Comparison of vegetation water contents derived from shortwave-infrared and passive-microwave sensors over central Iowa

Retrieval of soil moisture content using the vertical and horizontal polarizations of multiple frequency bands on microwave sensors can provide an estimate of vegetation water content (VWC). Another approach is to use foliar-water indices based on the absorption at shortwave-infrared wavelengths by liquid water in the leaves to determine canopy water content, which is then related to VWC. An example of these indices is the normalized difference infrared index (NDII), which was found to be linearly related to canopy water content using various datasets, including data from the Soil Moisture Experiments 2002 and 2005 in central Iowa. Here we compared independent estimates of VWC from WindSat to Moderate resolution Imaging Spectroradiometer (MODIS) NDII over central Iowa from 2003 to 2005. Results showed that there was a linear relationship between the MODIS and WindSat estimates of VWC, although WindSat-retrieved VWC was greater than MODIS-retrieved VWC. WindSat and MODIS have different satellite overpass times and in most climates we expect VWC to vary over a day due to transpiration and plant water stress. However, a sensitivity analysis indicated that the diurnal variation of VWC should not have a significant effect on retrievals of VWC by either method. The results of this study indicated that soil moisture retrievals from microwave sensors may be improved using VWC from optical sensors determined by foliar-water indices and classifications of land cover type.

[1]  W. J. Shuttleworth,et al.  Using vegetation indices for soil-moisture retrievals from passive microwave radiometry , 2001 .

[2]  W. Linwood Jones,et al.  The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Luiz Eduardo Oliveira E. Cruz de Aragão,et al.  Spatial validation of the collection 4 MODIS LAI product in eastern Amazonia , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[4]  C. Tucker.  Remote sensing of leaf water content in the near infrared , 1980 .

[5]  T. Holmes,et al.  An analysis of spatiotemporal variations of soil and vegetation moisture from a 29‐year satellite‐derived data set over mainland Australia , 2009 .

[6]  Li Li,et al.  Retrieval of land surface parameters using passive microwave measurements at 6-18 GHz , 1999, IEEE Trans. Geosci. Remote. Sens..

[7]  Y. Knyazikhin,et al.  Validation of Moderate Resolution Imaging Spectroradiometer leaf area index product in croplands of Alpilles, France , 2005 .

[8]  Michael Freilich,et al.  Committee on Earth Science and Applications from Space , 2012 .

[9]  E. Njoku,et al.  Vegetation and surface roughness effects on AMSR-E land observations , 2006 .

[10]  Robert J. Gurney,et al.  The effects of scene heterogeneity on soil moisture retrieval from passive microwave data , 2008 .

[11]  H. Gausman,et al.  Interaction of Isotropic Light with a Compact Plant Leaf , 1969 .

[12]  David L. Verbyla,et al.  Assessment of the MODIS Leaf Area Index Product (MOD15) in Alaska , 2005 .

[13]  S. Chatterjee,et al.  Regression Analysis by Example , 1979 .

[14]  Craig S. T. Daughtry,et al.  Discriminating Crop Residues from Soil by Shortwave Infrared Reflectance , 2001 .

[15]  Roberta E. Martin,et al.  PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .

[16]  David Riaño,et al.  Water content estimation from hyperspectral images and MODIS indexes in Southeastern Arizona , 2008 .

[17]  E. Raymond Hunt,et al.  Airborne remote sensing of canopy water thickness scaled from leaf spectrometer data , 1991 .

[18]  Michael Vohland,et al.  Using imaging and non-imaging spectroradiometer data for the remote detection of vegetation water content , 2008 .

[19]  Shusen Wang,et al.  Remote sensing of grassland–shrubland vegetation water content in the shortwave domain , 2006 .

[20]  K. Niklas,et al.  Canonical rules for plant organ biomass partitioning and annual allocation. , 2002, American journal of botany.

[21]  S. Tarantola,et al.  Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications , 2002 .

[22]  C. Schueler,et al.  NASA MODIS previews NPOESS VIIRS capabilities , 2006 .

[23]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[24]  B. Rock,et al.  Detection of changes in leaf water content using Near- and Middle-Infrared reflectances , 1989 .

