Kurtis J. Thome

The Ground-Based Absolute Radiometric Calibration of Landsat 8 OLI

This paper presents the vicarious calibration results of Landsat 8 OLI that were obtained using the reflectance-based approach at test sites in Nevada, California, Arizona, and South Dakota, USA. Additional data were obtained using the Radiometric Calibration Test Site, which is a suite of instruments located at Railroad Valley, Nevada, USA. The results for the top-of-atmosphere spectral radiance show an average difference of −2.7, −0.8, 1.5, 2.0, 0.0, 3.6, 5.8, and 0.7% in OLI bands 1–8 as compared to an average of all of the ground-based measurements. The top-of-atmosphere spectral reflectance shows an average difference of 1.6, 1.3, 2.0, 1.9, 0.9, 2.1, 3.1, and 2.1% from the ground-based measurements. Except for OLI band 7, the spectral radiance results are generally within ±5% of the design specifications, and the reflectance results are generally within ±3% of the design specifications. The results from the data collected during the tandem Landsat 7 and 8 flight in March 2013 indicate that ETM+ and OLI agree to each other to within ±2% in similar bands in top-of-atmosphere spectral radiance, and to within ±4% in top-of-atmosphere spectral reflectance.

Absolute Radiometric Calibration of Landsat Using a Pseudo Invariant Calibration Site

Pseudo invariant calibration sites (PICS) have been used for on-orbit radiometric trending of optical satellite systems for more than 15 years. This approach to vicarious calibration has demonstrated a high degree of reliability and repeatability at the level of 1-3% depending on the site, spectral channel, and imaging geometries. A variety of sensors have used this approach for trending because it is broadly applicable and easy to implement. Models to describe the surface reflectance properties, as well as the intervening atmosphere have also been developed to improve the precision of the method. However, one limiting factor of using PICS is that an absolute calibration capability has not yet been fully developed. Because of this, PICS are primarily limited to providing only long term trending information for individual sensors or cross-calibration opportunities between two sensors. This paper builds an argument that PICS can be used more extensively for absolute calibration. To illustrate this, a simple empirical model is developed for the well-known Libya 4 PICS based on observations by Terra MODIS and EO-1 Hyperion. The model is validated by comparing model predicted top-of-atmosphere reflectance values to actual measurements made by the Landsat ETM+ sensor reflective bands. Following this, an outline is presented to develop a more comprehensive and accurate PICS absolute calibration model that can be Système international dunités (SI) traceable. These initial concepts suggest that absolute calibration using PICS is possible on a broad scale and can lead to improved on-orbit calibration capabilities for optical satellite sensors.

Impact of urbanization on US surface climate

We combine Landsat and MODIS data in a land model to assess the impact of urbanization on US surface climate. For cities built within forests, daytime urban land surface temperature (LST) is much higher than that of vegetated lands. For example, in Washington DC and Atlanta, daytime mean temperature differences between impervious and vegetated lands reach 3.3 and 2.0 °C, respectively. Conversely, for cities built within arid lands, such as Phoenix, urban areas are 2.2 °C cooler than surrounding shrubs. We find that the choice and amount of tree species in urban settings play a commanding role in modulating cities LST. At continental and monthly scales, impervious surfaces are 1.9 °C ± 0.6 °C warmer than surroundings during summer and expel 12% of incoming precipitation as surface runoff compared to 3.2% over vegetation. We also show that the carbon lost to urbanization represents 1.8% of the continental total, a striking number considering urbanization occupies only 1.1% of the US land. With a small areal extent, urbanization has significant effects on surface energy, water and carbon budgets and reveals an uneven impact on surface climate that should inform upon policy options for improving urban growth including heat mitigation and carbon sequestration.

