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DOE OSTI2023

An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites

In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. Here we developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (i.e. percentage of tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470-2819 mm year -1 ). Among these sites, we evaluated the PlanetScope-derived deciduousness with corresponding measures derived from WorldView-2 (n=9 sites) and local phenocams (n=9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90m×90m) with r 2 =0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r 2 ranging from 0.62-0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Analysis of the profile characteristics of corn and soybeans using field reflectance data

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗

NASA NTRS2011

Multiangle Implementation of Atmospheric Correction (MAIAC): 2. Aerosol Algorithm

An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 micron) and shortwave infrared (2.1 micron) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.

Lyapustin, A.↗

NASA NTRS1980

Effects of heavy metals on the absorbance and reflectance spectra of plants

The spectral responses of plants to various concentrations of heavy metals in their rooting media are investigated in relation to the application of remote sensing methods to the detection of vegetation under stress. Absorption photometry of chloroplasts, measurements of metal and chlorophyll concentrations and reflectance spectrometry were performed on leaves of pea, sunflower and soybean plants grown under greenhouse conditions with the addition of various concentrations of Cd, Cu, Pb and Zn to their rooting media and on leaves of oak trees growing naturally in an area of a copper-arsenic mineralization. Under laboratory conditions, the most general effect observed was growth inhibition and ultimately death, with pea plants also exhibiting changes of chlorophyll a/ chlorophyll b ratios with Cd and Cu and reflectance increases in the visible and decreases in the infrared. Although results for other species indicate that reflectance effects are dependent on species, correlations between reflectance and metal exposure is confirmed by the field investigations. It is concluded that a remote sensing system would be improved by the inclusion of bands around 1.65 and 2.20 microns to detect soil mineralization from plant spectra.

Horler, D. N. H.↗

DOE OSTI2020

Outdoor Testing of c-Si Photovoltaic Modules with Spectrally-Selective Mirrors for Operating Temperature Reduction

The efficiency of a c-Si cell drops with increasing cell temperature. A typical photovoltaic module with a c-Si cell will operate 20-30K above ambient temperature. Spectrally-selective photonic mirrors which reflect sub-bandgap light can reduce waste heat generated by parasitic absorption in the module and reduce module operating temperature. Here, a spectrally selective 4-layer and 12-layer mirror are designed and fabricated on module cover glass. When integrated into modules, these mirrors reduce the operating temperature of the module by 0.16K and 1.5K, respectively when compared to a module with bare outer glass.

14 SOLAR ENERGY↗

NASA NTRS1993

Development of a Cone Penetrometer for Measuring Spectral Characteristics of Soils in Situ

A patent was recently granted to the U.S. Army for an adaptation of a soil cone penetrometer that can be used to measure the spectral characteristics (fluorescence or reflectance) of soils adjacent to the penetrometer rod. The system can use a variety of light sources and spectral analytical equipment. A laser induced fluorescence measuring system has proven to be of immediate use in mapping the distribution of oil contaminated soil at waste disposal and oil storage areas. The fiber optic adaptation coupled with a cone penetrometer permits optical characteristics of the in-situ soil to be measured rapidly, safely, and inexpensively. The fiber optic cone penetrometer can be used to gather spectral data to a depth of approximately 25 to 30 m even in dense sands or stiff clays and can investigate 300 m of soil per day. Typical detection limits for oil contamination in sand is on the order of several hundred parts per million.

Lee, Landris T., Jr.↗

NASA NTRS1983

The red edge of plant leaf reflectance

A detailed study of the red edge spectral feature of green vegetation based on laboratory reflectance spectrophotometry is presented. A parameter lambda is defined as the wavelength is defined as the wavelength of maximum slope and found to be dependent on chlorophyll concentration. Species, development stage, leaf layering, and leaf water content of vegetation also influences lambda. The maximum slope parameter is found to be independent of simulated ground area coverage. The results are interpreted in terms of Beer's Law and Kubelka-Munk theory. The chlorophyll concentration dependence of lambda seems to be explained in terms of a pure absorption effect, and it is suggested that the existence of two lambda components arises from leaf scattering properties. The results indicate that red edge measurements will be valuable for assessment of vegetative chlorophyll status and leaf area index independently of ground cover variations, and will be particularly suitable for early stress detection.

