Relationship between X-band backscattering coefficients from high-resolution satellite SAR and biophysical variables in paddy rice

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 σ⁰ values in rice canopies were higher than the water surfaces by 8 dB. Although the σ⁰ was poorly correlated with the volume-related canopy variables such as leaf area index (LAI), the X-band σ⁰ was best correlated with the panicle biomass among all biophysical variables. This is the first evidence suggesting the potential of satellite SAR image for the direct assessment of rice yield at regional scales.     

The potential of Sentinel-2 data for estimating biophysical variables in a boreal forest: a simulation study

In this study we use ground reference data from 962 forest plots to demonstrate the potential of Sentinel-2 (S2) bands in estimating canopy biophysical properties in boreal forests in Finland. We simulated canopy bidirectional reflectance factors (BRFs) using the PARAS model, which applies photon recollision probability. Results showed that the highest correlation between simulated S2 BRFs and fraction of absorbed photosynthetically active radiation (fPAR) was for the band combination band 7/band 9 (wavelengths 773–793 nm and 935–955 nm, respectively) (the coefficient of determination (R²) was 0.93). For effective leaf area index (LAI_e) the best band combination was band 8/band 4 (wavelengths 785–900 nm and 650–680 nm, respectively) (R² = 0.93). Based on this study, the above-ground biomass (AGB) and S2 band combinations did not show strong relationships (R² = 0.24). The new inverted red-edge chlorophyll index (IRECI) and Sentinel-2 red-edge position – index (S2REP) showed moderate relationships with fPAR (R² = 0.61 and R² = 0.45, respectively) and LAI_e (R² = 0.56 and R² = 0.30, respectively). This study demonstrated the potential of the S2 data to estimate canopy biophysical properties.     

Estimating potato leaf chlorophyll content using ratio vegetation indices

Chlorophyll content at leaf level is an important variable because of its crucial role in photosynthesis and in understanding plant functioning. In this study, we tested the hypothesis that the ratio of a vegetation index (VI) for estimating canopy chlorophyll content (CCC) and one for estimating leaf area index (LAI) can be used to derive chlorophyll content at the leaf level. This hypothesis for estimating chlorophyll content at the leaf level was tested using simulations with the PROSAIL radiative transfer model and field spectroradiometry measurements in five consecutive years (2010–2014) for potato crops on experimental fields. During the growing season, in-situ field measurements of LAI and leaf chlorophyll content (LCC) were performed. Results showed that good estimates of LCC were feasible using ratio vegetation indices (VIs). This was tested at satellite level using RapidEye images. This letter presents a proof of concept for estimating LCC using Sentinel-2 data. Results confirm the importance of the red-edge bands for agricultural applications, but also showed that indices using the red-edge bands may be replaced by indices using green bands. It should now be tested with real Sentinel-2 data whether its spectral bands at 10 m spatial resolution are suitable for estimating LCC, avoiding the need for red-edge bands that only are available at 20 m.     

Quantification of rice canopy nitrogen balance index with digital imagery from unmanned aerial vehicle

With the rise of large-scale crop plantation in China, inexpensive but efficient remote-sensing measures for predicting the nitrogen status of crops are needed for optimal fertilizer management. In this research, a conventional digital camera with a charge coupled device was integrated into an unmanned aerial vehicle (UAV) to capture digital aerial images of paddy rice (Oryza sativa L.) at an altitude of 50 m. The fluorescence emissions of the rice leaves under light excitation were used by Multiplex® to non-destructively assess the chlorophyll and polyphenol content. The nitrogen balance index (NBI) of the rice leaves, known as the ratio of chlorophyll to polyphenols, was used to accurately determine canopy nitrogen concentrations. The dark green colour index (DGCI) available from the aerial images was used to assess the nitrogen concentrations in the field. It was found that DGCI values predicted the nitrogen concentrations and NBI with R² (coefficient of determination) = 0.672 (p < 0.001) and R² = 0.711 (p < 0.001), respectively. The results indicated that aerial photography from UAV had the ability to assess plant nitrogen status in the field in large-scale crop plantations.     

