narea at a given CCarea, which suggests a linkage between leaf functional traits and arid vegetation zonation. PMID:27443298

The response of ecosystem carbon fluxes to LAI and environmental drivers in a maize crop grown in two contrasting seasons.

PubMed

Vitale, Luca; Di Tommasi, Paul; D'Urso, Guido; Magliulo, Vincenzo

2016-03-01

The eddy correlation technique was used to investigate the influence of biophysical variables and crop phenological phases on the behaviour of ecosystem carbon fluxes of a maize crop, in two contrasting growing seasons. In 2009, the reduced water supply during the early growing stage limited leaf area expansion, thus negatively affecting canopy photosynthesis. The variability of gross primary production (GPP) and ecosystem respiration (R eco) was mainly explained by seasonal variation of leaf area index (LAI). The seasonal variation of R eco was positively influenced by soil temperatures (T soil) in 2008 but not in 2009. In 2008, a contribution of both autotrophic and heterotrophic components to total R eco could be hypothesized, while during 2009, autotrophic respiration is supposed to be the most important component. Crop phenological phases affected the response of ecosystem fluxes to biophysical drivers.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher

LAI is the major cause of divergence in CO2 fertilization effect in land surface models

NASA Astrophysics Data System (ADS)

Li, Q.; Luo, Y.; Lu, X.; Wang, Y.; Huang, X.; Lin, G., Sr.

2017-12-01

Concentration-carbon feedback (β), also called CO2 fertilization effect, is an important feedback between terrestrial ecosystems and atmosphere to alleviate global climate change. However, models participating in C4MIP and CMIP5 predicted diverse CO2 fertilization effects under future CO2 inceasing scenarios. Hence identifing the key processes dominating the divergence of β in land surface models is of significance. We calculated CO2 fertilization effects from leaf level, canopy gross productivity level, net ecosystem productivity level and ecosystem carbon stock level in Community Atmosphere Biosphere Land Exchange (CABLE) model. Our results identified LAI is the key factor dominating the divergence of β among C3 plants in CABLE model. Saturation of the ecosystem productivity to increasing CO2 is not only regulated by leaf-level response, but also the response of LAI to increasing CO2. The greatest variation among C3 plants at ecosystem level suggests that other processes such as different allocation patterns and soil carbon dynamics of various vegetation types are also responsible for the divergence. Our results indicate that processes regarding to LAI need to be better calibrated according to experiments and observations in order to better represent the response of ecosystem productivity to increasing CO2.

Mapping canopy gap fraction and leaf area index at continent-scale from satellite lidar

NASA Astrophysics Data System (ADS)

Mahoney, C.; Hopkinson, C.; Held, A. A.

2015-12-01

Information on canopy cover is essential for understanding spatial and temporal variability in vegetation biomass, local meteorological processes and hydrological transfers within vegetated environments. Gap fraction (GF), an index of canopy cover, is often derived over large areas (100's km2) via airborne laser scanning (ALS), estimates of which are reasonably well understood. However, obtaining country-wide estimates is challenging due to the lack of spatially distributed point cloud data. The Geoscience Laser Altimeter System (GLAS) removes spatial limitations, however, its large footprint nature and continuous waveform data measurements make derivations of GF challenging. ALS data from 3 Australian sites are used as a basis to scale-up GF estimates to GLAS footprint data by the use of a physically-based Weibull function. Spaceborne estimates of GF are employed in conjunction with supplementary predictor variables in the predictive Random Forest algorithm to yield country-wide estimates at a 250 m spatial resolution; country-wide estimates are accompanied with uncertainties at the pixel level. Preliminary estimates of effective Leaf Area Index (eLAI) are also presented by converting GF via the Beer-Lambert law, where an extinction coefficient of 0.5 is employed; deemed acceptable at such spatial scales. The need for such wide-scale quantification of GF and eLAI are key in the assessment and modification of current forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network (TERN), a key asset to policy makers with regards to the management of the national ecosystem, in fulfilling their government issued mandates.

Community Characteristics and Leaf Stoichiometric Traits of Desert Ecosystems Regulated by Precipitation and Soil in an Arid Area of China.

PubMed

Zhang, Xiaolong; Guan, Tianyu; Zhou, Jihua; Cai, Wentao; Gao, Nannan; Du, Hui; Jiang, Lianhe; Lai, Liming; Zheng, Yuanrun

2018-01-10

Precipitation is a key environmental factor determining plant community structure and function. Knowledge of how community characteristics and leaf stoichiometric traits respond to variation in precipitation is crucial for assessing the effects of global changes on terrestrial ecosystems. In this study, we measured community characteristics, leaf stoichiometric traits, and soil properties along a precipitation gradient (35-209 mm) in a desert ecosystem of Northwest China to explore the drivers of these factors. With increasing precipitation, species richness, aboveground biomass, community coverage, foliage projective cover (FPC), and leaf area index (LAI) all significantly increased, while community height decreased. The hyperarid desert plants were characterized by lower leaf carbon (C) and nitrogen/phosphorus (N/P) levels, and stable N and P, and these parameters did not change significantly with precipitation. The growth of desert plants was limited more by N than P. Soil properties, rather than precipitation, were the main drivers of desert plant leaf stoichiometric traits, whereas precipitation made the biggest contribution to vegetation structure and function. These results test the importance of precipitation in regulating plant community structure and composition together with soil properties, and provide further insights into the adaptive strategy of communities at regional scale in response to global climate change.

Community Characteristics and Leaf Stoichiometric Traits of Desert Ecosystems Regulated by Precipitation and Soil in an Arid Area of China

PubMed Central

Guan, Tianyu; Zhou, Jihua; Cai, Wentao; Gao, Nannan; Du, Hui; Jiang, Lianhe; Lai, Liming; Zheng, Yuanrun

2018-01-01

Precipitation is a key environmental factor determining plant community structure and function. Knowledge of how community characteristics and leaf stoichiometric traits respond to variation in precipitation is crucial for assessing the effects of global changes on terrestrial ecosystems. In this study, we measured community characteristics, leaf stoichiometric traits, and soil properties along a precipitation gradient (35–209 mm) in a desert ecosystem of Northwest China to explore the drivers of these factors. With increasing precipitation, species richness, aboveground biomass, community coverage, foliage projective cover (FPC), and leaf area index (LAI) all significantly increased, while community height decreased. The hyperarid desert plants were characterized by lower leaf carbon (C) and nitrogen/phosphorus (N/P) levels, and stable N and P, and these parameters did not change significantly with precipitation. The growth of desert plants was limited more by N than P. Soil properties, rather than precipitation, were the main drivers of desert plant leaf stoichiometric traits, whereas precipitation made the biggest contribution to vegetation structure and function. These results test the importance of precipitation in regulating plant community structure and composition together with soil properties, and provide further insights into the adaptive strategy of communities at regional scale in response to global climate change. PMID:29320458

A photosynthesis-based two-leaf canopy stomatal ...

EPA Pesticide Factsheets

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system—WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH

[Monitoring temporal dynamics in leaf area index of the temperate broadleaved deciduous forest in Maoershan region, Northeast China with tower-based radiation measurements.

PubMed

Liu, Fan; Wang, Chuan Kuan; Wang, Xing Chang

2016-08-01

Broadband vegetation indices (BVIs) derived from routine radiation measurements on eddy flux towers have the advantage of high temporal resolutions, and thus have the potential to obtain detailed information of dynamics in canopy leaf area index (LAI). Taking the temperate broadleaved deciduous forest around the Maoershan flux tower in Northeast China as a case, we investigated the controlling factors and smoothing method of four BVI time-series, i.e., broadband norma-lized difference vegetation index (NDVI B ), broadband enhanced vegetation index (EVI B ), the ratio of the near-infrared radiation reflectance to photosynthetically active radiation reflectance (SR NP ), and the ratio of the shortwave radiation reflectance to photosynthetically active radiation reflectance (SR SP ). We compared the seasonal courses of the BVIs with the LAI based on litterfall collection method. The values for each BVI were slightly different among the three calculation methods by Huemmrich, Wilson, and Jenkins, but showed similar seasonal patterns. The diurnal variations in BVIs were mainly influenced by the solar elevation and the angle between the solar elevation and slope, but the BVIs were relatively stable around 12:30. The noise of daily BVI time-series could be effectively smoothed by a threshold of clearness index (K). The seasonal courses of BVIs for each time of day around the noon had similar patterns, but their thresholds of K and the percen-tages of remaining data were different. Therefore, the daily values of BVIs might be optimized based on the smoothing and the proportion of remaining data. The NDVI B was closely correlated linearly with the LAI derived from the litterfall collection method, while the EVI B , SR NP , and SR SP had a logarithmic relationship with the LAI. The NDVI B had the advantage in tracking the seasonal dyna-mics in LAI and extrapolating LAI to a broader scale. Given that most eddy flux towers had equipped with energy balance measurements, a

Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis

PubMed Central

Yang, Bin; Knyazikhin, Yuri; Mõttus, Matti; Rautiainen, Miina; Stenberg, Pauline; Yan, Lei; Chen, Chi; Yan, Kai; Choi, Sungho; Park, Taejin; Myneni, Ranga B.

2017-01-01

This paper presents the theoretical basis of the algorithm designed for the generation of leaf area index and diurnal course of its sunlit portion from NASA’s Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR). The Look-up-Table (LUT) approach implemented in the MODIS operational LAI/FPAR algorithm is adopted. The LUT, which is the heart of the approach, has been significantly modified. First, its parameterization incorporates the canopy hot spot phenomenon and recent advances in the theory of canopy spectral invariants. This allows more accurate decoupling of the structural and radiometric components of the measured Bidirectional Reflectance Factor (BRF), improves scaling properties of the LUT and consequently simplifies adjustments of the algorithm for data spatial resolution and spectral band compositions. Second, the stochastic radiative transfer equations are used to generate the LUT for all biome types. The equations naturally account for radiative effects of the three-dimensional canopy structure on the BRF and allow for an accurate discrimination between sunlit and shaded leaf areas. Third, the LUT entries are measurable, i.e., they can be independently derived from both below canopy measurements of the transmitted and above canopy measurements of reflected radiation fields. This feature makes possible direct validation of the LUT, facilitates identification of its deficiencies and development of refinements. Analyses of field data on canopy structure and leaf optics collected at 18 sites in the Hyytiälä forest in southern boreal zone in Finland and hyperspectral images acquired by the EO-1 Hyperion sensor support the theoretical basis. PMID:28867834

Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

NASA Technical Reports Server (NTRS)

Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A.; Cook, Bruce

2016-01-01

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were

Seasonal Changes in Leaf Area of Amazon Forests from Leaf Flushing and Abscission

NASA Astrophysics Data System (ADS)

Samanta, A.; Knyazikhin, Y.; Xu, L.; Dickinson, R.; Fu, R.; Costa, M. H.; Ganguly, S.; Saatchi, S. S.; Nemani, R. R.; Myneni, R.

2011-12-01

A large increase in near-infrared (NIR) reflectance of Amazon forests during the light-rich dry season and a corresponding decrease during the light-poor wet season has been observed in satellite measurements. This has been variously interpreted as seasonal changes in leaf area resulting from net leaf flushing in the dry season and net leaf abscission in the wet season, enhanced photosynthetic activity during the dry season from flushing new leaves and as change in leaf scattering and absorption properties between younger and older leaves covered with epiphylls. Reconciling these divergent views using theory and observations is the goal of this article. The observed changes in NIR reflectance of Amazon forests could be due to similar, but small, changes in NIR leaf albedo (reflectance plus transmittance) only, from exchanging older leaves with newer ones, with total leaf area unchanged. However, this argument ignores accumulating evidence from ground-based studies of higher leaf area in the dry season relative to the wet season, seasonal changes in litterfall and does not satisfactorily explain why NIR reflectance of these forests decreases in the wet season. A more convincing explanation for the observed increase in NIR reflectance during the dry season and decrease during the wet season is one that invokes changes in both leaf area and leaf optical properties. Such an argument is consistent with known phonological behavior of tropical forests, ground-based reports of seasonal changes in leaf area, litterfall, leaf optical properties and fluxes of evapotranspiration, and thus, reconciles the various seemingly divergent views.

Seasonal changes in leaf area of Amazon forests from leaf flushing and abscission

NASA Astrophysics Data System (ADS)

Samanta, Arindam; Knyazikhin, Yuri; Xu, Liang; Dickinson, Robert E.; Fu, Rong; Costa, Marcos H.; Saatchi, Sassan S.; Nemani, Ramakrishna R.; Myneni, Ranga B.

2012-03-01

A large increase in near-infrared (NIR) reflectance of Amazon forests during the light-rich dry season and a corresponding decrease during the light-poor wet season has been observed in satellite measurements. This increase has been variously interpreted as seasonal change in leaf area resulting from net leaf flushing in the dry season or net leaf abscission in the wet season, enhanced photosynthetic activity during the dry season from flushing new leaves and as change in leaf scattering and absorption properties between younger and older leaves covered with epiphylls. Reconciling these divergent views using theory and observations is the goal of this article. The observed changes in NIR reflectance of Amazon forests could be due to similar, but small, changes in NIR leaf albedo (reflectance plus transmittance) resulting from the exchange of older leaves for newer ones, but with the total leaf area unchanged. However, this argument ignores accumulating evidence from ground-based reports of higher leaf area in the dry season than the wet season, seasonal changes in litterfall and does not satisfactorily explain why NIR reflectance of these forests decreases in the wet season. More plausibly, the increase in NIR reflectance during the dry season and the decrease during the wet season would result from changes in both leaf area and leaf optical properties. Such change would be consistent with known phenological behavior of tropical forests, ground-based reports of seasonal changes in leaf area, litterfall, leaf optical properties and fluxes of evapotranspiration, and thus, would reconcile the various seemingly divergent views.

Including the dynamic relationship between climatic variables and leaf area index in a hydrological model to improve streamflow prediction under a changing climate

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2015-06-01

Anthropogenic climate change is projected to enrich the atmosphere with carbon dioxide, change vegetation dynamics and influence the availability of water at the catchment scale. This study combines a nonlinear model for estimating changes in leaf area index (LAI) due to climatic fluctuations with the variable infiltration capacity (VIC) hydrological model to improve catchment streamflow prediction under a changing climate. The combined model was applied to 13 gauged sub-catchments with different land cover types (crop, pasture and tree) in the Goulburn-Broken catchment, Australia, for the "Millennium Drought" (1997-2009) relative to the period 1983-1995, and for two future periods (2021-2050 and 2071-2100) and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5) which were compared with the baseline historical period of 1981-2010. This region was projected to be warmer and mostly drier in the future as predicted by 38 Coupled Model Intercomparison Project Phase 5 (CMIP5) runs from 15 global climate models (GCMs) and for two emission scenarios. The results showed that during the Millennium Drought there was about a 29.7-66.3 % reduction in mean annual runoff due to reduced precipitation and increased temperature. When drought-induced changes in LAI were included, smaller reductions in mean annual runoff of between 29.3 and 61.4 % were predicted. The proportional increase in runoff due to modeling LAI was 1.3-10.2 % relative to not including LAI. For projected climate change under the RCP4.5 emission scenario, ignoring the LAI response to changing climate could lead to a further reduction in mean annual runoff of between 2.3 and 27.7 % in the near-term (2021-2050) and 2.3 to 23.1 % later in the century (2071-2100) relative to modeling the dynamic response of LAI to precipitation and temperature changes. Similar results (near-term 2.5-25.9 % and end of century 2.6-24.2 %) were found for climate change under the RCP8.5 emission scenario

Discerning spatial and temporal LAI and clear-sky FAPAR variability during summer at the Toolik Lake vegetation monitoring grid (North Slope, Alaska)

NASA Astrophysics Data System (ADS)

Heim, B.; Beamish, A. L.; Walker, D. A.; Epstein, H. E.; Sachs, T.; Chabrillat, S.; Buchhorn, M.; Prakash, A.

2016-12-01

Ground data for the validation of satellite-derived terrestrial Essential Climate Variables (ECVs) at high latitudes are sparse. Also for regional model evaluation (e.g. climate models, land surface models, permafrost models), we lack accurate ranges of terrestrial ground data and face the problem of a large mismatch in scale. Within the German research programs `Regional Climate Change' (REKLIM) and the Environmental Mapping and Analysis Program (EnMAP), we conducted a study on ground data representativeness for vegetation-related variables within a monitoring grid at the Toolik Lake Long-Term Ecological Research station; the Toolik Lake station lies in the Kuparuk River watershed on the North Slope of the Brooks Mountain Range in Alaska. The Toolik Lake grid covers an area of 1 km2 containing Eight five grid points spaced 100 meters apart. Moist acidic tussock tundra is the most dominant vegetation type within the grid. Eight five permanent 1 m2 plots were also established to be representative of the individual gridpoints. Researchers from the University of Alaska Fairbanks have undertaken assessments at these plots, including Leaf Area Index (LAI) and field spectrometry to derive the Normalized Difference Vegetation Index (NDVI). During summer 2016, we conducted field spectrometry and LAI measurements at selected plots during early, peak and late summer. We experimentally measured LAI on more spatially extensive Elementary Sampling Units (ESUs) to investigate the spatial representativeness of the permanent 1 m2 plots and to map ESUs for various tundra types. LAI measurements are potentially influenced by landscape-inherent microtopography, sparse vascular plant cover, and dead woody matter. From field spectrometer measurements, we derived a clear-sky mid-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). We will present the first data analyses comparing FAPAR and LAI, and maps of biophysically-focused ESUs for evaluation of the use of remote

A Newly Global Drought Index Product Basing on Remotely Sensed Leaf Area Index Percentile Using Severity-Area-Duration Algorithm

NASA Astrophysics Data System (ADS)

Li, Xinlu; Lu, Hui; Lyu, Haobo

2017-04-01

Drought is one of the typical natural disasters around the world, and it has also been an important climatic event particular under the climate change. Assess and monitor drought accurately is crucial for addressing climate change and formulating corresponding policies. Several drought indices have been developed and widely used in regional and global scale to present and monitor drought, which integrate datasets such as precipitation, soil moisture, snowpack, streamflow, evapotranspiration that deprived from land surface models or remotely sensed datasets. Vegetation is a prominent component of ecosystem that modulates the water and energy flux between land surface and atmosphere, and thus can be regarded as one of the drought indicators especially for agricultural drought. Leaf area index (LAI), as an important parameter that quantifying the terrestrial vegetation conditions, can provide a new way for drought monitoring. Drought characteristics can be described as severity, area and duration. Andreadis et al. has constructed a severity-area-duration (SAD) algorithm to reflect the spatial patterns of droughts and their dynamics over time, which is a progress of drought analysis. In our study, a newly drought index product was developed using the LAI percentile (LAIpct) SAD algorithm. The remotely sensed global GLASS (Global LAnd Surface Satellite) LAI ranging from 2001-2011 has been used as the basic data. Data was normalized for each time phase to eliminate the phenology effect, and then the percentile of the normalized data was calculated as the SAD input. 20% was set as the drought threshold, and a clustering algorithm was used to identify individual drought events for each time step. Actual drought events were identified when considering multiple clusters merge to form a larger drought or a drought event breaks up into multiple small droughts according to the distance of drought centers and the overlapping drought area. Severity, duration and area were

Climate influences the leaf area/sapwood area ratio in Scots pine.