Horler, D. N. H.↗

NASA NTRS1988

Spectral feature design in high dimensional multispectral data

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Chen, Chih-Chien Thomas↗

NASA NTRS2011

Thermal Optical Properties of Lunar Dust Simulants and Their Constituents

The total reflectance spectra of lunar simulant dusts (less than 20 micrometer particles) were measured in order to determine their integrated solar absorptance (alpha) and their thermal emittance (e) for the purpose of analyzing the effect of dust on the performance of thermal control surfaces. All of the simulants except one had a wavelength-dependant reflectivity (p(lambda)) near 0.10 over the wavelength range of 8 to 25 micrometers, and so are highly emitting at room temperature and lower. The 300 K emittance (epsilon) of all the lunar simulants except one ranged from 0.78 to 0.92. The exception was Minnesota Lunar Simulant 1 (MLS-1), which has little or no glassy component. In all cases the epsilon was lower for the less 20 micrometer particles than for larger particles reported earlier. There was considerably more variation in the lunar simulant reflectance in the solar spectral range (250 to 2500 nanometers) than in the thermal infrared. As expected, the lunar highlands simulants were more reflective in this wavelength range than the lunar mare simulants. The integrated solar absorptance (alpha) of the simulants ranged from 0.39 to 0.75. This is lower than values reported earlier for larger particles of the same simulants (0.41 to 0.82), and for representative mare and highlands lunar soils (0.74 to 0.91). Since the alpha of some mare simulants more closely matched that of highlands lunar soils, it is recommended that and values be the criteria for choosing a simulant for assessing the effects of dust on thermal control surfaces, rather than whether a simulant has been formulated as a highlands or a mare simulant.

Gaier, James R.↗

NASA NTRS2011

Thermal Optical Properties of Lunar Dust Simulants and Their Constituents

The total reflectance spectra of lunar simulant dusts (< 20 mm particles) were measured in order to determine their integrated solar absorptance (alpha) and their thermal emittance (epsilon) for the purpose of analyzing the effect of dust on the performance of thermal control surfaces. All of the simulants except one had a wavelength-dependent reflectivity (p (lambda)) near 0.10 over the wavelength range of 8 to 25 microns and so are highly emitting at room temperature and lower. The 300 K emittance (epsilon) of all the lunar simulants except one ranged from 0.78 to 0.92. The exception was Minnesota Lunar Simulant 1 (MLS-1), which has little or no glassy component. In all cases the epsilon was lower for the < 20 micron particles than for larger particles reported earlier. There was considerably more variation in the lunar simulant reflectance in the solar spectral range (250 to 2500 nm) than in the thermal infrared. As expected, the lunar highlands simulants were more reflective in this wavelength range than the lunar mare simulants. The integrated solar absorptance (alpha) of the simulants ranged from 0.39 to 0.75. This is lower than values reported earlier for larger particles of the same simulants (0.41 to 0.82), and for representative mare and highlands lunar soils (0.74 to 0.91). Since the of some mare simulants more closely matched that of highlands lunar soils, it is recommended that and values be the criteria for choosing a simulant for assessing the effects of dust on thermal control surfaces, rather than whether a simulant has been formulated as a highlands or a mare simulant.

Gaier, James R.↗

NASA NTRS2012

Estimation of Supraglacial Dust and Debris Geochemical Composition via Satellite Reflectance and Emissivity

We demonstrate spectral estimation of supraglacial dust, debris, ash and tephra geochemical composition from glaciers and ice fields in Iceland, Nepal, New Zealand and Switzerland. Surface glacier material was collected and analyzed via X-ray fluorescence spectroscopy (XRF) and X-ray diffraction (XRD) for geochemical composition and mineralogy. In situ data was used as ground truth for comparison with satellite derived geochemical results. Supraglacial debris spectral response patterns and emissivity-derived silica weight percent are presented. Qualitative spectral response patterns agreed well with XRF elemental abundances. Quantitative emissivity estimates of supraglacial SiO2 in continental areas were 67% (Switzerland) and 68% (Nepal), while volcanic supraglacial SiO2 averages were 58% (Iceland) and 56% (New Zealand), yielding general agreement. Ablation season supraglacial temperature variation due to differing dust and debris type and coverage was also investigated, with surface debris temperatures ranging from 5.9 to 26.6 C in the study regions. Applications of the supraglacial geochemical reflective and emissive characterization methods include glacier areal extent mapping, debris source identification, glacier kinematics and glacier energy balance considerations.