Algorithms for estimating green leaf area index in C3 and C4 crops for MODIS,Landsat TM/ETM+, MERIS,Sentinel MSI/OLCI,and Venµs sensors

This study developed a set of algorithms for satellite mapping of green leaf area index (LAI) in C3 and C4 crops. In situ hyperspectral reflectance and green LAI data, collected across eight years (2001–2008) at three AmeriFlux sites in Nebraska USA over irrigated and rain-fed maize and soybean, were used for algorithm development. The hyperspectral reflectance was resampled to simulate the spectral bands of sensors aboard operational satellites (Aqua and Terra: MODIS, Landsat: TM/ETM+), a legacy satellite (Envisat: MERIS), and future satellites (Sentinel-2, Sentinel-3, and Venµs). Among 15 vegetation indices (VIs) examined, five VIs – wide dynamic range vegetation index (WDRVI), green WDRVI, red edge WDRVI, and green and red edge chlorophyll indices – had a minimal noise equivalent for estimating maize and soybean green LAI ranging from 0 to 6.5 m² m^?2. The algorithms were validated using MODIS, TM/ETM+, and MERIS satellite data. The root mean square error of green LAI prediction in both crops from all sensors examined in this study ranged from 0.73 to 0.95 m² m^?2 and coefficient of variation ranged between 17.0 and 29.3%. The algorithms using the red edge bands of MERIS and future space systems Sentinel-2, Sentinel-3, and Venµs allowed accurate green LAI estimation over areas containing maize and soybean with no re-parameterization.     

CT of the pancreas: comparison of image quality and pancreatic duct depiction among model-based iterative,adaptive statistical iterative,and filtered back projection reconstruction techniques

The purpose of this study is to compare CT images of the pancreas reconstructed with model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASiR), and filtered back projection (FBP) techniques for image quality and pancreatic duct (PD) depiction. Data from 40 patients with contrast-enhanced abdominal CT [CTDIvol: 10.3 ± 3.0 (mGy)] during the late arterial phase were reconstructed with FBP, 40% ASiR–FBP blending, and MBIR. Two radiologists assessed the depiction of the main PD, image noise, and overall image quality using 5-point scale independently. Objective CT value and noise were measured in the pancreatic parenchyma, and the contrast-to-noise ratio (CNR) of the PD was calculated. The Friedman test and post-hoc multiple comparisons with Bonferroni test following one-way ANOVA were used for qualitative and quantitative assessment, respectively. For the subjective assessment, scores for MBIR were significantly higher than those for FBP and 40% ASiR (all P < 0.001). No significant differences in CT values of the pancreatic parenchyma were noted among FBP, 40% ASiR, and MBIR images (P > 0.05). Objective image noise was significantly lower and CNR of the PD was higher with MBIR than with FBP and 40% ASiR (all P < 0.05). Our results suggest that pancreatic CT images reconstructed with MBIR have lower image noise, better image quality, and higher conspicuity and CNR of the PD compared with FBP and ASiR.     

Groundnut Meal and Carrot Fortified Pasta: Optimization of Ingredients Level Using RSM