PubMed

Mencuccini, M; Grace, J

1995-01-01

We tested the hypothesis that the leaf area/sapwood area ratio in Scots pine (Pinus sylvestris L.) is influenced by site differences in water vapor pressure deficit of the air (D). Two stands of the same provenance were selected, one in western Scotland and one in eastern England, so that effects resulting from age, genetic variability, density and fertility were minimized. Compared with the Scots pine trees at the cooler and wetter site in Scotland, the trees at the warmer and drier site in England produced less leaf area per unit of conducting sapwood area both at a stem height of 1.3 m and at the base of the live crown, whereas stem permeability was similar at both sites. Also, trees at the drier site had less leaf area per unit branch cross-sectional area at the branch base than trees at the wetter site. For each site, the average values for leaf area, sapwood area and permeability were used, together with values of transpiration rates at different D, to calculate average stem water potential gradients. Changes in the leaf area/sapwood area ratio acted to maintain a similar water potential gradient in the stems of trees at both sites despite climatic differences between the sites.

Leaf mass per area, not total leaf area, drives differences in above-ground biomass distribution among woody plant functional types.

PubMed

Duursma, Remko A; Falster, Daniel S

2016-10-01

Here, we aim to understand differences in biomass distribution between major woody plant functional types (PFTs) (deciduous vs evergreen and gymnosperm vs angiosperm) in terms of underlying traits, in particular the leaf mass per area (LMA) and leaf area per unit stem basal area. We used a large compilation of plant biomass and size observations, including observations of 21 084 individuals on 656 species. We used a combination of semiparametric methods and variance partitioning to test the influence of PFT, plant height, LMA, total leaf area, stem basal area and climate on above-ground biomass distribution. The ratio of leaf mass to above-ground woody mass (MF /MS ) varied strongly among PFTs. We found that MF /MS at a given plant height was proportional to LMA across PFTs. As a result, the PFTs did not differ in the amount of leaf area supported per unit above-ground biomass or per unit stem basal area. Climate consistently explained very little additional variation in biomass distribution at a given plant size. Combined, these results demonstrate consistent patterns in above-ground biomass distribution and leaf area relationships among major woody PFTs, which can be used to further constrain global vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Analysis of Differences in Phenology Extracted from the Enhanced Vegetation Index and the Leaf Area Index

PubMed Central

Wang, Cong; Li, Jing; Wu, Shanlong; Xia, Chuanfu

2017-01-01

Remote-sensing phenology detection can compensate for deficiencies in field observations and has the advantage of capturing the continuous expression of phenology on a large scale. However, there is some variability in the results of remote-sensing phenology detection derived from different vegetation parameters in satellite time-series data. Since the enhanced vegetation index (EVI) and the leaf area index (LAI) are the most widely used vegetation parameters for remote-sensing phenology extraction, this paper aims to assess the differences in phenological information extracted from EVI and LAI time series and to explore whether either index performs well for all vegetation types on a large scale. To this end, a GLASS (Global Land Surface Satellite Product)-LAI-based phenology product (GLP) was generated using the same algorithm as the MODIS (Moderate Resolution Imaging Spectroradiometer)-EVI phenology product (MLCD) over China from 2001 to 2012. The two phenology products were compared in China for different vegetation types and evaluated using ground observations. The results show that the ratio of missing data is 8.3% for the GLP, which is less than the 22.8% for the MLCD. The differences between the GLP and the MLCD become stronger as the latitude decreases, which also vary among different vegetation types. The start of the growing season (SOS) of the GLP is earlier than that of the MLCD in most vegetation types, and the end of the growing season (EOS) of the GLP is generally later than that of the MLCD. Based on ground observations, it can be suggested that the GLP performs better than the MLCD in evergreen needleleaved forests and croplands, while the MLCD performs better than the GLP in shrublands and grasslands. PMID:28867773

Total belowground carbon flux in subalpine forests is related to leaf area index, soil nitrogen, and tree height

USGS Publications Warehouse

Berryman, Erin Michele; Ryan, Michael G.; Bradford, John B.; Hawbaker, Todd J.; Birdsey, R.

2016-01-01

In forests, total belowground carbon (C) flux (TBCF) is a large component of the C budget and represents a critical pathway for delivery of plant C to soil. Reducing uncertainty around regional estimates of forest C cycling may be aided by incorporating knowledge of controls over soil respiration and TBCF. Photosynthesis, and presumably TBCF, declines with advancing tree size and age, and photosynthesis increases yet C partitioning to TBCF decreases in response to high soil fertility. We hypothesized that these causal relationships would result in predictable patterns of TBCF, and partitioning of C to TBCF, with natural variability in leaf area index (LAI), soil nitrogen (N), and tree height in subalpine forests in the Rocky Mountains, USA. Using three consecutive years of soil respiration data collected from 22 0.38-ha locations across three 1-km2 subalpine forested landscapes, we tested three hypotheses: (1) annual soil respiration and TBCF will show a hump-shaped relationship with LAI; (2) variability in TBCF unexplained by LAI will be related to soil nitrogen (N); and (3) partitioning of C to TBCF (relative to woody growth) will decline with increasing soil N and tree height. We found partial support for Hypothesis 1 and full support for Hypotheses 2 and 3. TBCF, but not soil respiration, was explained by LAI and soil N patterns (r2 = 0.49), and the ratio of annual TBCF to TBCF plus aboveground net primary productivity (ANPP) was related to soil N and tree height (r2 = 0.72). Thus, forest C partitioning to TBCF can vary even within the same forest type and region, and approaches that assume a constant fraction of TBCF relative to ANPP may be missing some of this variability. These relationships can aid with estimates of forest soil respiration and TBCF across landscapes, using spatially explicit forest data such as national inventories or remotely sensed data products.

Photosynthetic leaf area modulates tiller bud outgrowth in sorghum: Bud outgrowth is sensitive to leaf area

DOE PAGES

Kebrom, Tesfamichael H.; Mullet, John E.

2014-12-12

Shoot branches or tillers develop from axillary buds. The dormancy versus outgrowth fates of buds depends on genetic, environmental and hormonal signals. Defoliation inhibits bud outgrowth indicating the role of leaf-derived metabolic factors such as sucrose in bud outgrowth. In this study, the sensitivity of bud outgrowth to selective defoliation was investigated. At 6 d after planting (6 DAP), the first two leaves of sorghum were fully expanded and the third was partially emerged. Therefore, the leaves were selectively defoliated at 6 DAP and the length of the bud in the first leaf axil was measured at 8 DAP. Budmore » outgrowth was inhibited by defoliation of only 2 cm from the tip of the second leaf blade. The expression of dormancy and sucrose-starvation marker genes was up-regulated and cell cycle and sucrose-inducible genes was down-regulated during the first 24 h postdefoliation of the second leaf.At 48 h, the expression of these genes was similar to controls as the defoliated plant recovers. Our results demonstrate that small changes in photosynthetic leaf area affect the propensity of tiller buds for outgrowth. Therefore, variation in leaf area and photosynthetic activity should be included when integrating sucrose into models of shoot branching.« less

Relationships of leaf dark respiration to leaf nitrogen, specific leaf area and leaf life-span: a test across biomes and functional groups

Treesearch

Peter B. Reich; Michael B. Walters; David S. Ellsworth; [and others; [Editor’s note: James M.. Vose is the SRS co-author for this publication.

1998-01-01

Based on prior evidence of coordinated multiple leaf trait scaling, the authors hypothesized that variation among species in leaf dark respiration rate (Rd) should scale with variation in traits such as leaf nitrogen (N), leaf life-span, specific leaf area (SLA), and net photosynthetic capacity (Amax). However, it is not known whether such scaling, if it exists, is...

Algorithm for retrieving vegetative canopy and leaf parameters from multi- and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Borel, Christoph

2009-05-01

In recent years hyper-spectral data has been used to retrieve information about vegetative canopies such as leaf area index and canopy water content. For the environmental scientist these two parameters are valuable, but there is potentially more information to be gained as high spatial resolution data becomes available. We developed an Amoeba (Nelder-Mead or Simplex) based program to invert a vegetative canopy radiosity model coupled with a leaf (PROSPECT5) reflectance model and modeled for the background reflectance (e.g. soil, water, leaf litter) to a measured reflectance spectrum. The PROSPECT5 leaf model has five parameters: leaf structure parameter Nstru, chlorophyll a+b concentration Cab, carotenoids content Car, equivalent water thickness Cw and dry matter content Cm. The canopy model has two parameters: total leaf area index (LAI) and number of layers. The background reflectance model is either a single reflectance spectrum from a spectral library() derived from a bare area pixel on an image or a linear mixture of soil spectra. We summarize the radiosity model of a layered canopy and give references to the leaf/needle models. The method is then tested on simulated and measured data. We investigate the uniqueness, limitations and accuracy of the retrieved parameters on canopy parameters (low, medium and high leaf area index) spectral resolution (32 to 211 band hyperspectral), sensor noise and initial conditions.

Estimating leaf area and leaf biomass of open-grown deciduous urban trees

Treesearch

David J. Nowak

1996-01-01

Logarithmic regression equations were developed to predict leaf area and leaf biomass for open-grown deciduous urban trees based on stem diameter and crown parameters. Equations based on crown parameters produced more reliable estimates. The equations can be used to help quantify forest structure and functions, particularly in urbanizing and urban/suburban areas.

Leaf area prediction models for Tsuga canadensis in Maine

Treesearch

Laura S. Kenefic; R.S. Seymour

1999-01-01

Tsuga canadensis (L.) Carr. (eastern hemlock) is a common species throughout the Acadian forest. Studies of leaf area and growth efficiency in this forest type have been limited by the lack of equations to predict leaf area of this species. We found that sapwood area was an effective leaf area surrogate in T. canadensis, though...

Remote sensing of temperate coniferous forest lead area index - The influence of canopy closure, understory vegetation and background reflectance

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

1990-01-01

Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

NASA Astrophysics Data System (ADS)

Anderson, Martha C.; Zolin, Cornelio A.; Hain, Christopher R.; Semmens, Kathryn; Tugrul Yilmaz, M.; Gao, Feng

2015-07-01

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought

Leaf phenology as one important driver of seasonal changes in isoprene emission in central Amazonia

DOE PAGES

Alves, Eliane G.; Tota, Julio; Turnipseed, Andrew; ...

2018-03-06

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of seasonal patterns of isoprene fluxes and associated mechanistic controls are still limited, especially in Amazonian evergreen forests. Here in this article, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest with meteorological observations and with tower-camera leaf phenology to improve understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas themore » lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature can not totally explain the isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf-age class (e.g. leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R 2=0.59, p<0.05). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm utilizing results from the camera-derived leaf phenology that provided LAI categorized in three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations of isoprene fluxes (R 2=0.52, p<0.05). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and of identifying forest adaptive mechanisms that underlie seasonal variation of isoprene emissions in Amazonia.« less

Leaf phenology as one important driver of seasonal changes in isoprene emission in central Amazonia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alves, Eliane G.; Tota, Julio; Turnipseed, Andrew

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of seasonal patterns of isoprene fluxes and associated mechanistic controls are still limited, especially in Amazonian evergreen forests. Here in this article, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest with meteorological observations and with tower-camera leaf phenology to improve understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas themore » lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature can not totally explain the isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf-age class (e.g. leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R 2=0.59, p<0.05). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm utilizing results from the camera-derived leaf phenology that provided LAI categorized in three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations of isoprene fluxes (R 2=0.52, p<0.05). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and of identifying forest adaptive mechanisms that underlie seasonal variation of isoprene emissions in Amazonia.« less

Species-Specific Effects on Throughfall Kinetic Energy in Subtropical Forest Plantations Are Related to Leaf Traits and Tree Architecture

PubMed Central

Bruelheide, Helge; Härdtle, Werner; Kröber, Wenzel; Li, Ying; von Oheimb, Goddert

2015-01-01

Soil erosion is a key threat to many ecosystems, especially in subtropical China where high erosion rates occur. While the mechanisms that induce soil erosion on agricultural land are well understood, soil erosion processes in forests have rarely been studied. Throughfall kinetic energy (TKE) is influenced in manifold ways and often determined by the tree’s leaf and architectural traits. We investigated the role of species identity in mono-specific stands on TKE by asking to what extent TKE is species-specific and which leaf and architectural traits account for variation in TKE. We measured TKE of 11 different tree species planted in monocultures in a biodiversity-ecosystem-functioning experiment in subtropical China, using sand-filled splash cups during five natural rainfall events in summer 2013. In addition, 14 leaf and tree architectural traits were measured and linked to TKE. Our results showed that TKE was highly species-specific. Highest TKE was found below Choerospondias axillaris and Sapindus saponaria, while Schima superba showed lowest TKE. These species-specific effects were mediated by leaf habit, leaf area (LA), leaf pinnation, leaf margin, stem diameter at ground level (GD), crown base height (CBH), tree height, number of branches and leaf area index (LAI) as biotic factors and throughfall as abiotic factor. Among these, leaf habit, tree height and LA showed the highest effect sizes on TKE and can be considered as major drivers of TKE. TKE was positively influenced by LA, GD, CBH, tree height, LAI, and throughfall amount while it was negatively influenced by the number of branches. TKE was lower in evergreen, simple leaved and dentate leaved than in deciduous, pinnated or entire leaved species. Our results clearly showed that soil erosion in forest plantations can be mitigated by the appropriate choice of tree species. PMID:26079260

Species-Specific Effects on Throughfall Kinetic Energy in Subtropical Forest Plantations Are Related to Leaf Traits and Tree Architecture.

PubMed

Goebes, Philipp; Bruelheide, Helge; Härdtle, Werner; Kröber, Wenzel; Kühn, Peter; Li, Ying; Seitz, Steffen; von Oheimb, Goddert; Scholten, Thomas

2015-01-01

Soil erosion is a key threat to many ecosystems, especially in subtropical China where high erosion rates occur. While the mechanisms that induce soil erosion on agricultural land are well understood, soil erosion processes in forests have rarely been studied. Throughfall kinetic energy (TKE) is influenced in manifold ways and often determined by the tree's leaf and architectural traits. We investigated the role of species identity in mono-specific stands on TKE by asking to what extent TKE is species-specific and which leaf and architectural traits account for variation in TKE. We measured TKE of 11 different tree species planted in monocultures in a biodiversity-ecosystem-functioning experiment in subtropical China, using sand-filled splash cups during five natural rainfall events in summer 2013. In addition, 14 leaf and tree architectural traits were measured and linked to TKE. Our results showed that TKE was highly species-specific. Highest TKE was found below Choerospondias axillaris and Sapindus saponaria, while Schima superba showed lowest TKE. These species-specific effects were mediated by leaf habit, leaf area (LA), leaf pinnation, leaf margin, stem diameter at ground level (GD), crown base height (CBH), tree height, number of branches and leaf area index (LAI) as biotic factors and throughfall as abiotic factor. Among these, leaf habit, tree height and LA showed the highest effect sizes on TKE and can be considered as major drivers of TKE. TKE was positively influenced by LA, GD, CBH, tree height, LAI, and throughfall amount while it was negatively influenced by the number of branches. TKE was lower in evergreen, simple leaved and dentate leaved than in deciduous, pinnated or entire leaved species. Our results clearly showed that soil erosion in forest plantations can be mitigated by the appropriate choice of tree species.

Relationships of leaf dark respiration to leaf nitrogen, specific leaf area and leaf life-span: a test across biomes and functional groups.

PubMed

Reich, Peter B; Walters, Michael B; Ellsworth, David S; Vose, James M; Volin, John C; Gresham, Charles; Bowman, William D

1998-05-01

Based on prior evidence of coordinated multiple leaf trait scaling, we hypothesized that variation among species in leaf dark respiration rate (R d ) should scale with variation in traits such as leaf nitrogen (N), leaf life-span, specific leaf area (SLA), and net photosynthetic capacity (A max ). However, it is not known whether such scaling, if it exists, is similar among disparate biomes and plant functional types. We tested this idea by examining the interspecific relationships between R d measured at a standard temperature and leaf life-span, N, SLA and A max for 69 species from four functional groups (forbs, broad-leafed trees and shrubs, and needle-leafed conifers) in six biomes traversing the Americas: alpine tundra/subalpine forest, Colorado; cold temperate forest/grassland, Wisconsin; cool temperate forest, North Carolina; desert/shrubland, New Mexico; subtropical forest, South Carolina; and tropical rain forest, Amazonas, Venezuela. Area-based R d was positively related to area-based leaf N within functional groups and for all species pooled, but not when comparing among species within any site. At all sites, mass-based R d (R d-mass ) decreased sharply with increasing leaf life-span and was positively related to SLA and mass-based A max and leaf N (leaf N mass ). These intra-biome relationships were similar in shape and slope among sites, where in each case we compared species belonging to different plant functional groups. Significant R d-mass -N mass relationships were observed in all functional groups (pooled across sites), but the relationships differed, with higher R d at any given leaf N in functional groups (such as forbs) with higher SLA and shorter leaf life-span. Regardless of biome or functional group, R d-mass was well predicted by all combinations of leaf life-span, N mass and/or SLA (r 2 ≥ 0.79, P < 0.0001). At any given SLA, R d-mass rises with increasing N mass and/or decreasing leaf life-span; and at any level of N mass , R d

Structure Measurements of Leaf and Woody Components of Forests with Dual-Wavelength Lidar Scanning Data

NASA Astrophysics Data System (ADS)

Strahler, A. H.; Li, Z.; Schaaf, C.; Howe, G.; Martel, J.; Hewawasam, K.; Douglas, E. S.; Chakrabarti, S.; Cook, T.; Paynter, I.; Saenz, E. J.; Wang, Z.; Woodcock, C. E.; Jupp, D. L. B.; Schaefer, M.; Newnham, G.