Casey, Kimberly Ann↗

DOE OSTI2023

Modeling Wavelength Dependent Mid-infrared (5.5–25 μm) Optical Constants of Silicate Glasses: A Genetic Algorithm Approach

Wavelength-dependent mid-infrared (400–1,800 cm -1 ; 5.56–25 μm) optical constants (real and imaginary indices of refraction; n and k) are determined using reflectance spectra at a spectral sampling of 4 cm -1 for several silicate glasses of varying SiO 2 wt% which include (a) basaltic volcanic glass from Kilauea, Hawaii, (b) synthetic andesite, (c) two synthetic dacites, (d) obsidian volcanic glass from Mount Lassen, California, (e) synthetic rhyodacite, and (f) rhyolitic volcanic glass from Mexico. Because glasses are optically isotropic, no specific orientation was required for spectral measurements, and polished glass samples were measured at random orientations using micro-FTIR spectrometer. Lorentz-Lorenz dispersion theory and Fresnel reflectance model for high symmetry materials were used to model the optical constants by optimizing oscillator parameters in modeled spectra to match laboratory spectra. A genetic algorithm (GA) approach automatically finds the natural oscillators and their parameters for each spectrum, and then uses these parameters in a non-linear least squares optimization routine. The study compared spectral parameters such as Christiansen feature, reststrahlen bands (RBs), and the peaks centered around 860–1,100 (peak 1) and 400–480 cm -1 (peak 2) of n and k to their respective SiO 2 wt% of the glasses. CF, RBs, peak 1 of n and k, and peak 2 of n shift to higher wavenumbers with increased SiO 2 wt%, whereas peak 2 of k shifts to lower wavenumbers with increased SiO 2 wt%. Derived optical constants of these glasses will improve quantitative abundance mapping of volcanic materials on the surfaces of silicate targets in the Solar System.

58 GEOSCIENCES↗

NASA NTRS1984

Dielectric Fabry-Perot mirror coatings for infrared astronomy

A number of Fabry-Perot (FP) coating designs have been developed specifically for IR astronomy. These have been optimized for uniform reflectance over five contiguous spectral ranges of particular astronomical interest between 1 and 5 microns. Wavelength coverage in individual designs is given by (maximum wavelength/minimum wavelength) greater than 1.4, over which reflective finesse is maintained near 35. Consideration has been made for the peculiar requirements of FP coatings. Visual alignment and testing of the FP has been made convenient by bringing the reflective finesse of the coating at 632.8 nm to the same value as the main IR reflection band. For example, a calcium fluoride FP can be aligned and tested at 632.8-nm He-Ne laser line, with the assurance of a corresponding finesse and spectral resolving power over its IR (3.6-5.1-micron) range. In addition, the FP can be used for IR spectroscopy while being simultaneously monitored and/or actively controlled at the laser wavelength. The potential for the coating itself to degrade the effective surface flatness of the FP through either mechanical stress or thickness nonuniformities is minimized by reducing to a minimum the number and thickness of coating layers. Several of these coatings have been fabricated and are actively in use at a number of observatories.

Trauger, J.↗

NASA NTRS2011

Faraday-Active Fabry-Perot Resonator: Transmission, Reflection, and Emissivity

The propagation of light within a semiconductor Faraday-active Fabry-Perot resonator (FAFR) is investigated theoretically and experimentally. It is shown that an external magnetic field radically changes the angular and spectral characteristics of transmission, reflection and emissivity of the resonator not only for polarized, but also for unpolarized light. Suppression of interference patterns and phase inversion of the interference extrema were observed in both monochromatic and polychromatic light. The investigations were carried out for the plane-parallel plates of n-InAs in the spectral range of free charge carrier absorption. The results can be used to create new controllable optical and spectroscopic devices for investigation of Faraday-active material properties and for control of parameters of plane-parallel layers and structures.

