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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Bi, Jingzhi Huang, Wei Li, Bei Cui, Lingbo X Development Department CH UAV Science & Technology Co. Ltd. Beijing China CH UAV Science & Technology Co. Ltd. Beijing China Technology Innovation Center for South China Sea Remote Sensing Surveying and Mapping Collaborative Application Ministry of Natural Resources Guangzhou China International Business Department CH UAV Science & Technology Co. Ltd. Beijing China

ISBN: (纸本)9798350384185

With the rapid development of UAV technology in various industries, it is particularly urgent to solve the complex multi-UAV multi-target *** application scenarios of this study are the UAV has the maximum load limit, the maximum range limit, a single UAV can not complete the task, and the materials required for each target point are *** solve this problem, a hybrid particle swarm optimization algorithm (HPSO) is proposed to allocate target *** the allocation is completed, the ant colony algorithm is used to solve the path planning of a single UAV, so as to calculate the target points and flight routes assigned to each *** hybrid particle swarm optimization (HPSO) takes the maximum payload and the range of the UAV as the constraint conditions, and the shortest path as the objective *** order to verify the effectiveness of this algorithm, the traditional mathematical algorithm integer programming is used to allocate target *** the allocation is completed, the ant colony algorithm is also used to plan the path of a single ***, carry out computational simulation, and three times of calculation and simulation were carried out on the hybrid particle swarm *** simulation results show that the hybrid particle swarm optimization (HPSO) has a significant advantage in the capacity limited target assignment *** it provides an effective solution to the problem of multi-UAV mission planning with capacity constraints, thereby improving the efficiency of UAV mission execution, reducing the cost of mission execution, and providing theoretical support and technical guarantee for the further application of UAV technology. © 2024 IEEE.

关键词： Ant colony optimization

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TTST: A Top-k Token Selective Transformer for remote sensing Image Super-Resolution

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IEEE Transactions on Image Processing 2024年 33卷 738-752页

作者： Xiao, Yi Yuan, Qiangqiang Jiang, Kui He, Jiang Lin, Chia-Wen Zhang, Liangpei Wuhan University School of Geodesy and Geomatics Wuhan430079 China Harbin Institute of Technology School of Computer Science and Technology Harbin150001 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu300 Taiwan Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan430079 China

Transformer-based method has demonstrated promising performance in image super-resolution tasks, due to its long-range and global aggregation capability. However, the existing Transformer brings two critical challenges for applying it in large-area earth observation scenes: (1) redundant token representation due to most irrelevant tokens;(2) single-scale representation which ignores scale correlation modeling of similar ground observation targets. To this end, this paper proposes to adaptively eliminate the interference of irreverent tokens for a more compact self-attention calculation. Specifically, we devise a Residual Token Selective Group (RTSG) to grasp the most crucial token by dynamically selecting the top-k keys in terms of score ranking for each query. For better feature aggregation, a Multi-scale Feed-forward Layer (MFL) is developed to generate an enriched representation of multi-scale feature mixtures during feed-forward process. Moreover, we also proposed a Global Context Attention (GCA) to fully explore the most informative components, thus introducing more inductive bias to the RTSG for an accurate reconstruction. In particular, multiple cascaded RTSGs form our final Top-k Token Selective Transformer (TTST) to achieve progressive representation. Extensive experiments on simulated and real-world remote sensing datasets demonstrate our TTST could perform favorably against state-of-the-art CNN-based and Transformer-based methods, both qualitatively and quantitatively. In brief, TTST outperforms the state-of-the-art approach (HAT-L) in terms of PSNR by 0.14 dB on average, but only accounts for 47.26% and 46.97% of its computational cost and parameters. The code and pre-trained TTST will be available at https://***/XY-boy/TTST for validation. © 1992-2012 IEEE.

