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Spatiotemporal changes in sunshine duration and its influential factors in Chongqing,China from 1961 to 2020

Journal of Mountain science 2024年第6期21卷 2005-2024页

作者： LI Jun XIA Hongxuan JIANG Jinge XU Weifeng WEN Di XU Junfeng College of Geography and Tourism Chongqing Normal UniversityChongqing 401331China key laboratory of GIS Application of Chongqing Chongqing 401331China Chongqing key laboratory of Earth Surface Processes and Environmental remote sensing in Three Gorges Reservoir area Chongqing 401331China Institute of remote sensing and Earth sciences School of Institute of Remote Sensing and Earth SciencesSchool of ScienceHangzhou Normal UniversityHangzhou 311121China

The surface solar radiation in most parts of the world has undergone a phenomenon known as global dimming and brightening,characterized by an initial decrease followed by an increase.As a result,the sunshine duration(SD)has decreased in the past 60 years.Against the backdrop of global dimming and brightening,SD has decreased to varying degrees in many regions of China.Using the observed data of SD,cloud amount(total cloud amount and low cloud amount,abbreviated as TCA and LCA),precipitation,and relative humidity(RH)from 34 meteorological stations in Chongqing during the period of 1961-2020,along with a digital elevation model(DEM)with a resolution of 90 m,this study analyzed the spatiotemporal variations and influencing factors of SD.The analysis employed methods such as linear regression,Mann-Kendall test,wavelet transformation,and DEM-based possible SD distributed model.The results showed that the annual SD in Chongqing has significantly decreased over the last 60 years,with a decreasing interannual trend rate(ITR)of 40.4 h/10a.Except for no obvious trend in spring,SD decreased significantly in summer,autumn and winter at the ITR of 21.1 h/10a,8.5 h/10a and 7.5 h/10a,respectively.An abrupt decrease in the annual SD was found in 1979.The difference before and after the abrupt decrease was 177.7 h.The difference before and after the abrupt decrease was 177.7 h.The annual SD possessed the oscillation period of 11a.The spatial heterogeneity of the mean annual SD during the last 60 years was obvious.The distribution of SD in Chongqing is high in the northeast and low in the southeast.In addition,about 73%of the total area in Chongqing showed a significant and very significant decreasing trend.The regions with significant changes are mainly concentrated in the regions with altitudes of 200~1000 m.The increasing LCA was the main cause of the decrease of the annual SD in the regions with 200-400 m altitude decreased the most and changed the most.Increasing LCA is the primary cause of the reduction in annual SD,showing

关键词： Sunshine duration Spatiotemporal changes Mann-Kendall test Wavelet analysis Geodetector model

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Multi-sensor multispectral reconstruction framework based on projection and reconstruction

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science China(Information sciences) 2024年第3期67卷 246-262页

作者： Tianshuai LI Tianzhu LIU Xian LI Yanfeng GU Yukun WANG Yushi CHEN School of Electronics and Information Engineering Harbin Institute of Technology Heilongjiang Province key laboratory of Space-Air-Ground Integrated Intelligent remote sensing

The scarcity and low spatial resolution of hyperspectral images(HSIs) have become a major problem limiting the application of the images. In recent years, spectral reconstruction(SR) has been applied to convert multispectral images(MSIs) with abundant quantities and high spatial resolution into HSIs. With the launch of several new multispectral(MS) satellites with a short repeat period, the simultaneous acquisition of images from multiple MS sensors in the same area is gradually becoming feasible. Unfortunately, existing SR methods only consider the reconstruction of the MSIs of a single sensor without considering using MSIs from different MS sensors to obtain a better construction effect through their complementary bands. However,multi-sensor SR is characterized by two problems: inconsistency in the amplitude information of real multisensor imaging and difficulty in the extraction of the complex correlations of bands from different sensors.To solve these problems, this paper proposes a multi-sensor SR framework based on a two-step approach in which the problems of amplitude inconsistency and band information extraction are solved using an ideal projection network and an ideal multi-sensor SR network, respectively. The effectiveness of the proposed method is verified by experiments on three datasets.

