Topological Quantum Computing

This set of lecture notes forms the basis of a series of lectures delivered at the 48th IFF Spring School 2017 on Topological Matter: Topological Insulators, Skyrmions and Majoranas at Forschungszentrum Juelich, Germany. The first part of the lecture notes covers the basics of abelian and non-abelian anyons and their realization in the Kitaev's honeycomb model. The second part discusses how to perform universal quantum computation using Majorana fermions.Comment: In Topological Matter: Topological Insulators, Skyrmions and Majoranas, Lecture notes of the 48th IFF Spring School 2017, eds. S. Bluegel, Y. Mokrusov, T. Schaepers, and Y. Ando (Forschungszentrum Juelich, Key Technologies, Vol. 139, 2017), Sec. D

Disruption in the Supply Chain for Beef and Pork: What Has Happened and What Was NAFTA Doing

Industrial Organization, International Relations/Trade,

Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring

In urban environments, aerosol distributions may change rapidly due to building and transport infrastructure and human population density variations. The recent availability of medium resolution Landsat-8 and Sentinel-2 satellite data provide the opportunity for aerosol optical depth (AOD) estimation at higher spatial resolution than provided by other satellites. AOD retrieved from 30 m Landsat-8 and 10 m Sentinel-2A data using the Land Surface Reflectance Code (LaSRC) were compared with coincident ground-based Aerosol Robotic Network (AERONET) Version 3 AOD data for 20 Chinese cities in 2016. Stringent selection criteria were used to select contemporaneous data; only satellite and AERONET data acquired within 10 min were considered. The average satellite retrieved AOD over a 1470 m1470 m window centered on each AERONET site was derived to capture fine scale urban AOD variations. AERONET Level 1.5 (cloud-screened) and Level 2.0 (cloud-screened and also quality assured) data were considered. For the 20 urban AERONET sites in 2016 there were 106 (Level 1.5) and 67 (Level 2.0) Landsat-8 AERONET AOD contemporaneous data pairs, and 118 (Level 1.5) and 89 (Level 2.0) Sentinel-2A AOD data pairs. The greatest AOD values (>1.5) occurred in Beijing, suggesting that the Chinese capital was one of the most polluted cities in China in 2016. The LaSRC Landsat-8 and Sentinel-2A AOD retrievals agreed well with the AERONET AOD data (linear regression slopes > 0.96; coefficient of determination r(exp 2) > 0.90; root mean square deviation < 0.175) and demonstrate that the LaSRC is an effective and applicable medium resolution AOD retrieval algorithm over urban environments. The Sentinel-2A AOD retrievals had better accuracy than the Landsat-8 AOD retrievals, which is consistent with previously published research.The implications of the research and the potential for urban aerosol monitoring by combining the freely available Landsat-8 and Sentinel-2 satellite data are discussed

A One Year Landsat 8 Conterminous United States Study of Cirrus and Non-Cirrus Clouds

The first year of available Landsat 8 data over the conterminous United States (CONUS), composed of 11,296 acquisitions sensed over more than 11 thousand million 30 m pixel locations, was analyzed comparing the spatial and temporal incidence of 30 m cloud and cirrus states available in the standard Landsat 8 Level 1 product suite. This comprehensive data analysis revealed that on average over a year of CONUS observations (i) 35.9% were detected with high confidence cloud, with spatio-temporal patterns similar to those observed by previous Landsat 5 and 7 cloud analyses; (ii) 28.2% were high confidence cirrus; (iii) 20.1% were both high confidence cloud and high confidence cirrus; and (iv) 6.9% were detected as high confidence cirrus but low confidence cloud. The results illustrate the potential of the 30 m cloud and cirrus states available in the standard Landsat 8 Level 1 product suite but imply that the historical CONUS Landsat archive has about 7% of undetected cirrus contaminated pixels. Systematic cloud detection commission errors over a minority of highly reflective exposed soil/sand surfaces were found and it is recommended that caution be taken when using the currently available Landsat 8 cloud data over similar surfaces

Fire-induced Albedo Change and Its Radative Forcing at the Surface in Northern Austrailia

This paper investigates the impact of fire on surface albedo and the associated radiative forcing over 56% of continental Australia encompassing the fire-prone northern tropical savanna. Fire-affected areas and albedos are derived for the 2003 fire season using daily Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data. Near-infrared and total shortwave albedos are observed to generally decrease after fire occurrence. Regionally, the total shortwave albedo drops by an average of 0.024, with increasing reductions as the dry season progresses and larger reductions in grasslands than woody savannas. These fire-induced albedo changes exert a positive forcing at the surface that increases from March to November. A mean ‘‘instantaneous’’ shortwave surface radiative forcing of 0.52 Wm -2 is estimated

The Global Availability of Landsat 5 TM and Landsat 7 ETM+ Land Surface Observations and Implications for Global 30m Landsat Data Product Generation

