REMOTE SENSING OF CLOUD BOTTOM HEIGHT AND CLOUD TEMPERATURE BY INFRARED RADIOMETER

The feasibility of retrieving cloud bottom height (CBH) and cloud bottom temperature (CBT) by infrared radiometer has been studied by simulations with a large number of historical radiosounding data and field obser- vations.The results show that it is feasible to retrieve CBH and CBT by radiometer observation in infrared band. In this paper we also demonstrate simply that through joint observations by a dual-wavelength (1.35 cm and 8.5mm) microwave radiometer and by infrared radiometer (8.5—12.5μm),it is possible to obtain total water vapor,liquid water content in clouds and CBH and CBT.

A Thin Cloud Removal Method from Remote Sensing Image for Water Body Identification

In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively.

Spatiotemporal Evolution of West Africa's Urban Landscape Characteristics Applying Harmonized DMSP-OLS and NPP-VIIRS Nighttime Light(NTL)Data

Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development.Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System(DMSP-OLS)and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite(NPP-VIIRS)Nighttime Light(NTL)data,this paper investigated the characteristics of urban landscape in West Africa.Using the harmonized NTL data,spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018.We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas.In addition,we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa.The accuracy of urban area extraction based on NTL data were R^(2)=0.8314 in 2000,R^(2)=0.8809 in 2006,R^(2)=0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R^(2)=0.8426 in 2018,by using Google Earth images as validation.The results indicated that there was a high rate and acceleration of urban landscapes in West Africa,with rates of 0.0160,0.0173,0.0189,and 0.0686,and accelerations of 0.31,0.42,0.54,and 0.90 for the periods of 1998–2003,2003–2008,2008–2013,and 2013–2018,respectively.The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland.However,cities located in the Sahel Region of Africa and in the middle zone expanded from north to south.Finally,the results showed that the urban landscape of West Africa was mainly in a scattered and disordered’diffusion’process,whereas only a few cities located in coastal areas experiencing the process of’coalescence’according to urban growth phase theory.This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.

Long-Term Consistent Recalibration of VIRR Solar Reflectance Data Record for Fengyun Polar-Orbiting Satellites

The visible infrared radiometer(VIRR)is the first instrument with longest measurements equipped on the Fengyun(FY)polar-orbiting satellites.Through re-processing of the historic VIRR measurements,long-term(over 20 yr)global data can be integrated from multiple participating VIRRs on a consistent radiometric scale,which are valuable to climate and climate change studies.Due to lack of an onboard calibration system for VIRR,the reflective solar bands must be vicariously calibrated.This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible(VIS)and near-infrared(NIR)data,and produced calibration coefficients for five VIRRs on FY-1 C/D and FY-3 A/B/C.The data quality was then evaluated with observations.The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme,in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer(MODIS).The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials.The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systematic correction derived from the Libya4 desert.The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations.The lifetime relative difference for each sensor are within 3.3%and 4.5%for channels 1 and 2.Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record.In general,the means of the directional and spectral corrected reflectance for each sensor are within 1%of the 20-yr average,implying that the VIRR reflectance of the invariant targets is consistent to within 1%among the sensors for channels 1 and 2.The VIRR data thus derived are reliable.

Evaluation of FY-3/VIRR Sea Surface Temperature Data for Climate Applications

We evaluated the sea surface temperature(SST)products derived from the visible infrared radiometer on board the Fengyun-3 satellites(FY-3/VIRR)during 2016-2018 from the perspective of climate applications.The data had previously been reprocessed by the National Satellite Meteorological Center of China Meteorological Administration based on an updated SST retrieval algorithm.The overall consistency between the FY-3/VIRR SST data and the optimum interpolation SST version 2.1(OIv2.1)was better for monthly means than for pentad means,and showed a clear dependence on the season and location.There was better consistency in winter than in summer,and in the tropical central-eastern Pacific than in the western Pacific warm pool,tropical North Indian Ocean,and tropical Atlantic Ocean.The monthly deviation of the global average SST anomaly was-0.03±0.07℃ and the average root-meansquare errors(RMSEs)presented clear seasonal fluctuations with a maximum of approximately 0.5℃ in summer.The poor consistency of the FY-3/VIRR SST in summer may be partially attributed to the bias of the OIv2.1 data in global oceans(especially the Indian Ocean)as a result of the spatially heterogeneous in situ measurements from ships,buoys,and Argo floats.Convective activities and clouds in the tropics may also influence the accuracy of the FY-3/VIRR SST retrievals.The Nino SST indices based on both FY-3/VIRR and OIv2.1 SST data displayed a generally similar evolution,including the start and end of El Nino and La Nina events and their amplitudes,although the deviations were slightly larger when the Pacific SST anomaly was in the neutral state of the El Nino-Southern Oscillation(ENSO).The deviations varied greatly with season in the tropical Indian and Atlantic oceans,suggesting the need to perform further analyses and validation of the FY-3/VIRR SST products in these two basins.

A Modified Becker's Split-Window Approach for Retrieving Land Surface Temperature from AVHRR and VIRR

In order to provide a long time-series,high spatial resolution,and high accuracy dataset of land surface temperature（LST） for climatic change research,a modified Becker and Li＇s split-window approach is proposed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer（AVHRR） onboard National Oceanic and Atmospheric Administration（NOAA）-7 to-18 and the Visible and InfraRed Radiometer（VIRR） onboard FY-3A.For this purpose,the Moderate Resolution Transmittance Model（MODTRAN） 4.1 was first employed to compute the spectral radiance at the top of atmosphere（TOA） under a variety of surface and atmosphere conditions.Then,a temperature dataset consists of boundary temperature T s（which is one of the input parameters to MODTRAN）,and channels 4 and 5 brightness temperatures（T 4 and T 5） were constructed.Note that channels 4 and 5 brightness temperatures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions（SRFs） of channels 4 and 5 of AVHRRs and VIRR.The coefficients of modified Becker and Li＇s split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method.As an example of validation,one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li＇s approach.The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88,the bias is 0.6 K,and the root mean square deviation（RMSD） is 2.1 K.Furthermore,about 70% and 37% pixels in the LST difference image,which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image,have the values within ± 2 and ± 1 K,respectively.