Liptuga, Anatoliy↗

NASA NTRSDate not supplied

Analysis of Spacecraft Materials Discrimination Using Color Indices for Remote Sensing for Space Situational Awareness

The increasing number of space missions have resulted in an augmented density of artificial objects positioned in orbital domains near Earth. Knowing the material composition of the resident space object can be of value in object identification and risk assessment using remote sensing techniques. To perform this task, it is increasingly imperative to optically characterize spacecraft materials to identify unique material-specific spectroscopic markers. In this work, a variety of materials frequently utilized by the aerospace industry in spacecraft design and construction were analyzed using reflectance spectroscopy. The collected data provide a spectral characterization baseline for modern-day and historical spacecraft materials. The color index was computed for standard astronomical and suggested theoretical filter passbands and compared to each other in their capability to discriminate materials belonging to different classes. The color index was calculated from reflectance spectra of common spacecraft materials in their pristine, as-received conditions that fell under different family groupings. Different color-index combinations were studied using color-color diagrams. Visual and quantitative analysis of the color-color diagrams were used to evaluate the possibility of discriminating materials from one another by means of optical measurements. Results of the analysis show that polyimide and photovoltaic materials are most easy to discriminate from all other materials via color indices using different filter passbands evaluated in this study.

spectral reflectance↗

NASA NTRS1989

Black light - How sensors filter spectral variation of the illuminant

Visual sensor responses may be used to classify objects on the basis of their surface reflectance functions. In a color image, the image data are represented as a vector of sensor responses at each point in the image. This vector depends both on the surface reflectance functions and on the spectral power distribution of the ambient illumination. Algorithms designed to classify objects on the basis of their surface reflectance functions typically attempt to overcome the dependence of the sensor responses on the illuminant by integrating sensor data collected from multiple surfaces. In machine vision applications, it is shown that it is often possible to design the sensor spectral responsivities so that the vector direction of the sensor responses does not depend upon the illuminant. The conditions under which this is possible are given and an illustrative calculation is performed. In biological systems, where the sensor responsivities are fixed, it is shown that some changes in the illumination cause no change in the sensor responses. Such changes in illuminant are called black illuminants. It is possible to express any illuminant as the sum of two unique components. One component is a black illuminant. The second component is called the visible component. The visible component of an illuminant completely characterizes the effect of the illuminant on the vector of sensor responses.

Brainard, David H.↗

NASA NTRS2000

Identification of Terrestrial Reflectance From Remote Sensing

Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.

Alter-Gartenberg, Rachel↗

NASA NTRS2005

NASA's Next Generation Sunphotometer for Ground-based Remote Sensing Applications

Atmospheric aerosol concentrations and their optical properties, in terms of which cause differential warming/cooling effects in the atmosphere and on the surface, constitute one of the largest sources of uncertainty in current assessments and predictions of global climatic change. This is especially true over the regions of bright-reflecting surface, such as desert and urban areas. Under the name of AERONET since the 90's, Cimel's sunphotometers have been deployed worldwide as the standard instrument for aerosol monitoring network, developed to support NASA, CNES, and NASDA's Earth satellite systems. PREDE's skyradiometers, as deployed in SKYNET, serve the similar role. One of the key ingredients for achieving accurate aerosol retrievals from satellite observations is comprehensive understanding of surface spectral BRF's (Bidirectional Reflectance Factors), defined as a ratio of radiance measurements reflected from a targeted surface and from a spectral-angular featureless referencing plate. Although the weather-resistant, automatic, sun/sky-scanning spectroradiometers enable Frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites, they are too slow for surface BRF measurements (20-25 seconds per 360 degree scan, in addition to filter wheel rotation time). We have designed a next generation sun photometer whose sensor head has no moving parts. A dedicated detector for each channel enables 12 simultaneous measurements ranging from the UV (380 nm) to shortwave-IR (2.13 micron) regions. The scan platform will be capable of traveling 360 degrees in about 6 seconds. This is sufficient to finish a BRDF scan every 30 degrees in azimuth and 15 degrees in elevation in less than 4 minutes. More details about this instrument will be presented, together with its applications to the aerosol and trace gas studies. The current plan for this instrument is to deploy during the EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment).

Shu, Peter K.↗