Journal articles: 'Reflectance fields'

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Meka, Abhimitra, Christian Häne, Rohit Pandey, Michael Zollhöfer, Sean Fanello, Graham Fyffe, Adarsh Kowdle, et al. "Deep reflectance fields." ACM Transactions on Graphics 38, no. 4 (July 12, 2019): 1–12. http://dx.doi.org/10.1145/3306346.3323027.

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Fuchs, Martin, Volker Blanz, Hendrik P. A. Lensch, and Hans-Peter Seidel. "Adaptive sampling of reflectance fields." ACM Transactions on Graphics 26, no. 2 (June 2007): 10. http://dx.doi.org/10.1145/1243980.1243984.

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Weyrich, T., H. Pfister, and M. Gross. "Rendering Deformable Surface Reflectance Fields." IEEE Transactions on Visualization and Computer Graphics 11, no. 01 (January 2005): 48–58. http://dx.doi.org/10.1109/tvcg.2005.14.

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Fieuzal, Remy, Vincent Bustillo, David Collado, and Gerard Dedieu. "Potential of Sentinel-2 Images for Estimating of Soil Resistivity over Agricultural Fields." Proceedings 24, no. 1 (June 5, 2019): 18. http://dx.doi.org/10.3390/iecg2019-06219.

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The aim of this study is to assess the possibilities of the VNIR (Visible and Near InfraRed) and SWIR (Short Wavelength InfraRed) satellite data for estimating intra-plot patterns of soil electrical resistivity consistent with ground measurements. The methodology is based on optical reflectances that constitute the input variables of random forest, alone or in combination with parameters derived from a digital elevation model (DEM). Over a field located in southwestern France, the results show high level of accuracy for the 0–50 and 0–100 cm soil layers (with R² of 0.69 and 0.59, and a relative RMSE of 18% and 16%, respectively), the performances being lower for the 0–170 cm layer (R² of 0.39, relative RMSE of 20%). The combined use of optical reflectances with parameters derived from the DEM slightly improves the performances, whatever the considered layer. The influence of each reflectance on soil electrical resistivity estimates is finally analyzed, showing that the wavelengths acquired in the SWIR have a relative higher importance than VNIR reflectance.

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Fernández-Reche, Jesús. "Reflectance measurement in solar tower heliostats fields." Solar Energy 80, no. 7 (July 2006): 779–86. http://dx.doi.org/10.1016/j.solener.2005.06.006.

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Bréon, François-Marie. "Reflectance of Broken Cloud Fields: Simulation and Parameterization." Journal of the Atmospheric Sciences 49, no. 14 (July 1992): 1221–32. http://dx.doi.org/10.1175/1520-0469(1992)049<1221:robcfs>2.0.co;2.

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Phan, Thu Thi Thanh, Rikimaru Atsushi, Kenta Sakata, Kazuyoshi Takahashi, and Junki Abe. "Estimation of rice vegetation coverage from DVI of Landsat 7 and 8 data." Science and Technology Development Journal 19, no. 2 (June 30, 2016): 138–45. http://dx.doi.org/10.32508/stdj.v19i2.678.

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Monitoring of rice growth is a requirement for high quality rice production. In addtion to plant height, number stem and rice leaf color, vegetation coverage (VC) which represents for percentage of ground covered by rice plant is also considered as an important index to validate rice growth. Thus, the study is to estimate rice vegetation coverage from difference vegetation index (DVI) calculated from reflectance of near-infrared and red band of Landsat 7 and 8 images. The field observations of the reflectance and the VC were carried out in two paddy rice varieties in 2013. Paddy field reflectance was observed by spectrometer Ocean Optics SD2000. The photos of paddies were taken from the height of 1 m by a digital camera in order to calculate the VC. The reflectances of paddy field corresponding to red and near-infrared bands of Landsat 7 and 8 were calculated from the field observation data. Satellite reflectance was also converted from pixel value of Landsat images. According to the data analysis, VC rapidly increased in two fields and got saturation status (VC>90%) at 65 days after transplanting (DAT) in the early July. DVI was approximately 25% when VC saturated. Additionally, DVI had strong correlation with VC with high determination coefficient (r2 =0.9) when VC was less than 90%. Thus, VC were computed from DVI, calculated from reflectances of Landsat images, using a regression model of VC and DVI. From the result of comparison between the estimated and computed VC, the possibility of estimating VC from DVI calculated from Landsat reflectance is confirmed.

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Bravo, Cédric, Dimitrios Moshou, Jonathan West, Alastair McCartney, and Herman Ramon. "Early Disease Detection in Wheat Fields using Spectral Reflectance." Biosystems Engineering 84, no. 2 (February 2003): 137–45. http://dx.doi.org/10.1016/s1537-5110(02)00269-6.

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Laferrière, A., and H. Gaonac'h. "Multifractal properties of visible reflectance fields from basaltic volcanoes." Journal of Geophysical Research: Solid Earth 104, B3 (March 10, 1999): 5115–26. http://dx.doi.org/10.1029/1998jb900023.

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Fuchs, Martin, Hendrik P. A. Lensch, Volker Blanz, and Hans-Peter Seidel. "Superresolution Reflectance Fields: Synthesizing images for intermediate light directions." Computer Graphics Forum 26, no. 3 (September 2007): 447–56. http://dx.doi.org/10.1111/j.1467-8659.2007.01067.x.

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Zhuravleva, Tatiana, and Ilmir Nasrtdinov. "Simulation of Bidirectional Reflectance in Broken Clouds: From Individual Realization to Averaging over an Ensemble of Cloud Fields." Remote Sensing 10, no. 9 (August 22, 2018): 1342. http://dx.doi.org/10.3390/rs10091342.

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In this paper, we describe the results of simulating the bidirectional reflectance in three-dimensional (3D) cloud fields. For the calculations of reflectance, we use original statistical algorithms that ensure the effects of atmospheric sphericity and molecular absorption in the solar spectral range are accounted for. Cloud fields are simulated on the basis of a Poisson model of broken clouds; clouds are approximated by truncated paraboloids of rotation. The cloud heterogeneity effect on the averaging of reflection functions over an ensemble of cloud fields is estimated using numerical averaging of the stochastic radiative transfer equation, using a randomization. The simulation is performed for a mono-directional receiver with wavelength channels 0.55 and 2.15 µm, different realizations with small and moderate cloud fractions, and a set of sun-view geometries. With the appearance of an isolated cloud in the sky, the reflection function is determined by cloud presence/absence on the line of sight (LS), shading of LS by clouds/non-obscuration directed “toward the Sun,” and illumination of LS by cloud-reflected radiation. Passage to cloud fields gives rise to such additional factors as mutual shading and multiple scattering between clouds, which are mainly determined by cloud elements located near LS and directed “toward the Sun”. Strong fluctuations of reflectance as a function of the relative azimuth angle between sun and view directions in a specific realization are smoothed out after averaging over an ensemble of cloud fields. In interpreting the results of retrieving the cloud characteristics according to measurements of reflected radiation, it should be kept in mind that for fixed illumination conditions, the mean bidirectional reflectance may differ several-fold from bidirectional reflectance in a specific 3D cloud structure.