With the advent of the free U.S. Landsat data policy it is now feasible to consider the generation of global coverage 30 m Landsat data sets with temporal reporting frequency similar to that provided by the monthly Web Enabled Landsat (WELD) products. A statistical Landsat metadata analysis is reported considering more than 800,000 Landsat 5 TM and Landsat 7 ETM + acquisitions obtained from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center archive. The global monthly probabilities of acquiring a cloud-free land surface observation for December 1998 to November 2001 (2000 epoch) and from December 2008 to November 2011 (2010 epoch) are reported to assess the availability of the Landsat data in the USGS Landsat archive for global multi-temporal land remote sensing applications. The global probabilities of acquiring a cloud-free land surface observation in each of three different seasons with the highest seasonal probabilities of cloud-free land surface observation are reported, considering one, two and three years of Landsat data, to assess the availability of Landsat data for global land cover mapping. The probabilities are derived considering Landsat 5 TM only, Landsat 7 ETM + only, and both sensors combined, to examine the relative benefits of using one or both Landsat sensors. The results demonstrate the utility of combing both Landsat 5 TM and Landsat 7 ETM + data streams to take advantage of their different acquisition patterns and to mitigate the deleterious impact of the Landsat 7 ETM + 2003 scan line failure. Sensor combination provided a greater global acquisition coverage with a 1.7% to 14.4% higher percentage of land locations acquired monthly compared to considering Landsat 7 ETM + data alone. The mean global monthly probability of a cloud-free land surface observation for the combined sensors was up to nearly 1.4 and 6.7 times greater than for ETM + and TM alone respectively. The probability of acquiring a cloud-free Landsat land surface observation in different seasons was greater when more years of data were considered and when both Landsat sensor data were combined. Considering combined sensors and 36 months of data, 86.4% and 84.2% of the global land locations had probabilities ≥ 0.95 for the 2000 and 2010 epochs respectively, with a global mean probability of 0.92 (σ 0.24) for the 2000 epoch and 0.90 (σ 0.28) for the 2010 epoch. These results indicate that 36 months of combined Landsat sensor data will provide sufficient land surface observations for 30 m global land cover mapping using a multi-temporal supervised classification scheme

Radiative Forcing Over the Conterminous United States Due to Contemporary Land Cover Use Albedo Change

Recently available satellite land cover land use (LCLU) and albedo data are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 36 ecoregions covering 43% of the conterminous United States (CONUS). Moderate Resolution Imaging Spectroradiometer (MODIS) snowfree broadband albedo values are derived from Landsat LCLU classification maps located using a stratified random sampling methodology to estimate ecoregion estimates of LCLU induced albedo change and surface radiative forcing. The results illustrate that radiative forcing due to LCLU change may be disguised when spatially and temporally explicit data sets are not used. The radiative forcing due to contemporary LCLU albedo change varies geographically in sign and magnitude, with the most positive forcings (up to 0.284 Wm-2) due to conversion of agriculture to other LCLU types, and the most negative forcings (as low as -0.247 Wm-2) due to forest loss. For the 36 ecoregions considered a small net positive forcing (i.e., warming) of 0.012 Wm-2 is estimated

Computationally Inexpensive Landsat 8 Operational Land Imager (OLI) Pansharpening

Pansharpening algorithms fuse higher spatial resolution panchromatic with lower spatial resolution multispectral imagery to create higher spatial resolution multispectral images. The free-availability and systematic global acquisition of Landsat 8 data indicate an expected need for global coverage and so computationally efficient Landsat 8 pansharpening. This study adapts and evaluates the established, and relatively computationally inexpensive, Brovey and context adaptive Gram Schmidt component substitution (CS) pansharpening methods for application to the Landsat 8 15 m panchromatic and 30 m red, green, blue, and near-infrared bands. The intensity images used by these CS pansharpening methods are derived as a weighted linear combination of the multispectral bands in three different ways using band spectral weights set (i) equally as the reciprocal of the number of bands; (ii) using fixed Landsat 8 spectral response function based (SRFB) weights derived considering laboratory spectra; and (iii) using image specific spectral weights derived by regression between the multispectral and the degraded panchromatic bands. The spatial and spectral distortion and computational cost of the different methods are assessed using Landsat 8 test images acquired over agricultural scenes in South Dakota, China, and India. The results of this study indicate that, for global Landsat 8 application, the context adaptive Gram Schmidt pansharpening with an intensity image defined using the SRFB spectral weights is appropriate. The context adaptive Gram Schmidt pansharpened results had lower distortion than the Brovey results and the least distortion was found using intensity images derived using the SRFB and image specific spectral weights but the computational cost using the image specific weights was greater than the using the SRFB weights. Recommendations for large area Landsat 8 pansharpening application are described briefly and the SRFB spectral weights are provided so users may implement computationally inexpensive Landsat 8 pansharpening themselves

A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring

Combination of different satellite data will provide increased opportunities for more frequent cloud-free surface observations due to variable cloud cover at the different satellite overpass times and dates. Satellite data from the polar-orbiting Landsat-8 (launched 2013), Sentinel-2A (launched 2015) and Sentinel-2B (launched 2017) sensors offer 10 m to 30 m multi-spectral global coverage. Together, they advance the virtual constellation paradigm for mid-resolution land imaging. In this study, a global analysis of Landsat-8, Sentinel-2A and Sentinel-2B metadata obtained from the committee on Earth Observation Satellite (CEOS) Visualization Environment (COVE) tool for 2016 is presented. A global equal area projection grid defined every 0.05° is used considering each sensor and combined together. Histograms, maps and global summary statistics of the temporal revisit intervals (minimum, mean, and maximum) and the number of observations are reported. The temporal observation frequency improvements afforded by sensor combination are shown to be significant. In particular, considering Landsat-8, Sentinel-2A, and Sentinel-2B together will provide a global median average revisit interval of 2.9 days, and, over a year, a global median minimum revisit interval of 14 min (±1 min) and maximum revisit interval of 7.0 days