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Orthogonal waveform design with fractional programming on the ambiguity suppression of SAR systems

Science China(information Sciences) 2024年第9期67卷 263-279页

作者： Yunkai DENG Yongwei ZHANG Zhimin ZHANG Wei WANG Heng ZHANG department of Space Microwave remote sensing System Aerospace Information Research InstituteChinese Academy of Sciences

Waveform diversity(WD) represents a dynamic and transformative technology widely used in radar systems to enhance sensitivity and discrimination capabilities. Recently, WD techniques have been extensively explored for their potential ambiguity suppression within synthetic aperture radar(SAR) *** these, the alternate transmitting mode combined with orthogonal waveforms emerges as a particularly promising solution. This study focuses on optimizing the power spectrum density(PSD) of signals to design and generate an orthogonal waveform pair that achieves both a low cross-correlation-to-autocorrelation ratio(CAR) and satisfactory imaging performance. Initially, we construct a fractional programming model with convex constraints to minimize the CAR. To address this challenge, we introduce an iterative optimization procedure for the PSD variable, which sequentially reduces the CAR. Each optimization step can be efficiently solved using a quadratically constrained quadratic program, ensuring that the resulting computational complexity remains low. Building on the optimized PSD, we established a parametric piecewise linear model to generate an orthogonal waveform pair. This model not only maintains a low CAR but achieves satisfactory imaging performance in real-time applications. Consequently, this orthogonal waveform pair effectively suppresses range ambiguity in SAR systems. Finally, we demonstrated the practicability and effectiveness of the proposed orthogonal waveforms through detailed simulation experiments, specifically targeting ambiguity suppression in conventional quad-polarization SAR systems.

关键词： synthetic aperture radar (SAR) waveform diversity (WD) ambiguity suppression orthogonal waveform fractional programming power spectrum density (PSD)

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Mapping of Flood Risk Zones Using Multi-Criteria Approach and Radar a Case Study of Ala and Akure-Ofosu Communities, Ondo State, Nigeria

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International Journal of Geosciences 2024年第8期15卷 605-631页

作者： Olamiposi Caleb Fagunloye department of remote sensing and Geoscience information systems Federal University of Technology Akure Nigeria

Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study investigates the Ala and Akure-Ofosu flood-prone zones;identifies elements that cause flooding in the study area;classifies each criterion by its effect;develops a flood risk map;estimates flood damage using Sentinel-1A SAR data;compares AHP results. Literature study and GIS-computer database georeferenced fieldwork data. Photos from the 2020 Sentinel 2A satellite have been organized. Built-up area, cropland, rock, the body of water, and forest Land use and cover, slope, rainfall, soil, Euclidean River Distance, and flow accumulation were mapped. These variables were integrated into a Multi-Criteria Analysis (MCA) using GIS tools, resulting in the creation of a flood risk map that categorizes the region into five risk zones: 5% of the area is identified as high-risk, 21% as low-risk, and 74% as moderate-risk. Copernicus SAR data from before and after the flood were processed on Google Earth Engine to map flood extent and ensured that the MCA map accurately reflected flood-prone areas. Periodic review, real-time flood susceptibility monitoring, early warning, and quick damage assessment are suggested to avoid flood danger and other environmental problems.

关键词： remote sensing Flooding GIS Akure Flood Risk Damage Assessment

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Performance validation of High Mountain Asia 8-meter Digital Elevation Model using ICESat-2 geolocated photons

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Journal of Mountain Science 2024年第8期21卷 2562-2578页

作者： Giribabu DANDABATHULA Subham ROY Omkar Shashikant GHATAGE Vaibhav Balaso KOLASE Shwetambari SATPUTE Koushik GHOSH Sahibnoor KAUR Satyanarayana PONDARI Apurba Kumar BERA Sushil Kumar SRIVASTAV Regional remote sensing Centre-West National Remote Sensing CentreIndian Space Research OrganisationJodhpur 342005India department of Geography School of Earth SciencesBharathidasan UniversityTiruchirappalli 620024India Centre for Climate Change and Water Research Suresh Gyan Vihar UniversityJaipur 302017India department of Geography Panjab UniversityChandigarh 160014India National remote sensing Centre Indian Space Research OrganisationHyderabad 500037India Regional Centres National Remote Sensing CentreIndian Space Research OrganisationNew Delhi 110049India

High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate *** accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of *** science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m *** this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land *** were made from statistical quantifiers and elevation *** the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test *** second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,*** third test site,situated in the Zanda County of the Qinghai-Tibet,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible ***,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological *** results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.

