Michio Shibayama

Seasonal visible, near-infrared and mid-infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass

Spectral reflectance factors were measured for paddy rice canopies in the visible (VIS), reflective near-infrared (NIR), and mid-infrared (MIR) wavelength regions. Radiometric and agronomic measurements were performed every other week from 45 days before heading to 64 days after heading in early- and late-planted rice plots consisting of five cultivars. The relation between radiometric data an and the leaf area index (LAI) and above-ground dry phytomass (GDM) was investigated during 11 development periods of 10-day intervals. Reflectance values in the VIS bands were lowest when the panicles emerged, whereas the values at 840 and 1100 nm increased until the time when the grains reached maturity. Reflectances at 1200 and 1650 nm were similar in pattern but less pronounced than at 840 and 1100 nm. Ratios using VIS and NIR reflectances (R840 / R560, R1100 / R840) for the whole season were associated with 71of the variation in LAI, while the difference between NIR and MIR reflectances (R1100 - R1650, R1100 - R1200) combined with ratios using VIS and NIR reflectances (R840 / R560, R1100 / R840) was associated with 93% of the variation in GDM of the paddy rice canopies. Thus, the use of mid-infrared wavelengths may result in improved estimates of seasonal GDM.

Canopy water deficit detection in paddy rice using a high resolution field spectroradiometer

Abstract Reflectance factor spectra in the visible, near, and mid-infrared ranges from canopies of rice plantings that were flooded throughout the crop season (controls) were compared with the treatment drained on a predetermined date, and sheltered from rainfall, to induce water stress. Spectra sampled at 5 nm intervals in the 400–900 nm range and 10 nm intervals in the 900–1900 nm range and their first derivatives were statistically analyzed by ANOVA for two sources of variation, cultivars and water stress, each measurement date. Near infrared (1190–1320 nm) and mid-infrared (1600 nm) band reflectances, and the first derivative at 1230 nm responded promptly to the removal of paddy surface water even for complete ground cover (LAI = 5) during vegetative development. The first derivative at 960 nm, corresponding to a small water absorption band, detected the water status of canopies about 10 days after drainage. Response in the first derivative preceded by a few days the leaf water content deficit, the visual symptoms of wilting and leaf roll, and the decrease in visible red (RED) and near infrared (NIR) reflectances expressed as the normalized difference vegetation index, NDVI = (NIR - RED) (NIR + RED) . Findings indicate that high spectral resolution reflectance measurements and their first derivatives in near and mid-infrared ranges offer a promising method for early detection of water stress in rice canopies.

Continuous Monitoring of Visible and Near-Infrared Band Reflectance from a Rice Paddy for Determining Nitrogen Uptake Using Digital Cameras

Abstract A two-band digital imaging system —one band for the visible red band (RED, 630−670 nm) and the other for the near infrared band (NIR, 820−900 nm)— was devised and positioned at a height of 12 m above a rice field of 300 m2 in area during the 2007 growing season. The imaging system automatically logged bird’seye view images at 10-min intervals from 0800−1600 every day. Radiometric corrections for the pairs of two-band images were done using solar irradiance sensors and preceding calibrations to calculate daily band-reflectance and the normalized difference vegetation index (NDVI) values for 9 plots of rice plants, with 3 levels of planting density and basal fertilization. The daily- averaged reflectance values in the RED and the NIR bands showed different but smooth seasonal changing patterns according to the growth of plants. At the maximum tiller number and the panicle formation stages, the RED and NIR reflectance values had correlation coefficients (r) of 0.79 and 0.81 with above-ground nitrogen absorption per unit land area (NA, g m-2), respectively, whereas the NDVI using the two band reflectance values showed r-value of -0.13. An empirically derived equation for the NA using two band reflectance values showed r-value of 0.96 and a root mean square of error (RMSE) 0.5 g m–2 (10% of the mean observed NA) in the estimation for the original (not validated) data set acquired at the maximum tiller number and the panicle formation stages. The results indicated that reflectance observation in the RED and NIR bands using the digital imaging system was potentially effective for assessing rice growth.

