scholarly journals Development of Land Surface Albedo Algorithm for the GK-2A/AMI Instrument

2020 ◽  
Vol 12 (15) ◽  
pp. 2500
Author(s):  
Kyeong-Sang Lee ◽  
Sung-Rae Chung ◽  
Changsuk Lee ◽  
Minji Seo ◽  
Sungwon Choi ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Monsoon Season ◽  
Atmospheric Correction ◽  
Optimization Method ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Temporal Consistency ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Mean Square Errors

The Korea Meteorological Administration successfully launched Korea’s next-generation meteorological satellite, Geo-KOMPSAT-2A (GK-2A), on 5 December 2018. It belongs to the new generation of GEO (Geostationary Elevation Orbit) satellite which offers capabilities to disseminate high spatial- (0.5–2 km) and high temporal-resolution (10 min) observations over a broad area, herein a geographic disk encompassing the Asia–Oceania region. The targeted objective is to enhance our understanding of climate change, owing to a bulk of coherent observations. For such, we developed an algorithm to map the land surface albedo (LSA), which is a major Essential Climate Variable (ECV). The retrieval algorithm devoted to GK-2A/Advanced Meteorological Imager (AMI) data considered Japan’s Himawari-8/Advanced Himawari Imager (AHI) data for prototyping, as this latter owns similar specifications to AMI. Our proposed algorithm is decomposed in three major steps: atmospheric correction, bidirectional reflectance distribution function (BRDF) modeling and angular integration, and narrow-to-broadband conversion. To perform BRDF modeling, the optimization method using normalized reflectance was applied, which improved the quality of BRDF modeling results, particularly when the number of observations was less than 15. A quality assessment was performed to compare our results to those of Moderate Resolution Imaging Spectroradiometer (MODIS) LSA products and ground measurement from Aerosol Robotic Network (AERONET) sites, Australian and New Zealand flux tower network (OzFlux) site and the Korea Flux Network (KoFlux) site from throughout 2017. Our results show dependable spatial and temporal consistency with MODIS broadband LSA data, and rapid changes in LSA due to snowfall and snow melting were well expressed in the temporal profile of our results. Our outcomes also show good agreement with the ground measurements from AERONET, OzFlux and KoFlux ground-based network with root mean square errors (RMSE) of 0.0223 and 0.0306, respectively, which is close to the accuracy of MODIS broadband LSA. Moreover, our results reveal still more reliable LSA products even when clouds are frequently present, such as during the summer monsoon season. It shows that our results are useful for continuous LSA monitoring.

scholarly journals A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

2013 ◽  
Vol 17 (6) ◽  
pp. 2121-2129 ◽  
Author(s):  
N. F. Liu ◽  
Q. Liu ◽  
L. Z. Wang ◽  
S. L. Liang ◽  
J. G. Wen ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Critical Role ◽  
Radiant Energy ◽  
High Temporal Resolution ◽  
Land Surface Parameter ◽  
Temporal Filter ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

scholarly journals A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States

2011 ◽  
Vol 11 (4) ◽  
pp. 12519-12560
Author(s):  
H. Zhang ◽  
A. Lyapustin ◽  
Y. Wang ◽  
S. Kondragunta ◽  
I. Laszlo ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
The United States ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Western Us ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polar Orbiting Satellite

Abstract. Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to seasonal average BRDF in the 2.1 μm channel from MODIS. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of the AOD and surface reflectance retrievals are evaluated through comparison against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US. They are comparable to the GASP retrievals in the eastern-central sites and are more accurate than GASP retrievals in the western sites. In the western US where surface reflectance is high, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

scholarly journals Developing Land Surface Directional Reflectance and Albedo Products from Geostationary GOES-R and Himawari Data: Theoretical Basis, Operational Implementation, and Validation

2019 ◽  
Vol 11 (22) ◽  
pp. 2655 ◽  
Author(s):  
He ◽  
Zhang ◽  
Liang ◽  
Yu ◽  
Wang
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Infrared Imaging ◽  
Atmospheric Correction ◽  
Satellite Observation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Operational Environment ◽  
Mean Square Errors ◽  
Directional Reflectance