关键词： remote sensing

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Land surface temperature and spectral indices: A seasonal study of Raipur City

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Geodesy and Geodynamics 2022年第1期13卷 72-82页

作者： Subhanil Guha Himanshu Govil Ajay Kumar Taloor Neetu Gill Anindita Dey Department of Applied Geology National Institute of Technology RaipurIndia Department of Remote Sensing&GIS University of JammuIndia Chhattisgarh Council of Science and Technology RaipurIndia Department of Geography Nazrul Balika VidyalayaGumaWest BengalIndia

This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature(LST)with some spectral indices like NDVI,NDWI,NDBI,and NDBaI by using a series of Landsat images for 1991-92,1995-96,1999-00,2004-05,2009-10,2014-15,and *** results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI(0.71)and NDBaI(0.52)while it builds a negative correlation with NDVI(-0.44).The LST-NDWI correlation is *** best correlation is noticed in the post-monsoon period,while the least correlation is observed in the winter *** study can support the environmental planning to build a sustainable city under a similar environment.

关键词： Land surface temperature(LST) NDVI NDWI NDBI NDBaI

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Groundwater Chemistry Of Umred Taluka, Nagpur District, Maharashtra 2

Groundwater Chemistry Of Umred Taluka, Nagpur District, Maha...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Sadawarti, Alpashi L Masurkar, Shubham P Anusha, N. Refonaa, J. Cheripelli, Ramesh Maharashtra Remote Sensing Application Centre Nagpur India Jmk Infosoft Solutions Private Limited Aurangabad India Hyderabad India Sathyabama Institute of Science and Technology Department of Cse Chennai India Vidya Jyothi Institute of Technology Department of It Hyderabad India

ISBN: (纸本)9798350360523

15 groundwater samples were gathered from distinct villages within the Umred taluka. A range of parameters were scrutinized for each of the collected samples. To ascertain the groundwater's appropriateness for drinking, the specifications outlined by the Bureau of Indian Standards (BIS) in 2012 were employed as a benchmark. With the exception of nitrate (NO 3-) levels exceeding the permissible limit in four samples;all other parameters adhered to the recommended BIS standards. The study also investigated the suitability of groundwater for irrigation based on various parameters, and the results suggest that the groundwater is indeed suitable for this purpose. The hydro chemical facies of the groundwater were determined through chemical analysis, and a Piper's trilinear diagram was utilized for this purpose. The diagram revealed a predominance of the combined cations of calcium and magnesium over the combined cations of sodium and potassium. Additionally, the weak acid bicarbonate outweighed the strong acids sulfate and chloride. The majority of the samples were situated in the Ca-HCO3 region. © 2024 IEEE.

关键词： Groundwater

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A Smart Application Frame of remote sensing in Non-grain Production Data Governance

A Smart Application Frame of Remote Sensing in Non-grain Pro...

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ISPRS Technical Commission I Midterm Symposium on Intelligent sensing and remote sensing Application

作者： Zhang, Longqi He, Wenwen Guo, Yunkai Teng, Xiao Department of Surveying and Mapping Engineering Changsha University of Science and Technology Changsha41004 China Hunan Provincial Third Surveying and Mapping Institute Changsha410009 China Institute of Mapping and Remote Sensing Application Changsha University of Technology Changsha41004 China

This study addresses the intricate challenges encountered in the data governance process of Non-grain Production (NGP) on Arable land. This involves managing data from diverse sources, with varying accuracies and formats, and utilizing multiple specialized software tools. An object-oriented approach is adopted to encapsulate experiential knowledge related to the data and associated processing methods, thus creating an Application Knowledge Body Model (AKBM). This model acts as a conduit between users and computational resources, encompassing various types of data and their corresponding processing and analysis methods. Moreover, by employing model inference techniques to devise methods for transitioning from raw data models to target models, a foundation is laid for the accumulation, sharing, and intelligent application of expertise on data, methods, models, and knowledge. The application examples demonstrate that users can directly construct new solutions containing relevant data and associated processing methods, rather than grappling with a multitude of data files and complex specialized software when encountering novel challenges. This promotes collaborative development in data governance on geospatial big data platforms, significantly enhancing governance efficiency, improving the quality of information support in NGP cultivation management, advancing current technological capabilities, and fostering the progression of related technologies. © Author(s) 2024.