Estimating Paddy Rice Leaf Area Index with Fixed Point Continuous Observation of Near Infrared Reflectance Using a Calibrated Digital Camera

Abstract A two-band digital imaging system—one band for visible red (RED, 630–670 nm) and the other for near infrared (NIR, 820–900 nm)—was positioned 12 m above a 600-m2 rice field. The imaging system automatically logged bird’s-eye-view images at 10-min intervals from 0700 to 1700 JST daily during the 2008 paddy rice season. Radiometric corrections and midterm field validations for the pairs of two-band images utilized solar irradiance sensors and prior calibrations to calculate 0900-1500 JST daily-averaged reflectance factor (DARF). The DARF values in the RED and the NIR bands agreed with observations made with a portable spectroradiometer and showed smooth seasonal changes in terms of plant growth. During the before-heading period, NIR DARF values had a correlation coefficient (r) of 0.91 with the leaf area index (LAI). An empirically derived equation for LAI using NIR DARF values and the cosines of angles between the view and the planting row directions, and the view and the meridian directions, showed R2 values of 0.93, in estimations of LAI from the dataset (number of observations=52) acquired at four sample points centrally located within the viewing field. Validation indicated that the equation also worked well for the other six observation points spread across the viewing field, the data of which were not used in deriving the equation parameters. The DARF values observed in the NIR band calibrated with solar spectral irradiance sensors were useful for assessing rice LAI during the before-heading periods.

A Portable Spectropolarimeter for Field Crop Canopies : Distinguishing species and cultivars of fully developed canopies by polarized light

Abstract A spectropolarimeter equipped with eight spectral bands in the visible, near– and short–wave infrared ranges (490–2200 nm) as well as a rotary film polarizer has been developed for measuring the reflectance and degree of polarization of light reflected from field crop canopies. This paper describes the design and specification of the instrument and the results of preliminary field experiments. Solar and view zenith angles and view azimuth direction relative to the solar position had a much greater influence on polarization than reflectance. For fully developed sweet potato and soybean canopies, the degree of polarization was a better discriminator of the canopy than each single band reflectance and a reflectance–based vegetation index such as normalized difference vegetation index (NDVI).

Water turbidity and perpendicular vegetation indices for paddy rice flood damage analyses

Abstract Reflectance factors were obtained for paddy rice at two sites in calibrated TM scenes acquired on two dates for the Kanto district of Japan—1 day after a typhoon inundated the paddies (6 August 1986, when the rice was at boot stage of development) and a month later (7 September 1986, during grain filling). A water turbidity index (WTI), analogous to soil brightness, and the perpendicular vegetation index (PVI) were computed for these data as WTI = 0.91 RED + 0.43 NIR and PVI = − 0.43 RED + 0.91 NIR , respectively. Rice yield measured for the inundation-damaged paddies and experimental nondamaged paddies at Tsukuba, Japan, were pooled and related to the PVI calculated from the respective TM scene and ground-measured reflectance factors. The ground and TM data coincided well, and the regression relation YIELD (t/ha) = 0.26 PVI − 3.0 for the pooled data. The relation between flood water turbidity at boot stage and yield was also examined for the two test sites; the more turbid the flood water, the greater the damage to the crop. The results demonstrate the possibility of spectrally assessing flood damage to rice and other crops.

Estimating the Mean Leaf Inclination Angle of Wheat Canopies Using Reflected Polarized Light

Abstract In this study, we extended previous work linking the polarization of reflected light from crop canopies with characteristics of the canopy structure, such as the leaf inclination angle. We obtained reflectance and polarized reflectance in 8 spectral bands from the canopies of two varieties of wheat, planted in plots fertilized with a basal dressing and topdressed at the jointing and booting stages. The optical measurements were carried out on 3 clear-sky days when the plants were at the stem-elongation, heading and ripening stages, respectively. On each measurement date, we assessed the leaf orientation geometry of the plants using a Plant Canopy Analyzer (LAI-2000), measured the leaf greenness (an indicator of leaf chlorophyll content) using a handheld SPAD-502 (SPAD) optical sensor, and also measured plant height. Both polarization and leaf greenness observations at the heading stage were able to distinguish the canopies that had received topdressing from those without topdressing. However, no significant correlation was observed between the polarization in the blue, green and red bands and the SPAD (r = 0.425ᵻ0.456, n = 12 observations, p < 0.05). On the other hand, the mean leaf inclination angle (= mean tip angle: MTA) measured by the LAI-2000 was inversely correlated with the polarization in the 3 visible bands (r = −0.85ᵻ−0.88, n = 12, p < 0.001). Adjusting the view zenith angle according to the solar position at the time of measurement improved the accuracy. We tested a linear regression model to predict the MTA of the two wheat varieties based on polarized reflectance in the red band centered at 660 nm (r 2 = 0.73, n = 12, p < 0.001). Validation of this model obtained in the subsequent cropping season confirmed that polarization measurements were potentially useful for estimating the MTA of wheat stands in which the panicles were located below the topmost leaf layer of the canopy.