2014-12-01

Forest structure plays a critical role in the exchange of energy, carbon and water between land and atmosphere and nutrient cycle. We can provide detailed forest structure measurements of leaf and woody components with the Dual Wavelength Echidna® Lidar (DWEL), which acquires full-waveform scans at both near-infrared (NIR, 1064 nm) and shortwave infrared (SWIR, 1548 nm) wavelengths from simultaneous laser pulses. We collected DWEL scans at a broadleaf forest stand and a conifer forest stand at Harvard Forest in June 2014. Power returned from leaves is much lower than from woody materials such as trunks and branches at the SWIR wavelength due to the liquid water absorption by leaves, whereas returned power at the NIR wavelength is similar from both leaves and woody materials. We threshold a normalized difference index (NDI), defined as the difference between returned power at the two wavelengths divided by their sum, to classify each return pulse as a leaf or trunk/branch hit. We obtain leaf area index (LAI), woody area index (WAI) and vertical profiles of leaf and woody components directly from classified lidar hits without empirical wood-to-total ratios as are commonly used in optical methods of LAI estimation. Tree heights, diameter at breast height (DBH), and stem count density are the other forest structure parameters estimated from our DWEL scans. The separation of leaf and woody components in tandem with fine-scale forest structure measurements will benefit studies on carbon allocation of forest ecosystems and improve our understanding of the effects of forest structure on ecosystem functions. This research is supported by NSF grant, MRI-0923389

Spatially Distributed Assimilation of Remotely Sensed Leaf Area Index and Potential Evapotranspiration for Hydrologic Modeling in Wetland Landscapes

NASA Astrophysics Data System (ADS)

Rajib, A.; Evenson, G. R.; Golden, H. E.; Lane, C.

2017-12-01

Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. Accordingly, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate realistic ground conditions, particularly those involved with complex land-atmosphere feedbacks, vegetation growth, and energy balances. Uncertainty persists despite using high resolution topography and/or detailed land use data. Thus, a good hydrologic model can produce right answers for wrong reasons. In this study, we develop an efficient approach for multi-variable assimilation of remotely sensed earth observations (EOs) into a hydrologic model and apply it in the 1700 km2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. Our goal is to employ EOs, specifically Leaf Area Index (LAI) and Potential Evapotranspiration (PET), as surrogates for the aforementioned processes without overruling the model's built-in physical/semi-empirical process conceptualizations. To do this, we modified the source code of an already-improved version of the Soil and Water Assessment Tool (SWAT) for wetland hydrology (Evenson et al. 2016 HP 30(22):4168) to directly assimilate remotely-sensed LAI and PET (obtained from the 500 m and 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products, respectively) into each model Hydrologic Response Unit (HRU). Two configurations of the model, one with and one without EO assimilation, are calibrated against streamflow observations at the watershed outlet. Spatio-temporal changes in the HRU-level water balance, based on calibrated outputs, are evaluated using MODIS Actual Evapotranspiration (AET) as a reference. It is expected that the model configuration having remotely sensed LAI and PET, will simulate more realistic land-atmosphere feedbacks, vegetation growth and energy balance. As a result, this will decrease simulated

Evaluation of the MODIS LAI product using independent lidar-derived LAI: A case study in mixed conifer forest

Treesearch

Jennifer L. R. Jensen; Karen S. Humes; Andrew T. Hudak; Lee A. Vierling; Eric Delmelle

2011-01-01

This study presents an alternative assessment of the MODIS LAI product for a 58,000 ha evergreen needleleaf forest located in the western Rocky Mountain range in northern Idaho by using lidar data to model (R2=0.86, RMSE=0.76) and map LAI at higher resolution across a large number of MODIS pixels in their entirety. Moderate resolution (30 m) lidar-based LAI estimates...

Coordination of crown structure, leaf plasticity and carbon gain within the crowns of three winter-deciduous mature trees.

PubMed

Uemura, Akira; Harayama, Hisanori; Koike, Nobuya; Ishida, Atsushi

2006-05-01

We examined the vertical profiles of leaf characteristics within the crowns of two late-successional (Fagus crenata Blume and Fagus japonica Maxim.) and one early-successional tree species (Betula grossa Sieb. et Zucc.) in a Japanese forest. We also assessed the contributions of the leaves in each crown layer to whole-crown instantaneous carbon gain at midday. Carbon gain was estimated from the relationship between electron transport and photosynthetic rates. We hypothesized that more irradiance can penetrate into the middle of the crown if the upper crown layers have steep leaf inclination angles. We found that such a crown has a high whole-crown carbon gain, even if leaf traits do not change greatly with decreasing crown height. Leaf area indices (LAIs) of the two Fagus trees (5.26-5.52) were higher than the LAI of the B. grossa tree (4.50) and the leaves of the F. crenata tree were more concentrated in the top crown layers than were leaves of the other trees. Whole-crown carbon gain per unit ground area (micromol m(-2) ground s(-1)) at midday on fine days in summer was 16.3 for F. crenata, 11.0 for F. japonica, and 20.4 for B. grossa. In all study trees, leaf dry mass (LMA) and leaf nitrogen content (N) per unit area decreased with decreasing height in the crown, but leaf N per unit mass increased. Variations (plasticity) between the uppermost and lowermost crown layers in LMA, leaf N, the ratio of chlorophyll to N and the ratio of chlorophyll a to b were smaller for F. japonica and B. grossa than for F. crenata. The light extinction coefficients in the crowns were lower for the F. japonica and B. grossa trees than for the F. crenata tree. The leaf carbon isotope ratio (delta(13)C) was higher for F. japonica and B. grossa than for F. crenata, especially in the mid-crown. These results suggest that, in crowns with low leaf plasticity but steep leaf inclination angles, such as those of F. japonica and B. grossa trees, irradiance can penetrate into the middle of

Integration of ALS and TLS for calibration and validation of LAI profiles from large footprint lidar

NASA Astrophysics Data System (ADS)

Armston, J.; Tang, H.; Hancock, S.; Hofton, M. A.; Dubayah, R.; Duncanson, L.; Fatoyinbo, T. E.; Blair, J. B.; Disney, M.

2016-12-01

The Global Ecosystem Dynamics Investigation (GEDI) is designed to provide measurements of forest vertical structure and above-ground biomass density (AGBD) over tropical and temperate regions. The GEDI is a multi-beam waveform lidar that will acquire transects of forest canopy vertical profiles in conditions of up to 99% canopy cover. These are used to produce a number of canopy height and profile metrics to model habitat suitability and AGBD. These metrics include vertical leaf area index (LAI) profiles, which require some pre-launch refinement of large-footprint waveform processing methods for separating canopy and ground returns and estimation of their reflectance. Previous research developments in modelling canopy gap probability to derive canopy and ground reflectance from waveforms have primarily used data from small-footprint instruments, however development of a generalized spatial model with uncertainty will be useful for interpreting and modelling waveforms from large-footprint instruments such as the NASA Land Vegetation and Ice Sensor (LVIS) with a view to implementation for GEDI. Here we present an analysis of waveform lidar data from the NASA Land Vegetation and Ice Sensor (LVIS), which were acquired in Gabon in February 2016 to support the NASA/ESA AfriSAR campaign. AfriSAR presents a unique opportunity to test refined methods for retrieval of LAI profiles in high above-ground biomass rainforests (up to 600 Mg/ha) with dense canopies (>90% cover), where the greatest uncertainty exists. Airborne and Terrestrial Laser Scanning data (TLS) were also collected, enabling quantification of algorithm performance in plots of dense canopy cover. Refinement of canopy gap probability and LAI profile modelling from large-footprint lidar was based on solving for canopy and ground reflectance parameters spatially by penalized least-squares. The sensitivities of retrieved cover and LAI profiles to variation in canopy and ground reflectance showed improvement

Measuring fraction of intercepted photosynthetically active radiation with a ceptometer: the importance of adopting a universal methodological approach

USDA-ARS?s Scientific Manuscript database

It is desirable to be able to predict above ground biomass production indirectly, without extensive sampling or destructive harvesting. Leaf area index (LAI) is the amount of leaf surface area per ground area and is an important parameter in ecophysiology. As LAI increases, the photosynthetically ...

Patient and prescriber perspectives on long-acting injectable (LAI) antipsychotics and analysis of in-office discussion regarding LAI treatment for schizophrenia

PubMed Central

2013-01-01

Background The research goal is to better understand prescriber, patient, and caregiver perspectives about long-acting injectable (LAI) antipsychotic therapy and how these perspectives affect LAI use. Addressing these perspectives in the clinic may lead to greater success in achieving therapeutic goals for the patient with schizophrenia. Methods Ethnographic information was collected from a non-random sample of 69 prescriber-patient conversations (60 with community mental health center [CMHC] psychiatrists; 9 with nurse-practitioners) recorded during treatment visits from August 2011 to February 2012, transcribed and analyzed. Discussions were categorized according to 11 predetermined CMHC topics. In-person observations were also conducted at 4 CMHCs, including home visits by researchers (n = 15 patients) prior to the CMHC visit and observations of patients receiving injections and interacting with staff. Telephone in-depth interviews with psychiatrists, patients, and caregivers to gather additional information on LAI discussion, prescription, or use were conducted. Results Antipsychotic treatment decisions were made without patient or caregiver input in 40 of 60 (67%) of psychiatrist-patient conversations. Involvement of patients or caregivers in treatment decisions was greater when discussing LAI (15 of 60 [25%]) vs oral antipsychotic treatment (5 of 60 [8%]). LAIs were not discussed by psychiatrists in 11 of 22 (50%) patients taking oral antipsychotics. When offered, more LAI-naïve patients expressed neutral (9 of 19 [47%]) rather than favorable (3 of 19 [16%]) or unfavorable (7 of 19 [37%]) responses. Prescribers were most concerned about potentially damaging the therapeutic relationship and side-effects when discussing LAIs while patient resistance was often related to negative feelings about injections. Psychiatrists had some success in overcoming patient objections to LAIs by addressing and decomposing initial resistance. More than half (11 of 19 [58

Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy

NASA Astrophysics Data System (ADS)

Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.

2014-12-01

Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in

Evaluating Leaf and Canopy Reflectance of Stressed Rice Plants to Monitor Arsenic Contamination.

PubMed

Bandaru, Varaprasad; Daughtry, Craig S; Codling, Eton E; Hansen, David J; White-Hansen, Susan; Green, Carrie E

2016-06-18

Arsenic contamination is a serious problem in rice cultivated soils of many developing countries. Hence, it is critical to monitor and control arsenic uptake in rice plants to avoid adverse effects on human health. This study evaluated the feasibility of using reflectance spectroscopy to monitor arsenic in rice plants. Four arsenic levels were induced in hydroponically grown rice plants with application of 0, 5, 10 and 20 µmol·L(-1) sodium arsenate. Reflectance spectra of upper fully expanded leaves were acquired over visible and infrared (NIR) wavelengths. Additionally, canopy reflectance for the four arsenic levels was simulated using SAIL (Scattering by Arbitrarily Inclined Leaves) model for various soil moisture conditions and leaf area indices (LAI). Further, sensitivity of various vegetative indices (VIs) to arsenic levels was assessed. Results suggest that plants accumulate high arsenic amounts causing plant stress and changes in reflectance characteristics. All leaf spectra based VIs related strongly with arsenic with coefficient of determination (r²) greater than 0.6 while at canopy scale, background reflectance and LAI confounded with spectral signals of arsenic affecting the VIs' performance. Among studied VIs, combined index, transformed chlorophyll absorption reflectance index (TCARI)/optimized soil adjusted vegetation index (OSAVI) exhibited higher sensitivity to arsenic levels and better resistance to soil backgrounds and LAI followed by red edge based VIs (modified chlorophyll absorption reflectance index (MCARI) and TCARI) suggesting that these VIs could prove to be valuable aids for monitoring arsenic in rice fields.

The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France

NASA Astrophysics Data System (ADS)

Fairbairn, David; Lavinia Barbu, Alina; Napoly, Adrien; Albergel, Clément; Mahfouf, Jean-François; Calvet, Jean-Christophe

2017-04-01

This study evaluates the impact of assimilating surface soil moisture (SSM) and leaf area index (LAI) observations into a land surface model using the SAFRAN-ISBA-MODCOU (SIM) hydrological suite. SIM consists of three stages: (1) an atmospheric reanalysis (SAFRAN) over France, which forces (2) the three-layer ISBA land surface model, which then provides drainage and runoff inputs to (3) the MODCOU hydro-geological model. The drainage and runoff outputs from ISBA are validated by comparing the simulated river discharge from MODCOU with over 500 river-gauge observations over France and with a subset of stations with low-anthropogenic influence, over several years. This study makes use of the A-gs version of ISBA that allows for physiological processes. The atmospheric forcing for the ISBA-A-gs model underestimates direct shortwave and long-wave radiation by approximately 5 % averaged over France. The ISBA-A-gs model also substantially underestimates the grassland LAI compared with satellite retrievals during winter dormancy. These differences result in an underestimation (overestimation) of evapotranspiration (drainage and runoff). The excess runoff flowing into the rivers and aquifers contributes to an overestimation of the SIM river discharge. Two experiments attempted to resolve these problems: (i) a correction of the minimum LAI model parameter for grasslands and (ii) a bias-correction of the model radiative forcing. Two data assimilation experiments were also performed, which are designed to correct random errors in the initial conditions: (iii) the assimilation of LAI observations and (iv) the assimilation of SSM and LAI observations. The data assimilation for (iii) and (iv) was done with a simplified extended Kalman filter (SEKF), which uses finite differences in the observation operator Jacobians to relate the observations to the model variables. Experiments (i) and (ii) improved the median SIM Nash scores by about 9 % and 18 % respectively. Experiment (iii

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Jin; Serbin, Shawn P.; Xu, Xiangtao

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here in this paper, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO 2 assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leafmore » quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO 2 assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO 2 assimilation and highlights the importance of

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

DOE PAGES

Wu, Jin; Serbin, Shawn P.; Xu, Xiangtao; ...

2017-04-18

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here in this paper, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO 2 assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leafmore » quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO 2 assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO 2 assimilation and highlights the importance of

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.

2018-01-01

With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

MODIS Measures Total U.S. Leaf Area

NASA Technical Reports Server (NTRS)

2002-01-01

This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the MODIS Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a MODIS data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy reflected by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana

Photosynthesis and canopy characteristics in genetically defined families of silver birch (Betula pendula).

PubMed

Wang, T; Tigerstedt, P M; Viherä-Aarnio, A

1995-10-01

Net photosynthetic rates (A) of leaves in upper and lower crown layers (A(upper) and A(lower)), leaf area index (LAI), mean tilt angle (MTA), several leaf characteristics, and volume growth were observed in fast- and slow-growing families of a 14-year-old full-sib and half-sib family progeny test of Betula pendula Roth. Each measure of net photosynthetic rate was calculated after correcting measured net photosynthesis for the effects of environmental variables. The differences in A(upper) and LAI among families were significant. The proportions of the total variance assigned to family for A(upper), A(lower) and LAI were 33.64, 28.93 and 54.99%, respectively. The mean A(upper) and LAI of the fast-growing families were significantly higher than those of the slow-growing families, whereas the mean A(lower) of the fast-growing families was significantly lower than that of the slow-growing families. There were also significant differences among families in leaf size, leaf shape, and the ratios leaf fresh weight/area and leaf dry weight/area. Between 27.55 and 54.55% of the total variance in these characteristics could be assigned to the family effect. Volume growth was positively correlated with A(upper) and LAI, but it was most strongly correlated with A(upper) x LAI.

Worldwide Historical Estimates of Leaf Area Index, 1932-2000

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scurlock, JMO

2002-02-06

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 andmore » other vegetation parameters. The LA1 data are linked to a bibliography of over 300 original source references. These historic LA1 data are mostly from natural and seminatural (managed) ecosystems, although some agricultural estimates are also included. Although methodologies for determining LA1 have changed over the decades, it is useful to represent the inconsistencies (e.g., in maximum value reported for a particular biome) that are actually found in the scientific literature. Needleleaf (coniferous) forests are by far the most commonly measured biome/land cover types in this compilation, with 22% of the measurements from temperate evergreen needleleaf forests, and boreal evergreen needleleaf forests and crops the next most common (about 9% each). About 40% of the records in the data set were published in the past 10 years (1991-2000), with a further 20% collected between 1981 and 1990. Mean LAI ({+-} standard deviation), distributed between 15 biome/land cover classes, ranged from 1.31 {+-} 0.85 for deserts to 8.72 {+-} 4.32 for tree plantations, with evergreen forests (needleleaf and broadleaf) displaying the highest LA1 among the natural terrestrial vegetation classes. We have identified statistical outliers in this data set, both globally and according to the different biome/land cover classes, but despite some decreases in mean LA1 values

[Photosynthetic gas exchange and water utilization of flag leaf of spring wheat with bunch sowing and field plastic mulching below soil on semi-arid rain-fed area.

