Toshihiro Sakamoto

Use of the RothC model to estimate the carbon sequestration potential of organic matter application in Japanese arable soils

Abstract We estimated the carbon (C) sequestration potential of organic matter application in Japanese arable soils at a country scale by applying the Rothamsted carbon (RothC) model at a 1-km resolution. After establishing the baseline soil organic carbon (SOC) content for 1990, a 25-year simulation was run for four management scenarios: A (minimum organic matter application), B (farmyard manure application), C (double cropping for paddy fields) and D (both B and C). The total SOC decreased during the simulation in all four scenarios because the C input in all four scenarios was lower than that required to maintain the baseline 1990 SOC level. Scenario A resulted in the greatest depletion, reflecting the effects of increased organic matter application in the other scenarios. The 25-year difference in SOC accumulation between scenario A and scenarios B, C and D was 32.3, 11.1 and 43.4 Mt C, respectively. The annual SOC accumulation per unit area was similar to a previous estimate, and the 25-year averages were 0.30, 0.10 and 0.41 t C ha−1 year−1 for scenarios B, C and D, respectively. The system we developed in the present study, that is, linking the RothC model and soil spatial data, can be useful for estimating the potential C sequestration resulting from an increase in organic matter input to Japanese arable soils, although more feasible scenarios need to be developed to enable more realistic estimation.

Detecting Spatiotemporal Changes of Corn Developmental Stages in the U.S. Corn Belt Using MODIS WDRVI Data

The dates of crop developmental stages are important variables for many applications including assessment of the impact of abnormal weather on crop yield. Time-series 250-m vegetation-index (VI) data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide valuable information for monitoring the spatiotemporal changes of corn growth across large geographic areas. The goal of this study is to evaluate the performance of a new crop phenology detection method, namely, two-step filtering (TSF), for revealing the spatiotemporal pattern of specific corn developmental stages (early vegetative: V2.5; silking: R1; dent: R5; mature: R6) over an eight-year period (2001-2008) across Iowa, Illinois, and Indiana using MODIS derived Wide Dynamic Range VI data. Weekly crop progress reports produced by the U.S. Department of Agriculture National Agricultural Statistics Service (NASS) were used to assess the accuracy of TSF-based estimates of corn developmental stages. The results showed that the corn developmental stages could be estimated with high accuracy (the root mean squared error ranged from 4.1 to 5.5 days, the determination coefficient ranged from 0.66 to 0.84, and the coefficient of variation ranged from 2.1% to 3.7%) based on NASS-derived statistics on an agricultural statistics district level. In particular, the annual changes in the spatiotemporal patterns of the estimated silking stage had a high level of agreement with those of the NASS-derived statistics. These results suggested that the TSF method could provide local-scale information of corn phenological stages, which had an advantage over the NASS-derived statistics particularly in terms of the spatial resolution.

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.

Agro-ecological interpretation of rice cropping systems in flood-prone areas using MODIS imagery

This study attempts a new approach using Moderate Resolution Imaging Spectroradiometer (MODIS) time-series imagery to evaluate the agro-ecological interpretation of rice-cropping systems in flood-prone areas. A series of wavelet-based methodologies were applied to reveal the dynamic relationships among annual flood inundation, rice phenology, and land-use change in the Vietnamese Mekong Delta (VMD). The rice-heading dates of multicropping areas were estimated by detecting the local maximal points in smoothed Enhanced Vegetation Index (EVI) profiles, using the Wavelet-based Filter for determining Crop Phenology (WFCP) and Wavelet-based Filter for evaluating the spatial distribution of Cropping Systems (WFCS) methods. The temporal information for annual flood intensity was determined for the six annual flood seasons over the period from 2000 to 2005 by the Waveletbased Filter for detecting spatio-temporal changes in the Flood Inundation (WFFI) method. Analysis using remote sensing techniques revealed an interaction between the regional environment and agricultural activity in the VMD. First, comparing the estimated heading date of the winterspring rice with the end date of flood inundation showed that the cropping season for the winter-spring rice in the flood-prone area fluctuates depending on the annual change in flood scale. This result implied that the onset of winter-spring rice is spatially and temporally linked to the variable flood-recession season, and hence the annual change in flood scale. Secondly, the field survey study of the yearly change in the rice-cropping system in the An Giang province from 2000 to 2006 showed that the triple rice-cropped area in the An Giang province expanded

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.

A modeling approach for assessing rice cropping cycle affected by flooding, salinity intrusion, and monsoon rains in the Mekong Delta, Vietnam

We developed a crop scheduling model for rice cultivation in the Vietnam Mekong Delta (VMD), focusing on the adaptive behavior of crop planning to various water resource constraints. In addition, we also examined the effects of environmental change on rice cultivation in the last decade. In the VMD, multiple rice cropping is practiced under a variety of adverse water conditions, including flooding, salinity intrusion, and irregular monsoon rains. These environmental changes influence the durations of growing seasons and the number of crops per year, resulting in changes in productivity. To validate the performance of the model, we compared model estimates for the heading date and changes in leaf area index at nine sites with estimates of these parameters derived from MODIS satellite time series data for the period 2002–2006. The root mean square errors of heading date between the modeled and satellite data in the upper, middle, and coastal regions of the delta were 17.6, 11.2, and 13.0 days, respectively. Based on the model, we examined case studies to assess the changes in cropping cycles and crop failures in the VMD due to extreme flooding in 2000 and salinity intrusion in 2004 by applying evaluation indices defined by available period for cultivation (APC) and safe margin for cropping (SMC) which is defined as the marginal time between APC and the period required for cultivation. Findings of case studies suggested that a small difference in the SMC of the cropping pattern is critical to the stability and productive capacity of the rice crop.

