Status of the MODIS Level 1B Algorithms and Calibration Tables

The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites, launched in December 1999 and May 2002, respectively. The MODIS Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the MODIS L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the MODIS collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle

A városi hősziget probléma új módszertani közelítései

Mára már a Föld lakosságának több mint fele nagyvárosokban él, így egyre nagyobb az igény, hogy megmérjük, felmérjük, modellezzük, előrejelezzük a városok módosult éghajlati sajátosságait, s hogy ezek negatív következményeit már az épületek, gyárak tervezési, telepítési fázisában kiszűrhessük, minimalizálhassuk. Kutatásaink során finom felbontású műholdas adatokat használtunk, digitális magassági modellt, digitális felszínborítottsági/felhasználati adatbázist. A kutatási projekt során elvégzett elemzések, s azok eredményei: (1) Finomfelbontású műholdas felvételek felhasználásával megtörtént a városi hősziget struktúra elemzése Magyarország, illetve Közép-Európa néhány nagyobb városára. Vizsgálatainkhoz a felszíni hőmérséklet-mezősorokat az amerikai Terra és Aqua műhold MODIS szenzorának 1 km-es térbeli felbontású méréseiből vettük. (2) A hősziget-hatás szerkezetének értékelését elvégeztük az évszakok, a domborzat és a felszíntípus függvényében a fővárosra, illetve a hazai nagyvárosokra. (3) Elvégeztük a NOAA-műholdak AVHRR-szenzoraival mért felszíni hőmérséklet-meghatározó algoritmusok összehasonlító elemzését. (4) Elemeztük a felszínborítottság évtizedes skálájú változásai nyomán létrejövő hatásokat. (5) Az NDVI mezők idősorainak tendencia-elemzése megtörtént a NOAA-műholdképek alapján, s matematikai statisztikai eljárások felhasználásával összehasonlítottuk a városi és az azokat körülvevő vidéki régiókat. | More than half of the world population are living in large urban agglomerations. Therefore, an increasing demand appeared for measuring, modelling and forecasting the urban climate, and minimalize or even possibly avoid the negative effects of the urban environment in the planning and building phases of new industrial investments or construction of new residential areas. In our research fine resolution satellite data sets are used, as well, as data sets from digital elevation models and land use/land cover characteristics. The following tasks have been accomplished. (1) Analyses of the structure of urban heat island (UHI) effect in several cities of Hungary and Central Europe on the base of fine resolution satellite images of sensor MODIS on-board satellites Terra and Aqua (with 1 km spatial resolution). (2) Evaluation of UHI structure of Budapest and other 9 Hungarian large cities depending on seasons, topography, and land cover. (3) Comparison of algorithms for determining surface temperature based on NOAA/AVHRR measurements. (4) Tendency analysis of decadal land cover change in the Carpathian basin. (5) Tendency analysis of NDVI fields on the base of NOAA/AVHRR data, and comparison of urban and rural regions using mathematical statistical methods

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications

Effects of Time-Varying Relative Spectral Response on the Calibration of MODIS Reflective Solar Bands

Calibration of the on-orbit gain changes of the narrow bandwidth reflective solar bands (RSB) of Terra and Aqua MODIS is usually based on the band center wavelength. The relative spectral response (RSR) of each band is assumed to be constant on orbit and the time dependence of an overall gain factor is calculated. Any on-orbit changes to the RSR of the MODIS bands will introduce some error into the calibration and may also have an impact on the Earth scene radiance retrieval. We consider two different ways to track how the RSR of the MODIS RSB may be changing on orbit, and the effect that these changes will have on the calibration. First, we examine in-band RSR measurements from the spectro-radiometric calibration assembly (SRCA) carried on-board both MODIS instruments. Second, we study the broadband degradation of the MODIS scan mirror and how it may be changing the effective out-of-band response of the RSB. We find that RSR changes have a small effect on the radiance calibrated using the on-board solar diffuser, generally less than 0.5% in all cases at any time in the missions, with bands 1, 8, and 9 impacted the most

Modelowanie dopływu promieniowania słonecznego do obszarów o urozmaiconej rzeźbie terenu w systemach informacji geograficznej