The new generation of geostationary satellite sensors is producing an unprecedented amount of Earth observations with high temporal, spatial and spectral resolutions, which enable us to detect and assess abrupt surface changes. In this study, we developed the land surface directional reflectance and albedo products from Geostationary Operational Environment Satellite-R (GOES-R) Advanced Baseline Imager (ABI) data using a method that was prototyped with the Moderate Resolution Imaging Spectroradiometer (MODIS) data in a previous study, and was also tested with data from the Advanced Himawari Imager (AHI) onboard Himawari-8. Surface reflectance is usually retrieved through atmospheric correction that requires the input of aerosol optical depth (AOD). We first estimated AOD and the surface bidirectional reflectance factor (BRF) model parameters simultaneously based on an atmospheric radiative transfer formulation with surface anisotropy, and then calculated the “blue-sky” surface broadband albedo and directional reflectance. This algorithm was implemented operationally by the National Oceanic and Atmospheric Administration (NOAA) to generate the GOES-R land surface albedo product suite with a daily updated clear-sky satellite observation database. The “operational” land surface albedo estimation from ABI and AHI data was validated against ground measurements at the SURFRAD sites and OzFlux sites and compared with the existing satellite products, including MODIS, Visible infrared Imaging Radiometer (VIIRS), and Global Land Surface Satellites (GLASS) albedo products, where good agreement was found with bias values of −0.001 (ABI) and 0.020 (AHI) and root-mean-square-errors (RMSEs) less than 0.065 for the hourly albedo estimation. Directional surface reflectance estimation, evaluated at more than 74 sites from the Aerosol Robotic Network (AERONET), was proven to be reliable as well, with an overall bias very close to zero and RMSEs within 0.042 (ABI) and 0.039 (AHI). Results show that the albedo and reflectance estimation can satisfy the NOAA accuracy requirements for operational climate and meteorological applications.

scholarly journals A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States

2011 ◽  
Vol 11 (23) ◽  
pp. 11977-11991 ◽  
Author(s):  
H. Zhang ◽  
A. Lyapustin ◽  
Y. Wang ◽  
S. Kondragunta ◽  
I. Laszlo ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Correlation Coefficients ◽  
The United States ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polar Orbiting Satellite

Abstract. Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 μm channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

scholarly journals Land Surface Albedo Derived on a Ten Daily Basis from Meteosat Second Generation Observations: the NRT and Climate Data Record Collections from the EUMETSAT LSA SAF

2018 ◽  
Author(s):  
Dominique Carrer ◽  
Suman Moparthy ◽  
Gabriel Lellouch ◽  
Xavier Ceamanos ◽  
Florian Pinault ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Second Generation ◽  
Weather Prediction ◽  
Atmospheric Correction ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Geostationary Satellites ◽  
Data Record ◽  
Climate Data Record

Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT, a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the SEVIRI instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day ALbedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a Climate Data Record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: one for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites.

scholarly journals Assessment of the EUMETSAT Multi Decadal Land Surface Albedo Data Record from Meteosat Observations

2021 ◽  
Vol 13 (10) ◽  
pp. 1992
Author(s):  
Alessio Lattanzio ◽  
Michael Grant ◽  
Marie Doutriaux-Boucher ◽  
Rob Roebeling ◽  
Jörg Schulz
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Time Range ◽  
Essential Variable ◽  
Spatial Coverage ◽  
Data Record ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask ◽  
Cloud Screening

Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record.

scholarly journals Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

2015 ◽  
Vol 9 (5) ◽  
pp. 1879-1893 ◽  
Author(s):  
K. Atlaskina ◽  
F. Berninger ◽  
G. de Leeuw
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Snow Cover Fraction ◽  
Air Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

scholarly journals Albedo over rough snow and ice surfaces

2014 ◽  
Vol 8 (3) ◽  
pp. 1069-1086 ◽  
Author(s):  
S. Lhermitte ◽  
J. Abermann ◽  
C. Kinnard
Keyword(s):  
Complex Terrain ◽  
Surface Albedo ◽  
Sampling Bias ◽  
Mountain Glaciers ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Sampling Biases ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Mean Square Errors ◽  
Effect Of Surface