Linking Climate to Incidence of Zoonotic Cutaneous Leishmaniasis (L. major) in Pre-Saharan North Africa

Shifts in surface climate may have changed the dynamic of zoonotic cutaneous leishmaniasis (ZCL) in the pre-Saharan zones of North Africa. Caused by Leishmania major, this form multiplies in the body of rodents serving as reservoirs of the disease. The parasite is then transmitted to human hosts by the bite of a Phlebotomine sand fly (Diptera: Psychodidae) that was previously fed by biting an infected reservoir. We examine the seasonal and interannual dynamics of the incidence of this ZCL as a function of surface climate indicators in two regions covering a large area of the semi-arid Pre-Saharan North Africa. Results suggest that in this area, changes in climate may have initiated a trophic cascade that resulted in an increase in ZCL incidence. We find the correlation between the rainy season precipitation and the same year Normalized Difference Vegetation Index (NDVI) to be strong for both regions while the number of cases of ZCL incidence lags the precipitation and NDVI by 2 years. The zoonotic cutaneous leishmaniasis seasonal dynamic appears to be controlled by minimum temperatures and presents a 2-month lag between the reported infection date and the presumed date when the infection actually occurred. The decadal increase in the number of ZCL occurrence in the region suggests that changes in climate increased minimum temperatures sufficiently and created conditions suitable for endemicity that did not previously exist. We also find that temperatures above a critical range suppress ZCL incidence by limiting the vector’s reproductive activity.

Landsat-7 ETM+: 12 Years On-Orbit Reflective-Band Radiometric Performance

The Landsat-7 ETM+ sensor has been operating on orbit for more than 12 years, and characterizations of its performance have been ongoing over this period. In general, the radiometric performance of the instrument has been remarkably stable: 1) noise performance has degraded by 2% or less overall, with a few detectors displaying step changes in noise of 2% or less; 2) coherent noise frequencies and magnitudes have generally been stable, though the within-scan amplitude variation of the 20 kHz noise in bands 1 and 8 disappeared with the failure of the scan line corrector and a new similar frequency noise (now about 18 kHz) has appeared in two detectors in band 5 and increased in magnitude with time; 3) bias stability has been better than 0.25 DN out of a normal value of 15 DN in high gain; 4) relative gains, the differences in response between the detectors in the band, have generally changed by 0.1% or less over the mission, with the exception of a few detectors with a step response change of 1% or less; and 5) gain stability averaged across all detectors in a band, which is related to the stability of the absolute calibration, has been more stable than the techniques used to measure it. Due to the inability to confirm changes in the gain (beyond a few detectors that have been corrected back to the band average), ETM+ reflective band data continues to be calibrated with the prelaunch measured gains. In the worst case, some bands may have changed as much as 2% in uncompensated absolute calibration over the 12 years.

Design and calibration of field deployable ground-viewing radiometers

Three improved ground-viewing radiometers were built to support the Radiometric Calibration Test Site (RadCaTS) developed by the Remote Sensing Group (RSG) at the University of Arizona. Improved over previous light-emitting diode based versions, these filter-based radiometers employ seven silicon detectors and one InGaAs detector covering a wavelength range of 400-1550 nm. They are temperature controlled and designed for greater stability and lower noise. The radiometer systems show signal-to-noise ratios of greater than 1000 for all eight channels at typical field calibration signal levels. Predeployment laboratory radiance calibrations using a 1 m spherical integrating source compare well with in situ field calibrations using the solar radiation based calibration method; all bands are within ±2.7% for the case tested.

Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

Abstract. The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat islands (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1°C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1–2°C. By contrast, the LSTs show a midday summer UHIS of 3–4°C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0°C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude. Résumé. L’Aire des Surfaces impérvieuses (ISA) de la banque Nationale de données sur les Couvertures du Sol (NLCD) et les températures de surface de MODIS (LST) des années 2006 et 2011 sont utilisées dans une analyse spatiale pour évaluer la signature des ilots de chaleur Urbains, basés sur la température de surface (UHIS), sur l’amplitude de la LST aux EUA, et faire des comparaisons avec les températures de l’air locales. Les ilots de chaleur basés sur la température de l’air (UHIA) calculés à partir des données journalières de température obtenues du Network Historique Climatologique Global (GHCN) sont comparés aux UHIS pour des arrangements urbains dans des biomes de végétation et des saisons différentes. Les aires impérvieuses (ISA) sont utilisées pour définir les zones urbaines et rurales ainsi que pour stratifier l’échantillonnage des LSTs et des températures de l’air des stations. On trouve que la LST de MODIS est en bon agrément avec la température de l’air durant la nuit, mais tend à la surestimer durant le jour, spécialement pendant l’été et dans les régions non-boisées. L’analyse des températures minimum montre que les peuplements urbains construits en milieu forestier ont une UHIA moyenne d’environ 1°C durant l’été. Les LSTs nocturnes ont des amplitudes similaires de 1–2°C. Par contraste, les LSTs de MODIS montrent des UHIS de 3–4°C dans les centres urbains en milieux forestiers alors que la valeur moyenne d’été des UHIA obtenue à partir des températures maximales avoisine 0°C. Les différences entre les LSTs et la température de l’air entre 2006 et 2011, sont en agreement quoiqu’avec des intensités différentes.