The present study was undertaken to optimize the level of groundnut meal, carrot juice and refined wheat flour for the development of pasta using response surface methodology. Different experimental combinations were designed using box-benken design of experiments considering 10–20 g groundnut meal, 14–30 mL carrot juice and 80–90 g refined wheat flour. Pasta samples with higher level of groundnut meal and carrot juice showed higher antioxidant activity and overall sensory acceptability. The samples with higher groundnut meal resulted in higher protein content. Pasta samples with higher amount of carrot juice showed higher rehydration ratio and lesser cooking time with low solid loss in cooking water. The food materials were optimized to obtain the best experimental combination for development of groundnut meal and carrot fortified pasta. Different levels of groundnut meal, carrot juice and wheat flour significantly affected the colour as well as cooking quality of pasta. The protein and antioxidant activity of pasta were increased with increasing level of groundnut meal and carrot juice in the sample. Optimized groundnut meal and carrot fortified pasta consisted of 17.64 % groundnut meal and 82.36 % wheat flour with 27.45 mL per 100 g formulation of carrot juice showing overall desirability as 0.849. This pasta sample required 3.49 min to cook with 4.71 % solid loss and rehydration ratio as 4.15 having 17.32 % protein content, 10.63 % antioxidant activity, 301.32 mg/100 g total phenols and overall sensory acceptability score as 8.7.     

New spectral metrics for mangrove forest identification

This study proposed three spectral metrics, namely spectral match degree (SMD), normalized difference mangrove index (NDMI) and shortwave infrared absorption depth (SIAD), to enhance the separability between mangrove forests and terrestrial vegetation in remote sensing imagery. The Landsat 8 OLI image of an interest area in Beilunhekou National Nature Reserve was used to test the spectral metrics. The derived spectral metrics and raw band reflectance data were classified using a support vector machine classifier. Mangrove forest maps were then identified from the classified images. Identification accuracies were compared and evaluated by determining the user’s accuracy (UA), producer’s accuracy (PA), overall accuracy (OA) and by conducting McNemar’s test. Results showed that the use of spectral metrics (UA = 85%, PA = 94%, OA = 95%) outperformed the use of raw band reflectance data (UA = 72%, PA = 82%, OA = 90%). McNemar’s test confirmed that the spectral metrics were significantly better than the raw band reflectance data (Z = 4.63, p < 0.05). Therefore, the proposed spectral metrics could improve the accuracy of mangrove forest identification.     

Fertilization and Crop Residue Addition Impacts on Yield Sustainability Under a Rainfed Maize–Wheat System in the Himalayas

A 9-year old experiment was conducted at Almora, India to study the effects of mineral sources of nutrients in different combinations with or without crop residue or farmyard manure (FYM) addition on crop productivity under a rainfed maize–wheat system. Plots under 100 % nitrogen–phosphorus–potassium (NPK) + FYM had maximum mean maize (5.00 Mg ha^?1) and wheat (2.61 Mg ha^?1) yields that were generally significantly higher than yields observed under other treatments. Total soil organic carbon (C) increased in all treatments except with mineral fertilization and control plots. While NPK treated plots had significantly higher benefit:cost ratio than NPK + FYM plots, organic C content in the NPK treated plots decreased over the initial soil and FYM treated plots had better soil physical and chemical properties than NPK only. Thus, the study showed that although the combined 100 % NPK and FYM application had higher productivity of the maize–wheat system, the same is as remunerative as 50 % NPK + FYM, if the cost of FYM was considered. However, depending upon the resource availability, farmers can also apply Kudzu, maize stalk and wheat straw annually along with adjusted dose of NPK to a crop and full dose of NPK to the other crop as the alternate options.     

Influence of skin type and wavelength on light wave reflectance

Purpose: A new application of photoplethysmography (PPG) has emerged recently to provide the possibility of heart rate monitoring without a telemetric chest strap. The aim of this study was to determine if a new device could detect pulsation over a broad range of skin types, and what light wavelength would be most suitable for detecting the signals. A light emitting diode-based PPG system was used to detect changes in pulsatile blood flow on 23 apparently healthy individuals (11 male and 12 female, 20–59 years old) of varying skin types classified according to a questionnaire in combination with digital photographs with a skin type chart. Four different light wavelengths (470, 520, 630, and 880 nm) were tested. Normalized modulation level is calculated as the AC/DC component ratio and represents the change in flow over the underlying constant state of flow or perfusion. Results: In the resting condition, green light wavelength (520 nm) displayed greater modulation (p < 0.001) than all the other wavelengths analyzed regardless of skin types. Type V (dark brown) skin type was significantly lower in modulation than all other skin types. In the exercise condition, both blue (470 nm) and green (520 nm) light wavelengths displayed greater signal-to-noise ratios than red (630 nm) or infrared (880 nm) light wavelengths (p < 0.001). Conclusions: We concluded that a PPG-based device can detect pulsation across all skin types and that a greater resolution was obtained using a green light wavelength at rest and a green or blue light wavelength during exercise.     

