scholarly journals Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements

2020 ◽  
Vol 12 (4) ◽  
pp. 616 ◽  
Author(s):  
Krista Alikas ◽  
Ilmar Ansko ◽  
Viktor Vabson ◽  
Ave Ansper ◽  
Kersti Kangro ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Field Measurements ◽  
Ground Truth ◽  
Local Data ◽  
Ground Truth Data ◽  
In Situ Data ◽  
Global Coverage

The Sentinel-3 mission launched its first satellite Sentinel-3A in 2016 to be followed by Sentinel-3B and Sentinel-3C to provide long-term operational measurements over Earth. Sentinel-3A and 3B are in full operational status, allowing global coverage in less than two days, usable to monitor optical water quality and provide data for environmental studies. However, due to limited ground truth data, the product quality has not yet been analyzed in detail with the fiducial reference measurement (FRM) dataset. Here, we use the fully characterized ground truth FRM dataset for validating Sentinel-3A Ocean and Land Colour Instrument (OLCI) radiometric products over optically complex Estonian inland waters and Baltic Sea coastal areas. As consistency between satellite and local data depends on uncertainty in field measurements, filtering of the in situ data has been made based on the uncertainty for the final comparison. We have compared various atmospheric correction methods and found POLYMER (POLYnomial-based algorithm applied to MERIS) to be most suitable for optically complex waters under study in terms of product accuracy, amount of usable data and also being least influenced by the adjacency effect.

scholarly journals Identification of Crop Type in Crowdsourced Road View Photos with Deep Convolutional Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1165
Author(s):  
Fangming Wu ◽  
Bingfang Wu ◽  
Miao Zhang ◽  
Hongwei Zeng ◽  
Fuyou Tian
Keyword(s):  
State Of The Art ◽  
Ground Truth ◽  
Decision Fusion ◽  
Identification Accuracy ◽  
Deep Convolutional Neural Networks ◽  
Ground Truth Data ◽  
In Situ Data ◽  
Crop Type ◽  
Crop Types

In situ ground truth data are an important requirement for producing accurate cropland type map, and this is precisely what is lacking at vast scales. Although volunteered geographic information (VGI) has been proven as a possible solution for in situ data acquisition, processing and extracting valuable information from millions of pictures remains challenging. This paper targets the detection of specific crop types from crowdsourced road view photos. A first large, public, multiclass road view crop photo dataset named iCrop was established for the development of crop type detection with deep learning. Five state-of-the-art deep convolutional neural networks including InceptionV4, DenseNet121, ResNet50, MobileNetV2, and ShuffleNetV2 were employed to compare the baseline performance. ResNet50 outperformed the others according to the overall accuracy (87.9%), and ShuffleNetV2 outperformed the others according to the efficiency (13 FPS). The decision fusion schemes major voting was used to further improve crop identification accuracy. The results clearly demonstrate the superior accuracy of the proposed decision fusion over the other non-fusion-based methods in crop type detection of imbalanced road view photos dataset. The voting method achieved higher mean accuracy (90.6–91.1%) and can be leveraged to classify crop type in crowdsourced road view photos.

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

scholarly journals Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness

2020 ◽  
Vol 12 (4) ◽  
pp. 650
Author(s):  
Pablo Sánchez-Gámez ◽  
Carolina Gabarro ◽  
Antonio Turiel ◽  
Marcos Portabella
Keyword(s):  
Soil Moisture ◽  
Sea Ice ◽  
Brightness Temperature ◽  
European Space Agency ◽  
Ground Truth ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
In Situ Data ◽  
L Band

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.

scholarly journals Rainfall Estimates on a Gridded Network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016

2020 ◽  
Vol 24 (2) ◽  
pp. 919-943 ◽  
Author(s):  
Steefan Contractor ◽  
Markus G. Donat ◽  
Lisa V. Alexander ◽  
Markus Ziese ◽  
Anja Meyer-Christoffer ◽  
...  
Keyword(s):  
Daily Precipitation ◽  
In Situ Data ◽  
Global Precipitation Climatology Centre ◽  
Historical Climatology ◽  
Global Land ◽  
Global Historical Climatology Network ◽  
Global Precipitation ◽  
Rainfall Estimates

Abstract. We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network – REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were quality-controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area-average estimates of daily precipitation for global land areas on a 1∘ × 1∘ latitude–longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets.

