scholarly journals Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

2018 ◽  
Vol 10 (10) ◽  
pp. 1641 ◽  
Author(s):  
Justin Murfitt ◽  
Laura Brown ◽  
Stephen Howell
Keyword(s):  
Microwave Remote Sensing ◽  
Absolute Error ◽  
In Situ Monitoring ◽  
Lake Ice ◽  
Local Climate ◽  
Ice Surface ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Phenology

Lake ice is an important component in understanding the local climate as changes in temperature have an impact on the timing of key ice phenology events. In recent years, there has been a decline in the in-situ monitoring of lake ice events in Canada and microwave remote sensing imagery from synthetic aperture radar (SAR) is more widely used due to the high spatial resolution and response of backscatter to the freezing and melting of the ice surface. RADARSAT-2 imagery was used to develop a threshold-based method for determining lake ice events for mid-latitude lakes in Central Ontario from 2008 to 2017. Estimated lake ice phenology events are validated with ground-based observations and are compared against the Moderate Resolution Imaging Spectroradiometer (MODIS band 2). The threshold-based method was found to accurately identify 12 out of 17 freeze events and 13 out of 17 melt events from 2015–2017 when compared to ground-based observations. Mean absolute errors for freeze events ranged from 2.5 to 10.0 days when compared to MODIS imagery while the mean absolute error for water clear of ice (WCI) ranged from 1.5 to 7.1 days. The method is important for the study of mid-latitude lake ice due to its unique success in detecting multiple freeze and melting events throughout the ice season.

scholarly journals Investigation of the ice surface albedo in the Tibetan Plateau lakes based on the field observation and MODIS products

2018 ◽  
Vol 64 (245) ◽  
pp. 506-516 ◽  
Author(s):  
ZHAOGUO LI ◽  
YINHUAN AO ◽  
SHIHUA LYU ◽  
JIAHE LANG ◽  
LIJUAN WEN ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Time Windows ◽  
The Tibetan Plateau ◽  
Lake Ice ◽  
Ice Surface ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Surface Temperature ◽  
Relationship Of

ABSTRACTThe Tibetan Plateau (TP) lakes are sensitive to climate change due to ice-albedo feedback, but almost no study has paid attention to the ice albedo of TP lakes and its potential impacts. Here we present a recent field experiment for observing the lake ice albedo in the TP, and evaluate the applicability of the Moderate Resolution Imaging Spectroradiometer (MODIS) products as well as ice-albedo parameterizations. Most of the observed lake ice albedos on TP are <0.12, and the clear blue ice albedo is only 0.075, much lower than reported in the previous studies. Even that of ice covered with snow patches is only 0.212. MOD10A1 albedo product has the best agreement with observations, followed by those of MYD10A1. MCD43A3 product is consistently higher than the observations. Due to an error of snow flag and inconsistent time windows in MCD43A2 and MCD43A3, at certain times, the albedo of the ice without snow is even higher than that covered with snow. When the solar zenith angle is not considered, there is no significant correlation between the albedo and the ice surface temperature. None of the existing ice-albedo parameterizations can reproduce well the observed relationship of the albedo and surface temperature.

scholarly journals Remote Sensing of Lake Ice Phenology across a Range of Lakes Sizes, ME, USA

2019 ◽  
Vol 11 (14) ◽  
pp. 1718 ◽  
Author(s):  
Shuai Zhang ◽  
Tamlin M. Pavelsky
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Surface Air Temperature ◽  
Absolute Error ◽  
Detection Algorithm ◽  
Lake Ice ◽  
Surface Areas ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Fraction ◽  
Ice Phenology