关键词： spectral reconstruction spectral superresolution hyperspectral image multispectral image neural networks multi-sensor

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Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

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Journal of Arid Land 2024年第1期16卷 46-70页

作者： ZHAO Xuqin LUO Min MENG Fanhao SA Chula BAO Shanhu BAO Yuhai College of Geographical science Inner Mongolia Normal UniversityHohhot 010022China Inner Mongolia key laboratory of remote sensing and Geographic Information Systems Hohhot 010022China

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

关键词： gross primary productivity(GPP) climate change warming aridification areas drought sensitivity cumulative effect duration(CED) Mongolian Plateau

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Data error propagation in stacked bioclimatic envelope models

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Integrative Zoology 2024年第2期19卷 262-276页

作者： Xueyan LI Babak NAIMI Peng GONG Miguel B.ARAÚJO Guangdong Provincial key laboratory of remote sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of ScienceGuangzhouChina ‘Rui Nabeiro’Biodiversity Chair CHANGE-MED InstituteUniversity ofÉvoraÉvoraPortugal Department of Geography and Department of Earth sciences University of Hong KongHong KongChina Department of Biogeography and Global Change National Museum of Natural SciencesCSICMadridSpain

Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes of species richness.If data limitations on individual species distributions are inevitable,but how do they affect inferences of patterns and processes of species richness?We investigate the influence of different data sources on estimated species richness gradients in China.We fitted BEMs using species distributions data for 334 bird species obtained from(1)global range maps,(2)regional checklists,(3)museum records and surveys,and(4)citizen science data using presence-only(Mahalanobis distance),presence-background(MAXENT),and presence–absence(GAM and BRT)BEMs.Individual species predictions were stacked to generate species richness gradients.Here,we show that different data sources and BEMs can generate spatially varying gradients of species richness.The environmental predictors that best explained species distributions also differed between data sources.Models using citizen-based data had the highest accuracy,whereas those using range data had the lowest accuracy.Potential richness patterns estimated by GAM and BRT models were robust to data uncertainty.When multiple data sets exist for the same region and taxa,we advise that explicit treatments of uncertainty,such as sensitivity analyses of the input data,should be conducted during the process of modeling.

关键词： richness patterns species distribution stacked bioclimatic envelope models uncertainty

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Improving the accuracy of precipitation estimates in a typical inland arid area of China using a dynamic Bayesian model averaging approach

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Journal of Arid Land 2024年第3期16卷 331-354页

作者： XU Wenjie DING Jianli BAO Qingling WANG Jinjie XU Kun College of Geography and remote sensing sciences Xinjiang UniversityUrumqi 830017China key laboratory of Smart City and Environment Modelling of Higher Education Institute Xinjiang UniversityUrumqi 830017China

Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Pre

关键词： precipitation estimates satellite-based and reanalysis precipitation dynamic Bayesian model averaging streamflow simulation Ebinur Lake Basin Xinjiang

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Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

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Journal of Arid Land 2024年第4期16卷 580-601页

作者： TANG Xiaoyan FENG Yongjiu LEI Zhenkun CHEN Shurui WANG Jiafeng WANG Rong TANG Panli WANG Mian JIN Yanmin TONG Xiaohua College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Shanghai key laboratory of Space Mapping and remote sensing for Planetary Exploration Tongji UniversityShanghai 200092China

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban grow

关键词： bat algorithm cellular automata(CA) probability-of-occurrence drought intensity algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model arid areas

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Monitoring Surface Deformation Using Distributed Scatterers InSAR

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Journal of Geodesy and Geoinformation science 2024年第1期7卷 42-58页

作者： LI Haocheng DONG Jie WANG Yi’an LIAO Mingsheng State key laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China School of remote sensing and Information Engineering Wuhan UniversityWuhan 430079China

In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction of distributed scatterers in Distributed Scatterers InSAR(DS-InSAR)has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points.This study traces the history of DS-InSAR,presents the definition and characteristics of distributed scatterers,and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps:statistically homogeneous pixel selection and phase optimization.Additionally,the latest research progress in this field is tracked and the possible development direction in the future is discussed.Through simulation experiments and two real InSAR case studies,the proposed algorithms are compared and verified,and the advantages of DS-InSAR in deformation measurement practice are demonstrated.This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.