PubMed

Yang, Wen Xiong; Liu, Na; Liu, Xiao Hua; Zhang, Xue Ting; Wang, Shi Hong; Yuan, Jun Xiu; Zhang, Xu Cheng

2016-07-01

Based on the field experiment which was conducted in Dingxi County of Gansu Province, and involved in the three treatments: (1) plastic mulching on entire land with soil coverage and bunching (PMS), (2) plastic mulching on entire land and bunching (PM), and (3) direct bunching without mulching (CK). The parameters of SPAD values, chlorophyll fluorescence parameters, photosynthetic gas exchange parameters, as well as leaf area index (LAI), yield, evapotranspiration, and water use efficiency in flag leaves of spring wheat were recorded and analyzed from 2012 to 2013 continuously. The results showed that SPAD values of wheat flag leaves increased in PMS by 10.0%-21.5% and 3.2%-21.6% compared to PM and CK in post-flowering stage, respectively. The maximum photochemical efficiency (F v /F m ) , actual photochemical efficiency (Φ PS 2 ) of photosystem 2 (PS2), and photochemical quenching coefficient (q P ) of PMS were higher than those of PM and CK, the maximum increment values were 6.1%, 9.6% and 30.9% as compared with PM, and significant differences were observed in filling stage (P＜0.05). The values of q N in PMS were lowest among the three treatments, and it decreased significantly by 23.8% and 15.4% in heading stage in 2012 and 2013 respectively, as compared with PM. The stoma conductance (g s ) of wheat flag leaves in PMS was higher than that of PM and CK, with significant difference being observed in filling stage, and it increased by 17.1% and 21.1% in 2012 and 2013 respectively, as compared with PM. The transpiration rate (T r ), net photosynthetic rate (P n ), and leaf instantaneous water use efficiency (WUE i ) except heading stage in 2013 of PMS increased by 5.4%-16.7%, 11.2%-23.7%, and 5.6%-7.2%, respectively, as compared with PM, and significant difference of WUE i was observed in flowering stage in 2012. The leaf area index (LAI) of PMS was higher than that of PM and CK, especially, it differed significantly in seasonal drought of 2013. Consequently

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison.

PubMed

Hu, Zhongmin; Shi, Hao; Cheng, Kaili; Wang, Ying-Ping; Piao, Shilong; Li, Yue; Zhang, Li; Xia, Jianyang; Zhou, Lei; Yuan, Wenping; Running, Steve; Li, Longhui; Hao, Yanbin; He, Nianpeng; Yu, Qiang; Yu, Guirui

2018-04-17

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons. © 2018 John Wiley & Sons Ltd.

Evaluating the condition of a mangrove forest of the Mexican Pacific based on an estimated leaf area index mapping approach.

PubMed

Kovacs, J M; King, J M L; Flores de Santiago, F; Flores-Verdugo, F

2009-10-01

Given the alarming global rates of mangrove forest loss it is important that resource managers have access to updated information regarding both the extent and condition of their mangrove forests. Mexican mangroves in particular have been identified as experiencing an exceptional high annual rate of loss. However, conflicting studies, using remote sensing techniques, of the current state of many of these forests may be hindering all efforts to conserve and manage what remains. Focusing on one such system, the Teacapán-Agua Brava-Las Haciendas estuarine-mangrove complex of the Mexican Pacific, an attempt was made to develop a rapid method of mapping the current condition of the mangroves based on estimated LAI. Specifically, using an AccuPAR LP-80 Ceptometer, 300 indirect in situ LAI measurements were taken at various sites within the black mangrove (Avicennia germinans) dominated forests of the northern section of this system. From this sample, 225 measurements were then used to develop linear regression models based on their relationship with corresponding values derived from QuickBird very high resolution optical satellite data. Specifically, regression analyses of the in situ LAI with both the normalized difference vegetation index (NDVI) and the simple ration (SR) vegetation index revealed significant positive relationships [LAI versus NDVI (R (2) = 0.63); LAI versus SR (R (2) = 0.68)]. Moreover, using the remaining sample, further examination of standard errors and of an F test of the residual variances indicated little difference between the two models. Based on the NDVI model, a map of estimated mangrove LAI was then created. Excluding the dead mangrove areas (i.e. LAI = 0), which represented 40% of the total 30.4 km(2) of mangrove area identified in the scene, a mean estimated LAI value of 2.71 was recorded. By grouping the healthy fringe mangrove with the healthy riverine mangrove and by grouping the dwarf mangrove together with the poor condition

Leaf density explains variation in leaf mass per area in rice between cultivars and nitrogen treatments.

PubMed

Xiong, Dongliang; Wang, Dan; Liu, Xi; Peng, Shaobing; Huang, Jianliang; Li, Yong

2016-05-01

Leaf mass per area (LMA) is an important leaf trait; however, correlations between LMA and leaf anatomical features and photosynthesis have not been fully investigated, especially in cereal crops. The objectives of this study were (a) to investigate the correlations between LMA and leaf anatomical traits; and (b) to clarify the response of LMA to nitrogen supply and its effect on photosynthetic nitrogen use efficiency (PNUE). In the present study, 11 rice varieties were pot grown under sufficient nitrogen (SN) conditions, and four selected rice cultivars were grown under low nitrogen (LN) conditions. Leaf anatomical traits, gas exchange and leaf N content were measured. There was large variation in LMA across selected rice varieties. Regression analysis showed that the variation in LMA was more closely related to leaf density (LD) than to leaf thickness (LT). LMA was positively related to the percentage of mesophyll tissue area (%mesophyll), negatively related to the percentage of epidermis tissue area (%epidermis) and unrelated to the percentage of vascular tissue area (%vascular). The response of LMA to N supplementation was dependent on the variety and was also mainly determined by the response of LD to N. Compared with SN, photosynthesis was significantly decreased under LN, while PNUE was increased. The increase in PNUE was more critical in rice cultivars with a higher LMA under SN supply. Leaf density is the major cause of the variation in LMA across rice varieties and N treatments, and an increase in LMA under high N conditions would aggravate the decrease in PNUE. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Assessment of actual transpiration rate in olive tree field combining sap-flow, leaf area index and scintillometer measurements

NASA Astrophysics Data System (ADS)

Agnese, C.; Cammalleri, C.; Ciraolo, G.; Minacapilli, M.; Provenzano, G.; Rallo, G.; de Bruin, H. A. R.

2009-09-01

Models to estimate the actual evapotranspiration (ET) in sparse vegetation area can be fundamental for agricultural water managements, especially when water availability is a limiting factor. Models validation must be carried out by considering in situ measurements referred to the field scale, which is the relevant scale of the modelled variables. Moreover, a particular relevance assumes to consider separately the components of plant transpiration (T) and soil evaporation (E), because only the first is actually related to the crop stress conditions. Objective of the paper was to assess a procedure aimed to estimate olive trees actual transpiration by combining sap flow measurements with the scintillometer technique at field scale. The study area, located in Western Sicily (Italy), is mainly cultivated with olive crop and is characterized by typical Mediterranean semi-arid climate. Measurements of sap flow and crop actual evapotranspiration rate were carried out during 2008 irrigation season. Crop transpiration fluxes, measured on some plants by means of sap flow sensors, were upscaled considering the leaf area index (LAI). The comparison between evapotranspiration values, derived by displaced-beam small-aperture scintillometer (DBSAS-SLS20, Scintec AG), with the transpiration fluxes obtained by the sap flow sensors, also allowed to evaluate the contribute of soil evaporation in an area characterized by low vegetation coverage.

Automated estimation of leaf distribution for individual trees based on TLS point clouds

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Rutzinger, Martin; Bremer, Magnus

2017-04-01

Light Detection and Ranging (LiDAR) especially the ground based LiDAR (Terrestrial Laser Scanning - TLS) is an operational used and widely available measurement tool supporting forest inventory updating and research in forest ecology. High resolution point clouds from TLS already represent single leaves which can be used for a more precise estimation of Leaf Area Index (LAI) and for higher accurate biomass estimation. However, currently the methodology for extracting single leafs from the unclassified point clouds for individual trees is still missing. The aim of this study is to present a novel segmentation approach in order to extract single leaves and derive features related to leaf morphology (such as area, slope, length and width) of each single leaf from TLS point cloud data. For the study two exemplary single trees were scanned in leaf-on condition on the university campus of Innsbruck during calm wind conditions. A northern red oak (Quercus rubra) was scanned by a discrete return recording Optech ILRIS-3D TLS scanner and a tulip tree (Liliodendron tulpifera) with Riegl VZ-6000 scanner. During the scanning campaign a reference dataset was measured parallel to scanning. In this case 230 leaves were randomly collected around the lower branches of the tree and photos were taken. The developed workflow steps were the following: in the first step normal vectors and eigenvalues were calculated based on the user specified neighborhood. Then using the direction of the largest eigenvalue outliers i.e. ghost points were removed. After that region growing segmentation based on the curvature and angles between normal vectors was applied on the filtered point cloud. On each segment a RANSAC plane fitting algorithm was applied in order to extract the segment based normal vectors. Using the related features of the calculated segments the stem and branches were labeled as non-leaf and other segments were classified as leaf. The validation of the different segmentation

The relationship of leaf photosynthetic traits V cmax and Jmax - to leaf nitrogen, leaf phosphorus, and specific leaf area: A meta-analysis and modeling study

DOE PAGES

Walker, Anthony P.; Beckerman, Andrew P.; Gu, Lianhong; ...

2014-07-25

Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between Vcmax and Jmax and leaf nitrogen (N) are typically derivedmore » from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global-scale relationship between Vcmax and Jmax and P or SLA limiting the ability of global-scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of Vcmax and Jmax with leaf N, P, and SLA. Vcmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N. Jmax was strongly related to Vcmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm 2), increasing leaf P from 0.05 to 0.22 gm 2 nearly doubled assimilation rates. Lastly, we show that plants may employ a conservative strategy of Jmax to Vcmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.« less

The relationship of leaf photosynthetic traits V cmax and Jmax - to leaf nitrogen, leaf phosphorus, and specific leaf area: A meta-analysis and modeling study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Anthony P.; Beckerman, Andrew P.; Gu, Lianhong

Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between Vcmax and Jmax and leaf nitrogen (N) are typically derivedmore » from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global-scale relationship between Vcmax and Jmax and P or SLA limiting the ability of global-scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of Vcmax and Jmax with leaf N, P, and SLA. Vcmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N. Jmax was strongly related to Vcmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm 2), increasing leaf P from 0.05 to 0.22 gm 2 nearly doubled assimilation rates. Lastly, we show that plants may employ a conservative strategy of Jmax to Vcmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.« less

Large seasonal swings in leaf area of Amazon rainforests

PubMed Central

Myneni, Ranga B.; Yang, Wenze; Nemani, Ramakrishna R.; Huete, Alfredo R.; Dickinson, Robert E.; Knyazikhin, Yuri; Didan, Kamel; Fu, Rong; Negrón Juárez, Robinson I.; Saatchi, Sasan S.; Hashimoto, Hirofumi; Ichii, Kazuhito; Shabanov, Nikolay V.; Tan, Bin; Ratana, Piyachat; Privette, Jeffrey L.; Morisette, Jeffrey T.; Vermote, Eric F.; Roy, David P.; Wolfe, Robert E.; Friedl, Mark A.; Running, Steven W.; Votava, Petr; El-Saleous, Nazmi; Devadiga, Sadashiva; Su, Yin; Salomonson, Vincent V.

2007-01-01

Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation–atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of ≈25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests. PMID:17360360

The relationship between leaf area growth and biomass accumulation in Arabidopsis thaliana

PubMed Central

Weraduwage, Sarathi M.; Chen, Jin; Anozie, Fransisca C.; Morales, Alejandro; Weise, Sean E.; Sharkey, Thomas D.

2015-01-01

Leaf area growth determines the light interception capacity of a crop and is often used as a surrogate for plant growth in high-throughput phenotyping systems. The relationship between leaf area growth and growth in terms of mass will depend on how carbon is partitioned among new leaf area, leaf mass, root mass, reproduction, and respiration. A model of leaf area growth in terms of photosynthetic rate and carbon partitioning to different plant organs was developed and tested with Arabidopsis thaliana L. Heynh. ecotype Columbia (Col-0) and a mutant line, gigantea-2 (gi-2), which develops very large rosettes. Data obtained from growth analysis and gas exchange measurements was used to train a genetic programming algorithm to parameterize and test the above model. The relationship between leaf area and plant biomass was found to be non-linear and variable depending on carbon partitioning. The model output was sensitive to the rate of photosynthesis but more sensitive to the amount of carbon partitioned to growing thicker leaves. The large rosette size of gi-2 relative to that of Col-0 resulted from relatively small differences in partitioning to new leaf area vs. leaf thickness. PMID:25914696

The relationship between leaf area growth and biomass accumulation in Arabidopsis thaliana

DOE PAGES

Weraduwage, Sarathi M.; Chen, Jin; Anozie, Fransisca C.; ...

2015-04-09

Leaf area growth determines the light interception capacity of a crop and is often used as a surrogate for plant growth in high-throughput phenotyping systems. The relationship between leaf area growth and growth in terms of mass will depend on how carbon is partitioned among new leaf area, leaf mass, root mass, reproduction, and respiration. A model of leaf area growth in terms of photosynthetic rate and carbon partitioning to different plant organs was developed and tested with Arabidopsis thaliana L. Heynh. ecotype Columbia (Col-0) and a mutant line, gigantea-2 (gi-2), which develops very large rosettes. Data obtained from growthmore » analysis and gas exchange measurements was used to train a genetic programming algorithm to parameterize and test the above model. The relationship between leaf area and plant biomass was found to be non-linear and variable depending on carbon partitioning. The model output was sensitive to the rate of photosynthesis but more sensitive to the amount of carbon partitioned to growing thicker leaves. The large rosette size of gi-2 relative to that of Col-0 resulted from relatively small differences in partitioning to new leaf area vs. leaf thickness.« less

Comparison of dwarf bamboos (Indocalamus sp.) leaf parameters to determine relationship between spatial density of plants and total leaf area per plant.

PubMed

Shi, Pei-Jian; Xu, Qiang; Sandhu, Hardev S; Gielis, Johan; Ding, Yu-Long; Li, Hua-Rong; Dong, Xiao-Bo

2015-10-01

The relationship between spatial density and size of plants is an important topic in plant ecology. The self-thinning rule suggests a -3/2 power between average biomass and density or a -1/2 power between stand yield and density. However, the self-thinning rule based on total leaf area per plant and density of plants has been neglected presumably because of the lack of a method that can accurately estimate the total leaf area per plant. We aimed to find the relationship between spatial density of plants and total leaf area per plant. We also attempted to provide a novel model for accurately describing the leaf shape of bamboos. We proposed a simplified Gielis equation with only two parameters to describe the leaf shape of bamboos one model parameter represented the overall ratio of leaf width to leaf length. Using this method, we compared some leaf parameters (leaf shape, number of leaves per plant, ratio of total leaf weight to aboveground weight per plant, and total leaf area per plant) of four bamboo species of genus Indocalamus Nakai (I. pedalis (Keng) P.C. Keng, I. pumilus Q.H. Dai and C.F. Keng, I. barbatus McClure, and I. victorialis P.C. Keng). We also explored the possible correlation between spatial density and total leaf area per plant using log-linear regression. We found that the simplified Gielis equation fit the leaf shape of four bamboo species very well. Although all these four species belonged to the same genus, there were still significant differences in leaf shape. Significant differences also existed in leaf area per plant, ratio of leaf weight to aboveground weight per plant, and leaf length. In addition, we found that the total leaf area per plant decreased with increased spatial density. Therefore, we directly demonstrated the self-thinning rule to improve light interception.

Reduced uncertainty of regional scale CLM predictions of net carbon fluxes and leaf area indices with estimated plant-specific parameters

NASA Astrophysics Data System (ADS)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2016-04-01

Reliable estimates of carbon fluxes and states at regional scales are required to reduce uncertainties in regional carbon balance estimates and to support decision making in environmental politics. In this work the Community Land Model version 4.5 (CLM4.5-BGC) was applied at a high spatial resolution (1 km2) for the Rur catchment in western Germany. In order to improve the model-data consistency of net ecosystem exchange (NEE) and leaf area index (LAI) for this study area, five plant functional type (PFT)-specific CLM4.5-BGC parameters were estimated with time series of half-hourly NEE data for one year in 2011/2012, using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, a Markov Chain Monte Carlo (MCMC) approach. The parameters were estimated separately for four different plant functional types (needleleaf evergreen temperate tree, broadleaf deciduous temperate tree, C3-grass and C3-crop) at four different sites. The four sites are located inside or close to the Rur catchment. We evaluated modeled NEE for one year in 2012/2013 with NEE measured at seven eddy covariance sites in the catchment, including the four parameter estimation sites. Modeled LAI was evaluated by means of LAI derived from remotely sensed RapidEye images of about 18 days in 2011/2012. Performance indices were based on a comparison between measurements and (i) a reference run with CLM default parameters, and (ii) a 60 instance CLM ensemble with parameters sampled from the DREAM posterior probability density functions (pdfs). The difference between the observed and simulated NEE sum reduced 23% if estimated parameters instead of default parameters were used as input. The mean absolute difference between modeled and measured LAI was reduced by 59% on average. Simulated LAI was not only improved in terms of the absolute value but in some cases also in terms of the timing (beginning of vegetation onset), which was directly related to a substantial improvement of the NEE estimates in

Light Diffusion in the Tropical Dry Forest of Costa Rica

NASA Astrophysics Data System (ADS)

Calvo-Rodriguez, S.; Sanchez-Azofeifa, G. A.

2016-06-01

Leaf Area Index (LAI) has been defined as the total leaf area (one-sided) in relation to the ground. LAI has an impact on tree growth and recruitment through the interception of light, which in turn affects primary productivity. Even though many instruments exist for estimating LAI from ground, they are often laborious and costly to run continuously. Measurements of LAI from the field using traditional sensors (e.g., LAI-2000) require multiple visits to the field under very specific sky conditions, making them unsuitable to operate in inaccessible areas and forests with dense vegetation, as well as areas where persistent sunny conditions are the norm like tropical dry forests. With this context, we proposed a methodology to characterize light diffusion based on NDVI and LAI measurements taken from the field in two successional stages in the tropical dry forest of Santa Rosa National Park in Costa Rica. We estimate a "K" coefficient to characterize light diffusion by the canopy, based on field NDVI measurements derived from optical phenology instruments and MODIS NDVI. From the coefficients determined, we estimated LAI values and compared them with ground measurements of LAI. In both successional stages ground measurements of LAI had no significant difference to the tower-derived LAI and the estimated LAI from MODIS NDVI.

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest.