Abstract. Both satellite and ground-based broadband albedo measurements over rough and complex terrain show several limitations concerning feasibility and representativeness. To assess these limitations and understand the effect of surface roughness on albedo, firstly, an intrasurface radiative transfer (ISRT) model is combined with albedo measurements over different penitente surfaces on Glaciar Tapado in the semi-arid Andes of northern Chile. Results of the ISRT model show effective albedo reductions over the penitentes up to 0.4 when comparing the rough surface albedo relative to the albedo of the flat surface. The magnitude of these reductions primarily depends on the opening angles of the penitentes, but the shape of the penitentes and spatial variability of the material albedo also play a major role. Secondly, the ISRT model is used to reveal the effect of using albedo measurements at a specific location (i.e., apparent albedo) to infer the true albedo of a penitente field (i.e., effective albedo). This effect is especially strong for narrow penitentes, resulting in sampling biases of up to ±0.05. The sampling biases are more pronounced when the sensor is low above the surface, but remain relatively constant throughout the day. Consequently, it is important to use a large number of samples at various places and/or to locate the sensor sufficiently high in order to avoid this sampling bias of surface albedo over rough surfaces. Thirdly, the temporal evolution of broadband albedo over a penitente-covered surface is analyzed to place the experiments and their uncertainty into a longer temporal context. Time series of albedo measurements at an automated weather station over two ablation seasons reveal that albedo decreases early in the ablation season. These decreases stabilize from February onwards with variations being caused by fresh snowfall events. The 2009/2010 and 2011/2012 seasons differ notably, where the latter shows lower albedo values caused by larger penitentes. Finally, a comparison of the ground-based albedo observations with Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer)-derived albedo showed that both satellite albedo products capture the albedo evolution with root mean square errors of 0.08 and 0.15, respectively, but also illustrate their shortcomings related to temporal resolution and spatial heterogeneity over small mountain glaciers.

Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements

2011 ◽  
Vol 50 (6) ◽  
pp. 1225-1235 ◽  
Author(s):  
Zhigang Yao ◽  
Jun Li ◽  
Jinlong Li ◽  
Hong Zhang
Keyword(s):  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Retrieval Algorithm ◽  
Surface Emissivity ◽  
Angle Dependence ◽  
Infrared Radiance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

scholarly journals MODIS-Derived Spatially Complete Surface Albedo Products: Spatial and Temporal Pixel Distribution and Zonal Averages

2008 ◽  
Vol 47 (11) ◽  
pp. 2879-2894 ◽  
Author(s):  
Eric G. Moody ◽  
Michael D. King ◽  
Crystal B. Schaaf ◽  
Steven Platnick
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Temporal Distribution ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Qualitative Comparison ◽  
Annual Cycles ◽  
Satellite Platform ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Five years (2000–04) of spatially complete snow-free land surface albedo data have been produced using high-quality-flagged diffuse bihemispherical (white sky) and direct-beam directional hemispherical (black sky) land surface albedo data derived from observations taken by the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument aboard the NASA Terra satellite platform (MOD43B3, collection 4). In addition, a spatially complete snow-free aggregate albedo climatological product was generated. These spatially complete products were prepared using an ecosystem-dependent temporal interpolation technique that retrieves missing data within 3%–8% error. These datasets have already been integrated into research and operational projects that require snow-free land surface albedo. As such, this paper provides details regarding the spatial and temporal distribution of the filled versus the original MOD43B3 data. The paper also explores the intra- and interannual variation in the 5-yr data record and provides a qualitative comparison of zonal averages and annual cycles of the filled versus the original MOD43B3 data. The analyses emphasize the data’s inter- and intraannual variation and show that the filled data exhibit large- and small-scale phenological behavior that is qualitatively similar to that of the original MOD43B3. These analyses thereby serve to showcase the inherent spectral, spatial, and temporal variability in the MOD43B3 data as well as the ability of the fill technique to preserve these unique regional and pixel-level phenological characteristics.

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