关键词： InSAR permanent scatterers distributed scatterers statistically homogeneous pixel selection phase optimization

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Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

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Journal of Geodesy and Geoinformation science 2024年第1期7卷 74-89页

作者： ZHAO Bofei SUI Haigang ZHU Yihao LIU Chang WANG Wentao State key laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

关键词： UAV ﬂood extraction target rescue detection real time

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An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data

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Acta Oceanologica Sinica 2024年第3期43卷 127-138页

作者： Lian He Senwen Huang Fengming Hui Xiao Cheng School of geospatial Engineering and science Sun Yat-Sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China key laboratory of Comprehensive Observation of Polar Environment(Sun Yat-Sen University) Ministry of EducationZhuhai 519082China

The aim of this study was to develop an improved thin sea ice thickness(SIT)retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data.This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort,Chukchi,East Siberian,Laptev and Kara seas and utilized the microwave polarization ratio(PR)at incidence angle of 40°.The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact,reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature.The relationship between the SIT and PR was found to be almost stable across the five selected regions.The SIT retrievals were then compared to other two existing algorithms(i.e.,UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen)and validated against independent SIT data obtained from moored upward looking sonars(ULS)and airborne electromagnetic(EM)induction sensors.The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error(RMSE)being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data.The proposed algorithm can be used for thin sea ice thickness(<1.0 m)estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.

关键词： Arctic sea ice sea ice thickness remote sensing Soil Moisture Active Passive(SMAP) Soil Moisture Ocean Salinity and Soil(SMOS)

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Spatiotemporal variations in glacier area and surface velocity of the northern Antarctic Peninsula during 2018-2022

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Advances in Climate Change Research 2024年第2期15卷 297-311页

作者： Yu-Long KANG Shi-Chang KANG Wan-Qin GUO Tao CHE Zong-Li JIANG Zhen-Feng WANG Qiang-Qiang XU Cheng-De YANG State key laboratory of Cryospheric science Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of sciences Beijing 100083China key laboratory of remote sensing of Gansu Province Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China School of Earth sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China

Ice sheet serves as a crucial indicator for assessing climate change.Mass loss in recent remote sensing-based studies indicated that the Antarctic Peninsula has rapid rates of glacier retreat and speed up of surface velocity.However,observations of seasonal variability of ice speed are limited,and glacier-area changes require multi-temporal monitoring.This study investigated the changes in area and surface velocities of∼375 glaciers on the northern Antarctic Peninsula(NAP)utilizing satellite images acquired by the Sentinel 1&2 satellites during 2018-2022.The results indicate that the glacier area reduced by approximately 166.1±44.2 km^(2)(-0.2%±0.1%per year)during the study period,with an acceleration after 2020(-0.4%±0.3%per year),and the most dramatic reduction happened on the eastern NAP.The maximum annual ice speeds on the NAP generally exceeded 3500 m per year,while the ice speeds in 2021 were the highest(exceeded 4210 m per year).The ice speed variability in austral autumn was higher than in other seasons,meanwhile the summer ice speeds showed an increasing trend.The glacier G012158E47018N,McNeile Glacier,glacier G299637E64094S and Drygalski Glacier showed the most remarkable ice speed variations represented by high daily velocities and strong fluctuations on their termini.Our results demonstrated that the variations in glacier area and seasonal ice speed on the NAP were responsive to the ice-ocean-atmosphere processes.Therefore,seasonal velocity and area variations should be considered when conducting accurate mass balance calculations,model validations and change mechanism analyses under climate warming scenarios.

关键词： Glacier area Seasonal ice speed Sentinel 1&2 Northern Antarctic Peninsula Ice-ocean-atmosphere processes

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