PubMed

Yang, Hualei; Yang, Xi; Zhang, Yongguang; Heskel, Mary A; Lu, Xiaoliang; Munger, J William; Sun, Shucun; Tang, Jianwu

2017-07-01

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf-level ChlF was linked with canopy-scale solar-induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R 2  = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower-based measurement of SIF and leaf-level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R 2  = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F q '/F m ', the fraction of absorbed photons that are used for photochemistry for a light-adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R 2  = 0.79; P < 0.0001). We also found that canopy SIF and SIF-derived GPP (GPP SIF ) were strongly correlated to leaf-level biochemistry and canopy structure, including chlorophyll content (R 2  = 0.65 for canopy GPP SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R 2  = 0.35 for canopy GPP SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R 2  = 0.36 for

Using the conservative nature of fresh leaf surface density to measure foliar area

NASA Astrophysics Data System (ADS)

Castillo, Omar S.; Zaragoza, Esther M.; Alvarado, Carlos J.; Barrera, Maria G.; Dasgupta-Schubert, Nabanita

2014-10-01

For a herbaceous species, the inverse of the fresh leaf surface density, the Hughes constant, is nearly conserved. We apply the Hughes constant to develop an absolute method of leafarea measurement that requires no regression fits, prior calibrations or oven-drying. The Hughes constant was determined in situ using a known geometry and weights of a sub-set obtained from the fresh leaves whose areas are desired. Subsequently, the leaf-areas (at any desired stratification level), were derived by utilizing the Hughes constant and the masses of the fresh leaves. The proof of concept was established for leaf-discs of the plants Mandevilla splendens and Spathiphyllum wallisii. The conservativeness of the Hughes constant over individual leaf-zones and different leaftypes from the leaves of each species was quantitatively validated. Using the globally averaged Hughes constant for each species, the leaf-area of these and additional co-species plants, were obtained. The leaf-area-measurement-by-mass was cross-checked with standard digital image analysis. There were no statistically significant differences between the leaf-area-measurement-by-mass and the digital image analysis measured leaf-areas and the linear correlation between the two methods was very good. Leaf-areameasurement- by-mass was found to be rapid and simple with accuracies comparable to the digital image analysis method. The greatly reduced cost of leaf-area-measurement-by-mass could be beneficial for small agri-businesses in developing countries.

Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

NASA Astrophysics Data System (ADS)

Yang, Junhua; Ji, Zhenming; Chen, Deliang; Kang, Shichang; Fu, Congshen; Duan, Keqin; Shen, Miaogen

2018-06-01

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level (surface-sensitive) channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets. Here, we used an improved land use and leaf area index (LAI) dataset in the WRF-3DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels (e.g., channel 3), the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.

Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar

NASA Technical Reports Server (NTRS)

Zhao, Feng; Strahler, Alan H.; Crystal L. Schaaf; Yao, Tian; Yang, Xiaoyuan; Wang, Zhuosen; Schull, Mitchell A.; Roman, Miguel O.; Woodcock, Curtis E.; Olofsson, Pontus;

LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

NASA Astrophysics Data System (ADS)

Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

2012-04-01

Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

Effect of solution and leaf surface polarity on droplet spread area and contact angle.

PubMed

Nairn, Justin J; Forster, W Alison; van Leeuwen, Rebecca M

2016-03-01

How much an agrochemical spray droplet spreads on a leaf surface can significantly influence efficacy. This study investigates the effect solution polarity has on droplet spreading on leaf surfaces and whether the relative leaf surface polarity, as quantified using the wetting tension dielectric (WTD) technique, influences the final spread area. Contact angles and spread areas were measured using four probe solutions on 17 species. Probe solution polarity was found to affect the measured spread area and the contact angle of the droplets on non-hairy leaves. Leaf hairs skewed the spread area measurement, preventing investigation of the influence of surface polarity on hairy leaves. WTD-measured leaf surface polarity of non-hairy leaves was found to correlate strongly with the effect of solution polarity on spread area. For non-polar leaf surfaces the spread area decreases with increasing solution polarity, for neutral surfaces polarity has no effect on spread area and for polar leaf surfaces the spread area increases with increasing solution polarity. These results attest to the use of the WTD technique as a means to quantify leaf surface polarity. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

BOREAS TF-11 SSA-Fen 1995 Leaf Area Index Data

NASA Technical Reports Server (NTRS)

Arkebauer, Timothy J.; Hall, Forrest G. (Editor); Knapp, David E. (Editor)

2000-01-01

The BOREAS TF-11 team gathered a variety of data to complement its tower flux measurements collected at the SSA-Fen site. These data are LAI measurements made by the TF-11 team throughout the 1995 growing season. The data include the LAI of plants that fall into six categories: total, Carex spp., Betula pumila, Menyanthes trifoliata, Salix spp., and other vascular plants. The data are stored in tabular ASCII files.

Error analysis of leaf area estimates made from allometric regression models

NASA Technical Reports Server (NTRS)

Feiveson, A. H.; Chhikara, R. S.

1986-01-01

Biological net productivity, measured in terms of the change in biomass with time, affects global productivity and the quality of life through biochemical and hydrological cycles and by its effect on the overall energy balance. Estimating leaf area for large ecosystems is one of the more important means of monitoring this productivity. For a particular forest plot, the leaf area is often estimated by a two-stage process. In the first stage, known as dimension analysis, a small number of trees are felled so that their areas can be measured as accurately as possible. These leaf areas are then related to non-destructive, easily-measured features such as bole diameter and tree height, by using a regression model. In the second stage, the non-destructive features are measured for all or for a sample of trees in the plots and then used as input into the regression model to estimate the total leaf area. Because both stages of the estimation process are subject to error, it is difficult to evaluate the accuracy of the final plot leaf area estimates. This paper illustrates how a complete error analysis can be made, using an example from a study made on aspen trees in northern Minnesota. The study was a joint effort by NASA and the University of California at Santa Barbara known as COVER (Characterization of Vegetation with Remote Sensing).

Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index

NASA Astrophysics Data System (ADS)

Majasalmi, Titta; Korhonen, Lauri; Korpela, Ilkka; Vauhkonen, Jari

2017-07-01

We propose 3D triangulations of airborne Laser Scanning (ALS) point clouds as a new approach to derive 3D canopy structures and to estimate forest canopy effective LAI (LAIe). Computational geometry and topological connectivity were employed to filter the triangulations to yield a quasi-optimal relationship with the field measured LAIe. The optimal filtering parameters were predicted based on ALS height metrics, emulating the production of maps of LAIe and canopy volume for large areas. The LAIe from triangulations was validated with field measured LAIe and compared with a reference LAIe calculated from ALS data using logarithmic model based on Beer's law. Canopy transmittance was estimated using All Echo Cover Index (ACI), and the mean projection of unit foliage area (β) was obtained using no-intercept regression with field measured LAIe. We investigated the influence species and season on the triangulated LAIe and demonstrated the relationship between triangulated LAIe and canopy volume. Our data is from 115 forest plots located at the southern boreal forest area in Finland and for each plot three different ALS datasets were available to apply the triangulations. The triangulation approach was found applicable for both leaf-on and leaf-off datasets after initial calibration. Results showed the Root Mean Square Errors (RMSEs) between LAIe from triangulations and field measured values agreed the most using the highest pulse density data (RMSE = 0.63, the coefficient of determination (R2) = 0.53). Yet, the LAIe calculated using ACI-index agreed better with the field measured LAIe (RMSE = 0.53 and R2 = 0.70). The best models to predict the optimal alpha value contained the ACI-index, which indicates that within-crown transmittance is accounted by the triangulation approach. The cover indices may be recommended for retrieving LAIe only, but for applications which require more sophisticated information on canopy shape and volume, such as radiative transfer models, the

Leaf Mass Area, Leaf Carbon and Nitrogen Content, Barrow, Alaska, 2012-2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rogers, Alistair; Ely, Kim; Serbin, Shawn

Carbon, Nitrogen and Leaf Mass Area of leaves sampled from the Barrow Environmental Observatory, Barrow, Alaska. Species measured; Arctophila fulva, Arctagrostis latifolia, Carex aquatilis, Dupontia fisheri, Eriophorum angustifolium, Petasites frigidus, Salix pulchra, Vaccinium vitis-idaea, Salix rotundifolia, Luzula arctica, Saxifraga punctata and Potentilla hyparctica.

Evaluation of four methods for estimating leaf area of isolated trees

Treesearch

P.J. Peper; E.G. McPherson

2003-01-01

The accurate modeling of the physiological and functional processes of urban forests requires information on the leaf area of urban tree species. Several non-destructive, indirect leaf area sampling methods have shown good performance for homogenous canopies. These methods have not been evaluated for use in urban settings where trees are typically isolated and...

Allocation to leaf area and sapwood area affects water relations of co-occurring savanna and forest trees.

PubMed

Gotsch, Sybil G; Geiger, Erika L; Franco, Augusto C; Goldstein, Guillermo; Meinzer, Frederick C; Hoffmann, William A

2010-06-01

Water availability is a principal factor limiting the distribution of closed-canopy forest in the seasonal tropics, suggesting that forest tree species may not be well adapted to cope with seasonal drought. We studied 11 congeneric species pairs, each containing one forest and one savanna species, to test the hypothesis that forest trees have a lower capacity to maintain seasonal homeostasis in water relations relative to savanna species. To quantify this, we measured sap flow, leaf water potential (Psi(L)), stomatal conductance (g (s)), wood density, and Huber value (sapwood area:leaf area) of the 22 study species. We found significant differences in the water relations of these two species types. Leaf area specific hydraulic conductance of the soil/root/leaf pathway (G (t)) was greater for savanna species than forest species. The lower G (t) of forest trees resulted in significantly lower Psi(L) and g (s) in the late dry season relative to savanna trees. The differences in G (t) can be explained by differences in biomass allocation of savanna and forest trees. Savanna species had higher Huber values relative to forest species, conferring greater transport capacity on a leaf area basis. Forest trees have a lower capacity to maintain homeostasis in Psi(L) due to greater allocation to leaf area relative to savanna species. Despite significant differences in water relations, relationships between traits such as wood density and minimum Psi(L) were indistinguishable for the two species groups, indicating that forest and savanna share a common axis of water-use strategies involving multiple traits.

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

NASA Astrophysics Data System (ADS)

Ran, Limei; Pleim, Jonathan; Song, Conghe; Band, Larry; Walker, John T.; Binkowski, Francis S.

2017-02-01

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by the PX PSN compared to significant overestimation by the PX Jarvis for a grassland site.

An evolutionary perspective on leaf economics: phylogenetics of leaf mass per area in vascular plants

PubMed Central

Flores, Olivier; Garnier, Eric; Wright, Ian J; Reich, Peter B; Pierce, Simon; Dìaz, Sandra; Pakeman, Robin J; Rusch, Graciela M; Bernard-Verdier, Maud; Testi, Baptiste; Bakker, Jan P; Bekker, Renée M; Cerabolini, Bruno E L; Ceriani, Roberta M; Cornu, Guillaume; Cruz, Pablo; Delcamp, Matthieu; Dolezal, Jiri; Eriksson, Ove; Fayolle, Adeline; Freitas, Helena; Golodets, Carly; Gourlet-Fleury, Sylvie; Hodgson, John G; Brusa, Guido; Kleyer, Michael; Kunzmann, Dieter; Lavorel, Sandra; Papanastasis, Vasilios P; Pérez-Harguindeguy, Natalia; Vendramini, Fernanda; Weiher, Evan

2014-01-01

In plant leaves, resource use follows a trade-off between rapid resource capture and conservative storage. This “worldwide leaf economics spectrum” consists of a suite of intercorrelated leaf traits, among which leaf mass per area, LMA, is one of the most fundamental as it indicates the cost of leaf construction and light-interception borne by plants. We conducted a broad-scale analysis of the evolutionary history of LMA across a large dataset of 5401 vascular plant species. The phylogenetic signal in LMA displayed low but significant conservatism, that is, leaf economics tended to be more similar among close relatives than expected by chance alone. Models of trait evolution indicated that LMA evolved under weak stabilizing selection. Moreover, results suggest that different optimal phenotypes evolved among large clades within which extremes tended to be selected against. Conservatism in LMA was strongly related to growth form, as were selection intensity and phenotypic evolutionary rates: woody plants showed higher conservatism in relation to stronger stabilizing selection and lower evolutionary rates compared to herbaceous taxa. The evolutionary history of LMA thus paints different evolutionary trajectories of vascular plant species across clades, revealing the coordination of leaf trait evolution with growth forms in response to varying selection regimes. PMID:25165520

Prediction of leaf area in individual leaves of cherrybark oak seedlings (Quercus pagoda Raf.)

Treesearch

Yanfei Guo; Brian Lockhart; John Hodges

1995-01-01

The prediction of leaf area for cherrybark oak (Quercus pagoda Raf.) seedlings is important for studying the physiology of the species. Linear and polynomial models involving leaf length, width, fresh weight, dry weight, and internodal length were tested independently and collectively to predict leaf area. Twenty-nine cherrybark oak seedlings were...

Seedlings of temperate rainforest conifer and angiosperm trees differ in leaf area display.

PubMed

Lusk, Christopher H; Pérez-Millaqueo, Manuel M; Saldaña, Alfredo; Burns, Bruce R; Laughlin, Daniel C; Falster, Daniel S

2012-07-01

The contemporary relegation of conifers mainly to cold or infertile sites has been ascribed to low competitive ability, as a result of the hydraulic inefficiency of tracheids and their seedlings' initial dependence on small foliage areas. Here it is hypothesized that, in temperate rainforests, the larger leaves of angiosperms also reduce self-shading and thus enable display of larger effective foliage areas than the numerous small leaves of conifers. This hypothesis was tested using 3-D modelling of plant architecture and structural equation modelling to compare self-shading and light interception potential of seedlings of six conifers and 12 angiosperm trees from temperate rainforests. The ratio of displayed leaf area to plant mass (LAR(d)) was used to indicate plant light interception potential: LAR(d) is the product of specific leaf area, leaf mass fraction, self-shading and leaf angle. Angiosperm seedlings self-shaded less than conifers, mainly because of differences in leaf number (more than leaf size), and on average their LAR(d) was about twice that of conifers. Although specific leaf area was the most pervasive influence on LAR(d), differences in self-shading also significantly influenced LAR(d) of large seedlings. The ability to deploy foliage in relatively few, large leaves is advantageous in minimizing self-shading and enhancing seedling light interception potential per unit of plant biomass. This study adds significantly to evidence that vegetative traits may be at least as important as reproductive innovations in explaining the success of angiosperms in productive environments where vegetation is structured by light competition.

Seedlings of temperate rainforest conifer and angiosperm trees differ in leaf area display

PubMed Central

Lusk, Christopher H.; Pérez-Millaqueo, Manuel M.; Saldaña, Alfredo; Burns, Bruce R.; Laughlin, Daniel C.; Falster, Daniel S.

2012-01-01

Background and Aims The contemporary relegation of conifers mainly to cold or infertile sites has been ascribed to low competitive ability, as a result of the hydraulic inefficiency of tracheids and their seedlings' initial dependence on small foliage areas. Here it is hypothesized that, in temperate rainforests, the larger leaves of angiosperms also reduce self-shading and thus enable display of larger effective foliage areas than the numerous small leaves of conifers. Methods This hypothesis was tested using 3-D modelling of plant architecture and structural equation modelling to compare self-shading and light interception potential of seedlings of six conifers and 12 angiosperm trees from temperate rainforests. The ratio of displayed leaf area to plant mass (LARd) was used to indicate plant light interception potential: LARd is the product of specific leaf area, leaf mass fraction, self-shading and leaf angle. Results Angiosperm seedlings self-shaded less than conifers, mainly because of differences in leaf number (more than leaf size), and on average their LARd was about twice that of conifers. Although specific leaf area was the most pervasive influence on LARd, differences in self-shading also significantly influenced LARd of large seedlings. Conclusions The ability to deploy foliage in relatively few, large leaves is advantageous in minimizing self-shading and enhancing seedling light interception potential per unit of plant biomass. This study adds significantly to evidence that vegetative traits may be at least as important as reproductive innovations in explaining the success of angiosperms in productive environments where vegetation is structured by light competition. PMID:22585929

Is leaf dry matter content a better predictor of soil fertility than specific leaf area?

PubMed Central

Hodgson, J. G.; Montserrat-Martí, G.; Charles, M.; Jones, G.; Wilson, P.; Shipley, B.; Sharafi, M.; Cerabolini, B. E. L.; Cornelissen, J. H. C.; Band, S. R.; Bogard, A.; Castro-Díez, P.; Guerrero-Campo, J.; Palmer, C.; Pérez-Rontomé, M. C.; Carter, G.; Hynd, A.; Romo-Díez, A.; de Torres Espuny, L.; Royo Pla, F.

2011-01-01

Background and Aims Specific leaf area (SLA), a key element of the ‘worldwide leaf economics spectrum’, is the preferred ‘soft’ plant trait for assessing soil fertility. SLA is a function of leaf dry matter content (LDMC) and leaf thickness (LT). The first, LDMC, defines leaf construction costs and can be used instead of SLA. However, LT identifies shade at its lowest extreme and succulence at its highest, and is not related to soil fertility. Why then is SLA more frequently used as a predictor of soil fertility than LDMC? Methods SLA, LDMC and LT were measured and leaf density (LD) estimated for almost 2000 species, and the capacity of LD to predict LDMC was examined, as was the relative contribution of LDMC and LT to the expression of SLA. Subsequently, the relationships between SLA, LDMC and LT with respect to soil fertility and shade were described. Key Results Although LD is strongly related to LDMC, and LDMC and LT each contribute equally to the expression of SLA, the exact relationships differ between ecological groupings. LDMC predicts leaf nitrogen content and soil fertility but, because LT primarily varies with light intensity, SLA increases in response to both increased shade and increased fertility. Conclusions Gradients of soil fertility are frequently also gradients of biomass accumulation with reduced irradiance lower in the canopy. Therefore, SLA, which includes both fertility and shade components, may often discriminate better between communities or treatments than LDMC. However, LDMC should always be the preferred trait for assessing gradients of soil fertility uncoupled from shade. Nevertheless, because leaves multitask, individual leaf traits do not necessarily exhibit exact functional equivalence between species. In consequence, rather than using a single stand-alone predictor, multivariate analyses using several leaf traits is recommended. PMID:21948627

Is leaf dry matter content a better predictor of soil fertility than specific leaf area?