关键词： High Mountain Asia Digital Elevation Model ICESat-2 geolocated photons Accuracy assessment

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Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

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Science China Earth Sciences 2024年第11期67卷 3610-3625页

作者： Zhiwei HE Bohui TANG Zhaoliang LI Faculty of Land Resources Engineering Kunming University of Science and Technology Key Laboratory of Plateau remote sensing Department of Education of Yunnan Province State Key Lab of Resources and Environmental information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences Key Laboratory of Agricultural remote sensing Ministry of Agriculture and Rural Affairs Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences

Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remote sensing technology 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 remote sensing 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.

关键词： Mountainous land surface temperature Topographic and adjacency effects Nonlinear generalized split-window algorithm Landsat-9 data DART model

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Long-term(2013-2022)mapping of winter wheat in the North China Plain using Landsat data:classification with optimal zoning strategy

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Big Earth Data 2024年第3期8卷 494-521页

作者： Yifei Liu Xuehong Chen Jin Chen Yunze Zang Jingyi Wang Miao Lu Liang Sun Qi Dong Bingwen Qiu Xiufang Zhu State Key Laboratory of remote sensing Science Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina Beijing Engineering Research Center for Global Land remote sensing Products Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina State Key Laboratory of Crop Gene Resources and Breeding Institute of Crop SciencesChinese Academy of Agricultural Sciences(CAAS)BeijingChina State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina Key Laboratory of Spatial Data Mining&information Sharing of Ministry of Education Academy of Digital China(Fujian)Fuzhou UniversityFuzhouChina

security and formulating agricultural *** data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this *** various methods,such as index-based methods,curve similarity-based methods and machine learning-based methods,have been developed for winter wheat mapping based on remote sensing,the former two often require satellite data with high temporal resolution,which are unsuitable for Landsat data with sparse *** learning is an effective method for crop classification using Landsat ***,applying machine learn-ing for winter wheat mapping in the North China Plain encounters two main issues:1)the lack of adequate and accurate samples for classifier training;and 2)the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this *** address these two issues,we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data,with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop ***,we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion,which divided the study area into six subzones with uni-form classification *** each subzone,a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI *** sample validation confirmed the high accuracy of the produced maps,with an average overall accuracy of 91.1%and an average kappa coefficient of 0.810 across different *** derived winter wheat area also has a good correlation(R2=0.949)with census area at the provincial *** results underscore the reliability of the produced annual winter wheat *** experiments demonstrate that

关键词： Winter wheat mapping Landsat machine learning North China Plain optimal zoning

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Island biogeography theory and the habitat heterogeneity jointly explain global patterns of Rhododendron diversity

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Plant Diversity 2024年第5期46卷 565-574页

作者： Yanwei Guan Yongru Wu Zheng Cao Zhifeng Wu Fangyuan Yu Haibin Yu Tiejun Wang School of Geographical Sciences and remote sensing Guangzhou UniversityGuangzhou 510006China School of Life Sciences Guangzhou UniversityGuangzhou 510006China department of Natural Resources Faculty of Geo-Information and Earth Observation(ITC)University of TwenteDrienerlolaan 5Enschede 7522 NBthe Netherlands

Mountain biodiversity is of great importance to biogeography and ***,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species *** this study,we determined which of six common hypotheses(e.g.,climate hypotheses,habitat heterogeneity hypothesis and island biogeography theory)best explain global patterns of species diversity in *** found that Rhododendron diversity patterns were most strongly explained by proxies of island biogeography theory(i.e.,mountain area)and habitat heterogeneity(i.e.,elevation range).When we examined other relationships important to island biogeography theory,we found that the planimetric area and the volume of mountains were positively correlated with the Rhododendron diversity,whereas the‘mountains-to-mainland’distance was negatively correlated with Rhododendron diversity and shared *** findings demonstrate that Rhododendron diversity can be explained by island biogeography theory and habitat heterogeneity,and mountains can be regarded as islands which supported island biogeography theory.