The Thermal Infrared Sensor on the Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM), a joint NASA and USGS mission, is scheduled for launch in December, 2012. The LDCM instrument payload will consist of the Operational Land Imager (OLI), provided by Ball Aerospace and Technology Corporation (BATC) under contract to NASA and the Thermal Infrared Sensor (TIRS), provided by NASAs Goddard Space Flight Center (GSFC). This paper outlines the design of the TIRS instrument and gives an example of its application to monitoring water consumption by measuring evapotranspiration.

Radiometric calibration of earth-observing sensors using an automated test site at Railroad Valley, Nevada

The Remote Sensing Group (RSG) at the University of Arizona uses the reflectance-based approach to radiometrically calibrate airborne and spaceborne sensors in the solar-reflective regime. The Radiometric Calibration Test Site (RadCaTS) concept was developed in 2004 to increase the amount of ground-based data collected. RadCaTS provides a methodology to determine the surface reflectance for any arbitrary test site in the absence of ground personnel. It is founded on the reflectance-based approach and has successfully operated at Railroad Valley, Nevada, with a suite of instruments including nadir-viewing multispectral radiometers, a Cimel sun photometer, and a meteorological station. RadCaTS data are currently used by RSG to supplement those collected by on-site personnel. This work presents a description of the RadCaTS automated concept, including the process used to determine surface reflectance and top-of-atmosphere (TOA) spectral radiance. The instrumentation required to measure the surface and atmosphere is introduced, followed by discussions regarding their placement on the 1 km2 site at Railroad Valley and their calibration. Lastly, the RadCaTS results are compared with those obtained from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectrometer (MODIS). The average percent difference in TOA spectral radiance is 4.1% between the six bands of ETM+ and RadCaTS and 3.6% between the seven land bands of Terra MODIS and RadCaTS.

Uncertainty Estimates for Imager Reference Inter-Calibration With CLARREO Reflected Solar Spectrometer

One of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission objectives is to provide a high accuracy calibration standard on orbit to enable inter-calibration of existing sensors. In order to perform an accurate inter-calibration of imaging radiometers, such as VIIRS, one must take into account instrument sensitivity to polarization of incoming light. Even if the sensitivity to polarization of an instrument is established or known on orbit, the knowledge of the polarization state of reflected light is required to make relevant radiometric corrections. In the case when coincident polarimetric measurements are not available, we propose to use a combination of empirical and theoretical models to predict the polarization of solar reflected light at the top-of-atmosphere. We used observations from on-orbit polarimeter PARASOL to derive a global set of empirical Polarization Distribution Models (PDM) as a function of scene type and viewing geometry. The PDM accuracy for the mean values is estimated to match the 3% PARASOL uncertainty in its polarization measurements. The instantaneous single sample uncertainty of the prototype PDMs for the linear degree of polarization is contained within 15%. We also present the formalism and numeric estimates for resulting uncertainty for inter-calibration of an imaging radiometer with the CLARREO reference observations, including uncertainty due to instrument sensitivity to polarization. The uncertainty estimates consider a range of scenarios with varying data sampling, uncertainty of polarization, and imaging radiometer sensitivity to polarization. These results are used to recommend CLARREO mission requirements relevant to reference inter-calibration and polarization effects.