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Roskovensky, J. K., and K. N. Liou. "Simultaneous Determination of Aerosol and Thin Cirrus Optical Depths over Oceans from MODIS Data: Some Case Studies." Journal of the Atmospheric Sciences 63, no. 9 (September 1, 2006): 2307–23. http://dx.doi.org/10.1175/jas3747.1.

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Abstract The importance of separating thin cirrus and aerosols from satellite remote sensing to produce broader and more accurate fields for the determination of respective radiative forcings is highlighted. This has been accomplished through the development of a new methodology for retrieving both thin cirrus and aerosol optical depths simultaneously over oceans from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. This method employs a procedure to quantify and remove the thin cirrus contribution to the observed reflectance through a correlation of visible and 1.38-μm reflectances so that the aerosol signal can be extracted. Aerosol optical depths are then retrieved through comparisons with the simulated reflectances created a priori. Using the aerosol optical depth along with the specific viewing geometry and surface reflectance as pointers to locations in a lookup table of modeled reflectances, cirrus optical depth and an effective ice crystal size can be retrieved. An iterative scheme has been created that uses the retrieved effective cirrus ice crystal size to account for the effect that the particle size distribution has on the correlation of visible and 1.38-μm reflectance. Retrievals of both aerosol and thin cirrus optical depths over the Atmospheric Radiation Measurement (ARM) Tropical Western Pacific (TWP) site of Nauru performed on a limited number of cases have proven to be consistent with values determined from ground measurements. Also, comparisons with the MODIS aerosol retrievals over a broad area of ocean have highlighted the potential usefulness of this procedure in increasing the amount of potential aerosol information recovered and removing the ever-present thin cirrus contamination.

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Hashimoto, Naoyuki, Yuki Saito, Masayasu Maki, and Koki Homma. "Simulation of Reflectance and Vegetation Indices for Unmanned Aerial Vehicle (UAV) Monitoring of Paddy Fields." Remote Sensing 11, no. 18 (September 12, 2019): 2119. http://dx.doi.org/10.3390/rs11182119.

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Reflectance and vegetation indices obtained from aerial images are often used for monitoring crop fields. In recent years, unmanned aerial vehicles (UAVs) have become popular and aerial images have been collected under various solar radiation conditions. The value of observed reflectance and vegetation indices are considered to be affected by solar radiation conditions, which may lead to inaccurate estimations of crop growth. In this study, in order to evaluate the effect of solar radiation conditions on aerial images, canopy reflectance in paddy fields was simulated by a radiative transfer model, FLiES (Forest Light Environmental Simulator), for various solar radiation conditions and canopy structures. Several parameters including solar zenith angle, proportion of diffuse light for incident sunlight, plant height, coordinates of plants and leaf area density, were tested in FLiES. The simulation results showed that the solar zenith angle did not vary the canopy reflectance under the conditions of the proportion of diffuse light at 1.0, but the variation was greater at lower proportions of diffuse light. The difference in reflectance caused by solar radiation was 0.01 and 0.1 at the maximum for red and near-infrared bands, respectively. The simulation results also showed that the differences in reflectance affect vegetation indices (Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index 2 (EVI2)). The variation caused by solar radiation conditions was the least for NDVI and the greatest for SR. However, NDVI was saturated at the least leaf area index (LAI), whereas SR was only slightly saturated. EVI2 was intermediate between SR and NDVI, both in terms of variation and saturation. The simulated reflectance and vegetation indices were similar to those obtained from the aerial images collected in the farmers’ paddy fields. These results suggest that a large proportion of diffuse light (close to 1.0) or a middle range of solar zenith angle (45 to 65 degrees) may be desirable for UAV monitoring. However, to maintain flexibility of time and occasion for UAV monitoring, EVI2 should be used to evaluate crop growth, although calibration based on solar radiation conditions is recommended.

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Son, Changjin, and Heongkyu Ju. "Magnetic Control of Optical Reflectance from Metallic Thin Film Using Surface Plasmon Resonance and Faraday Rotation." Materials 14, no. 12 (June 17, 2021): 3354. http://dx.doi.org/10.3390/ma14123354.

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We demonstrate magnetic control of optical reflectance with no ferromagnetic material via combining the Faraday rotation and the surface plasmon resonance (SPR) in a Kretschman configuration under magnetic fields < 0.5 T. The SPR produces the polarization sensitive reflectance from the Au or Ag thin film coated on a N-BK7 prism in which the Faraday rotation occurs. The gold (Au) or silver (Ag) metal film as a plasmonic film somewhat acts as an incident angle-dependent reflection polarizer that can sensitively sense the polarization change induced by the Faraday rotation that occurs in a prism. We find that combination of Faraday rotation and the surface plasmon can induce a significant magnetic modulation of reflectance normalized with respect to that obtained with no magnetic fields at a specific incident angle of light. The magnetic control of optical reflectance presented may find an application in polarizer-free photonic devices with no ferromagnetic material for magneto-optical modulation.

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Fritsch, J., and C. Neumeyer. "Colour Constancy in Goldfish—The Role of Surround Reflectance." Perception 25, no. 1_suppl (August 1996): 52. http://dx.doi.org/10.1068/v96l0405.

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Simultaneous colour contrast as well as colour constancy have been shown quantitatively for the goldfish. In behavioural experiments we investigated colour constancy in goldfish for green and purple colours. Two fish were trained with food rewards to select one of ten test-fields in hues ranging, in small steps of saturation, from deep green, through grey, to deep purple. In the training situation the whole disk was illuminated by white light, whereas in the test situation it was changed to green and purple light, respectively. The role of surround reflectance was investigated by presenting the test fields either on a black or on a white surround. With a black surround (low reflectance) in purple illumination the fish chose test fields that were more green than the training field indicating imperfect colour constancy. With a white surround (high reflectance), however, the fish chose testfields that were more purple. This ‘overcompensation’ indicates that a white surround induces a hue complementary to that of the illumination. A similar phenomenon is known as the Helson — Judd effect in human colour vision. For green illumination the phenomenon was similar. The effect could be decreased by reducing the white surround to small white annuli around the test fields. A decrease was also achieved by separating the white surround from the test fields by black annuli. Perfect colour constancy could thus be obtained with a certain size of a white surround as well as with a certain size of separation. We therefore assume that lateral interactions play an important role in colour constancy.

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Montealegre, Juan Pablo Garcia, Charles Wortmann, Richard Ferguson, Timothy Shaver, and James Schepers. "Nitrogen Sidedress Directed by Corn Canopy Reflectance for Manured Fields." Agronomy Journal 111, no. 5 (September 2019): 2453–61. http://dx.doi.org/10.2134/agronj2019.02.0073.

