The GaoFen7(GF7)optical satellite is the first Chinese civilian sub-meter high-resolution stereo mapping satellite and is equipped with a double linear array camera and laser altimeter to achieve large-scale topograph...
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The GaoFen7(GF7)optical satellite is the first Chinese civilian sub-meter high-resolution stereo mapping satellite and is equipped with a double linear array camera and laser altimeter to achieve large-scale topographic *** improve the accuracy of attitude determination,an attitude determination system comprised of four star sensors is *** to the measurement accuracy and steady performance,the star sensors 1a and 1b is usually used together for satellite attitude calculation,which is called the conventional mode of attitude ***,the combination of star sensors 2a and 2b is called the unconventional mode of attitude *** by variations in the incident angle of sunlight and solar radiation,thermal deformation occurs in the body and installation structure of the star sensor,which causes Attitude Low-Frequency Error(ALFE)and seriously influences the con-sistency of attitude determination results of different combination modes for multiple star sensors *** study proposes an ALFE analysis and calibration approach for the multiple star sensors system of GF7 satellite to ensure the consistency of attitude determination results of different combination *** on the statistical characteristics of the angles of the three axes,the installation parameters of the four star sensors are first *** analyzing the characteristics of the optical axis angles within 1420 orbit periods over 135 days,the segmented ALFE compensation model between the unconventional and conven-tional modes is proposed based on the Fourier series model and input parameter of *** on the on-orbit installation parameters and the ALFE model,the precise attitude determination results of the unconventional mode are *** results show that the attitude determination consistency after compensation is better than 2".Moreover,the reliable application time range of the compensation model is 30 days to satisfy the re
Feature extraction from satellite images has steadily but progressively grown in recent years. Numerous feature extraction techniques have been created as a result of the increase. The loss of certain features is one ...
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The Arctic-scale classification of sea ice type is important in the fields of macro-monitoring in the Arctic, climate change assessment, and long time-series interannual variability of sea ice. To date, a lack of deep...
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Severe flood events during the last decades have proved to be a devastating disaster for the densely populated and economy of Uttar Pradesh. Due to its ability to provide a concise view of spatial extent of the flood,...
Severe flood events during the last decades have proved to be a devastating disaster for the densely populated and economy of Uttar Pradesh. Due to its ability to provide a concise view of spatial extent of the flood, remotesensing techniques and synthetic aperture radar (SAR) systems in particular have been applied to flood mapping. The present study has identified flood-prone areas in Uttar Pradesh using the C-band (SAR) sensor of Sentinel-1. In this study, changes in flood inundation area during the monsoon season of 2021 have been estimated. Sentinel Application Platform (SNAP) has been used to perform SAR pre-processing which includes orbit file application, thermal noise removal, calibration, speckle filtering, and terrain correction. Subsequently, polarization, band math expression, thresholding, and image are processed. In addition, image mapping has been done in Arc-GIS tool for detailed investigation of flood inundation area. Detailed investigation of the flood inundated area found that overall, 7710 km2 is affected by the flood area. This study will be the potential use of microwave SAR remotesensing as a comprehensive and effective way of providing accurate surface water information for water resources management, flood warning, flood monitoring, and rapid and accurate flood damage assessment in the years to come.
Automatic label generation systems, which are capable to generate huge amounts of labels with limited human efforts, enjoy lots of potential in the deep learning era. These easy-to-come-by labels inevitably bear label...
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The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in ***,most remotesensing process models use the“biomass×harvest i...
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The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in ***,most remotesensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat ***,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional ***-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter *** this study,Fr equations were fitted for each organ of winter wheat using site-scale *** equations were then coupled into a process-based and remotesensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),*** PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.
It is instructive for aerial target interception to exploit the point/broadband electromagnetic scattering characteristics of particles cloud. The particles cloud is generated by the explosive targets after being stru...
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Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remotesensingtechnology is the only means to obtain large-scale, ...
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Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remotesensingtechnology is the only means to obtain large-scale, high spatial resolution LST. Accurately retrieving high spatial resolution mountainous LST(MLST) plays an important role in the study of mountain climate change. The complex terrain and strong spatial heterogeneity in mountainous areas change the geometric relationship between the surface and satellite sensors, affecting the radiation received by the sensors, and rendering the assumption of planar parallelism invalid. In this study, considering the influence of complex terrain in mountainous areas on atmospheric downward radiation and the thermal radiation contribution of adjacent pixels, a mountainous TIR radiative transfer model based on the sky view factor was developed. Combining with the atmospheric radiative transfer model MODTRAN 5.2, a nonlinear generalized split-window algorithm suitable for high spatial resolution MLST retrieval was constructed and applied to Landsat-9 TIRS-2satellite TIR remotesensing data. The analysis results indicate that neglecting the topographic and adjacency effects would lead to significant discrepancies in LST retrieval, with simulated data showing LST differences of up to 2.5 K. Furthermore, due to the lack of measured MLST in the field, the MLST accuracy obtained by this retrieval method was indirectly validated using the currently recognized highest-accuracy forward 3D radiative transfer model DART. The MLST and emissivity were input into the DART model to simulate the brightness temperature at the top of the atmosphere(TOA) of Landsat-9 band 10, and compared with the brightness temperature at TOA of Landsat-9 band 10. The RMSE(Root Mean Square Error) for the two subregions was0.50 and 0.61 K, respectively, indicating that the method proposed can retrieve high-precision MLST.
Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of indivi...
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Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this *** resulting model,the‘Humidity calibrated Drought Condition Index’(HcDCI)was applied for the years 2001 to 2019 in form of a case study to Weihai County,Shandong Province in East *** and development are based on a linear combination of the Vegetation Condition Index(VCI),the Temperature Condition Index(TCI),and the Rainfall Condition Index(RCI)using multi-source satellite data to create a basic Drought Condition Index(DCI).VCI and TCI were derived from MODIS(Moderate Resolution Imaging Spectroradiometer)data,while precipitation is taken from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station data)*** reasons of accuracy,the decisive coefficients were determined by the relative humidity of soils at depth of 10-20 cm of particular areas collected by an agrometeorological ground *** correlation between DCI and soil humidity was optimized with the factors of 0.53,0.33,and 0.14 for VCI,TCI,and RCI,*** model revealed,light agricultural droughts from 2003 to 2013 and in 2018,while more severe droughts occurred in 2001 and 2002,2014-2017,and *** droughts were most severe in January,March,and December,and our findings coincide with historical *** average temperature during 2012-2019 is 1℃ higher than that during the period 2001-2011 and the average precipitation during 2014-2019 is 192.77 mm less than that during *** spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield *** model thus,demonstrates its capability to reveal drought periods in detail,its transferability to other regions and its usefulness to take future measures.
Rapid large-area deep tissue imaging at long working distances is important for clinical diagnosis. A near-infrared metalens-based hybrid probe con-focal micro-endoscope (pCM) objective with a large field of view of 5...
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