关键词： remote sensing

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Land surface modeling informed by earth observation data:toward understanding blue-green-white water fluxes in High Mountain Asia

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地球空间信息科学学报（英文版） 2024年第3期27卷 703-727页

作者： Pascal Buri Simone Fatichi Thomas E.Shaw Catriona L.Fyffe Evan S.Miles Michael J.McCarthy Marin Kneib Shaoting Ren Achille Jouberton Stefan Fugger Li Jia Jing Zhang Cong Shen Chaolei Zheng Massimo Menenti Francesca Pellicciotti Swiss Federal Institute for Forest Snow and Landscape Research WSLBirmensdorfSwitzerland Department of Civil and Environmental Engineering National University of SingaporeSingaporeSingapore Swiss Federal Institute for Forest Snow and Landscape Research WSLBirmensdorfSwitzerland Institute of Science and Technology Austria(ISTA) KlosterneuburgAustria Institute of Science and Technology Austria(ISTA) KlosterneuburgAustria Institute of Environmental Geosciences Université Grenoble AlpesGrenobleFrance Department of Atmospheric and Cryospheric Sciences University of InnsbruckInnsbruckAustria State Key Laboratory of Tibetan Plateau Earth System Environment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina Swiss Federal Institute for Forest Snow and Landscape Research WSLBirmensdorfSwitzerland Institute of Environmental Engineering ETH ZurichZurichSwitzerland State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina National Space Sciences Center Chinese Academy of SciencesBeijingChina State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina Faculty of Civil Engineering and Geosciences Delft University of TechnologyDelftThe Netherlands

Mountains are important suppliers of freshwater to downstream areas,affecting large populations in particular in High Mountain Asia(HMA).Yet,the propagation of water from HMA headwaters to downstream areas is not fully understood,as interactions in the mountain water cycle between the cryo-,hydro-and biosphere remain *** review the definition of blue and green water fluxes as liquid water that contributes to runoff at the outlet of the selected domain(blue)and water lost to the atmosphere through vapor fluxes,that is evaporation from water,ground,and interception plus transpiration(green)and propose to add the term white water to account for the(often neglected)evaporation and sublimation from snow and *** provide an assessment of models that can simulate the cryo-hydro-biosphere continuum and the interactions between spheres in high mountain catchments,going beyond disciplinary *** surface models are uniquely able to account for such complexity,since they solve the coupled fluxes of water,energy,and carbon between the land surface and *** to the mechanistic nature of such models,specific variables can be compared systematically to independent remote sensing observations-providing vital insights into model accuracy and enabling the understanding of the complex watersheds of *** discuss recent developments in spaceborne earth observation products that have the potential to support catchment modeling in high mountain *** then present a pilot study application of the mechanistic land surface model Tethys & Chloris to a glacierized watershed in the Nepalese Himalayas and discuss the use of high-resolution earth observation data to constrain the meteorological forcing uncertainty and validate model *** use these insights to highlight the remaining challenges and future opportunities that remote sensing data presents for land surface modeling in HMA.

关键词： Land surface modeling remote sensing High Mountain Asia(HMA) blue-green water cryosphere-hydrosphere-biosphere continuum snow glaciers high mountain water cycle

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Using FY-3E Data to Independently Retrieve Sea Ice Thickness

Using FY-3E Data to Independently Retrieve Sea Ice Thickness

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yunjian Xie Yinqing Zhen Qingyun Yan School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Scientific studies worldwide have long put an emphasis on Arctic sea ice, viewing sea ice thickness (SIT) as a crucial determinant for forecasting local oceanic conditions, climate fluctuations, and assuring maritime transport safety. The present research pivots on the extraction of SIT, deploying a well-established two-layer (sea ice-seawater) model of Global Navigation Satellite System-Reflectometry (GNSS-R) and broadening it to incorporate recent data from the Fengyun-3E (FY-3E) satellite. The study presents a unique empirical method with the goal of lessening dependencies on supplementary data, thereby enabling independent SIT extraction purely via GNSS-R data. This effort highlights the feasibility of constructing a functional semiempirical model and parameterization scheme for the estimation of SIT through GNSS-R data.