PubMed

Hodgson, J G; Montserrat-Martí, G; Charles, M; Jones, G; Wilson, P; Shipley, B; Sharafi, M; Cerabolini, B E L; Cornelissen, J H C; Band, S R; Bogard, A; Castro-Díez, P; Guerrero-Campo, J; Palmer, C; Pérez-Rontomé, M C; Carter, G; Hynd, A; Romo-Díez, A; de Torres Espuny, L; Royo Pla, F

2011-11-01

Specific leaf area (SLA), a key element of the 'worldwide leaf economics spectrum', is the preferred 'soft' plant trait for assessing soil fertility. SLA is a function of leaf dry matter content (LDMC) and leaf thickness (LT). The first, LDMC, defines leaf construction costs and can be used instead of SLA. However, LT identifies shade at its lowest extreme and succulence at its highest, and is not related to soil fertility. Why then is SLA more frequently used as a predictor of soil fertility than LDMC? SLA, LDMC and LT were measured and leaf density (LD) estimated for almost 2000 species, and the capacity of LD to predict LDMC was examined, as was the relative contribution of LDMC and LT to the expression of SLA. Subsequently, the relationships between SLA, LDMC and LT with respect to soil fertility and shade were described. Although LD is strongly related to LDMC, and LDMC and LT each contribute equally to the expression of SLA, the exact relationships differ between ecological groupings. LDMC predicts leaf nitrogen content and soil fertility but, because LT primarily varies with light intensity, SLA increases in response to both increased shade and increased fertility. Gradients of soil fertility are frequently also gradients of biomass accumulation with reduced irradiance lower in the canopy. Therefore, SLA, which includes both fertility and shade components, may often discriminate better between communities or treatments than LDMC. However, LDMC should always be the preferred trait for assessing gradients of soil fertility uncoupled from shade. Nevertheless, because leaves multitask, individual leaf traits do not necessarily exhibit exact functional equivalence between species. In consequence, rather than using a single stand-alone predictor, multivariate analyses using several leaf traits is recommended.

Leaf area compounds height-related hydraulic costs of water transport in Oregon White Oak trees.

Treesearch

N. Phillips; B. J. Bond; N. G. McDowell; Michael G. Ryan; A. Schauer

2003-01-01

The ratio of leaf to sapwood area generally decreases with tree size, presumably to moderate hydraulic costs of tree height. This study assessed consequences of tree size and leaf area on water flux in Quercus garryana Dougl. ex. Hook (Oregon White Oak), a species in which leaf to sapwood area ratio increases with tree size. We tested hypotheses that...

Global remote sensing of water-chlorophyll ratio in terrestrial plant leaves.

PubMed

Kushida, Keiji

2012-10-01

I evaluated the use of global remote sensing techniques for estimating plant leaf chlorophyll a + b (C(ab); μg cm(-2)) and water (C(w); mg cm(-2)) concentrations as well as the ratio of C(w)/C(ab) with the PROSAIL model under possible distributions for leaf and soil spectra, leaf area index (LAI), canopy geometric structure, and leaf size. First, I estimated LAI from the normalized difference vegetation index. I found that, at LAI values <2, C(ab), C(w), and C(w)/C(ab) could not be reliably estimated. At LAI values >2, C(ab) and C(w) could be estimated for only restricted ranges of the canopy structure; however, the ratio of C(w)/C(ab) could be reliably estimated for a variety of possible canopy structures with coefficients of determination (R(2)) ranging from 0.56 to 0.90. The remote estimation of the C(w)/C(ab) ratio from satellites offers information on plant condition at a global scale.

Lower responsiveness of canopy evapotranspiration rate than of leaf stomatal conductance to open-air CO2 elevation in rice.

PubMed

Shimono, Hiroyuki; Nakamura, Hirofumi; Hasegawa, Toshihiro; Okada, Masumi

2013-08-01

An elevated atmospheric CO2 concentration ([CO2 ]) can reduce stomatal conductance of leaves for most plant species, including rice (Oryza sativa L.). However, few studies have quantified seasonal changes in the effects of elevated [CO2 ] on canopy evapotranspiration, which integrates the response of stomatal conductance of individual leaves with other responses, such as leaf area expansion, changes in leaf surface temperature, and changes in developmental stages, in field conditions. We conducted a field experiment to measure seasonal changes in stomatal conductance of the uppermost leaves and in the evapotranspiration, transpiration, and evaporation rates using a lysimeter method. The study was conducted for flooded rice under open-air CO2 elevation. Stomatal conductance decreased by 27% under elevated [CO2 ], averaged throughout the growing season, and evapotranspiration decreased by an average of 5% during the same period. The decrease in daily evapotranspiration caused by elevated [CO2 ] was more significantly correlated with air temperature and leaf area index (LAI) rather than with other parameters of solar radiation, days after transplanting, vapor-pressure deficit and FAO reference evapotranspiration. This indicates that higher air temperatures, within the range from 16 to 27 °C, and a larger LAI, within the range from 0 to 4 m(2)  m(-2) , can increase the magnitude of the decrease in evapotranspiration rate caused by elevated [CO2 ]. The crop coefficient (i.e. the evapotranspiration rate divided by the FAO reference evapotranspiration rate) was 1.24 at ambient [CO2 ] and 1.17 at elevated [CO2 ]. This study provides the first direct measurement of the effects of elevated [CO2 ] on rice canopy evapotranspiration under open-air conditions using the lysimeter method, and the results will improve future predictions of water use in rice fields. © 2013 John Wiley & Sons Ltd.

Suicide Prevention in Schizophrenia: Do Long-Acting Injectable Antipsychotics (LAIs) have a Role?

PubMed

Pompili, Maurizio; Orsolini, Laura; Lamis, Dorian A; Goldsmith, David R; Nardella, Adele; Falcone, Giulia; Corigliano, Valentina; Luciano, Mario; Fiorillo, Andrea

2017-01-01

Suicide risk is a major cause of death among patients with schizophrenia. Death by suicide has been reported in approximately 5% of schizophrenia patients although this figure appears to be an underestimate of the problem. A number of risk factors are routinely reported as associated with suicide risk among these patients, some of which are modifiable by targeted therapeutic strategies. Clozapine is the only compound that gathered evidence as an effective treatment for reducing suicide risk in schizophrenia. Long-Acting Injectable Antipsychotics (LAIs) have a range of advantages in terms of efficacy, safety and tolerability in the treatment of schizophrenia, and one area of interest is whether LAI-treatment may decrease suicidality by indirectly acting on a range of risk factors for suicide specific to schizophrenia patients. This background encouraged the present review of research pertaining to LAIs in relation to modifiable risk factors for suicide in schizophrenia. We viewed our task as gathering, speculating and critically appraising the available research relevant to the topic, with the aim of formulating a hypothesis to be tested with further research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Ratio of Cut Surface Area to Leaf Sample Volume for Water Potential Measurements by Thermocouple Psychrometers

PubMed Central

Walker, Sue; Oosterhuis, Derrick M.; Wiebe, Herman H.

1984-01-01

Evaporative losses from the cut edge of leaf samples are of considerable importance in measurements of leaf water potential using thermocouple psychrometers. The ratio of cut surface area to leaf sample volume (area to volume ratio) has been used to give an estimate of possible effects of evaporative loss in relation to sample size. A wide range of sample sizes with different area to volume ratios has been used. Our results using Glycine max L. Merr. cv Bragg indicate that leaf samples with area to volume values less than 0.2 square millimeter per cubic millimeter give psychrometric leaf water potential measurements that compare favorably with pressure chamber measurements. PMID:16663578

Spectral radiance estimates of leaf area and leaf phytomass of small grains and native vegetation

NASA Technical Reports Server (NTRS)

Aase, J. K.; Brown, B. S.; Millard, J. P.

1986-01-01

Similarities and/or dissimilarities in radiance characteristics were studied among barley (Hordeum vulgare L.), oats (Avena fatua L.), spring and winter wheat (Triticum aestivum L.), and short-grass prairie vegetation. The site was a Williams loam soil (fine-loamy mixed, Typic Argiborolls) near Sidney, Montana. Radiances were measured with a truck-mounted radiometer. The radiometer was equipped with four wavelength bands: 0.45 to 0.52, 0.52 to 0.60, 0.63 to 0.69, and 0.76 to 0.90 micron. Airborne scanner measurements were made at an altitude of 600 m four times during the season under clear sky conditions. The airborne scanner was equipped with the same four bands as the truck-mounted radiometer plus the following: 1.00 to 1.30, 1.55 to 1.75, 2.08 to 2.35, and 10.4 to 12.5 microns. Comparisons using individual wave bands, the near IR/red, (0.76 to 0.90 micron)/(0.63 to 0.69 micron) ratio and the normalized difference vegetation index, ND = (IR - red)/(IR + red), showed that only during limited times during the growing season were some of the small grains distinguishable from one another and from native rangeland vegetation. There was a common relation for all small grains between leaf area index and green leaf phytomass and between leaf area index or green leaf phytomass and the IR/red ratio.

DSCOVR EPIC L2 VESDR Data Release Announcement

Atmospheric Science Data Center

2018-06-14

... Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The VESDR product contains Leaf Area Index (LAI) ... FPAR, LAI, SLAI are useful for monitoring variability and change in global vegetation due to climate and anthropogenic influences, ...

DSCOVR EPIC L2 VESDR Data Release Announcement

Atmospheric Science Data Center

2018-06-07

... Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The VESDR product contains Leaf Area Index (LAI) ... FPAR, LAI, SLAI are useful for monitoring variability and change in global vegetation due to climate and anthropogenic influences, ...

Leaf area and photosynthesis of newly emerged trifoliolate leaves are regulated by mature leaves in soybean.

PubMed

Wu, Yushan; Gong, Wanzhuo; Wang, Yangmei; Yong, Taiwen; Yang, Feng; Liu, Weigui; Wu, Xiaoling; Du, Junbo; Shu, Kai; Liu, Jiang; Liu, Chunyan; Yang, Wenyu

2018-03-29

Leaf anatomy and the stomatal development of developing leaves of plants have been shown to be regulated by the same light environment as that of mature leaves, but no report has yet been written on whether such a long-distance signal from mature leaves regulates the total leaf area of newly emerged leaves. To explore this question, we created an investigation in which we collected data on the leaf area, leaf mass per area (LMA), leaf anatomy, cell size, cell number, gas exchange and soluble sugar content of leaves from three soybean varieties grown under full sunlight (NS), shaded mature leaves (MS) or whole plants grown in shade (WS). Our results show that MS or WS cause a marked decline both in leaf area and LMA in newly developing leaves. Leaf anatomy also showed characteristics of shade leaves with decreased leaf thickness, palisade tissue thickness, sponge tissue thickness, cell size and cell numbers. In addition, in the MS and WS treatments, newly developed leaves exhibited lower net photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (E), but higher carbon dioxide (CO 2 ) concentration in the intercellular space (Ci) than plants grown in full sunlight. Moreover, soluble sugar content was significantly decreased in newly developed leaves in MS and WS treatments. These results clearly indicate that (1) leaf area, leaf anatomical structure, and photosynthetic function of newly developing leaves are regulated by a systemic irradiance signal from mature leaves; (2) decreased cell size and cell number are the major cause of smaller and thinner leaves in shade; and (3) sugars could possibly act as candidate signal substances to regulate leaf area systemically.

Impact of Hurricane Iniki on native Hawaiian Acacia koa forests: damage and two-year recovery

Treesearch

Robin A. Harrington; James H. Fownes; Paul G. Scowcroft; Cheryl S. Vann

1997-01-01

Damage to Hawaiian Acacia koa forest by Hurricane Iniki was assessed by comparison with our previous measures of stand structure and leaf area index (LAI) at sites along a precipitation/elevation gradient on western Kauai. Reductions in LAI ranged from 29 to 80% and were correlated with pre-hurricane LAI and canopy height. The canopy damage...

Leaf area and net photosynthesis during development of Prunus serotina seedlings

Treesearch

Stephen B. Horsley; Kurt W. Gottschalk

1993-01-01

We used the plastochron index to study the relationship between plant age, leaf age and development, and net photosynthesis of black cherry (Prtmus serotina Ehrh.) seedlings. Leaf area and net photosynthesis were measured on all leaves >=75 mm of plants ranging in age from 7 to 20 plastochrons. Effects of plant developmental stage...

Transforming Pinus pinaster forest to recreation site: preliminary effects on LAI, some forest floor, and soil properties.

PubMed

Öztürk, Melih; Bolat, İlyas

2014-04-01

This study investigates the effects of forest transformation into recreation site. A fragment of a Pinus pinaster plantation forest was transferred to a recreation site in the city of Bartın located close to the Black Sea coast of northwestern Turkey. During the transformation, some of the trees were selectively removed from the forest to generate more open spaces for the recreationists. As a result, Leaf Area Index (LAI) decreased by 0.20 (about 11%). Additionally, roads and pathways were introduced into the site together with some recreational equipment sealing parts of the soil surface. Consequently, forest environment was altered with a semi-natural landscape within the recreation site. The purpose of this study is to assess the effects of forest transformation into recreation site particularly in terms of the LAI parameter, forest floor, and soil properties. Preliminary monitoring results indicate that forest floor biomass is reduced by 26% in the recreation site compared to the control site. Soil temperature is increased by 15% in the recreation site where selective removal of trees expanded the gaps allowing more light transmission. On the other hand, the soil bulk density which is an indicator of soil compaction is unexpectedly slightly lower in the recreation site. Organic carbon (C(org)) and total nitrogen (N(total)) together with the other physical and chemical parameter values indicate that forest floor and soil have not been exposed to much disturbance. However, subsequent removal of trees that would threaten the vegetation, forest floor, and soil should not be allowed. The activities of the recreationists are to be concentrated on the paved spaces rather than soil surfaces. Furthermore, long-term monitoring and management is necessary for both the observation and conservation of the site.

An Observing System Simulation Experiment of assimilating leaf area index and soil moisture over cropland

NASA Astrophysics Data System (ADS)

Lafont, Sebastien; Barbu, Alina; Calvet, Jean-Christophe

2013-04-01

A Land Data Assimilation System (LDAS) is an off-line data assimilation system featuring uncoupled land surface model which is driven by observation-based atmospheric forcing. In this study the experiments were conducted with a surface externalized (SURFEX) modelling platform developed at Météo-France. It encompasses the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The photosynthetic activity depends on the vegetation types. The input soil and vegetation parameters are provided by the ECOCLIMAP II global database which assigns the ecosystem classes in several plant functional types as grassland, crops, deciduous forest and coniferous forest. New versions of the model have been recently developed in order to better describe the agricultural plant functional types. We present a set of observing system simulation experiments (OSSE) which asses leaf area index (LAI) and soil moisture assimilation for improving the land surface estimates in a controlled synthetic environment. Synthetic data were assimilated into ISBA-A-gs using an Extended Kalman Filter (EKF). This allows for an understanding of model responses to an augmentation of the number of crop types and different parameters associated to this modification. In addition, the interactions between uncertainties in the model and in the observations were investigated. This study represents the first step of a process that envisages the extension of LDAS to the new versions of the ISBA-A-gs model in order to assimilate remote sensing observations.

Leaf mass area, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

DOE Data Explorer

Ely, Kim [Brookhaven National Lab; Rogers, Alistair [Brookhaven National Lab; Serbin, Shawn [Brookhaven National Lab; Wu, Jin [BNL; Wolfe, Brett [Smithsonian; Dickman, Turin [Los Alamos National Lab; Collins, Adam [Los Alamos National Lab; Detto, Matteo [Princeton; Grossiord, Charlotte [Los Alamos National Lab; McDowell, Nate [Los Alamos National Lab; Michaletz, Sean

2017-01-01

Leaf mass per unit area measured on a monthly basis from Feb to April 2016 at SLZ and PNM. Data from BCI only available for March. This data was collected as part of the 2016 ENSO campaign. See related datasets (existing and future) for further sample details, leaf water potential, leaf spectra, gas exchange and leaf chemistry.

The Thermal Infrared Sensor on the Landsat Data Continutiy Mission

USDA-ARS?s Scientific Manuscript database

The REGularized canopy reFLECtance (REGFLEC) modeling tool integrates leaf optics, canopy reflectance, and atmospheric radiative transfer model components, facilitating accurate retrieval of leaf area index (LAI) and leaf chlorophyll content (Cab) directly from at-sensor radiances in green, red and ...

Combining observations in the reflective solar and thermal domains for improved mapping of carbon, water and energy fluxes

USDA-ARS?s Scientific Manuscript database

The REGularized canopy reFLECtance (REGFLEC) modeling tool integrates leaf optics, canopy reflectance, and atmospheric radiative transfer model components, facilitating accurate retrieval of leaf area index (LAI) and leaf chlorophyll content (Cab) directly from at-sensor radiances in green, red and ...

An evolutionary attractor model for sapwood cross section in relation to leaf area.

PubMed

Westoby, Mark; Cornwell, William K; Falster, Daniel S

2012-06-21

Sapwood cross-sectional area per unit leaf area (SA:LA) is an influential trait that plants coordinate with physical environment and with other traits. We develop theory for SA:LA and also for root surface area per leaf area (RA:LA) on the premise that plants maximizing the surplus of revenue over costs should have competitive advantage. SA:LA is predicted to increase in water-relations environments that reduce photosynthetic revenue, including low soil water potential, high water vapor pressure deficit (VPD), and low atmospheric CO(2). Because sapwood has costs, SA:LA adjustment does not completely offset difficult water relations. Where sapwood costs are large, as in tall plants, optimal SA:LA may actually decline with (say) high VPD. Large soil-to-root resistance caps the benefits that can be obtained from increasing SA:LA. Where a plant can adjust water-absorbing surface area of root per leaf area (RA:LA) as well as SA:LA, optimal RA:SA is not affected by VPD, CO(2) or plant height. If selection favours increased height more so than increased revenue-minus-cost, then height is predicted to rise substantially under improved water-relations environments such as high-CO(2) atmospheres. Evolutionary-attractor theory for SA:LA and RA:LA complements models that take whole-plant conductivity per leaf area as a parameter. Copyright © 2012 Elsevier Ltd. All rights reserved.