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Gerrits, A. M., T. J. B. M. Janssen, A. Wittlin, N. Y. Chen, and P. J. M. van Bentum. "Far infrared reflectance of YBa2Cu3O7−δ at high magnetic fields." Physica C: Superconductivity 235-240 (December 1994): 1115–16. http://dx.doi.org/10.1016/0921-4534(94)91782-5.

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Dimyati, Muhammad, Kustiyo Kustiyo, and Ratih Dewanti Dimyati. "Paddy field classification with MODIS-terra multi-temporal image transformation using phenological approach in Java Island." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (April 1, 2019): 1346. http://dx.doi.org/10.11591/ijece.v9i2.pp1346-1358.

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This paper presents the paddy field classification model using the approach based on periodic plant life cycle events and how these elevations in climate as well as habitat factors, such as elevation. The data used are MODIS-Terra two tiles of H28v09 and H29v09 of 2016, consist of 46 series of 8-daily data, with 500 meter resolution in Java region. The paddy field classification method based on the phenological model is done by Maximum Likelihood on the transformed annual multi-temporal image of the reflectance data, index data, and the combination of reflectance and index data. The results of the study showed that, with the reference of the Paddy Field Map from the Ministry of Agriculture (MoA), the overall accuracies of the paddy field classification results using the combination of reflectance and index data provide the highest (85.4%) among the reflectance data (83.5%) and index data (81.7%). The accuracy levels were varied; these depend on the slope and the types of paddy fields. Paddy fields on the slopes of 0-2% could be well identified by MODIS-Terra data, whereas it was difficult to identify the paddy fields on the slope >2%. Rain-fed lowland paddy field type has a lower user accuracy than irrigated paddy fields. This study also performed correlation (r2) between the analysis results and the statistical data based on district and provincial boundaries were >0.85 and >0.99 respectively. These correlations were much higher than the previous study results, which reached 0.49-0.65 (hilly-flat areas of county-level), and 0.80-0.88 (hilly-flat areas of provincial level) for China, and reached 0.44 for Indonesia.

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Sisák, István. "Rapeseed crop damage by wildlife assessed from Landsat images." Review on Agriculture and Rural Development 8, no. 1-2 (May 21, 2019): 11–15. http://dx.doi.org/10.14232/rard.2019.1-2.11-15.

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Rapeseed is the fourth most important crop in Hungary regarding its cultivation area. Crop damage by deer and boar has been becoming strongly debated issue in the last few years. More exact clarification of damage was aimed at in this study with help of Landast images. Six rapeseed fields were investigated both in 2012 and 2013 in the administrative area of Várfölde, Bánokszentgyörgy, Bázakerettye and Borsfa (Zala County, Hungary). The total area in 2013 was 43 hectares. 100 % wildlife damage affected 3.9 hectares and 10 hectares were free from any damage. The total area in 2012 was 40 hectares in which 3.3 hectares were free from damage but neither fields suffered total damage. Yield map from 2017 of a 26 hectares field near to Gutorfölde and Szentkozmadombja was used to validate the space image based assessment method with real yield data. Landsat 7 images with acquisition dates of 2013.04.16., 2013.05.18. and 2013.06.03. were downloaded from the website of US Geological Service. All bands and NDVI index were investigated for all dates to establish best estimator for differences between damaged and not damaged fields. Band 5 (SWIR: 1.55-1.75 μm) in 16th of April proved to be the best. It was concluded with help of the reflectance data (zero damage: 96.4, complete damage:164.5, partial damage:124.7 on the average) that yield reduction was 41.5 % on areas with partial damage. There was no complete damage in 2012. However, reflectance data of not damaged fields were very close to each other in the two years (96.4 in 2013 and 89.9 in 2012 on the average) thus, it could be assumed that the same is true for reflectance data of completely damaged fields, so data from 2013 can be used for the comparison. Based on the data (zero damage: 89.9/2012, complete damage:164.5/2013, partial damage:118.4/2012 on the average) it was calculated, that one field suffered 38 % yield reduction, one hectare portion of another field suffered 23 % yield reduction, and other fields were not damaged significantly. Yield map from 2017 and Landsat 8 SWIR reflectance (Band 6: 1.566 – 1.651 μm) in 3rd of April have shown strong correlation (R2=0,634), which was a direct evidence that both yield and wildlife damage of rapeseed can be reliably assessed from Landsat SWIR reflectance data acquired in April.

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Diekmann, F. J., and E. Raschke. "On the sampling of airborne reflectance measurements above broken cloud fields." Archives for Meteorology, Geophysics, and Bioclimatology Series B 36, no. 2 (June 1986): 157–71. http://dx.doi.org/10.1007/bf02278326.

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Mecikalski, John R., Wayne M. MacKenzie, Marianne König, and Sam Muller. "Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part II: Use of Visible Reflectance." Journal of Applied Meteorology and Climatology 49, no. 12 (December 1, 2010): 2544–58. http://dx.doi.org/10.1175/2010jamc2480.1.

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Abstract This study is a companion research effort to “Part I,” which emphasized use of infrared data for understanding various aspects of growing convective clouds in the Meteosat Second Generation (MSG) satellite’s Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery. Reflectance and derived brightness variability (BV) fields from MSG SEVIRI are used here to understand relationships between cloud-top signatures and physical processes for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. This study uses daytime SEVIRI visible (VIS) and near-infrared (NIR) reflectances from 0.6 to 3.9 μm (3-km sampling distance), as well as high-resolution visible (1-km sampling distance) fields. Data from 123 CI events observed during the 2007 Convection and Orographically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, so to meet this study’s objectives. These data are those used in Part I. A total of 27 VIS–NIR and BV “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the fields that contain the most unique information for describing principally cloud-top glaciation, as well as the presence of vigorous updrafts. Time changes in 1.6- and 3.9-μm reflectances, as well as BV in advance of CI, are shown to contain the most unique information related to the formation and increase in size of ice hydrometeors. Several methods are proposed on how results from this analysis may be used to monitor growing convective clouds per MSG pixel or per cumulus cloud “object” over 1-h time frames.

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Rocha, M. G., L. R. Amaral, and C. F. M. Dencowski. "Early stage sugarcane biomass accumulation prediction by proximal sensing and crop parameters." Advances in Animal Biosciences 8, no. 2 (June 1, 2017): 216–19. http://dx.doi.org/10.1017/s2040470017000176.

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Due to the lack of reliable yield monitor for sugarcane, production factors which impact and limit stalk yield within fields are not well-known. Thus, this study aims to evaluate whether canopy sensor technology is able to identify sugarcane biomass variability and whether obtaining other agronomic variable data can assist on biomass quantification. For that, forty targeted plots were allocated within two sugarcane-producing fields and data consisted on manual biometric evaluation, aboveground biomass measurement and canopy reflectance. As an ongoing experiment, only two evaluations were addressed (~0.3 and 0.5 m stalk height). On the earliest stage, canopy sensor readings were correlated to sugarcane biomass and their sensitivity to biomass variability was high. Further, data collected on the first evaluation was efficient in predicting biomass amount after 30 days. On the second, canopy sensor readings effectiveness to predict biomass was reduced. These findings suggest that crop canopy reflectance sensing is a useful approach to investigate sugarcane biomass spatial-variability within fields on early stages.