关键词： Mountain biodiversity Rhododendron Island biogeography theory Habitat heterogeneity Biogeographical hypotheses Plant diversity

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Time series analysis of L-band PALSAR-2 images in Istanbul and Kocaeli,Turkey

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Big Earth Data 2024年第3期8卷 467-493页

作者： Sadra Karimzadeh Abdullah Can Zulfikar Masashi Matsuoka department of remote sensing and GIS University of TabrizTabrizIran department of Architecture and Building Engineering Tokyo Institute of TechnologyYokohamaJapan Disaster Management Institute Istanbul Technical UniversityMaslakIstanbulTurkey

ABSTRACT Conducting long measurements of infrastructure deformation is a critical engineering *** methods are both timeconsuming and expensive,limiting their use for large-scale *** synergy of synthetic aperture radar(SAR)and geographic information systems(GIS)offers a complementary *** study focuses on the feasibility of using time series analysis of L-band PALSAR-2 images to discover land displacements in Istanbul and Kocaeli,significant industrial and residential areas in ***-2 phase and intensity information were *** phase analysis,14 L-band images from 2014 to 2021 were taken into *** baseline subset(SBAS)analysis was performed using 44 pairs,and results of the velocity,coherence and back-scattering values are *** of all pairs and their correlations were *** Component Analysis(PCA)reduced the dimension of coherence pairs,enhancing feature extraction and the final geocoded velocity map revealed a fastest subsidence rate of−58 mm/yr and a mean subsidence of−20 mm/*** findings were confirmed through mean vertical velocity from Sentinel-1 datasets and field *** results showed that immature land subsidence in the mentioned areas are growing slowly,which can be taken as a serious risk in future.

关键词： InSAR time series PALSAR-2 SAR intensity infrastructure deformation

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Mapping lineaments using Landsat 8 OLI and SRTM data;a case study of the eastern part of the Ouarzazate Basin,Morocco

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Journal of Mountain Science 2024年第3期21卷 987-1003页

作者： MOUJANE Said ALGOUTI Ahmed ALGOUTI Abdellah FARAH Abdelouahed ABOULFARAJ Abdelfatah NAFOURI Imane Geoscience Geotourism Natural Hazards and remote sensing Laboratory(2GRNT) Department of GeologyFaculty of Sciences SemlaliaUniversity of Cadi AyyadBP 239040000MarrakechMorocco

The integration of remote sensing and geographic information system(GIS)was employed in this study to delineate the structural lineaments within the eastern section of the Ouarzazate Basin,situated between the southern front of the Central High Atlas and the northern slopes of the Eastern Anti-Atlas(also known as the Saghro Massif).To achieve this objective,Landsat 8 Operational Land Imager(OLI)and Shuttle Radar Topography Mission(SRTM)data were *** Component Analysis(PCA)was computed and a directional filter was applied to the first PCA and the panchromatic band(B8).Additionally,shading was applied to the SRTM data in four directions;N0°,N45°,N90°,N135°.After removing of the non-geological linear structures,the results obtained,using the automatic extraction method,allowed us to produce a synthetic map that included 1251 lineaments with an average length of 1331 m and was dominated by NE-SW,ENE-WSW and E-W directions,***,the high lineament density is clearly noted in the Anti-Atlas(Saghro Massif)and at the level of the northern part,extending from the Ait Ibrirne to Arg-Ali Oubourk *** lineament density can always be found around the major faults affecting this *** data collected during the field investigations and from geological maps show that the major direction of the faults and structural accidents range mostly between N45°,N70°and N75°.The correlation of remote sensing results with those collected in the field shows a similarity and coincidence with each *** these results,it is possible to consider the automatic extraction method as a supplementary kind that can serve classical geology by quickly enriching it with additional *** shown in this work,this method provides more information when applied in arid areas where the fields are well outcropped.

关键词： remote sensing GIS Landsat 8 OLI SRTM Ouarzazate Basin Central High Atlas

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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 *** 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 *** 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)*** species predictions were stacked to generate species richness ***,we show that different data sources and BEMs can generate spatially varying gradients of species *** environmental predictors that best explained species distributions also differed between data *** using citizen-based data had the highest accuracy,whereas those using range data had the lowest *** richness patterns estimated by GAM and BRT models were robust to data *** 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 model performance in mapping cropland soil organic matter using time-series remote sensing data

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Journal of Integrative Agriculture 2024年第8期23卷 2820-2841页

作者： Xianglin Zhang Jie Xue Songchao Chen Zhiqing Zhuo Zheng Wang Xueyao Chen Yi Xiao Zhou Shi Institute of Applied remote sensing and information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China department of Land Management Zhejiang UniversityHangzhou 310058China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou 311215China Institute of Digital Agriculture Zhejiang Academy of Agricultural SciencesHangzhou 310021China Key Laboratory of Spectroscopy sensing Ministry of Agriculture and Rural AffairsHangzhou 310058China

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management *** a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different ***,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human *** overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in *** results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on *** the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to *** recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average *** the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final *** the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping

关键词： cropland soil organic matter digital soil mapping machine learning feature selection model averaging

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