The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series

Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction

Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel

Enhancing Remote Sensing Based Yield Forecasting: Application to Winter Wheat in United States

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. In this study we present a new model based on the extrapolation of the pure wheat signal (100 percent of wheat within the pixel) from MODIS (Moderate-resolution Imaging Spectroradiometer) data at 1-kilometer resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national and state level yield of winter wheat in the United States from 2001 to 2016

Land and cryosphere products from Suomi NPP VIIRS: overview and status

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS

Optical Properties of Boreal Region Biomass Burning Aerosols in Central Alaska and Seasonal Variation of Aerosol Optical Depth at an Arctic Coastal Site

Long-term monitoring of aerosol optical properties at a boreal forest AERONET site in interior Alaska was performed from 1994 through 2008 (excluding winter). Large interannual variability was observed, with some years showing near background aerosol optical depth (AOD) levels (<0.1 at 500 nm) while 2004 and 2005 had August monthly means similar in magnitude to peak months at major tropical biomass burning regions. Single scattering albedo (omega (sub 0); 440 nm) at the boreal forest site ranged from approximately 0.91 to 0.99 with an average of approximately 0.96 for observations in 2004 and 2005. This suggests a significant amount of smoldering combustion of woody fuels and peat/soil layers that would result in relatively low black carbon mass fractions for smoke particles. The fine mode particle volume median radius during the heavy burning years was quite large, averaging approximately 0.17 micron at AOD(440 nm) = 0.1 and increasing to approximately 0.25 micron at AOD(440 nm) = 3.0. This large particle size for biomass burning aerosols results in a greater relative scattering component of extinction and, therefore, also contributes to higher omega (sub 0). Additionally, monitoring at an Arctic Ocean coastal site (Barrow, Alaska) suggested transport of smoke to the Arctic in summer resulting in individual events with much higher AOD than that occurring during typical spring Arctic haze. However, the springtime mean AOD(500 nm) is higher during late March through late May (approximately 0.150) than during summer months (approximately 0.085) at Barrow partly due to very few days with low background AOD levels in spring compared with many days with clean background conditions in summer

Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

The compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 m. In this article, we describe the methods to create global products of forest cover and cover change at Landsat resolutions. Nevertheless, there are many challenges in ensuring the creation of high-quality products. And we propose various ways in which the challenges can be overcome. Among the challenges are the need for atmospheric correction, incorrect calibration coefficients in some of the data-sets, the different phenologies between compilations, the need for terrain correction, the lack of consistent reference data for training and accuracy assessment, and the need for highly automated characterization and change detection. We propose and evaluate the creation and use of surface reflectance products, improved selection of scenes to reduce phenological differences, terrain illumination correction, automated training selection, and the use of information extraction procedures robust to errors in training data along with several other issues. At several stages we use Moderate Resolution Spectroradiometer data and products to assist our analysis. A global working prototype product of forest cover and forest cover change is included

Detailed α-decay study of 180Tl

International audienceA detailed $\alpha$-decay spectroscopy study of $^{180}\mathrm{Tl}$ has been performed at ISOLDE (CERN). $Z$-selective ionization by the Resonance Ionization Laser Ion Source (RILIS) coupled to mass separation provided a high-purity beam of $^{180}\mathrm{Tl}$. Fine-structure $\alpha$ decays to excited levels in the daughter $^{176}\mathrm{Au}$ were identified and an $\alpha$-decay scheme of $^{180}\mathrm{Tl}$ was constructed based on an analysis of $\alpha$-$\gamma$ and $\alpha$-$\gamma$-$\gamma$ coincidences. Multipolarities of several $\gamma$-ray transitions deexciting levels in $^{176}\mathrm{Au}$ were determined. Based on the analysis of reduced $\alpha$-decay widths, it was found that all $\alpha$ decays are hindered, which signifies a change of configuration between the parent and all daughter states

Kronos: A Java-Based Software System for the Processing and Retrieval of Large Scale AVHRR Data

At regional scales, satellite-based sensors are the primary source of information to study the earths environment, as they provide the needed dynamic temporal view of the earth\u27s surface. Raw satellite orbit data have to be processed and mapped into a standard projection to produce multitemporal data sets which can then be used for regional or global earth science studies. In this paper, we describe a software system Kronos for the generation of custom-tailored data products from the Advanced Very High Resolution Radiometer (AVHRR) sensor. Kronos allows the generation of a rich set of products that can be easily specified through a Java interface by scientists wishing to carry out earth system modeling or analysis based on AVHRR Global Area Coverage (GAC) data. Kronos is based on a flexible methodology and consists of four major components: ingest and preprocessing, indexing and storage, search and processing engine, and a Java interface. We illustrate the power of our methodology by including a few special data products generated by Kronos.\u2

Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation

The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land surfaces with a spatial resolution of up to 250 m

Preliminary study of relationships between hypnotic susceptibility and personality disorder functioning styles in healthy volunteers and personality disorder patients

<p>Abstract</p> <p>Background</p> <p>Hypnotic susceptibility is one of the stable characteristics of individuals, but not closely related to the personality traits such as those measured by the five-factor model in the general population. Whether it is related to the personality disorder functioning styles remains unanswered.</p> <p>Methods</p> <p>In 77 patients with personality disorders and 154 healthy volunteers, we administered the Stanford Hypnotic Susceptibility Scale: Form C (SHSSC) and the Parker Personality Measure (PERM) tests.</p> <p>Results</p> <p>Patients with personality disorders showed higher passing rates on SHSSC Dream and Posthypnotic Amnesia items. No significant correlation was found in healthy volunteers. In the patients however, SHSSC Taste hallucination (β = 0.26) and Anosmia to Ammonia (β = -0.23) were significantly correlated with the PERM Borderline style; SHSSC Posthypnotic Amnesia was correlated with the PERM Schizoid style (β = 0.25) but negatively the PERM Narcissistic style (β = -0.23).</p> <p>Conclusions</p> <p>Our results provide limited evidence that could help to understand the abnormal cognitions in personality disorders, such as their hallucination and memory distortions.</p