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Workneh, F., D. C. Jones, and C. M. Rush. "Quantifying Wheat Yield Across the Field as a Function of Wheat Streak Mosaic Intensity: A State Space Approach." Phytopathology® 99, no. 4 (April 2009): 432–40. http://dx.doi.org/10.1094/phyto-99-4-0432.

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Wheat streak mosaic virus (WSMV), vectored by the wheat curl mite Aceria tosichella, is one of the major limiting factors in wheat production in the Texas Panhandle. The mites are blown by wind into wheat fields from nearby volunteer wheat fields or fields supporting vegetation which harbor virulent mites. Consequently, gradients of wheat streak severity are often observed stretching from the edges of wheat fields into the center or beyond. To describe the magnitude of the spatial relationships between grain yield and wheat streak intensity across the field, studies were conducted in 2006 and 2007 in three infected fields. Wheat streak severity was quantified with reflectance measurements (remote sensing) at 555-nm wave length using a hand-held radiometer. Measurements were taken in several equally spaced 1 m2 locations along a total of eight transects and grain yield was assessed from a 0.8 m2 area of each location. State space analysis was used to describe the relationships in which yield data and reflectance values were used as dependent and explanatory variables, respectively. A structural time series model was formulated as a state space model where the unobserved components were modeled explicitly. In the analysis the state of yield at current location (d) was related to the state of wheat streak intensity either at current locations (d) or lagged locations with autoregressive values of the first order (d–1) or greater. There were significant cross-correlations between yield and wheat streak intensity up to distances of 150 m (P ≤ 0.05). Grain yield at the current position was significantly correlated with reflectance values at the same location and/or at lagged locations. The spatial aspects of the yield-reflectance relationships were best described by state space models with stochastic trends without slopes or deterministic trends with or without slopes. The models correctly predicted almost all of the observed yield values as a function of wheat streak intensity across the field within the 95% confidence interval. Results obtained in this study suggest that state space methodology can be a powerful tool in the study of plant disease spread as a function of other variables.

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Susaki, J., K. Hara, JongGeol Park, Y. Yasuda, K. Kajiwara, and Y. Honda. "Validation of temporal BRDFs of paddy fields estimated from MODIS reflectance data." IEEE Transactions on Geoscience and Remote Sensing 42, no. 6 (June 2004): 1262–70. http://dx.doi.org/10.1109/tgrs.2004.826798.

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Macke, A., R. Dlhopolsky, J. Mueller, R. Stuhlmann, and E. Raschke. "A study of bidirectional reflectance functions for broken cloud fields over ocean." Advances in Space Research 16, no. 10 (January 1995): 55–58. http://dx.doi.org/10.1016/0273-1177(95)00380-w.

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Bloem, Elke, Heike Gerighausen, Xijuan Chen, and Ewald Schnug. "The Potential of Spectral Measurements for Identifying Glyphosate Application to Agricultural Fields." Agronomy 10, no. 9 (September 17, 2020): 1409. http://dx.doi.org/10.3390/agronomy10091409.

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Glyphosate is one of the most widely used non-selective systemic herbicides, but nowadays its application is controversially discussed. Optical remote sensing techniques might provide a sufficient tool for monitoring glyphosate use. In order to investigate the potential of this technology, a laboratory experiment was set-up using pots with rolled grass sods. Glyphosate-treated plants were compared to drought-stressed and control plants. All pots were frequently measured using a field spectrometer and a hyperspectral-imaging camera. Plant samples were analysed for photosynthetic pigments, polyphenols and dry matter content. Eight selected vegetation indices were calculated from the spectral measurements. The results show that photosynthetic pigments were sensitive to differentiate between control and glyphosate treated plants already 2 days after application. From the vegetation indices, the normalized difference lignin index (NDLI) responded most sensitively followed by indices referring to photosynthetic pigments, namely, the carotenoid reflectance index (CRI-1) and the photochemical reflectance index (PRI). It can be concluded that spectral vegetation indices are, in principal, a suitable proxy to non-destructively monitor glyphosate application on agricultural fields. Further research is needed to verify its applicability under field conditions. An operational monitoring is, however, currently limited by the requirements for temporal and spectral resolution of the satellite sensors.

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Hively, W. Dean, Gregory W. McCarty, James B. Reeves, Megan W. Lang, Robert A. Oesterling, and Stephen R. Delwiche. "Use of Airborne Hyperspectral Imagery to Map Soil Properties in Tilled Agricultural Fields." Applied and Environmental Soil Science 2011 (2011): 1–13. http://dx.doi.org/10.1155/2011/358193.

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Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm,∼10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n=315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted withR2>0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a3×3low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

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Bronson, K. F., T. A. Wheeler, C. M. Brown, R. K. Taylor, P. C. Scharf, and E. M. Barnes. "Use of Nitrogen Calibration Ramps and Canopy Reflectance on Farmers' Irrigated Cotton Fields." Soil Science Society of America Journal 76, no. 3 (May 2012): 1060–67. http://dx.doi.org/10.2136/sssaj2011.0344.

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Brucato, Alberto, and Lucio Rizzuti. "Simplified Modeling of Radiant Fields in Heterogeneous Photoreactors. 1. Case of Zero Reflectance." Industrial & Engineering Chemistry Research 36, no. 11 (November 1997): 4740–47. http://dx.doi.org/10.1021/ie960259j.

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Tollerud, Heather J., Jesslyn F. Brown, and Thomas R. Loveland. "Investigating the Effects of Land Use and Land Cover on the Relationship between Moisture and Reflectance Using Landsat Time Series." Remote Sensing 12, no. 12 (June 13, 2020): 1919. http://dx.doi.org/10.3390/rs12121919.

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To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly ( p < 0.01 ) higher visible reflectance during dry periods than during wet, occurring in nearly all regional, temporal, and LULC categories investigated. In grassland, the relationship is especially strong; there is an average reflectance increase of more than a third between very wet and very dry conditions (red band), and ∼99% of pixels have a significant relationship. In cropland, the effective moisture-reflectance relationship is more variable, suggesting that management decisions are an important factor in cropland-reflectance relationships.

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Lefcourt, Alan, Mark Siemens, and Paula Rivadeneira. "Optical Parameters for Using Visible-Wavelength Reflectance or Fluorescence Imaging to Detect Bird Excrements in Produce Fields." Applied Sciences 9, no. 4 (February 19, 2019): 715. http://dx.doi.org/10.3390/app9040715.

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Consumption of produce contaminated with pathogens of fecal origin is the most common source of food borne illnesses. Current practice is to visually survey fields for evidence of fecal contamination, and to exclude problematic areas from harvest. Bird excrement is known to contain human pathogens, and is often not detectable in produce fields using current survey methods. The goal of this project was to identify parameters for optical detection of bird excrements to support development of instruments to be used to supplement existing visual surveys. Under daylight ambient conditions, results suggested that reflectance imaging at around 500–530 nm or 610–640 nm could be used to detect excrements from the three bird species tested. Images were acquired using ad hoc camera parameters; however, normalizing intensities for individual images at 525 nm and using a fixed detection threshold allowed detection of 100% of bird excrements with no false positives against the background that consisted of local soil and fresh romaine and spinach leaves. Similar results were obtained using fluorescence imaging. Fluorescent imaging was accomplished in a darkened room using 405-nm illumination. The largest consistent differences in intensity responses between excrements and the brightest non-excrement object in the background matrix occurred at around 550 nm. Results suggested that using reflectance or fluorescence imaging for detection of bird excrements could be a valuable tool for reducing risks of consuming contaminated produce. One possibility would be to incorporate appropriate reflectance imaging capabilities in drones under the control of the individuals currently conducting field surveys.

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SARKAR, ADITI, ARNAB GANGOPADHYAY, and A. SARKAR. "LEFT-HANDED MAXWELLIAN BEHAVIOR OF NATURAL MICA." Modern Physics Letters B 25, no. 30 (November 21, 2011): 2323–33. http://dx.doi.org/10.1142/s0217984911027534.

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In this work, meta-material like behavior of natural Mica are studied. This work makes an attempt to analyze the left-handed Maxwellian (LHM) properties of Mica. The investigations carried out on natural Mica specimen are optical reflectance, optical absorbance and DC current–voltage-characteristics (CVC). Optical reflectance of Mica sheet with plane polarized monochromatic light shows distinct difference with conventional theoretical results. The DC CVC also measured with complete electromagnetic shielding. There exists a clear difference in DC characteristic for presence and absence of stray electromagnetic fields. The X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and ultraviolet-visible spectroscopy (UV-VIS) analysis are also carried out for further analysis. The results obtained from the optical reflectance characteristics using polarized light indicate LHM behavior as may be found in a meta-material. Micro-structural and electrical analysis shows that it is a nano-structured layered material.

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Rowan, Lawrence C., Carmen Anton‐Pacheco, David W. Brickey, Marguerite J. Kingston, Alba Payas, Norma Vergo, and James K. Crowley. "Digital classification of contact metamorphic rocks in Extremadura, Spain, using Landsat thematic mapper data." GEOPHYSICS 52, no. 7 (July 1987): 885–97. http://dx.doi.org/10.1190/1.1442359.

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Landsat Thematic Mapper (TM) images of an extensively cultivated part of Extremadura, Spain, have been used to distinguish soil developed on contact metamorphic rocks in aureoles around late Hercynian granitic plutons from soil formed on stratigraphically equivalent Late Proterozoic slate and metagraywacke that has been regionally metamorphosed to the greenschist facies. Reflectance spectra of contact metamorphic soil have lower reflectance, especially in the 1.6 μm wavelength region, and weaker Al‐OH, Mg‐OH, and [Formula: see text] absorption features than do spectra of the slate‐metagraywacke soil. These spectral differences are attributed to highly absorbing carbonaceous material in the contact metamorphic soil that was subjected to high temperatures during emplacement of the plutons. These spectral reflectance differences are evident in a density‐sliced TM band 5 image, in color‐ratio composite images that incorporate TM 4 : 5, 4 : 3, and 3 : 1 ratios, and in principal‐component composite images. Digital classification of the numerous tilled, vegetation‐free fields was used to map the contact metamorphic soil in an August, 1984, TM scene of the Caceres study area. First, TM 4 : 3 was used to identify these fields. Then ranges of TM 5 and TM 3 : 1 values were determined for selected tilled fields within and outside the contact aureoles. Field evaluation of a classification map based on TM 5 plus TM 3 : 1 shows more extensive aureoles than published geologic maps and few misclassified areas. Similar results were achieved using TM 4 : 5 instead of TM 5. This approach was subsequently used to map two linear zones of contact metamorphic rocks in the San Nicolas mine area where only two small exposures of granite have been documented. Landsat Multispectral Scanner (MSS) images can also be used to map contact aureoles in the study areas, but extensive field evaluation is required because of more frequent misclassification.

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Breure, T. S., A. E. Milne, R. Webster, S. M. Haefele, J. A. Hannam, S. Moreno-Rojas, and R. Corstanje. "Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management." Precision Agriculture 22, no. 1 (August 10, 2020): 226–48. http://dx.doi.org/10.1007/s11119-020-09739-x.

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AbstractHow well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Topsoil from two fields was sampled and analysed for various nutrients, particle-size distribution and organic carbon concentration. Crop measurements (lettuce diameter) were derived from aerial-imagery. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than PLSR that used the soil spectra as predictor variables. Predictions from LMMs were more precise than those from the PLSR using soil spectra. All model predictions improved when the effects of variety were considered. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop.

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Morel, André, Kenneth J. Voss, and Bernard Gentili. "Bidirectional reflectance of oceanic waters: A comparison of modeled and measured upward radiance fields." Journal of Geophysical Research 100, no. C7 (1995): 13143. http://dx.doi.org/10.1029/95jc00531.

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Red'ko, R. "Modification of the optical reflectance spectra of epitaxial gallium arsenide by weak magnetic fields." Journal of Applied Physics 112, no. 7 (October 2012): 073513. http://dx.doi.org/10.1063/1.4756996.

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Bley, Sebastian, Hartwig Deneke, and Fabian Senf. "Meteosat-Based Characterization of the Spatiotemporal Evolution of Warm Convective Cloud Fields over Central Europe." Journal of Applied Meteorology and Climatology 55, no. 10 (October 2016): 2181–95. http://dx.doi.org/10.1175/jamc-d-15-0335.1.

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AbstractThe spatiotemporal evolution of warm convective cloud fields over central Europe is investigated on the basis of 30 cases using observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the geostationary Meteosat platforms. Cloud fields are tracked in successive satellite images using cloud motion vectors. The time-lagged autocorrelation is calculated for spectral reflectance and cloud property fields using boxes of 16 × 16 pixels and adopting both Lagrangian and Eulerian perspectives. The 0.6-μm reflectance, cloud optical depth, and water path show a similar characteristic Lagrangian decorrelation time of about 30 min. In contrast, significantly lower decorrelation times are observed for the cloud effective radius and droplet density. It is shown that the Eulerian decorrelation time can be decomposed into an advective component and a convective component using the spatial autocorrelation function. In an Eulerian frame cloud fields generally decorrelate faster than in a Lagrangian one. The Eulerian decorrelation time contains contributions from the spatial decorrelation of the cloud field advected by the horizontal wind. A typical spatial decorrelation length of 7 km is observed, which suggests that sampling of SEVIRI observations is better in the temporal domain than in the spatial domain when investigating small-scale convective clouds. An along-track time series of box-averaged cloud liquid water path is derived and compared with the time series that would be measured at a fixed location. Supported by previous results, it is argued that this makes it possible to discriminate between local changes such as condensation and evaporation on the one hand and advective changes on the other hand.

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Susaki, J., H. Sato, A. Kuriki, K. Kajiwara, and Y. Honda. "ESTIMATION OF LAND SURFACE ALBEDO FROM GCOM-C/SGLI SURFACE REFLECTANCE." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021 (June 17, 2021): 227–34. http://dx.doi.org/10.5194/isprs-annals-v-3-2021-227-2021.

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Abstract. This paper examines algorithms for estimating terrestrial albedo from the products of the Global Change Observation Mission – Climate (GCOM-C) / Second-generation Global Imager (SGLI), which was launched in December 2017 by the Japan Aerospace Exploration Agency. We selected two algorithms: one based on a bidirectional reflectance distribution function (BRDF) model and one based on multi-regression models. The former determines kernel-driven BRDF model parameters from multiple sets of reflectance and estimates the land surface albedo from those parameters. The latter estimates the land surface albedo from a single set of reflectance with multi-regression models. The multi-regression models are derived for an arbitrary geometry from datasets of simulated albedo and multi-angular reflectance. In experiments using in situ multi-temporal data for barren land, deciduous broadleaf forests, and paddy fields, the albedos estimated by the BRDF-based and multi-regression-based algorithms achieve reasonable root-mean-square errors. However, the latter algorithm requires information about the land cover of the pixel of interest, and the variance of its estimated albedo is sensitive to the observation geometry. We therefore conclude that the BRDF-based algorithm is more robust and can be applied to SGLI operational albedo products for various applications, including climate-change research.

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Che’Ya, Nik Norasma, Ernest Dunwoody, and Madan Gupta. "Assessment of Weed Classification Using Hyperspectral Reflectance and Optimal Multispectral UAV Imagery." Agronomy 11, no. 7 (July 19, 2021): 1435. http://dx.doi.org/10.3390/agronomy11071435.

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Weeds compete with crops and are hard to differentiate and identify due to their similarities in color, shape, and size. In this study, the weed species present in sorghum (sorghum bicolor (L.) Moench) fields, such as amaranth (Amaranthus macrocarpus), pigweed (Portulaca oleracea), mallow weed (Malva sp.), nutgrass (Cyperus rotundus), liver seed grass (Urochoa panicoides), and Bellive (Ipomea plebeian), were discriminated using hyperspectral data and were detected and analyzed using multispectral images. Discriminant analysis (DA) was used to identify the most significant spectral bands in order to discriminate weeds from sorghum using hyperspectral data. The results demonstrated good separation accuracy for Amaranthus macrocarpus, Urochoa panicoides, Malva sp., Cyperus rotundus, and Sorghum bicolor (L.) Moench at 440, 560, 680, 710, 720, and 850 nm. Later, the multispectral images of these six bands were collected to detect weeds in the sorghum crop fields using object-based image analysis (OBIA). The results showed that the differences between sorghum and weed species were detectable using the six selected bands, with data collected using an unmanned aerial vehicle. Here, the highest spatial resolution had the highest accuracy for weed detection. It was concluded that each weed was successfully discriminated using hyperspectral data and was detectable using multispectral data with higher spatial resolution.

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Markelin, L., E. Honkavaara, R. Näsi, K. Nurminen, and T. Hakala. "Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3 (August 11, 2014): 205–10. http://dx.doi.org/10.5194/isprsarchives-xl-3-205-2014.

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Remote sensing based on unmanned airborne vehicles (UAVs) is a rapidly developing field of technology. UAVs enable accurate, flexible, low-cost and multiangular measurements of 3D geometric, radiometric, and temporal properties of land and vegetation using various sensors. In this paper we present a geometric processing chain for multiangular measurement system that is designed for measuring object directional reflectance characteristics in a wavelength range of 400–900 nm. The technique is based on a novel, lightweight spectral camera designed for UAV use. The multiangular measurement is conducted by collecting vertical and oblique area-format spectral images. End products of the geometric processing are image exterior orientations, 3D point clouds and digital surface models (DSM). This data is needed for the radiometric processing chain that produces reflectance image mosaics and multiangular bidirectional reflectance factor (BRF) observations. The geometric processing workflow consists of the following three steps: (1) determining approximate image orientations using Visual Structure from Motion (VisualSFM) software, (2) calculating improved orientations and sensor calibration using a method based on self-calibrating bundle block adjustment (standard photogrammetric software) (this step is optional), and finally (3) creating dense 3D point clouds and DSMs using Photogrammetric Surface Reconstruction from Imagery (SURE) software that is based on semi-global-matching algorithm and it is capable of providing a point density corresponding to the pixel size of the image. We have tested the geometric processing workflow over various targets, including test fields, agricultural fields, lakes and complex 3D structures like forests.

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Barros, Pedro P. S., Inana X. Schutze, Fernando H. Iost Filho, Pedro T. Yamamoto, Peterson R. Fiorio, and José A. M. Demattê. "Monitoring Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) Infestation in Soybean by Proximal Sensing." Insects 12, no. 1 (January 9, 2021): 47. http://dx.doi.org/10.3390/insects12010047.

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Although monitoring insect pest populations in the fields is essential in crop management, it is still a laborious and sometimes ineffective process. Imprecise decision-making in an integrated pest management program may lead to ineffective control in infested areas or the excessive use of insecticides. In addition, high infestation levels may diminish the photosynthetic activity of soybean, reducing their development and yield. Therefore, we proposed that levels of infested soybean areas could be identified and classified in a field using hyperspectral proximal sensing. Thus, the goals of this study were to investigate and discriminate the reflectance characteristics of soybean non-infested and infested with Bemisia tabaci using hyperspectral sensing data. Therefore, cages were placed over soybean plants in a commercial field and artificial whitefly infestations were created. Later, samples of infested and non-infested soybean leaves were collected and transported to the laboratory to obtain the hyperspectral curves. The results allowed us to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance. In conclusion, these results show that hyperspectral sensing can potentially be used to monitor whitefly populations in soybean fields.

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Barros, Pedro P. S., Inana X. Schutze, Fernando H. Iost Filho, Pedro T. Yamamoto, Peterson R. Fiorio, and José A. M. Demattê. "Monitoring Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) Infestation in Soybean by Proximal Sensing." Insects 12, no. 1 (January 9, 2021): 47. http://dx.doi.org/10.3390/insects12010047.

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Although monitoring insect pest populations in the fields is essential in crop management, it is still a laborious and sometimes ineffective process. Imprecise decision-making in an integrated pest management program may lead to ineffective control in infested areas or the excessive use of insecticides. In addition, high infestation levels may diminish the photosynthetic activity of soybean, reducing their development and yield. Therefore, we proposed that levels of infested soybean areas could be identified and classified in a field using hyperspectral proximal sensing. Thus, the goals of this study were to investigate and discriminate the reflectance characteristics of soybean non-infested and infested with Bemisia tabaci using hyperspectral sensing data. Therefore, cages were placed over soybean plants in a commercial field and artificial whitefly infestations were created. Later, samples of infested and non-infested soybean leaves were collected and transported to the laboratory to obtain the hyperspectral curves. The results allowed us to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance. In conclusion, these results show that hyperspectral sensing can potentially be used to monitor whitefly populations in soybean fields.

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Hively, W., Brian Lamb, Craig Daughtry, Jacob Shermeyer, Gregory McCarty, and Miguel Quemada. "Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices." Remote Sensing 10, no. 10 (October 18, 2018): 1657. http://dx.doi.org/10.3390/rs10101657.

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Crop residues serve many important functions in agricultural conservation including preserving soil moisture, building soil organic carbon, and preventing erosion. Percent crop residue cover on a field surface reflects the outcome of tillage intensity and crop management practices. Previous studies using proximal hyperspectral remote sensing have demonstrated accurate measurement of percent residue cover using residue indices that characterize cellulose and lignin absorption features found between 2100 nm and 2300 nm in the shortwave infrared (SWIR) region of the electromagnetic spectrum. The 2014 launch of the WorldView-3 (WV3) satellite has now provided a space-borne platform for the collection of narrow band SWIR reflectance imagery capable of measuring these cellulose and lignin absorption features. In this study, WorldView-3 SWIR imagery (14 May 2015) was acquired over farmland on the Eastern Shore of Chesapeake Bay (Maryland, USA), was converted to surface reflectance, and eight different SWIR reflectance indices were calculated. On-farm photographic sampling was used to measure percent residue cover at a total of 174 locations in 10 agricultural fields, ranging from plow-till to continuous no-till management, and these in situ measurements were used to develop percent residue cover prediction models from the SWIR indices using both polynomial and linear least squares regressions. Analysis was limited to agricultural fields with minimal green vegetation (Normalized Difference Vegetation Index < 0.3) due to expected interference of vegetation with the SWIR indices. In the resulting residue prediction models, spectrally narrow residue indices including the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Lignin Cellulose Absorption Index (LCA) were determined to be more accurate than spectrally broad Landsat-compatible indices such as the Normalized Difference Tillage Index (NDTI), as determined by respective R2 values of 0.94, 0.92, and 0.84 and respective residual mean squared errors (RMSE) of 7.15, 8.40, and 12.00. Additionally, SINDRI and LCA were more resistant to interference from low levels of green vegetation. The model with the highest correlation (2nd order polynomial SINDRI, R2 = 0.94) was used to convert the SWIR imagery into a map of crop residue cover for non-vegetated agricultural fields throughout the imagery extent, describing the distribution of tillage intensity within the farm landscape. WorldView-3 satellite imagery provides spectrally narrow SWIR reflectance measurements that show utility for a robust mapping of crop residue cover.

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Ahn, H. Y., D. Y. Shin, J. S. Kim, D. C. Seo, and C. U. Choi. "Absolute Radiometric Calibration of KOMPSAT-3A." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 271–74. http://dx.doi.org/10.5194/isprsarchives-xli-b1-271-2016.

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This paper presents a vicarious radiometric calibration of the Korea Multi-Purpose Satellite-3A (KOMPSAT-3A) performed by the Korea Aerospace Research Institute (KARI) and the Pukyong National University Remote Sensing Group (PKNU RSG) in 2015.The primary stages of this study are summarized as follows: (1) A field campaign to determine radiometric calibrated target fields was undertaken in Mongolia and South Korea. Surface reflectance data obtained in the campaign were input to a radiative transfer code that predicted at-sensor radiance. Through this process, equations and parameters were derived for the KOMPSAT-3A sensor to enable the conversion of calibrated DN to physical units, such as at-sensor radiance or TOA reflectance. (2) To validate the absolute calibration coefficients for the KOMPSAT-3A sensor, we performed a radiometric validation with a comparison of KOMPSAT-3A and Landsat-8 TOA reflectance using one of the six PICS (Libya 4). Correlations between top-of-atmosphere (TOA) radiances and the spectral band responses of the KOMPSAT-3A sensors at the Zuunmod, Mongolia and Goheung, South Korea sites were significant for multispectral bands. The average difference in TOA reflectance between KOMPSAT-3A and Landsat-8 image over the Libya 4, Libya site in the red-green-blue (RGB) region was under 3%, whereas in the NIR band, the TOA reflectance of KOMPSAT-3A was lower than the that of Landsat-8 due to the difference in the band passes of two sensors. The KOMPSAT-3Aensor includes a band pass near 940 nm that can be strongly absorbed by water vapor and therefore displayed low reflectance. Toovercome this, we need to undertake a detailed analysis using rescale methods, such as the spectral bandwidth adjustment factor.

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Ahn, H. Y., D. Y. Shin, J. S. Kim, D. C. Seo, and C. U. Choi. "Absolute Radiometric Calibration of KOMPSAT-3A." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 271–74. http://dx.doi.org/10.5194/isprs-archives-xli-b1-271-2016.

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This paper presents a vicarious radiometric calibration of the Korea Multi-Purpose Satellite-3A (KOMPSAT-3A) performed by the Korea Aerospace Research Institute (KARI) and the Pukyong National University Remote Sensing Group (PKNU RSG) in 2015.The primary stages of this study are summarized as follows: (1) A field campaign to determine radiometric calibrated target fields was undertaken in Mongolia and South Korea. Surface reflectance data obtained in the campaign were input to a radiative transfer code that predicted at-sensor radiance. Through this process, equations and parameters were derived for the KOMPSAT-3A sensor to enable the conversion of calibrated DN to physical units, such as at-sensor radiance or TOA reflectance. (2) To validate the absolute calibration coefficients for the KOMPSAT-3A sensor, we performed a radiometric validation with a comparison of KOMPSAT-3A and Landsat-8 TOA reflectance using one of the six PICS (Libya 4). Correlations between top-of-atmosphere (TOA) radiances and the spectral band responses of the KOMPSAT-3A sensors at the Zuunmod, Mongolia and Goheung, South Korea sites were significant for multispectral bands. The average difference in TOA reflectance between KOMPSAT-3A and Landsat-8 image over the Libya 4, Libya site in the red-green-blue (RGB) region was under 3%, whereas in the NIR band, the TOA reflectance of KOMPSAT-3A was lower than the that of Landsat-8 due to the difference in the band passes of two sensors. The KOMPSAT-3Aensor includes a band pass near 940 nm that can be strongly absorbed by water vapor and therefore displayed low reflectance. Toovercome this, we need to undertake a detailed analysis using rescale methods, such as the spectral bandwidth adjustment factor.

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Workneh, F., S. O’Shaughnessy, S. Evett, and C. M. Rush. "Relationships Between Early Wheat Streak Mosaic Severity Levels and Grain Yield: Implications for Management Decisions." Plant Disease 101, no. 9 (September 2017): 1621–26. http://dx.doi.org/10.1094/pdis-02-17-0176-re.

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Wheat streak mosaic (WSM) caused by Wheat streak mosaic virus, which is transmitted by the wheat curl mite (Aceria tosichella), is a major yield-limiting disease in the Texas High Plains. In addition to its impact on grain production, the disease reduces water-use efficiency by affecting root development. Because of the declining Ogallala Aquifer water level, water conservation has become one of the major pressing issues in the region. Thus, questions are often raised as to whether it is worthwhile to irrigate infected fields in light of the water conservation issues, associated energy costs, and current wheat prices. To address some of these questions, field experiments were conducted in 2013 and 2016 at two separate locations to determine whether grain yield could be predicted from disease severity levels, assessed early in the spring, for potential use as a decision tool for crop management, including irrigation. In both fields, disease severity assessments started in April, using a handheld hyperspectral radiometer with which reflectance measurements were taken weekly in multiple plots in arbitrarily selected locations across the fields. The relationship between WSM severity levels and grain yield for the different assessment dates were determined by fitting reflectance and yield values into the logistic regression function. The model predicted yield levels with r2 values ranging from 0.67 to 0.85 (P < 0.0001), indicating that the impact of WSM on grain yield could be fairly well predicted from early assessments of WSM severity levels. As the disease is normally progressive over time, this type of information will be useful for making management decisions of whether to continue irrigating infected fields, especially if combined with an economic threshold for WSM severity levels.

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Zhang, Ying, Ping-Xiang Hu, and Jay Gao. "A reflectance spectra-based approach to mapping salt fields using PCA-fused Landsat TM data." Advances in Space Research 47, no. 9 (May 2011): 1490–96. http://dx.doi.org/10.1016/j.asr.2010.09.027.

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Papadopoulos, Antonis V., and Dionissios P. Kalivas. "Assessing Soil and Crop Characteristics at Sub-Field Level Using Unmanned Aerial System and Geospatial Analysis." Sustainability 13, no. 5 (March 6, 2021): 2855. http://dx.doi.org/10.3390/su13052855.

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Practicing agriculture is a multiparametric and for this reason demanding task. It involves the management of many factors and thorough strategic planning in a highly variable and uncertain environment. Crop production is a function of agricultural practices as applied in natural resources, such as soil and plants. When referring to conventional agriculture, variability in these resources is neglected, as any field is treated homogenously. On the other hand, site-specific crop management, which was promoted through the advance of technologies, regarding collecting and analyzing data and applying agricultural decisions at a sub-field level, considers field spatial and temporal variations. Localizing inputs in a field rationalizes agricultural waste management and offers promising perspectives towards a circular economy. In this context, two cotton fields in central Greece were selected for this study. During the growing period, reflectance data were acquired, before planting at the end of April, and 100 days after planting at the end of July, with a commercial unmanned aerial system (UAS). The fields were grid sampled for soil (clay content, pH, calcium carbonate percentage, organic matter, total nitrogen, and electrical conductivity) and plant properties (total nitrogen, potassium, iron, copper, and zinc) determination. All data were manipulated through geographical information systems (GIS) and further participated in principal component analysis (PCA) application. PCA revealed important relations and groupings between soil reflectance and organic matter, carbonates, and clay content in both fields (72 to 87% of the total variance in the initial parameters was explained by the extracted components). However, in plant data, the resulting components accounted for less variability in initial data (62 to 72%). PCA resulting scores were introduced in the Fuzzy c-means clustering algorithm, which categorized sub-areas of the fields into two discrete zones per field. Zoning, in the case of soil properties, was accompanied with the statistically important (p < 0.01) discrimination of the mean values (except for total nitrogen and pH), implicating a promising zonal management scheme. The zone delineation process regarding plant properties yielded areas that did not share statistically significant variations, except for the mean values of iron concentration (p < 0.01). According to the results, spatial variations were revealed across the fields, mostly in soil properties, which can be directly monitored through aerial reflectance data. The applied methodology can be used in extension services or by agronomists for producing fertilizer application maps. Further, when integrated with a broader spatial decision support system, it can be used by policy makers for adapting circular economy strategies in crop production.

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Várnai, T., A. Marshak, and W. Yang. "Multi-satellite aerosol observations in the vicinity of clouds." Atmospheric Chemistry and Physics Discussions 12, no. 12 (December 13, 2012): 32039–61. http://dx.doi.org/10.5194/acpd-12-32039-2012.

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Abstract. Improved characterization of aerosol properties in the vicinity of clouds is important for better understanding two critical aspects of climate: aerosol-cloud interactions and the direct radiative effect of aerosols. Satellite measurements have provided important insights into aerosol properties near clouds, but also suggested that the observations can be affected by 3-D radiative processes and instrument blurring not considered in current data interpretation methods. This study examines systematic changes in particle properties and radiation fields that influence satellite measurements of aerosols in the vicinity of clouds. For this, the paper presents a statistical analysis of a yearlong global dataset of co-located MODIS and CALIOP observations and theoretical simulations. The results reveal that CALIOP-observed aerosol particle size and optical thickness, and MODIS-observed solar reflectance increase systematically in a wide transition zone around clouds. It is estimated that near-cloud changes in particle populations – including both aerosols and undetected cloud particles – are responsible for roughly two thirds of the observed increase in 0.55 μm MODIS reflectance. The results also indicate that 3-D radiative processes significantly contribute to near-cloud reflectance enhancements, while instrument blurring does not.

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Zhao, Shulei, Parrish Clawson Brady, Meng Gao, Robert Ian Etheredge, George W. Kattawar, and Molly E. Cummings. "Broadband and polarization reflectors in the lookdown, Selene vomer." Journal of The Royal Society Interface 12, no. 104 (March 2015): 20141390. http://dx.doi.org/10.1098/rsif.2014.1390.

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Abstract:

Predator evasion in the open ocean is difficult because there are no objects to hide behind. The silvery surface of fish plays an important role in open water camouflage. Various models have been proposed to account for the broadband reflectance by the fish skin that involve one-dimensional variations in the arrangement of guanine crystal reflectors, yet the three-dimensional organization of these guanine platelets have not been well characterized. Here, we report the three-dimensional organization and the optical properties of integumentary guanine platelets in a silvery marine fish, the lookdown ( Selene vomer ). Our structural analysis and computational modelling show that stacks of guanine platelets with random yaw angles in the fish skin produce broadband reflectance via colour mixing. Optical axes of the guanine platelets and the collagen layer are aligned closely and provide bulk birefringence properties that influence the polarization reflectance by the skin. These data demonstrate how the lookdown preserves or alters polarization states at different incident polarization angles. These optical properties resulted from the organization of these guanine platelets and the collagen layer may have implications for open ocean camouflage in varying light fields.

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Journal articles on the topic 'Reflectance fields'

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