scholarly journals Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters

2019 ◽  
Vol 11 (19) ◽  
pp. 2297 ◽  
Author(s):  
Kristi Uudeberg ◽  
Ilmar Ansko ◽  
Getter Põru ◽  
Ave Ansper ◽  
Anu Reinart
Keyword(s):  
Remote Sensing ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Suspended Sediments ◽  
Reflectance Spectra ◽  
Water Type ◽  
Colored Dissolved Organic Matter ◽  
Water Color ◽  
Sentinel 2

The European Space Agency’s Copernicus satellites Sentinel-2 and Sentinel-3 provide observations with high spectral, spatial, and temporal resolution which can be used to monitor inland and coastal waters. Such waters are optically complex, and the water color may vary from completely clear to dark brown. The main factors influencing water color are colored dissolved organic matter, phytoplankton, and suspended sediments. Recently, there has been a growing interest in the use of the optical water type (OWT) classification in the remote sensing of ocean color. Such classification helps to clarify relationships between different properties inside a certain class and quantify variation between classes. In this study, we present a new OWT classification based on the in situ measurements of reflectance spectra for boreal region lakes and coastal areas without extreme optical conditions. This classification divides waters into five OWT (Clear, Moderate, Turbid, Very Turbid, and Brown) and shows that different OWTs have different remote sensing reflectance spectra and that each OWT is associated with a specific bio-optical condition. Developed OWTs are distinguishable by both the MultiSpectral Instrument (MSI) and the Ocean and Land Color Instrument (OLCI) sensors, and the accuracy of the OWT assignment was 95% for both the MSI and OLCI bands. To determine OWT from MSI images, we tested different atmospheric correction (AC) processors, namely ACOLITE, C2RCC, POLYMER, and Sen2Cor and for OLCI images, we tested AC processors ALTNNA, C2RCC, and L2. The C2RCC AC processor was the most accurate and reliable for use with MSI and OLCI images to estimate OWTs.

scholarly journals Mass balance of Trambau Glacier, Rolwaling region, Nepal Himalaya: in-situ observations, long-term reconstruction and mass-balance sensitivity

2019 ◽  
Vol 65 (252) ◽  
pp. 605-616 ◽  
Author(s):  
SOJIRO SUNAKO ◽  
KOJI FUJITA ◽  
AKIKO SAKAI ◽  
RIJAN B. KAYASTHA
Keyword(s):  
Mass Balance ◽  
High Elevation ◽  
Climatic Conditions ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Balance Study ◽  
Nepal Himalaya ◽  
In Situ Data

ABSTRACTWe conducted a mass-balance study of debris-free Trambau Glacier in the Rolwaling region, Nepal Himalaya, which is accessible to 6000 m a.s.l., to better understand mass-balance processes and the effect of precipitation on these processes on high-elevation Himalayan glaciers. Continuous in situ meteorological and mass-balance observations that spanned the three melt seasons from May 2016 are reported. An energy- and mass-balance model is also applied to evaluate its performance and sensitivity to various climatic conditions. Glacier-wide mass balances ranging from −0.34 ± 0.38 m w.e. in 2016 to −0.82 ± 0.53 m w.e. in 2017/18 are obtained by combining the observations with model results for the areas above the highest stake. The estimated long-term glacier mass balance, which is reconstructed using the ERA-Interim data calibrated with in situ data, is −0.65 ± 0.39 m w.e. a−1for the 1980–2018 period. A significant correlation with annual precipitation (r= 0.77,p< 0.001) is observed, whereas there is no discernible correlation with summer mean air temperature. The results indicate the continuous mass loss of Trambau Glacier over the last four decades, which contrasts with the neighbouring Mera Glacier in balance.

scholarly journals West African Summer Monsoon Precipitation Variability as Represented by Reanalysis Datasets

Climate ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 111
Author(s):  
Kwesi Akumenyi Quagraine ◽  
Francis Nkrumah ◽  
Cornelia Klein ◽  
Nana Ama Browne Klutse ◽  
Kwesi Twentwewa Quagraine
Keyword(s):  
Summer Monsoon ◽  
Southern Oscillation ◽  
West African Monsoon ◽  
West African ◽  
Positive Trend ◽  
In Situ Data ◽  
Dry Conditions ◽  
Long Term Trends