Remote sensing of ice phenology for small lakes is hindered by a lack of satellite observations with both high temporal and spatial resolutions. By merging multi-source satellite data over individual lakes, we present a new algorithm that successfully estimates ice freeze and thaw timing for lakes with surface areas as small as 0.13 km2 and obtains consistent results across a range of lake sizes. We have developed an approach for classifying ice pixels based on the red reflectance band of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, with a threshold calibrated against ice fraction from Landsat Fmask over each lake. Using a filter derived from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) surface air temperature product, we removed outliers in the time series of lake ice fraction. The time series of lake ice fraction was then applied to identify lake ice breakup and freezeup dates. Validation results from over 296 lakes in Maine indicate that the satellite-based lake ice timing detection algorithm perform well, with mean absolute error (MAE) of 5.54 days for breakup dates and 7.31 days for freezeup dates. This algorithm can be applied to lakes worldwide, including the nearly two million lakes with surface area between 0.1 and 1 km2.

scholarly journals Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

2015 ◽  
Vol 8 (10) ◽  
pp. 4025-4041 ◽  
Author(s):  
H.-J. Kang ◽  
J.-M. Yoo ◽  
M.-J. Jeong ◽  
Y.-I. Won
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Data Sets ◽  
High Latitudes ◽  
Ice Surface ◽  
Moderate Resolution ◽  
Microwave Sounding ◽  
Polar Oceans ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Surface Temperature

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16–24 April and 15–23 September) 2003–2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992–0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968–0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~ 2.8 ± 1.9 K decade−1) in the northern high regions (70–80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

scholarly journals Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS

2018 ◽  
Vol 10 (11) ◽  
pp. 1803 ◽  
Author(s):  
Qu Zhou ◽  
Liqiao Tian ◽  
Jian Li ◽  
Qingjun Song ◽  
Wenkai Li
Keyword(s):  
Ocean Color ◽  
Aquatic Environments ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Analysis System ◽  
Cross Calibration ◽  
Data Analysis System ◽  
Mean Square Errors ◽  
Calibration Coefficients

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.

scholarly journals MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP

2015 ◽  
Vol 8 (11) ◽  
pp. 11893-11924 ◽  
Author(s):  
B. Marchant ◽  
S. Platnick ◽  
K. Meyer ◽  
G. T. Arnold ◽  
J. Riedi
Keyword(s):  
Hydrological Cycle ◽  
Temporal Distribution ◽  
Phase Discrimination ◽  
Ice Surface ◽  
Phase Classification ◽  
Microphysical Property ◽  
Moderate Resolution ◽  
Cloud Optical Thickness ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Thermodynamic Phase

Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

scholarly journals A lake ice phenology dataset for the Northern Hemisphere based on passive microwave remote sensing

2021 ◽  
pp. 1-19
Author(s):  
Xingxing Wang ◽  
Yubao Qiu ◽  
Yixiao Zhang ◽  
Juha Lemmetyinen ◽  
Bin Cheng ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Northern Hemisphere ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Lake Ice ◽  
Passive Microwave Remote Sensing ◽  
Ice Phenology

scholarly journals The Spatial–Spectral–Environmental Extraction Endmember Algorithm and Application in the MODIS Fractional Snow Cover Retrieval

2020 ◽  
Vol 12 (22) ◽  
pp. 3693
Author(s):  
Hongyu Zhao ◽  
Xiaohua Hao ◽  
Jian Wang ◽  
Hongyi Li ◽  
Guanghui Huang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Absolute Error ◽  
Satellite Observation ◽  
Landsat 8 ◽  
Endmember Extraction ◽  
Analysis Model ◽  
Fractional Snow Cover ◽  
Extraction Algorithm ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Endmember extraction is a primary and indispensable component of the spectral mixing analysis model applicated to quantitatively retrieve fractional snow cover (FSC) from satellite observation. In this study, a new endmember extraction algorithm, the spatial–spectral–environmental (SSE) endmember extraction algorithm, is developed, in which spatial, spectral and environmental information are integrated together to automatically extract different types of endmembers from moderate resolution imaging spectroradiometer (MODIS) images. Then, combining the linear spectral mixture analysis model (LSMA), the SSE endmember extraction algorithm is practically applied to retrieve FSC from standard MODIS surface reflectance products in China. The new algorithm of MODIS FSC retrieval is named as SSEmod. The accuracy of SSEmod is quantitatively validated with 16 higher spatial-resolution FSC maps derived from Landsat 8 binary snow cover maps. Averaged over all regions, the average root-mean-square-error (RMSE) and mean absolute error (MAE) are 0.136 and 0.092, respectively. Simultaneously, we also compared the SSEmod with MODImLAB, MODSCAG and MOD10A1. In all regions, the average RMSE of SSEmod is improved by 2.3%, 2.6% and 5.3% compared to MODImLAB for 0.157, MODSCAG for 0.157 and MOD10A1 for 0.189. Therefore, our SSE endmember extraction algorithm is reliable for the MODIS FSC retrieval and may be also promising to apply other similar satellites in view of its accuracy and efficiency.