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine

PubMed Central

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-01-01

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants. PMID:27120600

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine.

PubMed

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-04-23

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.

Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

NASA Astrophysics Data System (ADS)

Wang, R.; Chen, J. M.; Luo, X.

2016-12-01

Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

Comparison of direct and indirect methods for assessing leaf area index across a tropical rain forest landscape

Treesearch

Paulo C. Olivas; Steven F. Oberbauer; David B. Clark; Deborah A. Clark; Michael G. Ryan; Joseph J. O' Brien; Harlyn Ordonez

2013-01-01

Many functional properties of forests depend on the leaf area; however, measuring leaf area is not trivial in tall evergreen vegetation. As a result, leaf area is generally estimated indirectly by light absorption methods. These indirect methods are widely used, but have never been calibrated against direct measurements in tropical rain forests, either at point or...

Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest

NASA Astrophysics Data System (ADS)

Ali, Abebe Mohammed; Darvishzadeh, Roshanak; Skidmore, Andrew K.; Duren, Iris van; Heiden, Uta; Heurich, Marco

2016-03-01

Assessments of ecosystem functioning rely heavily on quantification of vegetation properties. The search is on for methods that produce reliable and accurate baseline information on plant functional traits. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate two functional leaf traits: leaf dry matter content (LDMC) and specific leaf area (SLA). Inversion of PROSPECT usually aims at quantifying its direct input parameters. This is the first time the technique has been used to indirectly model LDMC and SLA. Biophysical parameters of 137 leaf samples were measured in July 2013 in the Bavarian Forest National Park, Germany. Spectra of the leaf samples were measured using an ASD FieldSpec3 equipped with an integrating sphere. PROSPECT was inverted using a look-up table (LUT) approach. The LUTs were generated with and without using prior information. The effect of incorporating prior information on the retrieval accuracy was studied before and after stratifying the samples into broadleaf and conifer categories. The estimated values were evaluated using R2 and normalized root mean square error (nRMSE). Among the retrieved variables the lowest nRMSE (0.0899) was observed for LDMC. For both traits higher R2 values (0.83 for LDMC and 0.89 for SLA) were discovered in the pooled samples. The use of prior information improved accuracy of the retrieved traits. The strong correlation between the estimated traits and the NIR/SWIR region of the electromagnetic spectrum suggests that these leaf traits could be assessed at canopy level by using remotely sensed data.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Fisk, J.; Holm, J. A.; Bailey, V. L.; Gough, C. M.

2014-12-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging U.S. forests. We tested whether three forest ecosystem models—Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models—could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J.; Holm, J. A.; Bailey, V.; Gough, C. M.

2014-07-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J. P.; Holm, J. A.; Bailey, V.; Bohrer, G.; Gough, C. M.

2015-01-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

Evaluation of Global LAI/FPAR Products from VIIRS and MODIS: Spatiotemporal Consistency and Uncertainty

NASA Astrophysics Data System (ADS)

Xu, B.; Park, T.; Yan, K.; Chen, C.; Jing, L.; Qinhuo, L.; Song, W.; Knyazikhin, Y.; Myneni, R.

2017-12-01

The operational EOS MODIS LAI/FPAR algorithm has been successfully transitioned to Suomi-NPP VIIRS by optimizing a small set of configurable parameters in Look-Up-Tables (LUTs). Our preliminary evaluation results show a reasonable agreement between VIIRS and MODIS LAI/FPAR retrievals. However, we still need more comprehensive investigations to assure the continuity of multi-sensor based global LAI/FPAR time series, as the preliminary evaluation was spatiotemporally limited. Here, we used a multi-year (2012-2016) global LAI/FPAR product generated from VIIRS Version 1 and MODIS Collection 6 to evaluate their spatiotemporal consistency at global and site scales. We also quantified the uncertainty of the product by defining and measuring theoretical and physical terms. For both consistency and uncertainty evaluation, we accounted varying biome types and temporal resolutions (i.e., 8-day, seasonal and annual steps). A newly developed approach (a.k.a., Grading and Upscaling Ground Measurements, GUGM) generating accurate validation datasets was implemented to help validating both products. Our results clearly indicate that the LAI/FPAR retrievals from VIIRS and MODIS are quite consistent at different spatio- (i.e., global and site) and temporal- (i.e., 8-day, seasonal and annual) scales. It is also worthy to note that the rate of retrievals from the radiative transfer based main algorithm is also comparable. However, we also saw a relatively larger LAI/FPAR discrepancy over highly dense tropical forests and a slightly less retrieval rate (main algorithm) from VIIRS over high latitude regions. For the uncertainty assessment, the theoretical uncertainty of VIIRS LAI (FPAR) is less than 0.2 (0.06) for non-forest and 0.9 (0.08) for forest, which is nearly identical to those of MODIS. The physical uncertainties of VIIRS and MODIS LAI (FPAR) products assessed by comparing to ground measurements are estimated by 0.60 (0.10) and 0.55 (0.11), respectively. All of the results

Sapwood area as an estimator of leaf area and foliar weight in cherrybark oak and green ash

Treesearch

James S. Meadows; John D. Hodges

2002-01-01

The relationships between foliar weight/leaf area and four stem dimensions (d.b.h., total stem cross-sectional area, total sapwood area, and current sapwood area at breast height) were investigated in two important bottomland tree species of the Southern United States, cherrybark oak (Quercus falcata var. pagodifolia ...

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

2017-10-01

In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of

Optimal allocation of leaf epidermal area for gas exchange.

PubMed

de Boer, Hugo J; Price, Charles A; Wagner-Cremer, Friederike; Dekker, Stefan C; Franks, Peter J; Veneklaas, Erik J

2016-06-01

A long-standing research focus in phytology has been to understand how plants allocate leaf epidermal space to stomata in order to achieve an economic balance between the plant's carbon needs and water use. Here, we present a quantitative theoretical framework to predict allometric relationships between morphological stomatal traits in relation to leaf gas exchange and the required allocation of epidermal area to stomata. Our theoretical framework was derived from first principles of diffusion and geometry based on the hypothesis that selection for higher anatomical maximum stomatal conductance (gsmax ) involves a trade-off to minimize the fraction of the epidermis that is allocated to stomata. Predicted allometric relationships between stomatal traits were tested with a comprehensive compilation of published and unpublished data on 1057 species from all major clades. In support of our theoretical framework, stomatal traits of this phylogenetically diverse sample reflect spatially optimal allometry that minimizes investment in the allocation of epidermal area when plants evolve towards higher gsmax . Our results specifically highlight that the stomatal morphology of angiosperms evolved along spatially optimal allometric relationships. We propose that the resulting wide range of viable stomatal trait combinations equips angiosperms with developmental and evolutionary flexibility in leaf gas exchange unrivalled by gymnosperms and pteridophytes. © 2016 The Authors New Phytologist © 2016 New Phytologist Trust.

Effects of nitrogen fertilization on growth and reflectance characteristics of winter wheat

NASA Technical Reports Server (NTRS)

Hinzman, L. D.; Bauer, M. E.; Daughtry, C. S. T.

1986-01-01

The use of remote sensing to determine seasonal changes in agronomic and spectral properties of winter wheat canopies with different levels of N fertilization is investigated. Field experiments were conducted at Purdue Agronomy Farm, West Lafayette, IN during the 1978-1979 and 1979-1980 growing season. Spectral reflectance, total leaf N concentration, leaf chlorophyll concentration, leaf are index (LAI), and fresh and dry phytomass are measured and analyzed. Three distinct wheat canopies are detected for the O, 60, and 120 kg N/ha levels of fertilization; it is observed that with an increase in N the reflectance in the visible, and middle IR wavelengths decrease, and the IR reflectance is increased. The canopies with 120 kg N/ha display the highest LAI, maintain green leaf area the longest, and increase in fresh and dry phytomass. The relationship between spectral and agronomic variables is examined; the effect of changing chlorophyll concentration and LAI on the reflectance is studied.

Combined effects of climate and land management on watershed vegetation dynamics in an arid environment

Treesearch

Peilong Liu; Lu Hao; Cen Pan; Decheng Zhou; Yongqiang Liu; Ge Sun

2017-01-01

Leaf area index (LAI) is a key parameter to characterize vegetation dynamics and ecosystemstructure that determines the ecosystem functions and services such as cleanwater supply and carbon sequestration in awatershed. However, linking LAI dynamics and environmental controls (i.e., coupling biosphere, atmosphere, and anthroposphere) remains challenging and such type of...

Vertical leaf area distribution, light transmittance, and application of the Beer-Lambert Law in four mature hardwood stands in the southern Appalachians

Treesearch

James M. Vose; Neal H. Sullivan; Barton D. Clinton; Paul V. Bolstad

1995-01-01

We quantified stand leaf area index and vertical leaf area distribution, and developed canopy extinction coefficients (k), in four mature hardwood stands. Leaf area index, calculated from litter fall and specific leaf area (cm²·g-1), ranged from 4.3 to 5.4 m²·m-2. In three of the four stands, leaf area was distributed in...

Effects of trees on momentum exchange within and above a real urban environment

NASA Astrophysics Data System (ADS)

Salesky, S.; Giometto, M. G.; Christen, A.; Egli, P. E.; Schmid, M. F.; Tooke, T. R.; Coops, N. C.; Parlange, M. B.

2017-12-01

Large-eddy simulations (LES) are used to gain insight into the effects of trees on momentum transfer rates characterizing the atmosphere within and above a real urban canopy. Several areas are considered that are part of a neighbourhood in the city of Vancouver, BC, Canada where a small fraction of trees are taller than buildings. In this area, eight years of continuous wind and turbulence measurements are available from a 30 m meteorological tower. Buildings and vegetation geometries are obtained from airborne light detection and ranging (LiDAR) data. In the LES algorithm, buildings are accounted through an immersed boundary method, whereas vegetation is parameterized via a location-specific leaf area density. LES are performed varying wind direction and leaf area densities. Surface roughness lengths (z0) from both LES and tower measurements are sensitive to the 0 ≤ LAI/λ < 3 parameter, where LAI is the leaf area index and λ is the frontal area fraction of buildings characterizing a given canopy. For instance, tower measurements predict a 19% seasonal increase in z0, slightly lower than the 27% increase featured by LES for the most representative canopy (leaves-off LAI/λ = 0.74, leaves-on LAI/λ = 2.24). Removing vegetation from such a canopy would cause a dramatic drop of approximately 50% in z0 when compared to the reference summer value. The momentum displacement height (d) from LES also consistently increases as LAI/λ increases, due to the disproportionate amount of drag that the (few) relatively taller trees exert on the flow. Within the urban canopy, the effects of trees are twofold: on one hand, they act as a direct momentum sink for the mean flow; on the other, they reduce downward turbulent transport of high-momentum fluid, significantly reducing the wind intensity at the heights where people live and buildings consume energy.

Effect of weed control treatments on total leaf area of plantation black walnut (Juglans nigra)

Treesearch

Jason Cook; Michael R. Saunders

2013-01-01

Determining total tree leaf area is necessary for describing tree carbon balance, growth efficiency, and other measures used in tree-level and stand-level physiological growth models. We examined the effects of vegetation control methods on the total leaf area of sapling-size plantation black walnut trees using allometric approaches. We found significant differences in...

Allometric relationships predicting foliar biomass and leaf area:sapwood area ratio from tree height in five Costa Rican rain forest species.

PubMed

Calvo-Alvarado, J C; McDowell, N G; Waring, R H

2008-11-01

We developed allometric equations to predict whole-tree leaf area (A(l)), leaf biomass (M(l)) and leaf area to sapwood area ratio (A(l):A(s)) in five rain forest tree species of Costa Rica: Pentaclethra macroloba (Willd.) Kuntze (Fabaceae/Mim), Carapa guianensis Aubl. (Meliaceae), Vochysia ferru-gi-nea Mart. (Vochysiaceae), Virola koshnii Warb. (Myristicaceae) and Tetragastris panamensis (Engl.) Kuntze (Burseraceae). By destructive analyses (n = 11-14 trees per species), we observed strong nonlinear allometric relationships (r(2) > or = 0.9) for predicting A(l) or M(l) from stem diameters or A(s) measured at breast height. Linear relationships were less accurate. In general, A(l):A(s) at breast height increased linearly with tree height except for Penta-clethra, which showed a negative trend. All species, however, showed increased total A(l) with height. The observation that four of the five species increased in A(l):A(s) with height is consistent with hypotheses about trade--offs between morphological and anatomical adaptations that favor efficient water flow through variation in the amount of leaf area supported by sapwood and those imposed by the need to respond quickly to light gaps in the canopy.

Moderate forest disturbance as a stringent test for gap and big-leaf models

DOE PAGES

Bond-Lamberty, Benjamin; Fisk, Justin P.; Holm, Jennifer; ...

2015-01-27

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experimentmore » in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.« less

How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

NASA Astrophysics Data System (ADS)

Jiang, C.; Ryu, Y.; Fang, H.

2016-12-01

Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

The Change in the area of various land covers on the Tibetan Plateau during 1957-2015

NASA Astrophysics Data System (ADS)

Cuo, Lan; Zhang, Yongxin

2017-04-01

With average elevation of 4000 m and area of 2.5×106 km2, Tibetan Plateau hosts various fragile ecosystems such as perennial alpine meadow, perennial alpine steppe, temperate evergreen needleleaf trees, temperate deciduous trees, temperate shrub grassland, and barely vegetated desert. Perennial alpine meadow and steppe are the two dominant vegetation types on the heartland of the plateau. MODIS Leaf Area Index (LAI) ranges from 0 to 2 in most part of the plateau. With climate change, these ecosystems are expected to undergo alteration. This study uses a dynamic vegetation model - Lund-Potsdam-Jena (LPJ) to investigate the change of the barely vegetated area and other vegetation types caused by climate change during 1957-2015 on the Tibetan Plateau. Model simulated foliage projective coverage (FPC) and plant functional types (PFTs) are selected for the investigation. The model is evaluated first using both field surveyed land cover map and MODIS LAI images. Long term trends of vegetation FPC is examined. Decadal variations of vegetated and barely vegetated land are compared. The impacts of extreme precipitation, air temperature and CO2 on the expansion and contraction of barely vegetated and vegetated areas are shown. The study will identify the dominant climate factors in affecting the desert area in the region.

Effects of foliage clumping on the estimation of global terrestrial gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Jing M.; Mo, Gang; Pisek, Jan; Liu, Jane; Deng, Feng; Ishizawa, Misa; Chan, Douglas

2012-03-01

Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3-dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

Chlorophyll content retrieval from hyperspectral remote sensing imagery.

PubMed

Yang, Xiguang; Yu, Ying; Fan, Wenyi

2015-07-01

Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases. Hyperspectral remote sensing with high spatial resolution can be used for estimating chlorophyll content. In this study, the chlorophyll content was retrieved step by step using Hyperion imagery. Firstly, the spectral curve of the leaf was analyzed, 25 spectral characteristic parameters were identified through the correlation coefficient matrix, and a leaf chlorophyll content inversion model was established using a stepwise regression method. Secondly, the pixel reflectance was converted into leaf reflectance by a geometrical-optical model (4-scale). The three most important parameters of reflectance conversion, including the multiple scattering factor (M 0 ), and the probability of viewing the sunlit tree crown (P T ) and the background (P G ), were estimated by leaf area index (LAI), respectively. The results indicated that M 0 , P T , and P G could be described as a logarithmic function of LAI, with all R (2) values above 0.9. Finally, leaf chlorophyll content was retrieved with RMSE = 7.3574 μg/cm(2), and canopy chlorophyll content per unit ground surface area was estimated based on leaf chlorophyll content and LAI. Chlorophyll content mapping can be useful for the assessment of forest growth stage and diseases.

Tree Diversity Enhances Stand Carbon Storage but Not Leaf Area in a Subtropical Forest.

PubMed

Castro-Izaguirre, Nadia; Chi, Xiulian; Baruffol, Martin; Tang, Zhiyao; Ma, Keping; Schmid, Bernhard; Niklaus, Pascal A

2016-01-01

Research about biodiversity-productivity relationships has focused on herbaceous ecosystems, with results from tree field studies only recently beginning to emerge. Also, the latter are concentrated largely in the temperate zone. Tree species diversity generally is much higher in subtropical and tropical than in temperate or boreal forests, with reasons not fully understood. Niche overlap and thus complementarity in the use of resources that support productivity may be lower in forests than in herbaceous ecosystems, suggesting weaker productivity responses to diversity change in forests. We studied stand basal area, vertical structure, leaf area, and their relationship with tree species richness in a subtropical forest in south-east China. Permanent forest plots of 30 x 30 m were selected to span largely independent gradients in tree species richness and secondary successional age. Plots with higher tree species richness had a higher stand basal area. Also, stand basal area increases over a 4-year census interval were larger at high than at low diversity. These effects translated into increased carbon stocks in aboveground phytomass (estimated using allometric equations). A higher variability in tree height in more diverse plots suggested that these effects were facilitated by denser canopy packing due to architectural complementarity between species. In contrast, leaf area was not or even negatively affected by tree diversity, indicating a decoupling of carbon accumulation from leaf area. Alternatively, the same community leaf area might have assimilated more C per time interval in more than in less diverse plots because of differences in leaf turnover and productivity or because of differences in the display of leaves in vertical and horizontal space. Overall, our study suggests that in species-rich forests niche-based processes support a positive diversity-productivity relationship and that this translates into increased carbon storage in long-lived woody

Measurement of tree canopy architecture

NASA Technical Reports Server (NTRS)

Martens, S. N.; Ustin, S. L.; Norman, J. M.

1991-01-01

The lack of accurate extensive geometric data on tree canopies has retarded development and validation of radiative transfer models. A stratified sampling method was devised to measure the three-dimensional geometry of 16 walnut trees which had received irrigation treatments of either 100 or 33 per cent of evapotranspirational (ET) demand for the previous two years. Graphic reconstructions of the three-dimensional geometry were verified by 58 independent measurements. The distributions of stem- and leaf-size classes, lengths, and angle classes were determined and used to calculate leaf area index (LAI), stem area, and biomass. Reduced irrigation trees have lower biomass of stems, leaves and fruit, lower LAI, steeper leaf angles and altered biomass allocation to large stems. These data can be used in ecological models that link canopy processes with remotely sensed measurements.