The inflow of solar radiation to the active surface is among the crucial factors determining its radiation balance and thus the climate conditions. Due to limited research and a multitude of surfaces, the determination of the spatial distribution of solar radiation on the basis of in situ research is hampered. Therefore actinometrical models are used to calculate the value of solar irradiance with reference to digital elevation models. Two actinometrical models were described: r.sun implemented in the GRASS GIS software and the Area Solar Radiation (ARS) provided in the ArcMap program, a part of the ArcGIS package. A digital elevation model of the East Carpathian Mountains in Romania was used as entry data for the above described models and a comparative analysis of the following characteristics was performed: total solar irradiance, direct irradiance, diffused irradiance and direct daylight duration. It was determined that despite the fact that both actinometrical models show different values of solar irradiance for the same area, they reflect similar spatial distributions. While both models are deemed valid tools for calculating solar radiation in mountainous areas, elementary knowledge of the tools is a must in order to use the results in an informed and responsible way.777977Badania Fizjograficzn

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

Parallax correction in collocating CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) observations: Method and application to convection study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95467/1/jgrd17318.pd

VIIRS On-Orbit Optical Anomaly - Investigation, Analysis, Root Cause Determination and Lessons Learned

A gradual, but persistent, decrease in the optical throughput was detected during the early commissioning phase for the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imager Radiometer Suite (VIIRS) Near Infrared (NIR) bands. Its initial rate and unknown cause were coincidently coupled with a decrease in sensitivity in the same spectral wavelength of the Solar Diffuser Stability Monitor (SDSM) raising concerns about contamination or the possibility of a system-level satellite problem. An anomaly team was formed to investigate and provide recommendations before commissioning could resume. With few hard facts in hand, there was much speculation about possible causes and consequences of the degradation. Two different causes were determined as will be explained in this paper. This paper will describe the build and test history of VIIRS, why there were no indicators, even with hindsight, of an on-orbit problem, the appearance of the on-orbit anomaly, the initial work attempting to understand and determine the cause, the discovery of the root cause and what Test-As-You-Fly (TAYF) activities, can be done in the future to greatly reduce the likelihood of similar optical anomalies. These TAYF activities are captured in the lessons learned section of this paper

Differentiation of Soil Conditions over Low Relief Areas Using Feedback Dynamic Patterns

In many areas, such as plains and gently undulating terrain, easy-to-measure soil-firming factors such as landform and vegetation do not co-vary with soil conditions across space to the level that they can be effectively used in digital soil mapping. A challenging problem is how to develop a new environmental variable that co-varies with soil spatial variation under these situations. This study examined the idea that change patterns (dynamic feedback patterns) of the land surface, such as those captured daily by remote sensing images during a short period (6-7 d) after a major rain event, can be used to differentiate soil types. To examine this idea, we selected two study areas with different climates: one in northeastern China and the other in northwestern China. Images from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to capture land surface feedback, To measure feedback dynamics, we used spectral information divergence (SID). Results of an independent-samples t-test showed that there was a significant difference in SID values between pixel pairs of the same soil subgroup and those of different subgroups. This indicated that areas with different soil types (subgroup level) exhibited significantly different dynamic feedback patterns, and areas within the same soil type have similar dynamic feedback patterns. It was also found that the more similar the soil types, the more similar the feedback patterns. These findings could lead to the development of a new environmental covariate that could be used to improve the accuracy of soil mapping in low-relief areas. © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA All rights reserved

Differentiation of Soil Conditions over Low Relief Areas Using Feedback Dynamic Patterns

In many areas, such as plains and gently undulating terrain, easy-to-measure soil-forming factors such as landform and vegetation do not co-vary with soil conditions across space to the level that they can be effectively used in digital soil mapping. A challenging problem is how to develop a new environmental variable that co-varies with soil spatial variation under these situations. This study examined the idea that change patterns (dynamic feedback patterns) of the land surface, such as those captured daily by remote sensing images during a short period (6-7 d) after a major rain event, can be used to differentiate soil types. To examine this idea, we selected two study areas with different climates: one in northeastern China and the other in northwestern China. Images from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to capture land surface feedback. To measure feedback dynamics, we used spectral information divergence (SID). Results of an independent-samples t-test showed that there was a significant difference in SID values between pixel pairs of the same soil subgroup and those of different subgroups. This indicated that areas with different soil types (subgroup level) exhibited significantly different dynamic feedback patterns, and areas within the same soil type have similar dynamic feedback patterns. It was also found that the more similar the soil types, the more similar the feedback patterns. These findings could lead to the development of a new environmental covariate that could be used to improve the accuracy of soil snapping in low-relief areas