Annual mapping of large forest disturbances across Canada’s forests using 250 m MODIS imagery from 2000 to 2011

2014 ◽  
Vol 44 (12) ◽  
pp. 1545-1554 ◽  
Author(s):  
L. Guindon ◽  
P.Y. Bernier ◽  
A. Beaudoin ◽  
D. Pouliot ◽  
P. Villemaire ◽  
...  
Keyword(s):  
Validation Dataset ◽  
Commission Error ◽  
Forest Disturbances ◽  
Forest Change ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Supplementary Material ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Data Layers

Disturbances such as fire and harvesting shape forest dynamics and must be accounted for when modelling forest properties. However, acquiring timely disturbance information for all of Canada’s large forest area has always been challenging. Therefore, we developed an approach to detect annual forest change resulting from fire, harvesting, or flooding using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery at 250 m spatial resolution across Canada and to estimate the within-pixel fractional change (FC). When this approach was applied to the period from 2000 to 2011, the accuracy of detection of burnt, harvested, or flooded areas against our validation dataset was 82%, 80%, and 85%, respectively. With FC, 77% of the area burnt and 82% of the area harvested within the validation dataset were correctly identified. The methodology was optimized to reduce the commission error but tended to omit smaller disturbances as a result. For example, the omitted area for harvest blocks greater than 80 ha was less than 14% but increased to between 38% and 50% for harvest blocks of 20 to 30 ha. Detection of burnt and harvested areas in some regions was hindered by persistent haze or cloud cover or by insect outbreaks. All resulting data layers are available as supplementary material.

scholarly journals Surface albedo as a proxy for the mass balance of Greenland’s terrestrial ice

1969 ◽  
Vol 31 ◽  
pp. 91-94
Author(s):  
William Colgan ◽  
Jason E. Box ◽  
Robert S. Fausto ◽  
Dirk Van As ◽  
Valentina R. Barletta ◽  
...  
Keyword(s):  
Mass Balance ◽  
Real Time ◽  
Surface Albedo ◽  
Empirical Relation ◽  
Time Estimates ◽  
Ice Surface ◽  
Moderate Resolution ◽  
Ice Mass Balance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Satellite

Satellite observations are critical to understanding the mass balance of Greenland’s terrestrial ice (Fig. 1). The Gravity Recovery and Climate Experiment (GRACE) satellite constellation provides monthly gravimetry observations that can directly assess mass balance. Temporal data gaps have begun to appear in the GRACE record due to declining satellite function. In anticipation of further deterioration in the coverage of GRACE, we have explored an empirical relation between ice-surface albedo (or reflectance) and ice-mass balance to fill the gaps in the gravimetry record of Greenland’s ice-mass balance. As surface albedo observed by the moderate-resolution imaging spectroradiometer (MODIS) aboard the Terra satellite is available in near real-time, employing a MODISderived proxy permits near real-time estimates of Greenland ice-mass balance. The Geological Survey of Denmark and Greenland has begun employing the albedo – mass-balance relation described here to issue near real-time estimates of Greenland ice-mass balance during the summer melt season at www.polarportal.org.

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