Estimating Rice Leaf Greenness (SPAD) Using Fixed-Point Continuous Observations of Visible Red and Near Infrared Narrow-Band Digital Images

Abstract A narrow-band dual camera system demonstrated a new close-range sensing technique to seasonally track trends in leaf greenness in rice paddies. A weatherproof digital imaging system for the visible red (RED, 620−650 nm) and near infrared band (NIR, 820−900 nm) was positioned 12 m above a 600-m2 rice field. During the 2009 and 2010 paddyrice seasons, the system automatically logged images at 10-min intervals throughout the day. Radiometric corrections for the images utilized solar irradiance sensors and prior calibration to calculate 0900-1500 JST daily-averaged reflectance factors (DARF). The DARF in RED (DARF-RED) and NIR (DARF-NIR) values were transformed to provide a daily-averaged normalizeddifference vegetation index (DA-NDVI). The DA-NDVI increased more rapidly in the vegetative growth period, and reached an asymptotic plateau earlier than the DARF-NIR. From transplanting to harvest, leaf greenness values (measured by the SPAD index) were measured for the central part of the uppermost leaves of targeted canopies weekly with a chlorophyll meter. We developed a leaf greenness index (LGI), the ratio of DA-NDVI to DARF-NIR, and a simple calculation method for area means to reduce the background effect. The modified area means of LGI followed the seasonal trend in SPAD value well; its patternwas inherently different from the patterns of any of the original three parameters: DARF-RED, DARF-NIR or DA-NDVI. Throughout the paddy seasons in the two years, a regression equation for estimating SPAD values using the LGI, daily solar radiation, the cosine of angle between the view and the meridian directions and the cosine of culmination solar zenith angle performed favorably (R2=0.815). The nitrogen concentration per dry plant hill (g kg-1) had a close relation to the SPAD values estimated using the equation.

A Multiband Polarimetric Imager for Field Crop Survey: ―Instrumentation and Preliminary Observations of Heading-stage Wheat Canopies―

Abstract A spectral and polarization image observation technique for detecting multiband polarimetric characteristics of reflected light from field-growing plants under daylight conditions was developed and the potential application of the method to in-situ assessments of wheat-leaf orientation at the heading stage was assessed. The developed digital imaging system corresponded to wavelength bands centered at 470, 550, and 647 nm, each with bandwidths of 10 nm. The instrument was fitted with a glass polarizer, which rotated from 0 to 360º in 15º steps, and polarized images of 1360 ×1024 pixels were captured at heading in wheat plots subjected to different fertilizer regimes at the jointing stage. Degree of polarization (DP) and mean brightness (MB) of the three bands were calculated from images of several pairs of top-dressed and non-top-dressed (non-dressed) plots, with a camera depression angle of 15–20º on two clear days. The relative azimuth angles between the view and insolation were approximately 135º (oblique front) and 180º (right in front), respectively. The mean DP for each plot area in the images varied between 0.3 and 1.4%. Although most of the top-dressed plots had significantly higher DPs than the non-dressed plots in the 550 nm band, few of the MB images in any band showed a clear difference between the top-dressed and non-dressed plots.

Daytime and Nighttime Field Spectral Imagery of Ripening Paddy Rice for Determining Leaf Greenness and 1000-Grain Weight

Abstract A spectral-image observation technique to measure the reflectance information of rice plant organs (instead of the overall canopy) under either daylight or artificial light at night was developed, and examined for its usefulness as a method for the in-situ assessment of leaf greenness and grain quality during the ripening period. Generally, conditions are less significant for nighttime measurement since cloudiness does not affect the nighttime observations, and the evening calm helps extend the practical observation hours. A digital imaging system corresponding to the wavelength range of 450 nm to 720 nm, at intervals of 10 nm, collected spectral reflectance images of ripening rice-paddy plots on three clear days in daylight and during the night, respectively. The imaging system observed the rice canopies illuminated by the sun during the daytime and with two 100-W xenon lamps at night on each day. The reflectance values observed at several points on the illuminated leaves and panicles were normalized using the mean and the standard deviation for each spectrum. The normalized reflectance (NR) spectra obtained in the day and night agreed well with each other for the same target organs. Exemplary estimation trials for leaf greenness (SPAD value) using the NR spectra, and correlation analyses between 1000-grain weight of harvested rice grains and the NR spectra indicated that nighttime measurement could substitute for daytime measurement.