关键词： Procurement Temperature distribution Satellites Salinity (geophysical) Satellite navigation systems Data models Safety

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Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

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Advances in Atmospheric sciences 2024年第2期41卷 193-208页

作者： Xiaojing YU Lixia ZHANG Tianjun ZHOU Jianghua ZHENG LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044China University of Chinese Academy of Sciences Beijing 100049China College of Geography&Remote Sensing Sciences Xinjiang UniversityUrumqi 830046China

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are *** the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 o

关键词： droughts hydrothermal conditions drylands CMIP6 model evaluation

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A New Multiangle Method for Estimating Fractional Biocrust Coverage from Sentinel-2 Data in Arid Areas

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IEEE Transactions on Geoscience and remote sensing 2024年 62卷 1-15页

作者： Sun, Hui Ma, Xu Liu, Ying Zhou, Guiyun Ding, Jianli Lu, Lei Wang, Tiejun Yang, Qiuli Shu, Qingtai Zhang, Fei College of Geography and Remote Sensing Sciences Xinjiang University Xinjiang Key Laboratory of Oasis Ecology Urumqi830046 China Xinjiang University Xinjiang Key Laboratory of Oasis Ecology Post-Doctoral Mobile Stationm College of Geography and Remote Sensing Sciences Urumqi830046 China Xinjiang University College of Life Science and Technology Urumqi830046 China University of Electronic Science and Technology School of Resources and Environment Chengdu611731 China Lanzhou University College of Earth and Environmental Sciences Lanzhou730000 China Enschede7500 AE Netherlands Southwest Forestry University School of Forestry Kunming650224 China Zhejiang Normal University College of Geography and Environmental Sciences Jinhua321000 China

The spatiotemporal distribution of biocrusts can be used to monitor regional water resources in desert ecosystems. However, a lack of biocrust products from remotely sensed images with fine spatial resolution (FSR) limits scientific research in this area. To address this issue, we establish an estimation model for biocrusts (EMBC) with three steps for FSR images. Then, the large-scale fractional biocrust coverage (FBC) in deserts was mapped from Sentinel-2 images with a spatial resolution of 10 m. First, we develop a fraction biocrust cover index (FBCI) based on radiative transfer theory. Next, a multiangle calculation equation involving FBCI is established and the parameters for a pixel dichotomy model are solved by an inverse method using a linear kernel-driven model. Finally, this pixel dichotomy model with FBCI is used to calculate FBC. We validate the model using field measurements and compare the validation results with those estimated by a random forest model and a backpropagation neural network model. This comparison demonstrates that the value of FBC estimated by EMBC is highly consistent with field measurements (root-mean-square error (RMSE) = 0.0774 and systematic deviation = -4.05%). Furthermore, the values of FBC estimated by EMBC and the two other models have a high level of consistency in terms of spatial distribution (RMSE © 1980-2012 IEEE.

关键词： remote sensing

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Reconstructing NDVI for Lakes: Early Insights Leveraging CYGNSS and ERA-5 Data

Reconstructing NDVI for Lakes: Early Insights Leveraging CYG...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yinqing Zhen Qingyun Yan School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The increasingly serious water pollution in numerous lakes has resulted in the more frequent occurrences of algal bloom disaster in recent decades. Assessing the severity of these algal bloom events can be accomplished through the utilization of remote sensing methodologies, with measurements facilitated by the Normalized Difference Vegetation Index (NDVI). However, the effectiveness of NDVI observations via optical sensors is often impeded by the presence of cloud and fog cover in regions encompassing various water bodies, such as Taihu Lake. Sensors operating in the microwave band, particularly the emerging Global Satellite Navigation System-Reflectometry (GNSS-R) technique can avoid this problem effectively, and it also offers notable advantages in terms of temporal resolution and cost-efficiency. In this study, we propose a novel approach for the retrieval of lake-surface NDVI values on overcast days based on GNSS-R and meteorological data, with the aid of a machine learning regression algorithm, specifically the Bagging Tree method. The resultant NDVI regression model demonstrates an impressive coefficient of determination (R 2 ) of 0.95, a Root Mean Square Error (RMSE) of 0.021, and a mean Absolute Error (MAE) of 0.010. The recovered NDVI images exhibit remarkable clarity and closely approximate the reference NDVI imagery.

关键词： Normalized difference vegetation index Machine learning algorithms Satellites Machine learning Lakes Approximation algorithms Water pollution

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