Focusing on West Africa, a region riddled with in situ data scarcity, we evaluate the summer monsoon monthly rainfall characteristics of five global reanalysis datasets: ERA5, ERA-Interim, JRA-55, MERRA2, and NCEP-R2. Their performance in reproducing the West African monsoon (WAM) climatology, interannual variability, and long-term trends for the main monsoon months are compared to gauge-only and satellite products. We further examine their ability to reproduce teleconnections between sea surface temperatures and monsoon rainfall. All reanalyses are able to represent the average rainfall patterns and seasonal cycle; however, regional biases can be marked. ERA5, ERA-Interim, and NCEP-R2 underestimate rainfall over areas of peak rainfall, with ERA5 showing the strongest underestimation, particularly over the Guinea Highlands. The meridional northward extent of the monsoon rainband is well captured by JRA-55 and MERRA2 but is too narrow in ERA-Interim, for which rainfall stays close to the Guinea Coast. Differences in rainband displacement become particularly evident when comparing strong El Niño Southern Oscillation (ENSO) years, where all reanalyses except ERA-Interim reproduce wetter Sahelian conditions for La Niña, while overestimating dry conditions at the coast except for NCEP-R2. Precipitation trends are not coherent across reanalyses and magnitudes are generally overestimated compared to observations, with only JRA-55 and NCEP-R2 displaying the expected positive trend in the Sahel. ERA5 generally outperforms ERA-Interim, highlighting clear improvements over its predecessor. Ultimately, we find the strengths of reanalyses to strongly vary across the region.

Field Study on Pump Vibration and ISO’s New Criteria

1999 ◽  
Vol 121 (4) ◽  
pp. 798-803 ◽  
Author(s):  
Toshiyuki Osada ◽  
Takashi Kawakami ◽  
Tadashi Yokoi ◽  
Yoshinobu Tsujimoto
Keyword(s):  
Rotational Speed ◽  
Work Group ◽  
Field Measurements ◽  
Rotating Machinery ◽  
International Organization ◽  
Vibration Level ◽  
Term Operation ◽  
New Criteria

ISO 10816-3 (a new standard of International Organization for Standardization) was established as vibration criteria for industrial rotating machinery based on the bearing housing vibration in situ. The appropriateness of the application of the proposed vibration criteria to pumps was discussed and studied by a work group in Japan. For the assessment, the data of vibration level in field were measured, and the effects of driver output, rotational speed, and pump type were studied. This paper describes the applicability of the new ISO criteria to the evaluation of vibration level of pumps, based on the results of the field measurements. It was found that the new boundaries of evaluation zones, which are acceptable for unrestricted long-term operation of pumps, are quite appropriate and satisfactory.

scholarly journals A comparison of empirical and physically based glacier surface melt models for long-term simulations of glacier response

2014 ◽  
Vol 60 (224) ◽  
pp. 1140-1154 ◽  
Author(s):  
Jeannette Gabbi ◽  
Marco Carenzo ◽  
Francesca Pellicciotti ◽  
Andreas Bauder ◽  
Martin Funk
Keyword(s):  
Shortwave Radiation ◽  
Radiation Balance ◽  
Volume Changes ◽  
Glacier Surface ◽  
Surface Evolution ◽  
Ice Volume ◽  
In Situ Data ◽  
Physically Based

AbstractWe investigate the performance of five glacier melt models over a multi-decadal period in order to assess their ability to model future glacier response. The models range from a simple degree-day model, based solely on air temperature, to more-sophisticated models, including the full shortwave radiation balance. In addition to the empirical models, the performance of a physically based energy-balance (EB) model is examined. The melt models are coupled to an accumulation and a surface evolution model and applied in a distributed manner to Rhonegletscher, Switzerland, over the period 1929–2012 at hourly resolution. For calibration, seasonal mass-balance measurements (2006–12) are used. Decadal ice volume changes for six periods in the years 1929–2012 serve for model validation. Over the period 2006–12, there are almost no differences in performance between the models, except for EB, which is less consistent with observations, likely due to lack of meteorological in situ data. However, simulations over the long term (1929–2012) reveal that models which include a separate term for shortwave radiation agree best with the observed ice volume changes, indicating that their melt relationships are robust in time and thus suitable for long-term modelling, in contrast to more empirical approaches that are oversensitive to temperature fluctuations.

scholarly journals Evaluation of MODIS Albedo Product over Ice Caps in Iceland and Impact of Volcanic Eruptions on Their Albedo

2017 ◽  
Author(s):  
Simon Gascoin ◽  
Sverrir Guðmundsson ◽  
Guðfinna Aðalgeirsdóttir ◽  
Finnur Pálsson ◽  
Louise Schmidt ◽  
...  
Keyword(s):  
Correlation Coefficients ◽  
Field Measurements ◽  
Volcanic Eruptions ◽  
Ground Truth ◽  
Climate Forcing ◽  
Balance Model ◽  
Ice Caps ◽  
Good Ability ◽  
Mean Square Errors

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnaj&ouml;kull and Langj&ouml;kull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallaj&ouml;kull and Gr&iacute;msv&ouml;tn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangaj&ouml;kull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

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