Seasonal Profiles of Polarized Reflectance and Leaf Inclination Distribution of Wheat Canopies

Abstract Reflectance and polarized reflectance in the visible red band were measured for wheat canopies in a wide range of solar zenith angles to explore the relations among reflectance and polarization, view and illumination geometry, and crop canopy development. The reflected sunlight in a 10˚ field of view was measured with a radiometer at approximately 1.6 m in height. The view zenith angles were set from 0˚ to 75˚ at 15˚ intervals, and the observation azimuth was towards the sun. The relation between the polarization and solar zenith angle depended both on the view zenith angle and the growth stage. Multiple regressions were applied to estimate the polarization and reflectance at solar zenith 40˚. Seasonal profiles of LAI, leaf inclination distribution, reflectance, and polarized reflectance indicate that polarization includes information for canopy structure such as leaf inclination distribution. Observations at solar zenith angles of more or less than 40˚ may also give similar results when the view zenith angle is appropriately set, corresponding to the solar zenith angle at the time of measurement.

Detecting phenophases of subarctic shrub canopies by using automated reflectance measurements

Abstract Boreal and subarctic plant phenophases are advantageous indicators of climatic change on a global scale. Remote sensing is a promising technique for assessing such changes over extended areas. An automated field measuring system collected seasonal reflectances of natural shrubs in visible, near-, and mid-infrared wavelength ranges. A boom-mounted four-band spectroradiometer was installed on a 4-m-high tower to measure seasonal radiances in green (520–600 nm), red (630–690 nm), near-infrared (765–900 nm), and mid-infrared (1570–1730 nm) spectral bands from undisturbed subarctic shrub vegetation during the 1994 and 1995 growing seasons (mid-June to mid-September) in northernmost Finland (69°45′N, 27°00′E, 105 m above sea level). The radiometer was vertically looking down on four fixed ground plots and a weatherproof reference panel continuously during all the daylight hours. The reflectance factor calculations, using the reference panel and solarimeter readings, included corrections for the reference panel degradation and non-Lambertian characteristics. Daily averages of visible and near-infrared band reflectance factors offered smooth seasonal trends in spite of the variation in solar irradiance at the times of data collection. The turning point dates in the trends of seasonal near-infrared (765–900 nm) and red (630–690 nm) reflectance factors might indicate the end of growth and the beginning of autumn changes, respectively. The normalized difference vegetation index and ratio of green (520–600 nm) to red (630–690 nm) band reflectance factors, however, seemed to be more accurate in monitoring them.

Regression-Based Models to Predict Rice Leaf Area Index Using Biennial Fixed Point Continuous Observations of Near Infrared Digital Images

Abstract A weatherproof digital imaging system for the near infrared band (NIR, 820–900 nm) was positioned 12 m above a 600-m2 rice field. During the 2008 and 2009 paddy rice seasons, the system automatically logged images at 10-min intervals throughout the day. Radiometric corrections for the NIR images utilized a solar irradiance sensor and prior calibrations to calculate 0900–1500 JST daily-averaged reflectance factors (DARF). Prior to heading, empirically derived equations for predicting leaf area index (LAI) using the 2008 DARF values in NIR, the cosines of angles between the view and the planting row directions, and between the view and the meridian directions were verified with the 2009 data set. Transformation of a model variable by arcsine square root function improved the performance of the LAI prediction by reducing the errors and bias at low LAI values. Adding variables to incorporate lateral angular components to the horizontal viewing angular parameters hardly affected the overall performance of the models and did not reduce variation. This was probably because the height and position of the camera system were the same in successive years. In-plot means of two or four predicted values in each plot reduced the root-mean square error 30%. These results indicate that radiometric NIR images derived using a fixed-point observation system can accurately predict LAI and the simple multiple linear regression equations developed for a given year can be used the following year without in-situ recalibration.