scholarly journals Monthly-averaged maps of surface BRDF parameters in ten spectral bands for land and water masses

2018 ◽  
Author(s):  
Philippe Blanc ◽  
Benoit Gschwind ◽  
Lionel Ménard ◽  
Lucien Wald
Keyword(s):  
Original Data ◽  
Observation System ◽  
Creative Commons ◽  
Spectral Bands ◽  
The Usa ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution

Abstract. The construction of worldwide maps of surface bidirectional reflectance distribution function (BRDF) parameters is presented. The original data stems from the National Aeronautics and Space Administration (NASA) of the USA which is making available maps of BRDF parameters that are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The first parameter fiso describes the isotropic part of the BRDF while the two others fvol and fgeo describe the anisotropic part and are linked to the viewing and illuminating geometry. The original data has been averaged for each calendar month for the period 2004–2011 and a spatial completion of data was performed, especially in water-covered areas. The resulting complete maps are available in ten spectral bands: [459–479] nm, [545–565] nm, [620–670] nm, [400–700] nm, [841–876] nm, [1230–1250] nm, [1628–1652] nm, [2105–2155] nm, [250–5000] nm, [700–5000] nm, [250–5000] nm. The maps form a Global Earth Observation System of Systems (GEOSS) Data Collection of Open Resources for Everyone (Data-CORE) supporting the GEOSS Data Sharing Principles. They are referenced by the doi:10.23646/85d2cd5f-ccaa-482e-a4c9-b6e0c59d966c and available in NetCDF format under the Creative Commons license CC-BY.

scholarly journals Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework

2021 ◽  
Vol 13 (17) ◽  
pp. 3541
Author(s):  
Jianyu Zheng ◽  
Xin Huang ◽  
Supriya Sangondimath ◽  
Jianwu Wang ◽  
Zhibo Zhang
Keyword(s):  
Vital Role ◽  
Parallel Execution ◽  
Observation System ◽  
Single Node ◽  
Spectral Bands ◽  
Service Oriented ◽  
Moderate Resolution ◽  
Level 3 ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument onboard NASA’s Terra (launched in 1999) and Aqua (launched in 2002) satellite missions as part of the more extensive Earth Observation System (EOS). By measuring the reflection and emission by the Earth-Atmosphere system in 36 spectral bands from the visible to thermal infrared with near-daily global coverage and high-spatial-resolution (250 m ~ 1 km at nadir), MODIS is playing a vital role in developing validated, global, interactive Earth system models. MODIS products are processed into three levels, i.e., Level-1 (L1), Level-2 (L2) and Level-3 (L3). To shift the current static and “one-size-fits-all” data provision method of MODIS products, in this paper, we propose a service-oriented flexible and efficient MODIS aggregation framework. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements and the aggregation can run in parallel to achieve a speedup. The experiments show that our aggregation results are almost identical to the current MODIS L3 products and our parallel execution with 8 computing nodes can work 88.63 times faster than a serial code execution on a single node.

scholarly journals Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests

2021 ◽  
Vol 18 (2) ◽  
pp. 621-635
Author(s):  
Jan Pisek ◽  
Angela Erb ◽  
Lauri Korhonen ◽  
Tobias Biermann ◽  
Arnaud Carrara ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Distribution Function ◽  
Boreal Forests ◽  
Bidirectional Reflectance Distribution Function ◽  
Bidirectional Reflectance ◽  
Modis Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution

Abstract. Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing.

scholarly journals Computationally Efficient Methods of Collocating Satellite, Aircraft, and Ground Observations

2009 ◽  
Vol 26 (8) ◽  
pp. 1585-1595 ◽  
Author(s):  
Frederick W. Nagle ◽  
Robert E. Holz
Keyword(s):  
Observation System ◽  
Computationally Efficient ◽  
Laptop Computer ◽  
Geometric Problem ◽  
Temporal Sampling ◽  
Wide Range ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The usefulness of measurements from satellite-borne instruments is enhanced if these measurements can be compared to measurements from other instruments mounted aboard the same or different satellite, with measurements from aircraft, or with ground measurements. The process of associating measurements from disparate instruments and platforms is referred to as collocation. In a few cases, two instruments mounted aboard the same spacecraft have been engineered to function in tandem, but commonly this is not the case. The collocation process may then become an awkward geometric problem of finding which of many observations within one dataset corresponds to an observation in another set, possibly from another platform. This paper presents methods that can be applied to a wide range of satellite, aircraft, and surface measurements that allow for efficient collocation with measurements having varying spatial and temporal sampling. Examples of applying the methods are presented that highlight the benefits of efficient collocation. This includes identifying the occurrence of simultaneous nadir observations (SNOs); collocation of sounder, imager, and active remotely sensed measurements on the NASA Earth Observation System (EOS); and collocation of the polar orbiting imager, sounder, and microwave measurements with geostationary observations. It is possible, using an inexpensive laptop computer, to collocate Moderate Resolution Imaging Spectroradiometer (MODIS) imager observations from the Aqua satellite with geostationary observations rapidly enough to deal with these measurements in real time, making either dataset, enhanced by the other, a potentially operational product. A “tool kit” is suggested consisting of computer procedures useful in collocation.

scholarly journals Observed HIRS and MODIS High-Cloud Frequencies in the 2000s

2019 ◽  
Vol 58 (11) ◽  
pp. 2469-2478
Author(s):  
Richard A. Frey ◽  
W. Paul Menzel
Keyword(s):  
Cloud Detection ◽  
High Cloud ◽  
Clear Sky ◽  
Spectral Bands ◽  
Moderate Resolution ◽  
Summer Maximum ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Parameter ◽  
Cloud Top Pressure