The feasibility of sub-millisievert coronary CT angiography with low tube voltage,prospective ECG gating,and a knowledge-based iterative model reconstruction algorithm

We evaluated the feasibility of sub-millisievert (mSv) coronary CT angiography (CCTA) using low tube voltage, prospective ECG gating, and a knowledge-based iterative model reconstruction algorithm. Twenty-four non-obese healthy subjects (M:F 13:11; mean age 50.2 ± 7.8 years) were enrolled. Three sets of CT images were reconstructed using three different reconstruction methods: filtered back projection (FBP), iterative reconstruction (IR), and knowledge-based iterative model reconstruction (IMR). The scanning parameters were as follows: step-and-shoot axial scanning, 80 kVp, and 200 mAs. On the three sets of CT images, the attenuation and image noise values were measured at the aortic root. The signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were calculated at the proximal right coronary artery and the left main coronary artery. The qualitative image quality of the CCTA with IMR was assessed using a 4-point grading scale (grade 1, poor; grade 4, excellent). The mean radiation dose of the CCTA was 0.89 ± 0.09 mSv. The attenuation values with IMR were not different from those of other reconstruction methods. The image noise with IMR was significantly lower than with IR and FBP. Compared to FBP, the noise reduction rate of IMR was 69 %. The SNR and CNR of CCTA with IMR were significantly higher than with FBP or IR. On the qualitative analysis with IMR, all included segments were diagnostic (grades 2, 3, and 4), and the mean image quality score was 3.6 ± 0.6. In conclusion, CCTA with low tube voltage, prospective ECG gating, and an IMR algorithm might be a feasible method that allows for sub-millisievert radiation doses and good image quality when used with non-obese subjects.     

Automated aorta segmentation in low-dose chest CT images

Purpose

   Abnormalities of aortic surface and aortic diameter can be related to cardiovascular disease and aortic aneurysm. Computer-based aortic segmentation and measurement may aid physicians in related disease diagnosis. This paper presents a fully automated algorithm for aorta segmentation in low-dose non-contrast CT images.

Methods

   The original non-contrast CT scan images as well as their pre-computed anatomy label maps are used to locate the aorta and identify its surface. First a seed point is located inside the aortic lumen. Then, a cylindrical model is progressively fitted to the 3D image space to track the aorta centerline. Finally, the aortic surface is located based on image intensity information. This algorithm has been trained and tested on 359 low-dose non-contrast CT images from VIA-ELCAP and LIDC public image databases. Twenty images were used for training to obtain the optimal set of parameters, while the remaining images were used for testing. The segmentation result has been evaluated both qualitatively and quantitatively. Sixty representative testing images were used to establish a partial ground truth by manual marking on several axial image slices.

Results

   Compared to ground truth marking, the segmentation result had a mean Dice Similarity Coefficient of 0.933 (maximum 0.963 and minimum 0.907). The average boundary distance between manual segmentation and automatic segmentation was 1.39 mm with a maximum of 1.79 mm and a minimum of 0.83 mm.

Conclusion

   Both qualitative and quantitative evaluations have shown that the presented algorithm is able to accurately segment the aorta in low-dose non-contrast CT images.     

