A review of the application of BRDF models to infer land cover parameters at regional and global scales

2001 ◽  
Vol 25 (4) ◽  
pp. 483-511 ◽  
Author(s):  
Gareth Roberts
Keyword(s):  
Land Surface ◽  
Lower Boundary ◽  
Terrestrial Ecosystems ◽  
Remotely Sensed Data ◽  
Area Index ◽  
Lower Boundary Condition ◽  
Surface Parameters ◽  
Case Examples ◽  
Global Circulation Models ◽  
Land Surface Parameters

This paper presents a review of the application of Bi-directional Reflectance Distribution Function (BRDF) models in the inference of land surface parameters at regional and global scales using remotely sensed data. Information on land surface parameters, such as Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR), aerodynamic surface roughness and albedo, are valuable for understanding the transfer of energy and mass between terrestrial ecosystems and the atmosphere (e.g., carbon, nitrogen and methane cycling) and for ingestion into the lower boundary condition of global circulation models (GCM)s. Conventional techniques for acquiring information on land surface parameters do not account for or utilize the directional nature of surface reflectance. This paper reviews empirical, semi-empirical and, to a lesser extent, physical BRDF models that describe the surface BRDF. In each case examples are given of their application in inferring land surface parameters. The review concludes by discussing the future prospects of BRDF modelling using spaceborne sensors.

scholarly journals Development of high resolution land surface parameters for the Community Land Model

2012 ◽  
Vol 5 (2) ◽  
pp. 1435-1481 ◽  
Author(s):  
Y. Ke ◽  
L. R. Leung ◽  
M. Huang ◽  
A. M. Coleman ◽  
H. Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Area Index ◽  
Surface Parameters ◽  
Community Land Model ◽  
Source Data ◽  
Land Surface Parameters

Abstract. There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the model from the National Center for Atmospheric Research (NCAR). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely-sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western US to demonstrate their use in high-resolution modeling. Future work will include global offline CLMsimulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

scholarly journals Estimation of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem in China using real-time remote sensing data

2012 ◽  
Vol 12 (3) ◽  
pp. 6551-6592 ◽  
Author(s):  
M. Li ◽  
X. Huang ◽  
J. Li ◽  
Y. Song
Keyword(s):  
Real Time ◽  
Land Surface ◽  
Dynamic Models ◽  
Meteorological Data ◽  
Leaf Age ◽  
Area Index ◽  
Surface Parameters ◽  
Volatile Organic ◽  
Land Surface Parameters

Abstract. Because of the high emission rate and reactivity, biogenic volatile organic compounds (BVOCs) play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and coarsely resolved meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in the atmosphere, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature), with MM5 (the Fifth-Generation Mesoscale Model) providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8) and seven monoterpene species (C10H16) in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer) data were introduced to update the land surface parameters and to improve the simulation performance of MM5, and to determine the influence of leaf area index (LAI) and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value compared with past studies. Therein, the most important individual contributor was isoprene (9.36 Tg C yr−1), followed by α-pinene (1.24 Tg C yr−1) and β-pinene (0.84 Tg C yr−1). Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial and temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. While Southeast China was the top-ranking contributor of monoterpenes, in which the dominant vegetation genera consist of evergreen coniferous forests. Temporally, BVOC emissions primarily occurred in July and August, with daily emissions peaking at about 13:00∼14:00 h (Beijing Time, BJT). In this study, we present an improved estimation of BVOC emissions, which provides important information for further exploration of the role of BVOCs in atmospheric processes.

scholarly journals Development of high resolution land surface parameters for the Community Land Model

2012 ◽  
Vol 5 (6) ◽  
pp. 1341-1362 ◽  
Author(s):  
Y. Ke ◽  
L. R. Leung ◽  
M. Huang ◽  
A. M. Coleman ◽  
H. Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Remotely Sensed ◽  
Area Index ◽  
Surface Parameters ◽  
Advantages And Disadvantages ◽  
Community Land Model ◽  
Source Data ◽  
Land Surface Parameters

Abstract. There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the Community Earth System Model (CESM). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. Advantages and disadvantages of each dataset were discussed in order to provide guidance on the use of the data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western US to demonstrate their use in high-resolution modeling. A remapping method from the latitude/longitude grid of the CLM data to the WRF grids with map projection was also demonstrated. Future work will include global offline CLM simulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

scholarly journals The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme

2004 ◽  
Vol 5 (6) ◽  
pp. 1131-1146 ◽  
Author(s):  
H. Richter ◽  
A. W. Western ◽  
F. H. S. Chiew
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Soil Parameters ◽  
Model Parameters ◽  
Lower Boundary Condition ◽  
Land Surface Scheme ◽  
Vegetation Parameters ◽  
Surface Scheme

Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.

Retrieving land surface parameters over Sahel from ERS wind scatterometer data

2001 ◽  
Author(s):  
Lionel Jarlan ◽  
Pierre Mazzega ◽  
Eric Mougin ◽  
Pierre L. Frison
Keyword(s):  
Land Surface ◽  
Surface Parameters ◽  
Land Surface Parameters

scholarly journals Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019 ◽  
Vol 11 (18) ◽  
pp. 2103 ◽  
Author(s):  
Francisco Javier García-Haro ◽  
Fernando Camacho ◽  
Beatriz Martínez ◽  
Manuel Campos-Taberner ◽  
Beatriz Fuster ◽  
...  
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Terrestrial Ecosystems ◽  
Environmental Applications ◽  
Climate Data ◽  
Area Index ◽  
Infrared Imager ◽  
Statistical Relationships ◽  
Spectral Mixture

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.

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