AbstractThis paper compares the cloud parameter data records derived from High Resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from the years 2003 through 2013. Cloud-top pressure (CTP) and effective emissivity (εf; cloud emissivity multiplied by cloud fraction) are derived using the 15-μm spectral bands in the CO2 absorption band and implementing the CO2-slicing technique; the approach is robust for high semitransparent clouds but weak for low clouds with little thermal contrast from clear-sky radiances. The high-cloud (HiCld; with CTP less than 440 hPa) seasonal cycles of HIRS and MODIS observations are found to be in sync, but the HIRS frequency of detection is about 10% higher than that of MODIS (which is attributed to a lower threshold for cloud detection in the HIRS CO2 bands). Differences are largest during nighttime and at the beginning of the time series (2003–06). Both show Northern Hemisphere (NH) and Southern Hemisphere (SH) seasonal HiClds are out of phase and both agree within 2% on NH–SH HiCld differences. During the summer, maximum HiCld frequency averages 5% more in the NH.

scholarly journals Reconstruction of Spatiotemporally Continuous MODIS-Band Reflectance in East and South Asia from 2012 to 2015

2020 ◽  
Vol 12 (21) ◽  
pp. 3674
Author(s):  
Bo Gao ◽  
Huili Gong ◽  
Jie Zhou ◽  
Tianxing Wang ◽  
Yuanyuan Liu ◽  
...  
Keyword(s):  
South Asia ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Basic Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Intermediate Variables ◽  
Bidirectional Reflectance Distribution

To reconstruct Moderate Resolution Imaging Spectroradiometer (MODIS) band reflectance with optimal spatiotemporal continuity, three bidirectional reflectance distribution function (BRDF) models—the Ross-Thick-Li-Sparse Reciprocal (RTLSR) model, Gao model, and adjusted BF model—were used to retrieve MODIS-band reflectance for cloudy MODIS pixels according to different inversion conditions with a proposed filling algorithm. Then, a spatiotemporally continuous MODIS-band reflectance dataset for most of Asia with more than 98% spatiotemporal coverage was reconstructed from 2012 to 2015. The validation highlighted an evident improvement in filling cloudy MODIS observations; a reasonable spatial distribution, such as in South Asia and Southeast Asia; and acceptable precision for the filled MODIS pixels, with the root mean square error percentage (RMSE%) at 9.7–9.8% and 12–16% for the Gao and adjusted BF models, respectively. In the course of reconstructing the spatiotemporal continuous MODIS-band reflectance, the differences among the three models were discussed further. For a 16-day period with a stable and unchanged land surface, the RTLSR model, as a basic model, accurately derived land surface reflectance (no more than 10% RMSE% for MCD43C1 V006 band 1) and outperformed the other two models. When the inversion period is sufficiently long (e.g., 108 days, 188 days, 268 days, or a full year), the Gao/adjusted BF model provides better precision than the RTLSR model by considering the normalized difference vegetation index (NDVI) and soil moisture/NDVI as intermediate variables used to adjust the BRDF parameters in real time. The Gao model is optimal when the inversion period is sufficiently long. Based on combining the RTLSR model and Gao/adjusted BF model, we proposed a filling algorithm to derive a dataset of MODIS-band reflectance with optimal spatiotemporal continuity.

scholarly journals Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland

2017 ◽  
Vol 11 (4) ◽  
pp. 1575-1589 ◽  
Author(s):  
John Faulkner Burkhart ◽  
Arve Kylling ◽  
Crystal B. Schaaf ◽  
Zhuosen Wang ◽  
Wiley Bogren ◽  
...  
Keyword(s):  
Unmanned Aerial System ◽  
Fundamental Parameter ◽  
Surface Reflectance ◽  
Bidirectional Reflectance ◽  
Clear Sky ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution ◽  
Reflectance Measurements

Abstract. Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300–920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

scholarly journals Cloud Detection of MODIS Multispectral Images

2014 ◽  
Vol 31 (2) ◽  
pp. 347-365 ◽  
Author(s):  
Loredana Murino ◽  
Umberto Amato ◽  
Maria Francesca Carfora ◽  
Anestis Antoniadis ◽  
Bormin Huang ◽  
...  
Keyword(s):  
Real Data ◽  
Cloud Detection ◽  
Infrared Sensors ◽  
Modis Data ◽  
Spectral Bands ◽  
Local Methods ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask

Abstract Methods coming from statistics and pattern recognition to estimate the cloud mask from radiance measured by visible and infrared sensors on board satellites are gaining greater consideration for their ability to properly exploit the increasing number of channels available with current and next-generation sensors. Endowed with physical arguments, they give rise to robust methods for accurately estimating the cloud mask. Application of such classification methods to Moderate Resolution Imaging Spectroradiometer (MODIS) data is discussed in this paper. Three different types of MODIS datasets are considered: synthetic (radiance is simulated by proper radiative transfer models); annotated (real MODIS data labeled by a meteorologist as clear or cloudy); and real MODIS data, whose truth is obtained from the official MODIS cloud mask product. A full assessment of the MODIS spectral bands is performed, aimed at understanding the role of the spectral bands in detecting clouds and at achieving top performance with very few properly chosen spectral channels. Local methods that use spatial correlation of images to improve classification, reducing the pseudonuisance of nonlocal methods, have also been tested on real data.

Sign in / Sign up

Export Citation Format

Share Document