Growth Behaviour of Transgenic Cotton with Peanut Intercropping System Using Modified Fertilization Technique

Global cotton cultivation, particularly in India, was transformed after the introduction of transgenic cotton hybrids. Realizing the increasing acreage under transgenic cotton in future, the aim of this study was to evaluate growth behaviour of transgenic cotton with peanut intercropping system and sole cotton crop by using 25–50 % substitution of recommended dose of nitrogen (RDN) of cotton through farm yard manure (FYM) along with 100 % RDN through urea and control (0N). Plant growth parameters like plant height, leaf area index, leaf chlorophyll, and N contents were measured at various growth stages of cotton for correlating them with seed cotton yield. Peanut intercropping in cotton did not significantly affect cotton growth parameters and indices except leaf area duration (P = 0.04) as compared with sole crop of cotton. On the other hand, cotton growth parameters with substitution of 25 % RDN of cotton through FYM were higher than or similar to its corresponding 100 % RDN of cotton through urea only. The results showed that there were highly significant (P < 0.01) linear relationships between leaf N and chlorophyll contents at each growth stage, and with plant height and leaf area index during cotton growth. Seed cotton yield was also highly (P < 0.01) correlated with plant growth parameters like plant height, leaf area index, chlorophyll content and leaf N content at various growth stages of cotton. The present study explains plant growth behaviour of transgenic cotton with peanut intercropping system and integrated use of manure and fertilizer for simultaneously enhancing lint and oilseed production.     

Adenosine-stress dynamic myocardial perfusion imaging using 128-slice dual-source CT in patients with normal body mass indices: effect of tube voltage,tube current,and iodine concentration on image quality and radiation dose

The aim of this study was to evaluate the image quality and radiation dose in adenosine-stress dynamic myocardial CT perfusion (CTP) imaging using different tube voltages, tube current settings, and contrast materials containing different iodine concentrations in subjects with normal body mass indices (BMI). We included 92 patients (BMI range, 18.5–24.8) who underwent dynamic CTP for the evaluation of coronary artery disease using a 128-slice dual-source computed tomography. The protocols employed the following dynamic scan parameters: protocol I with 100 kV, fixed tube current (FTC), and medium-concentration contrast material (MC, 350 mg iodine/mL); protocol II with 100 kV, automatic tube current modulation (ATCM), and MC; protocol III with 100 kV, ATCM, and high-concentration contrast material (HC, 400 mg iodine/mL); protocol IV with 80 kV, adopted FTC, and HC. Subjective image quality on a 1–3 point scale and objective image quality with respect to the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were assessed. Protocol IV showed higher CNR and SNR than the other protocols (P < 0.01), while the CNR and SNR values did not significantly differ among the other three protocols. There was no significant difference in subjective image quality among the protocols. The radiation dose in protocol IV was the lowest among the protocols (P < 0.01), while protocol IV resulted in a 54 % overall reduction in mean effective radiation dose compared with protocol I. Dynamic myocardial CTP performed at 80 kV with adapted FTC provided high CNR and SNR while preserving subjective image quality and reducing radiation exposure.     

Readout-segmented echo-planar imaging in diffusion-weighted imaging of the kidney: comparison with single-shot echo-planar imaging in image quality

Objective

The purpose of this study was to compare the image quality of readout-segmented echo-planar imaging (RS-EPI) and that of standard single-shot echo-planar imaging (SS-EPI) in the kidney in a rat model.

Materials and methods

Twelve Wistar rats undergoing MRI examinations were imaged with two diffusion-weighted (DW) imaging protocols: a standard SS-EPI and a new RS-EPI protocol, both with a 1.0 × 1.0 × 3.0 mm voxel. The two groups of diffusion-weighted images were independently scored on geometric distortion, image blurring, signal dropout, and the overall image quality by two radiologists. Signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) were measured on both sequences. Inter-rater agreement (IRA) was evaluated by Fleiss kappa (κ) and inter-class correlation coefficient (ICC) statistics. Comparisons of image qualities were made by Wilcoxon signed-rank test and paired-sample t test.

Results

Both RS-EPI and SS-EPI had good IRAs in scoring image qualities (κ = 0.607–0.833) and measuring renal ADCs (ICC = 0.828–0.945). Compared to SS-EPI, RS-EPI produced less geometric distortion (median score 1.5 versus 2.5, p < 0.0001), less image blurring (1.75 versus 2.0, p = 0.0003), less signal dropout (1.0 versus 3.0, p = 0.0001), and a lower score in overall image artifacts (4.25 versus 7.25; p < 0.0001). RS-EPI had higher SNR of renal DW images than SS-EPI (p < 0.001). The intra-variability of ADCs in cortex, outer medulla, and inner medulla ranged from 9.6 % to 11.1 % (Pearson correlation coefficient ρ = 0.675–0.729; p < 0.001) between the two protocols.

Conclusion

We showed that for DWI of the kidney at 1.0 × 1.0 × 3.0 mm³ voxel sizes, the new protocol provided better image quality than standard SS-EPI protocol.

     

Dual-energy CT of pancreatic adenocarcinoma: reproducibility of primary tumor measurements and assessment of tumor conspicuity and margin sharpness

Purpose

To determine the inter- and intra-reader agreement of size, conspicuity, and margin sharpness of pancreatic adenocarcinoma on monochromatic, polychromatic, and iodine map dual-energy CT (DECT) images.

Methods

Retrospective review of DECT images from 61 patients with untreated pancreatic adenocarcinoma was performed by three radiologists independently. Pancreatic parenchymal phase images were generated as 50 and 70 keV, 140 kVp quality control (QC), and iodine map images. These were analyzed in a blinded randomized order during four reading sessions separated by 5–7 days. For each image set, readers recorded the longest axial and perpendicular primary tumor dimensions, and qualitatively scored tumor conspicuity and edge sharpness on 5-point scales. Linear mixed model was used to estimate and compare tumor measurements, tumor conspicuity, and tumor edge sharpness scores between readers and image sets. Kappa statistics were used to determine inter-observer agreement for tumor conspicuity and edge sharpness.

Results

The range of tumor measures (mean of longest dimension ± standard deviation) was 3.18 ± 1.41 to 3.83 ± 1.57 cm. Reproducibility of tumor measurements was very high with mild variability (s ² = 0.01–0.10) between readers for the different image sets. Inter-observer agreement values for tumor conspicuity (κ = 0.01–0.17) and edge sharpness (κ = 0.12–0.25) were low for all image sets, although two of three readers scored tumor conspicuity and edge sharpness higher on monochromatic and iodine map DECT images than on 140 kVp QC images (p < 0.05).

Conclusions

Pancreatic adenocarcinoma measurements were highly reproducible on DECT images, and subjective reader preference trended toward monochromatic and iodine images rather than polychromatic images.

     

Quantitative Analysis of Contrast-Enhanced Ultrasound Imaging in Invasive Breast Cancer: A Novel Technique to Obtain Histopathologic Information of Microvessel Density

We examined whether enhancement area ratios obtained by the new bubble detection method correlate with histologic microvessel density in invasive breast cancer. Forty consecutive patients with invasive breast cancer lesions underwent contrast-enhanced ultrasound. The ratio of enhanced area to manually segmented tumor area (enhancement area ratio) was obtained with the new method at peak and delayed phases (50–54, 55–59, 60–64 and 65–69 s). We also analyzed time–intensity curves to obtain peak intensity and area under curve. Enhancement area ratios in both peak and delayed phases (50–54, 55–59, 60–64 and 65–69 s) were significantly correlated with microvessel density (r = 0.57, 0.62, 0.68, 0.61 and 0.58; p = 0.0001, <0.0001, <.0001, <.0001 and 0.0001, respectively). In time–intensity curve analysis, peak intensity was significantly correlated (r = 0.43, p = 0.0073), whereas area under the curve was not (r = 0.29, p = 0.0769). Enhancement area ratios obtained by the new method were correlated with microvessel density in invasive breast cancer.     