[25]  Li Li,et al.  A preliminary survey of radio-frequency interference over the U.S. in Aqua AMSR-E data , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Pablo J. Zarco-Tejada,et al.  Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[27]  S. Ustin,et al.  Multi-temporal vegetation canopy water content retrieval and interpretation using artificial neural networks for the continental USA , 2008 .

[28]  Michael E. Schaepman,et al.  Using spectral information from the NIR water absorption features for the retrieval of canopy water content , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[29]  Tim R. McVicar,et al.  Assessment of the MODIS LAI product for Australian ecosystems , 2006 .

[30]  S. Running,et al.  Extrapolating plant water flow resistances and capacitances to regional scales , 1991 .

[31]  T. Jackson,et al.  Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands , 2005 .

[32]  Susan L. Ustin,et al.  Investigating the Relationship Between Liquid Water and Leaf Area in Clonal Populus , 1998 .

[33]  Shobha Kondragunta,et al.  Estimating forest biomass in the USA using generalized allometric models and MODIS land products , 2006 .

[34]  T. Jackson,et al.  III. Measuring surface soil moisture using passive microwave remote sensing , 1993 .

[35]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[36]  S. Goward,et al.  Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model , 1992 .

[37]  Thomas J. Jackson,et al.  Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[38]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[39]  Thomas J. Jackson,et al.  Soil moisture retrieval from AMSR-E , 2003, IEEE Trans. Geosci. Remote. Sens..

[40]  S. Ustin,et al.  Estimating Vegetation Water content with Hyperspectral data for different Canopy scenarios: Relationships between AVIRIS and MODIS Indexes , 2006 .

[41]  Thomas J. Jackson,et al.  Vegetation water content during SMEX04 from ground data and Landsat 5 Thematic Mapper imagery , 2008 .

[42]  The Factor b as a Function of Frequency, Polarization and Canopy Type , 2003 .

[43]  S. Ustin,et al.  Water content estimation in vegetation with MODIS reflectance data and model inversion methods , 2003 .

[44]  Bernardo Friedrich Theodor Rudorff,et al.  Assessment of MODIS LAI retrievals over soybean crop in Southern Brazil , 2006 .

[45]  J. Peñuelas,et al.  The reflectance at the 950–970 nm region as an indicator of plant water status , 1993 .

[46]  T. Schmugge,et al.  Vegetation effects on the microwave emission of soils , 1991 .

[47]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[48]  T. Jackson,et al.  Remote sensing of vegetation water content from equivalent water thickness using satellite imagery , 2008 .

[49]  D. Sims,et al.  Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features , 2003 .

[50]  D. Roberts,et al.  Spectral and Structural Measures of Northwest Forest Vegetation at Leaf to Landscape Scales , 2004, Ecosystems.

[51]  John R. Miller,et al.  Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .

[52]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[53]  Xianjun Hao,et al.  Sensitivity studies of the moisture effects on MODIS SWIR reflectance and vegetation water indices , 2008 .

[54]  R. Jeu,et al.  Multisensor historical climatology of satellite‐derived global land surface moisture , 2008 .

[55]  Xianjun Hao,et al.  Remote sensing of canopy water content: scaling from leaf data to MODIS , 2009, Optical Engineering + Applications.

[56]  Karl J Niklas,et al.  Global Allocation Rules for Patterns of Biomass Partitioning in Seed Plants , 2002, Science.

[57]  Wade T. Crow,et al.  Evaluating the Utility of Remotely Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[58]  Thomas J. Jackson,et al.  WindSat Global Soil Moisture Retrieval and Validation , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[59]  S. Ustin,et al.  Estimating leaf biochemistry using the PROSPECT leaf optical properties model , 1996 .

[60]  Jean-Pierre Wigneron,et al.  The b-factor as a function of frequency and canopy type at H-polarization , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[61]  Jiancheng Shi,et al.  An observing system simulation experiment for hydros radiometer-only soil moisture products , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[62]  B. Gao.  NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[63]  Alfred T. C. Chang,et al.  Estimating surface soil moisture from satellite microwave measurements and a satellite derived vegetation index , 1988 .