Variation in crown light utilization characteristics among tropical canopy trees.

PubMed

Kitajima, Kaoru; Mulkey, Stephen S; Wright, S Joseph

2005-02-01

Light extinction through crowns of canopy trees determines light availability at lower levels within forests. The goal of this paper is the exploration of foliage distribution and light extinction in crowns of five canopy tree species in relation to their shoot architecture, leaf traits (mean leaf angle, life span, photosynthetic characteristics) and successional status (from pioneers to persistent). Light extinction was examined at three hierarchical levels of foliage organization, the whole crown, the outermost canopy and the individual shoots, in a tropical moist forest with direct canopy access with a tower crane. Photon flux density and cumulative leaf area index (LAI) were measured at intervals of 0.25-1 m along multiple vertical transects through three to five mature tree crowns of each species to estimate light extinction coefficients (K). Cecropia longipes, a pioneer species with the shortest leaf life span, had crown LAI <0.5. Among the remaining four species, crown LAI ranged from 2 to 8, and species with orthotropic terminal shoots exhibited lower light extinction coefficients (0.35) than those with plagiotropic shoots (0.53-0.80). Within each type, later successional species exhibited greater maximum LAI and total light extinction. A dense layer of leaves at the outermost crown of a late successional species resulted in an average light extinction of 61% within 0.5 m from the surface. In late successional species, leaf position within individual shoots does not predict the light availability at the individual leaf surface, which may explain their slow decline of photosynthetic capacity with leaf age and weak differentiation of sun and shade leaves. Later-successional tree crowns, especially those with orthotropic branches, exhibit lower light extinction coefficients, but greater total LAI and total light extinction, which contribute to their efficient use of light and competitive dominance.

[Estimation of rice LAI by using NDVI at different spectral bandwidths].

PubMed

Wang, Fu-min; Huang, Jing-feng; Tang, Yan-lin; Wang, Xiu-zhen

2007-11-01

The canopy hyperspectral reflectance data of rice at its different development stages were collected from field measurement, and the corresponding NDVIs as well as the correlation coefficients of NDVIs and LAI were computed at extending bandwidth of TM red and near-infrared (NIR) spectra. According to the variation characteristics of best fitted R2 with spectral bandwidth, the optimal bandwidth was determined. The results showed that the correlation coefficients of LAI and ND-VI and the maximum R2 of the best fitted functions at different spectral bandwidths had the same variation trend, i.e., decreased with increasing bandwidth when the bandwidth was less than 60 nm. However, when the bandwidth was beyond 60 nm, the maximum R2 somewhat fluctuated due to the effect of NIR. The analysis of R2 variation with bandwidth indicated that 15 nm was the optimal bandwidth for the estimation of rice LAI by using NDVI.

Correlations of leaf area with length and width measurements of leaves of black oak, white oak, and sugar maple

Treesearch

Philip M. Wargo

1978-01-01

Correlations of leaf area with length, width, and length times width of leaves of black oak, white oak, and sugar maple were determined to see if length and/or width could be used as accurate estimators of leaf area. The correlation of length times width with leaf area was high (r > + .95) for all three species. The linear equation Y = a + bX, where X = length times...

Foliar and ecosystem respiration in an old-growth tropical rain forest

Treesearch

Molly A. Cavaleri; Steven F. Oberbauer; Michael G. Ryan

2008-01-01

Foliar respiration is a major component of ecosystem respiration, yet extrapolations are often uncertain in tropical forests because of indirect estimates of leaf area index (LAI).A portable tower was used to directly measure LAI and night-time foliar respiration from 52 vertical transects throughout an old-growth tropical rain forest in Costa Rica. In this study, we (...

Viewing forests from below: fine root mass declines relative to leaf area in aging lodgepole pine stands.

PubMed

Schoonmaker, A S; Lieffers, V J; Landhäusser, S M

2016-07-01

In the continued quest to explain the decline in productivity and vigor with aging forest stands, the most poorly studied area relates to root system change in time. This paper measures the wood production, root and leaf area (and mass) in a chronosequence of fire-origin lodgepole pine (Pinus contorta Loudon) stands consisting of four age classes (12, 21, 53, and ≥100 years), each replicated ~ five times. Wood productivity was greatest in the 53-year-old stands and then declined in the ≥100-year-old stands. Growth efficiency, the quantity of wood produced per unit leaf mass, steadily declined with age. Leaf mass and fine root mass plateaued between the 53- and ≥100-year-old stands, but leaf area index actually increased in the older stands. An increase in the leaf area index:fine root area ratio supports the idea that older stand are potentially limited by soil resources. Other factors contributing to slower growth in older stands might be lower soil temperatures and increased self-shading due to the clumped nature of crowns. Collectively, the proportionally greater reduction in fine roots in older stands might be the variable that predisposes these forests to be at a potentially greater risk of stress-induced mortality.

Forest growth along a rainfall gradient in Hawaii: Acacia koa stand structure, productivity, foliar nutrients, and water- and nutrient-use efficiencies

Treesearch

Robin A. Harrington; James H. Fownes; Frederick C. Meinzer; Paul G. Scowcroft

1995-01-01

We tested whether variation in growth of native koa (Acacia koa) forest along a rainfall gradient was attributable to differences in leaf area index (LAI) or to differences in physiological performance per unit of leaf area. Koa stands were studied on western Kauai prior to Hurricane Iniki, and ranged from 500 to 1130 m elevation and from 850 to...

Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity

PubMed Central

Wang, Ruili; Yu, Guirui; He, Nianpeng; Wang, Qiufeng; Zhao, Ning; Xu, Zhiwei; Ge, Jianping

2015-01-01

To explore the latitudinal variation of stomatal traits from species to community level and their linkage with net primary productivity (NPP), we investigated leaf stomatal density (SDL) and stomatal length (SLL) across 760 species from nine forest ecosystems in eastern China, and calculated the community-level SD (SDC) and SL (SLC) through species-specific leaf area index (LAI). Our results showed that latitudinal variation in species-level SDL and SLL was minimal, but community-level SDC and SLC decreased clearly with increasing latitude. The relationship between SD and SL was negative across species and different plant functional types (PFTs), but positive at the community level. Furthermore, community-level SDC correlated positively with forest NPP, and explained 51% of the variation in NPP. These findings indicate that the trade-off by regulating SDL and SLL may be an important strategy for plant individuals to adapt to environmental changes, and temperature acts as the main factor influencing community-level stomatal traits through alteration of species composition. Importantly, our findings provide new insight into the relationship between plant traits and ecosystem function. PMID:26403303

Branch age and light conditions determine leaf-area-specific conductivity in current shoots of Scots pine.

PubMed

Grönlund, Leila; Hölttä, Teemu; Mäkelä, Annikki

2016-08-01

Shoot size and other shoot properties more or less follow the availability of light, but there is also evidence that the topological position in a tree crown has an influence on shoot development. Whether the hydraulic properties of new shoots are more regulated by the light or the position affects the shoot acclimation to changing light conditions and thereby to changing evaporative demand. We investigated the leaf-area-specific conductivity (and its components sapwood-specific conductivity and Huber value) of the current-year shoots of Scots pine (Pinus sylvestris L.) in relation to light environment and topological position in three different tree classes. The light environment was quantified in terms of simulated transpiration and the topological position was quantified by parent branch age. Sample shoot measurements included length, basal and tip diameter, hydraulic conductivity of the shoot, tracheid area and density, and specific leaf area. In our results, the leaf-area-specific conductivity of new shoots declined with parent branch age and increased with simulated transpiration rate of the shoot. The relation to transpiration demand seemed more decisive, since it gave higher R(2) values than branch age and explained the differences between the tree classes. The trend of leaf-area-specific conductivity with simulated transpiration was closely related to Huber value, whereas the trend of leaf-area-specific conductivity with parent branch age was related to a similar trend in sapwood-specific conductivity. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Enhancement of understory productivity by asynchronous phenology with overstory competitors in a temperate deciduous forest.

PubMed

Jolly, William M; Nemani, Ramakrishna; Running, Steven W

2004-09-01

Some saplings and shrubs growing in the understory of temperate deciduous forests extend their periods of leaf display beyond that of the overstory, resulting in periods when understory radiation, and hence productivity, are not limited by the overstory canopy. To assess the importance of the duration of leaf display on the productivity of understory and overstory trees of deciduous forests in the north eastern United States, we applied the simulation model, BIOME-BGC with climate data for Hubbard Brook Experimental Forest, New Hampshire, USA and mean ecophysiological data for species of deciduous, temperate forests. Extension of the overstory leaf display period increased overstory leaf area index (LAI) by only 3 to 4% and productivity by only 2 to 4%. In contrast, extending the growing season of the understory relative to the overstory by one week in both spring and fall, increased understory LAI by 35% and productivity by 32%. A 2-week extension of the growing period in both spring and fall increased understory LAI by 53% and productivity by 55%.

The temporal response to drought in a Mediterranean evergreen tree: comparing a regional precipitation gradient and a throughfall exclusion experiment.

PubMed

Martin-Stpaul, Nicolas K; Limousin, Jean-Marc; Vogt-Schilb, Hélène; Rodríguez-Calcerrada, Jesus; Rambal, Serge; Longepierre, Damien; Misson, Laurent

2013-08-01

Like many midlatitude ecosystems, Mediterranean forests will suffer longer and more intense droughts with the ongoing climate change. The responses to drought in long-lived trees differ depending on the time scale considered, and short-term responses are currently better understood than longer term acclimation. We assessed the temporal changes in trees facing a chronic reduction in water availability by comparing leaf-scale physiological traits, branch-scale hydraulic traits, and stand-scale biomass partitioning in the evergreen Quercus ilex across a regional precipitation gradient (long-term changes) and in a partial throughfall exclusion experiment (TEE, medium term changes). At the leaf scale, gas exchange, mass per unit area and nitrogen concentration showed homeostatic responses to drought as they did not change among the sites of the precipitation gradient or in the experimental treatments of the TEE. A similar homeostatic response was observed for the xylem vulnerability to cavitation at the branch scale. In contrast, the ratio of leaf area over sapwood area (LA/SA) in young branches exhibited a transient response to drought because it decreased in response to the TEE the first 4 years of treatment, but did not change among the sites of the gradient. At the stand scale, leaf area index (LAI) decreased, and the ratios of stem SA to LAI and of fine root area to LAI both increased in trees subjected to throughfall exclusion and from the wettest to the driest site of the gradient. Taken together, these results suggest that acclimation to chronic drought in long-lived Q. ilex is mediated by changes in hydraulic allometry that shift progressively from low (branch) to high (stand) organizational levels, and act to maintain the leaf water potential within the range of xylem hydraulic function and leaf photosynthetic assimilation. © 2013 John Wiley & Sons Ltd.

Attribution and Characterisation of Sclerophyll Forested Landscapes Over Large Areas

NASA Astrophysics Data System (ADS)

Jones, Simon; Soto-Berelov, Mariela; Suarez, Lola; Wilkes, Phil; Woodgate, Will; Haywood, Andrew

2016-06-01

This paper presents a methodology for the attribution and characterisation of Sclerophyll forested landscapes over large areas. First we define a set of woody vegetation data primitives (e.g. canopy cover, leaf area index (LAI), bole density, canopy height), which are then scaled-up using multiple remote sensing data sources to characterise and extract landscape woody vegetation features. The advantage of this approach is that vegetation landscape features can be described from composites of these data primitives. The proposed data primitives act as building blocks for the re-creation of past woody characterisation schemes as well as allowing for re-compilation to support present and future policy and management and decision making needs. Three main research sites were attributed; representative of different sclerophyll woody vegetated systems (Box Iron-bark forest; Mountain Ash forest; Mixed Species foothills forest). High resolution hyperspectral and full waveform LiDAR data was acquired over the three research sites. At the same time, land management agencies (Victorian Department of Environment, Land Water and Planning) and researchers (RMIT, CRC for Spatial Information and CSIRO) conducted fieldwork to collect structural and functional measurements of vegetation, using traditional forest mensuration transects and plots, terrestrial lidar scanning and high temporal resolution in-situ autonomous laser (VegNet) scanners. Results are presented of: 1) inter-comparisons of LAI estimations made using ground based hemispherical photography, LAI 2200 PCA, CI-110 and terrestrial and airborne laser scanners; 2) canopy height and vertical canopy complexity derived from airborne LiDAR validated using ground observations; and, 3) time-series characterisation of land cover features. 1. Accuracy targets for remotely sensed LAI products to match within ground based estimates are ± 0.5 LAI or a 20% maximum (CEOS/GCOS) with new aspirational targets of 5%). In this research we

Plant size and leaf area influence phenological and reproductive responses to warming in semiarid Mediterranean species.

PubMed

Valencia, Enrique; Méndez, Marcos; Saavedra, Noelia; Maestre, Fernando T

2016-08-01

Changes in vegetative and reproductive phenology rank among the most obvious plant responses to climate change. These responses vary broadly among species, but it is largely unknown whether they are mediated by functional attributes, such as size or foliar traits. Using a manipulative experiment conducted over two growing seasons, we evaluated the responses in reproductive phenology and output of 14 Mediterranean semiarid species belonging to three functional groups (grasses, nitrogen-fixing legumes and forbs) to a ~3°C increase in temperature, and assessed how leaf and size traits influenced them. Overall, warming advanced flowering and fruiting phenology, extended the duration of flowering and reduced the production of flowers and fruits. The observed reduction in flower and fruit production with warming was likely related to the decrease in soil moisture promoted by this treatment. Phenological responses to warming did not vary among functional groups, albeit forbs had an earlier reproductive phenology than legumes and grasses. Larger species with high leaf area, as well as those with small specific leaf area, had an earlier flowering and a longer flowering duration. The effects of warming on plant size and leaf traits were related to those on reproductive phenology and reproductive output. Species that decreased their leaf area under warming advanced more the onset of flowering, while those that increased their vegetative height produced more flowers. Our results advance our understanding of the phenological responses to warming of Mediterranean semiarid species, and highlight the key role of traits such as plant size and leaf area as determinants of such responses.

Leaf Mass Area, Leaf Carbon and Nitrogen Content, Kougarok Road and Teller Road, Seward Peninsula, Alaska, 2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shawn Serbin; Alistair Rogers; Kim Ely

Carbon, Nitrogen and Leaf Mass Area of leaves sampled from locations on the Kougarok Rd (transect A) and Teller Rd NGEE Arctic study sites, Seward Peninsula, Alaska. Species include: Alnus viridis spp. fruticosa, Arctostaphylos rubra, Betula glandulosa, Chamerion latifolium, Petasites frigidus, Salix alaxensis, Salix glauca, Salix pulchra, Salix richardsonii and Vaccinium uliginosum.

Leaf area and light use efficiency patterns of Norway spruce under different thinning regimes and age classes

PubMed Central

Gspaltl, Martin; Bauerle, William; Binkley, Dan; Sterba, Hubert

2013-01-01

Silviculture focuses on establishing forest stand conditions that improve the stand increment. Knowledge about the efficiency of an individual tree is essential to be able to establish stand structures that increase tree resource use efficiency and stand level production. Efficiency is often expressed as stem growth per unit leaf area (leaf area efficiency), or per unit of light absorbed (light use efficiency). We tested the hypotheses that: (1) volume increment relates more closely with crown light absorption than leaf area, since one unit of leaf area can receive different amounts of light due to competition with neighboring trees and self-shading, (2) dominant trees use light more efficiently than suppressed trees and (3) thinning increases the efficiency of light use by residual trees, partially accounting for commonly observed increases in post-thinning growth. We investigated eight even-aged Norway spruce (Picea abies (L.) Karst.) stands at Bärnkopf, Austria, spanning three age classes (mature, immature and pole-stage) and two thinning regimes (thinned and unthinned). Individual leaf area was calculated with allometric equations and absorbed photosynthetically active radiation was estimated for each tree using the three-dimensional crown model Maestra. Absorbed photosynthetically active radiation was only a slightly better predictor of volume increment than leaf area. Light use efficiency increased with increasing tree size in all stands, supporting the second hypothesis. At a given tree size, trees from the unthinned plots were more efficient, however, due to generally larger tree sizes in the thinned stands, an average tree from the thinned treatment was superior (not congruent in all plots, thus only partly supporting the third hypothesis). PMID:25540477

Tree differences in primary and secondary growth drive convergent scaling in leaf area to sapwood area across Europe.

PubMed

Petit, Giai; von Arx, Georg; Kiorapostolou, Natasa; Lechthaler, Silvia; Prendin, Angela Luisa; Anfodillo, Tommaso; Caldeira, Maria C; Cochard, Hervé; Copini, Paul; Crivellaro, Alan; Delzon, Sylvain; Gebauer, Roman; Gričar, Jožica; Grönholm, Leila; Hölttä, Teemu; Jyske, Tuula; Lavrič, Martina; Lintunen, Anna; Lobo-do-Vale, Raquel; Peltoniemi, Mikko; Peters, Richard L; Robert, Elisabeth M R; Roig Juan, Sílvia; Senfeldr, Martin; Steppe, Kathy; Urban, Josef; Van Camp, Janne; Sterck, Frank

2018-06-01

Trees scale leaf (A L ) and xylem (A X ) areas to couple leaf transpiration and carbon gain with xylem water transport. Some species are known to acclimate in A L  : A X balance in response to climate conditions, but whether trees of different species acclimate in A L  : A X in similar ways over their entire (continental) distributions is unknown. We analyzed the species and climate effects on the scaling of A L vs A X in branches of conifers (Pinus sylvestris, Picea abies) and broadleaved (Betula pendula, Populus tremula) sampled across a continental wide transect in Europe. Along the branch axis, A L and A X change in equal proportion (isometric scaling: b ˜ 1) as for trees. Branches of similar length converged in the scaling of A L vs A X with an exponent of b = 0.58 across European climates irrespective of species. Branches of slow-growing trees from Northern and Southern regions preferentially allocated into new leaf rather than xylem area, with older xylem rings contributing to maintaining total xylem conductivity. In conclusion, trees in contrasting climates adjust their functional balance between water transport and leaf transpiration by maintaining biomass allocation to leaves, and adjusting their growth rate and xylem production to maintain xylem conductance. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.