Agronomic Performance and Nutrient Accumulation Behaviour in Groundnut-Cluster Bean Cropping System as Influenced by Irrigation Water Salinity

Varied levels of salinity in irrigation water remained a serious issue to shrink agricultural productivity in Saurashtra region of Gujarat. Groundnut, being a prominent crop in this zone, suffered to quite an extent due to induced salinity. In the present study, the authors have simulated a field condition where four different saline water of EC_iw of 0.5, 2.0, 4.0, 6.0 dS m^?1 were used for irrigation in groundnut (rainy/kharif)–cluster bean (summer) rotation. Both the crops were assessed by their respective growth and yield traits. A marked decrease was observed in seedling emergence, plant height, root length and pod yield at highest salinity, EC_iw 6.0 dS m^?1 whereas the same trend was noticed for plant height, dry weight of plant and final plant stand for cluster bean in the next season. However, pod yield of both the crops did not decrease up to EC_iw 2.0 dS m^?1. The ionic imbalance in different plant parts is another major impact of salinity. Na showed enhanced accumulation in plant parts where groundnut roots accumulated 42.0 and 75.4 % higher than shoots and kernels, respectively at highest EC_iw; while other nutrients (N, P, Ca, K) showed a declining effect with increasing salinity.     

Super-Optimal NPK Along with Foliar Iron Application Influences Bioavailability of Iron and Zinc of Wheat

Deficiency of wheat grain iron (Fe) and zinc (Zn) is common nutritional problem in the developing countries and thus increasing their concentrations is a major challenge. Field experiments were conducted to investigate the effect of different levels of fertilizer nitrogen, phosphorus, potassium (100–200 % NPK) and foliar Fe application (3 % FeSO₄.7H₂O at 40, 60, and 75 days after sowing) on improving Fe and Zn concentrations in grain and molar ratio of phosphorus/iron (P/Fe) and phosphorus/zinc (P/Zn). Data obtained during the two year (2010–2011 and 2011–2012) field experiment reveals that foliar Fe spray along with fertilizer NPK significantly increased the grain Fe concentration by 6–15 %; whereas a sharp decrease in the grain Zn concentration under super optimal fertilization is attributed to the depressive effect of excessive phosphorus in the treatments. Molar ratio of P/Fe in wheat grains signifies the increased bioavailability of Fe in wheat grains but P/Zn increase under super-optimal NPK application calls for P management to correct the reduced level of Zn in wheat grains.     

Radiometric characterization and validation for the KOMPSAT-3 sensor

A radiometric characterization of the Korea Multi-Purpose Satellite (KOMPSAT) Series multispectral imagery was performed by the Korea Aerospace Research Institute (KARI) and the Pukyong National University Remote Sensing Group (PKNU RSG). This paper presents a vicarious radiometric calibration performed by KARI and PKNU RSG in 2012 and 2014. Correlations between top-of-atmosphere (TOA) radiances and the spectral band responses of the KOMPSAT-3 sensors at Zuunmod, Mongolia and Goheung, South Korea, were significant for multispectral bands. KOMPSAT-3 calibration coefficients for all bands estimated in 2012 continued to agree well with calibration coefficients estimated in 2014 (within 1.5%). As a result of this study, KARI will update and publish the KOMPSAT-3 multispectral radiometric calibration coefficients as official values. The average difference in TOA reflectance between KOMPSAT-3 and Landsat-8 images over the Libya 4, Libya and Railroad Valley Playa, USA, in the red–green–blue region was under 3%, whereas in the near-infrared band, the TOA reflectance of KOMPSAT-3 was lower than that of Landsat-8 due to the difference in the bandwidths of two sensors. The KOMPSAT-3 sensor includes a bandwidth near 940 nm that can be strongly absorbed by water vapour and therefore displayed low reflectance.