Yoshio Inoue 교수

Present climate and socioeconomic issues would threaten the global food and environmental security. Smart farming (SF) based on advances in sensing, robotic, and information and communication technologies is a promising approach to support the efficient, sustainable, and profitable crop production. This paper discusses the background needs for SF and the role of remote sensing. Recent advances in remote sensing technology (platforms, sensors, algorithms) for diagnostic information of crops and s

Canopy chlorophyll content (CCC) is an essential ecophysiological variable for photosynthetic functioning. Remote sensing of CCC is vital for a wide range of ecological and agricultural applications. The objectives of this study were to explore simple and robust algorithms for spectral assessment of CCC. Hyperspectral datasets for six vegetation types (rice, wheat, corn, soybean, sugar beet and natural grass) acquired in four locations (Japan, France, Italy and USA) were analysed. To explore the

Visible and near- and mid- infrared spectral measurements were made on intact and detached leaves of four crop species (Corn, Peanut, Soybean and Wheat) using two spectroradiometers under three different conditions : field measurements under artificial light and solar radiation conditions with and without an integrating sphere, and laboratory measurements with an integrating sphere. In the regions of 1350-1480, 1800-2000, and 2350-2500 nm wavelenghts, measurements of spectral reflectance (ρ) of

Spectral reflectance of differentially-managed rice canopies was measured over an entire growing season and analyzed with special attention to linking remotely sensed information with a simple growth model. The fraction of absorbed photosynthetically active radiation (fAPAR), which is often used as a key variable in simple process models, was well correlated writh spectral vegetation indices (VI). VIs, such as NDVI and SAVI, were derived from the ratio of reflectance at two wavelengths (R660 nm

Information on the ecological and physiological status of crops is essential for growth diagnostics and yield prediction. Within-field or between-field spatial information is required, especially with the recent trend toward precision agriculture, which seeks the efficient use of agrochemicals, water, and energy. The study of carbon and nitrogen cycles as well as environmental management on local and regional scales requires assessment of the spatial variability of biophysical and ecophysiologic

Photosynthetic light response curves and reflectance spectra (380–2500 nm) were measured for soybean (Glycine max L. Merr.) leaves with a range of chlorophyll concentrations at various soil water contents. Regression lines for the relationship between the photosynthetic light use efficiency (LUEp) and photochemical reflectance index (PRI) under different soil water content θ almost all passed through a common point (PRI, LUEp) = (−0.04, 0), so that the LUEp could be expressed simply as LUEp = kA

An AOTF (Acousto-Optic Tunable Filter)-based spectral imager was developed for hyperspectral measurement of plant reflectance in the field. A hyperspectral image cube for the spectral region between 450-900 nm could be acquired at 3 to 5 nm resolution intervals within a few seconds. The system was light and compact, and both the spectral wavelengths and intervals were programmable with PC control. Wavelengths could be tuned rapidly, either sequentially or randomly. The hyperspectral image cube f

The objective of this study was to explore unique capabilities of X-band satellite synthetic aperture radar (SAR) sensors for the assessment of rice growth and yield. X-band SAR images were acquired by COSMO-SkyMed at spotlight mode during the maturing stage. Detailed plant biophysical and morphological measurements were made on the ground concurrently with the satellite SAR observations. The backscattering coefficients (σ0) of rice canopies and water surfaces were consistent over two years. The

A blimp-based remote sensing system was developed for monitoring land surface variables from low altitudes. The blimp was a helium-filled envelope 23m long with a maximum diameter of 7m. The blimp was designed to cruise at a maximum speed of 40kmh-1 at altitudes between 30 and 400m, under radio control, with a payload of approximately 100kg. The radio-controlled data acquisition system consisted of four monochromatic CCD video cameras with interference filters. The ability of the blimp to hover