Using directional TIR measurements and 3D simulations to assess the limitations and opportunities of water stress indices

Abstract Multidirectional remotely sensed optical and thermal images acquired within a row cotton crop in Montpellier (France) were used to test the opportunities and limitations of an existing water stress index, the Water Deficit Index (WDI, based on the trapezoid approach). The WDI was applied with multidirectional crop surface temperatures ( T s ) and reflectance data acquired on a row-cotton crop with different water and cover conditions from 11 different view angles in the east/west plane. This data set allowed a biophysical analysis of this index both inside and outside its validity domain, initially limited in terms of T s measurements in a [−20°, +20°] view angles interval around nadir. Results showed that the WDI was a robust approach, since its calculation is based on the relationship between crop cover and T s . However, it yielded some directional errors in the case of sparse crops even in its validity domain where the relative variation of WDI between oblique angles and nadir could reach 14% (and more than 40% for larger view angles). The same degree of variability was observed between WDI values estimated on a same plot at two different times in a given day from a nadir observation. In a large range of crop heterogeneity, hourly sunlit soil fraction presented a stronger influence on T s than the total soil fraction. However, by adapting the view angle to daytime measurements and crop structure, it seemed possible to overcome sunlit soil effects. These experimental results were tested and extrapolated using a 3D crop energy balance model ( Thermo ). It allowed simulations of directional T s measurements according to various sun/sensor angular configurations, crop structure, and water status characteristics. This confirmed the limitations of the trapezoid method both within and outside its validity domain. Moreover, Thermo allowed the computation of a “directional” WDI accounting for angular and hourly sunlit soil effects variability on T s . The interest of adapting the view angle to daytime measurements and crop structure was confirmed by comparing this “directional” WDI with the “theoretical” one (based on the original trapezoid approach). These results should encourage further development of water stress indices based on bidirectional thermal infrared and optical measurements to quantify and thus overcome sunlit soil fraction effects.

[1]  Daniel S. Kimes,et al.  Directional radiometric measurements of row-crop temperatures , 1983 .

[2]  S. Idso,et al.  Canopy temperature as a crop water stress indicator , 1981 .

[3]  K. L. Petersen,et al.  Stomatal Responses of Field-Grown Cotton to Radiation and Soil Moisture , 1991 .

[4]  Thomas J. Schmugge,et al.  An interpretation of methodologies for indirect measurement of soil water content , 1995 .

[5]  R. Percy,et al.  Stomatal conductance predicts yields in irrigated Pima cotton and bread wheat grown at high temperatures , 1998 .

[6]  Hamlyn G. Jones,et al.  Use of infrared thermometry for estimation of stomatal conductance as a possible aid to irrigation scheduling , 1999 .

[7]  Albert Olioso,et al.  Using multidirectional thermography to characterize water status of cotton , 2003 .

[8]  Sherwood B. Idso,et al.  Non-water-stressed baselines: A key to measuring and interpreting plant water stress , 1982 .

[9]  Roger H. Shaw,et al.  A numerical experiment on the mean wind structure inside canopies of vegetation , 1980 .

[10]  D. S. Kimes,et al.  Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion techniques , 1983 .

[11]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[12]  D. D. Fangmeier,et al.  Quantifying wheat water stress with the crop water stress index to schedule irrigations , 1994 .

[13]  Hamlyn G. Jones,et al.  Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces , 1999 .

[14]  J. R. Mahan,et al.  Thermal environment of cotton irrigated using canopy temperature , 2004, Irrigation Science.

[15]  R. Gillies.  A verification of the 'triangle' method for obtaining surface water content and energy fluxes from remote measurements of Normalized Difference Vegetation Index (NDVI) and surface radiant temperature , 1997 .

[16]  Ray Jackson,et al.  Detection and Evaluation of Plant Stresses for Crop Management Decisions , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[17]  M. S. Moran,et al.  Opportunities and limitations for image-based remote sensing in precision crop management , 1997 .

[18]  P. Clouvel,et al.  3D Simulation of Directional Temperature Variability Within a Row-Cotton Crop: Toward an Improvement of Experimental Crop Water Status Monitoring Using Thermal Infrared , 2003, Precision Agriculture.

[19]  Jean Dauzat,et al.  Simulation of leaf transpiration and sap flow in virtual plants: model description and application to a coffee plantation in Costa Rica. , 2001 .

[20]  M. S. Moran,et al.  Irrigation management in Arizona using satellites and airplanes , 1994, Irrigation Science.

[21]  R. Jackson.  Canopy Temperature and Crop Water Stress , 1982 .

[22]  Brent Clothier,et al.  ESTIMATION OF SOIL HEAT FLUX FROM NET RADIATION DURING THE GROWTH OF ALFALFA , 1986 .

[23]  D. F. Wanjura,et al.  Canopy temperature and water stress of cotton crops with complete and partial ground cover , 1984, Irrigation Science.

[24]  D. F. Wanjura,et al.  Crop water stress index relationships with crop productivity , 1990, Irrigation Science.

[25]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .