Implications of whole-disc DSCOVR EPIC spectral observations for estimating Earth's spectral reflectivity based on low-earth-orbiting and geostationary observations

Earth’s reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)’s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)’s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth’s reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth’s reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth’s reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between −0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between −10% and 23%.The NASA/GSFC DSCOVR project is funded by NASA Earth Science Division. W. Song, G. Yan, and X. Mu were also supported by the key program of National Natural Science Foundation of China (NSFC; Grant No. 41331171). This research was conducted and completed during a 13-month research stay of the lead author in the Department of Earth and Environment, Boston University as a joint Ph.D. student, which was supported by the Chinese Scholarship Council (201606040098). DSCOVR EPIC L1B data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. The authors would like to thank the editor who handled this paper and the two anonymous reviewers for providing helpful and constructive comments and suggestions that significantly helped us improve the quality of this paper. (NASA Earth Science Division; 41331171 - key program of National Natural Science Foundation of China (NSFC); 201606040098 - Chinese Scholarship Council)Accepted manuscrip

Optimal Design of Plant Canopy Based on Light Interception: A Case Study With Loquat

Canopy architecture determines the light distribution and light interception in the canopy. Reasonable shaping and pruning can optimize tree structure; maximize the utilization of land, space and light energy; and lay the foundation for achieving early fruiting, high yield, health and longevity. Due to the complexity of loquat canopy architecture and the multi-year period of tree growth, the variables needed for experiments in canopy type training are hardly accessible through field measurements. In this paper, we concentrated on exploring the relationship between branching angle and light interception using a three-dimensional (3D) canopy model in loquat (Eriobotrya japonica Lindl). First, detailed 3D models of loquat trees were built by integrating branch and organ models. Second, the morphological models of different loquat trees were constructed by interactive editing. Third, the 3D individual-tree modeling software LSTree integrated with the OpenGL shadow technique, a radiosity model and a modified rectangular hyperbola model was used to calculate the silhouette to total area ratio, the distribution of photosynthetically active radiation within canopies and the net photosynthetic rate, respectively. Finally, the influence of loquat tree organ organization on the light interception of the trees was analyzed with different parameters. If the single branch angle between the level 2 scaffold branch and trunk is approximately 15° and the angles among the level 2 scaffold branches range from 60 to 90°, then a better light distribution can be obtained. The results showed that the branching angle has a significant impact on light interception, which is useful for grower manipulation of trees, e.g., shoot bending (scaffold branch angle). Based on this conclusion, a reasonable tree structure was selected for intercepting light. This quantitative simulation and analytical method provides a new digital and visual method that can aid in the design of tree architecture

Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite

Acquiring accurate and timely information on the spatial distribution of paddy rice fields and the corresponding yield is an important first step in meeting the regional and global food security needs. In this study, using dense vegetation index profiles and meteorological parameters from the Communication, Ocean, and Meteorological Satellite (COMS) geostationary satellite, we estimated paddy areas and applied a novel approach based on a remote sensing-integrated crop model (RSCM) to simulate spatiotemporal variations in rice yield in Northeastern Asia. Estimated seasonal vegetation profiles of plant canopy from the Geostationary Ocean Color Imager (GOCI) were constructed to classify paddy fields as well as their productivity based on a bidirectional reflectance distribution function model (BRDF) and adjusted normalized difference vegetation indices (VIs). In the case of classification, the overall accuracy for detected paddy fields was 78.8% and the spatial distribution of the paddy area was well represented for each selected county based on synthetic applications of dense-time GOCI vegetation index and MODIS water index. For most of the Northeast Asian administrative districts investigated between 2011 and 2017, simulated rice mean yields for each study site agreed with the measured rice yields, with a root-mean-square error of 0.674 t ha−1, a coefficient of determination of 0.823, a Nash-Sutcliffe efficiency of 0.524, and without significant differences (p-value = 0.235) according to a sample t-test (α = 0.05) for the entire study period. A well-calibrated RSCM, driven by GOCI images, can facilitate the development of novel approaches for the monitoring and management of crop productivity over classified paddy areas, thereby enhancing agricultural decision support systems

Measuring and modeling near-surface reflected and emitted radiation fluxes at the FIFE site

Information is presented pertaining to the measurement and estimation of reflected and emitted components of the radiation balance. Information is included about reflectance and transmittance of solar radiation from and through the leaves of some grass and forb prairie species, bidirectional reflectance from a prairie canopy is discussed and measured and estimated fluxes are described of incoming and outgoing longwave and shortwave radiation. Results of the study showed only very small differences in reflectances and transmittances for the adaxial and abaxial surfaces of grass species in the visible and infrared wavebands, but some differences in the infrared wavebands were noted for the forbs. Reflectance from the prairie canopy changed as a function of solar and view zenith angles in the solar principal plane with definite asymmetry about nadir. The surface temperature of prairie canopies was found to vary by as much as 5 C depending on view zenith and azimuth position and on the solar azimuth. Aerodynamic temperature calculated from measured sensible heat fluxes ranged from 0 to 3 C higher than nadir-viewed temperatures. Models were developed to estimate incoming and reflected shortwave radiation from data collected with a Barnes Modular Multiband Radiometer. Several algorithms for estimating incoming longwave radiation were evaluated and compared to actual measures of that parameter. Net radiation was calculated using the estimated components of the shortwave radiation streams, determined from the algorithms developed, and from the longwave radiation streams provided by the Brunt, modified Deacon, and the Stefan-Boltzmann models. Estimates of net radiation were compared to measured values and found to be within the measurement error of the net radiometers used in the study

Leaf orientation and the spectral reflectance of field crops

Leaf angle distribution (LAD) is one of the most important parameters used to describe the structure of horizontally homogeneous vegetation canopies, such as field crops. LAD affects how incident photosynthetically active radiation is distributed on plant leaves, thus directly affecting plant productivity. However, the LAD of crops is difficult to quantify; usually it is assumed to be spherical. The purpose of this dissertation is to develop leaf angle estimation methods and study their effect on leaf area index (LAI) and chlorophyll a and b content (Cab) measured from optical observation. The study area was located in Viikki agricultural experimental field, Helsinki, Finland. Six crop species, faba bean, narrow-leafed lupin, turnip rape, oat, barley and wheat, were included in this study. A digital camera was used to take photographs outside the plot to record crop LAD. LAI and Cab were determined for each plot. Airborne imaging spectroscopy data was acquired using an AISA Eagle II imaging spectrometer covering the spectral range in visible and near-infrared (400 1000 nm). A recently developed method for the determination of leaf inclination angle was applied in field crops. This method was previously applied only to small and flat leaves of tree species. The error of LAI determination caused by the assumption of spherical LAD varied between 0 and 1.5 LAI units. The highest correlation between leaf mean tilt angle (MTA) and spectral reflectance was found at a wavelength of 748 nm. MTA was retrieved from imaging spectroscopy data using two algorithms. One method was to retrieve MTA from reflectance at 748 nm using a look-up table. The second method was to estimate MTA using the strong dependence of blue (479 nm) and red (663 nm) on MTA. The two approaches provide a new means to determine crop canopy structure from remote sensing data. LAI and MTA effects on Cab sensitive vegetation indices were examined. Three indices (REIP, TCARI/OSAVI and CTR6) showed strong correlations with Cab and similar performance in model-simulated and empirical datasets. However, only two (TCARI/OSAVI and CTR6) were independent from LAI and MTA. These two indices were considered as robust proxies of crop leaf Cab. Keywords: leaf angle; leaf area index; leaf chlorophyll; digital photograph; imaging spectroscopy; PROSAIL model; vegetation indice

Earth resources: A continuing bibliography with indexes (issue 58)

This bibliography lists 500 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Multiangular crop differentiation and LAI estimation using PROSAIL model inversion

xiii, 161 leaves : ill., map ; 29 cmUnderstanding variations in remote sensing data with illumination and sensor angle changes is important in agricultural crop monitoring. This research investigated field bidirectional reflectance factor (BRF) in crop differentiation and PROSAIL leaf area index (LAI) estimation. BRF and LAI data were collected for planophile and erectophile crops at three growth stages. In the solar principal plane, BRF differed optimally at 860 nm 60 days after planting (DAP) for canola and pea, at 860 nm 45 and 60 DAP for wheat and barley, and at 860 nm and 670 nm 45 and 60 DAP for planophiles versus erectophiles. The field BRF data helped better understand PROSAIL LAI estimation. NDVI was preferred for estimating LAI, however the MTVI2 vegetation index showed high sensitivity to view angles, particularly for erectophiles. The hotspot was important for crop differentiation and LAI. Availability of more along-track, off-nadir looking spaceborne sensors was recommended for agricultural crop monitoring

Mathematical and computational methods for functional-structural plant modelling using L-systems and their applications to modelling the kiwifruit vine

Mathematical and computational modelling provides a framework within which the understanding of plant growth and development can be further advanced. By abstracting from reality, it provides a way to test our hypotheses of the behaviour of real plants, offers simple explanations of observed phenomenon, and allows us to make quantitative predictions under new conditions. In particular, functional-structural plant models are well suited for these types of studies, because they capture the complex interactions between plant architecture and physiological processes as governed by the environment. The aim of this research was to investigate and develop mathematical and computational methods for use in functional-structural plant modelling, and, in particular, to allow easy incorporation of various aspects of plant growth and development at different spatial and temporal scales into one complex dynamical system. To this end, a functional-structural kiwifruit vine model was constructed using an L-system based plant modelling platform. The model was used to integrate the kiwifruit vine's architectural development with mechanistic modelling of carbon transport and allocation. The branching pattern was captured at the individual shoot level by modelling axillary shoot development using a discrete-time Markov chain. An existing carbon transport-resistance model was extended to account for several source/sink components of individual plant elements. The model was then interfaced with the light simulation program QuasiMC, and used to estimate the absorbed irradiance of each leaf during the course of the vine's development. Furthermore, the operation of QuasiMC was illustrated and analysed using an abstract virtual canopy (a triangle mix) and the kiwifruit vine model as examples. Several simulations, inspired by biological experiments, were performed to illustrate the capabilities of the kiwifruit model, including the plastic response of shoot growth to local carbon supply, the branching patterns of two Actinidia species, the effect of carbon limitation and topological distance on fruit size, and the complex behaviour of sink competition for carbon. The model was able to represent the major features of kiwifruit growth and function, and provided a solid foundation for investigating plant modelling methodology. A major challenge in functional-structural plant modelling is the integration of several previously modelled aspects of plant function into one model. To meet this challenge, the kiwifruit model provided the inspiration for extending L-systems with a new modules of modules approach, which combines pseudo-L-systems with sets of productions and lists of modules to consider within those sets. Using the new approach, a model of a kiwifruit shoot was constructed that integrates previously modelled aspects of the shoot's architecture with carbon dynamics, apical dominance and biomechanics. In the short term, the kiwifruit model will be used to help explore the vine's physiology and genetic control. For example, it will help give a physiological interpretation of experimental results on competition for carbon between vegetative and reproductive components of the vine. In the long term, it will serve as the basis for development of decision support systems to help improve kiwifruit production