This paper discusses the role of Geoinformatics as a new scientific discipline designed for handling of geospatial information.Depending on the scientific background of the people involved in shaping the emerging disc...This paper discusses the role of Geoinformatics as a new scientific discipline designed for handling of geospatial information.Depending on the scientific background of the people involved in shaping the emerging discipline,emphasis may be placed on different aspects of Geoinformatics.Applications and developments may address geoscientific,spatial planning,or computer science related matters.The scientific field of Geoinformatics encompasses the acquisition and storing of geospatial data,the modelling and presentation of spatial information,geoscientific analyses and spatial planning,and the development of algorithms and geospatial database systems.It is the position of the author that these tools from Geoinformatics are necessary to bridge the gap between Digital Earth models and the real world with its real-world problems(‘connecting through location’).It is,however,crucial that Geoinformatics represents a coherent integrated approach to the acquisition,storage,analysis,modeling,presentation,and dissemination of geo-processes and not a patchwork solution of unconnected fields of activity.Geoinformatics is as such not a part of Geography,Surveying,or Computer Science,but a new self-contained scientific discipline.The current paper highlights international and national trends of the discipline and presents a number of Geoinformatics initiatives.The research and teaching activities of the newly formed Institute for Geoinformatics and Remote Sensing(IGF)at the University of Osnabrueck serve as an example for these initiatives.All these developments have lead to the long overdue formation of a scientific‘Society for Geoinformatics’(German:Gesellschaft fu¨r Geoinformatik-GfGI)in Germany.展开更多
The use of AI technologies in remote sensing(RS)tasks has been the focus of many individuals in both the professional and academic domains.Having more accessible interfaces and tools that allow people of little or no ...The use of AI technologies in remote sensing(RS)tasks has been the focus of many individuals in both the professional and academic domains.Having more accessible interfaces and tools that allow people of little or no experience to intuitively interact with RS data of multiple formats is a potential provided by this integration.However,the use of AI and AI agents to help automate RS-related tasks is still in its infancy stage,with some frameworks and interfaces built on top of well-known vision language models(VLM)such as GPT-4,segment anything model(SAM),and grounding DINO.These tools do promise and draw guidelines on the potentials and limitations of existing solutions concerning the use of said models.In this work,the state of the art AI foundation models(FM)are reviewed and used in a multi-modal manner to ingest RS imagery input and perform zero-shot object detection using natural language.The natural language input is then used to define the classes or labels the model should look for,then,both inputs are fed to the pipeline.The pipeline presented in this work makes up for the shortcomings of the general knowledge FMs by stacking pre-processing and post-processing applications on top of the FMs;these applications include tiling to produce uniform patches of the original image for faster detection,outlier rejection of redundant bounding boxes using statistical and machine learning methods.The pipeline was tested with UAV,aerial and satellite images taken over multiple areas.The accuracy for the semantic segmentation showed improvement from the original 64%to approximately 80%-99%by utilizing the pipeline and techniques proposed in this work.GitHub Repository:MohanadDiab/LangRS.展开更多
Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the ...Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the operation of such farming from 16/17th century till 1945,many changes in land use/land cover and landscape at all occurred,which are generally evaluated positively.Turbulent events including political,economic and social changes and the displacement of the German-speaking population associated with them in the mid-20th century rapidly ended this development,causing significant landscape changes,such as the abandonment of agricultural land and succession,afforestation,expansion of the alpine tree line,reduction of diversity.The aim of our study is to evaluate changes of land cover(forests,dwarf pine,grasslands,other areas)from 1936/1946 till 2021,secondary succession and driving forces of change for selected meadow enclaves in the Krkonose Mountains and the Hruby Jeseník Mountains after the decline of mountain chalet farming since the middle of 20th century.We used remote sensing methods(aerial imagery)and field research(dendrochronology and comparative photography)to detect the land use/land cover changes in the selected study areas in the Krkono?e Mountains and the Hruby Jeseník Mountains.We documented the process of the succession,which occurred almost immediately after the end of farming,peaking about 10–20 years later,with an earlier start in the Hruby Jeseník Mountains.The succession led to the significant change of land use/land cover and these processes were similar in both mountain ranges.The largest changes were a decrease in grasslands by 62%–64%and an increase in forest area by 33%–40%for both study areas.The abandonment of land is the main consequence of a crucial political driving forces(displacement of German-speaking population)in the Krkono?e Mountains and the Hruby Jeseník Mountains.展开更多
This study explores the integration of Synthetic Aperture Radar(SAR)imagery with deep learning and metaheuristic feature optimization techniques for enhanced oil spill detection.This study proposes a novel hybrid appr...This study explores the integration of Synthetic Aperture Radar(SAR)imagery with deep learning and metaheuristic feature optimization techniques for enhanced oil spill detection.This study proposes a novel hybrid approach for oil spill detection.The introduced approach integrates deep transfer learning with the metaheuristic Binary Harris Hawk optimization(BHHO)and Principal Component Analysis(PCA)for improved feature extraction and selection from input SAR imagery.Feature transfer learning of the MobileNet convolutional neural network was employed to extract deep features from the SAR images.The BHHO and PCA algorithms were implemented to identify subsets of optimal features from the entire feature dataset extracted by MobileNet.A supplemented hybrid feature set was constructed from the PCA and BHHO-generated features.It was used as input for oil spill detection using the logistic regression supervised machine learning classification algorithm.Several feature set combinations were implemented to test the classification performance of the logistic regression classifier in comparison to that of the proposed hybrid feature set.Results indicate that the highest oil spill detection accuracy of 99.2%has been achieved using the logistic regression classification algorithm,with integrated feature input from subsets identified using the PCA and the BHHO feature selection techniques.The proposed method yielded a statistically significant improvement in the classification performance of the used machine learning model.The significance of our study lies in its unique integration of deep learning with optimized feature selection,unlike other published studies,to enhance oil spill detection accuracy.展开更多
The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to e...The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.展开更多
The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regener...The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regeneration cycle.This study aims to identify the indicators influencing forest fire vulnerability and compare maps of forest fire susceptibility that are based on the Intergovernmental Panel on Climate Change tripartite model,with a focus on the vulnerable Hyrcanian forest region in Golestan Province,northern Iran,where forest fires have caused considerable economic losses.On the basis of expert opinions and a literature review,we used geographic information systems,remote sensing and machine learning techniques to select and weigh 30 biophysical,environmental and socioeconomic indicators that affect forest fire vulnerability in the study area.These indicators were rigorously normalized,weighted and amalgamated into a comprehensive forest fire vulnerability index to analyze forest exposure,sensitivity and adaptive capacity.We thus identified and mapped areas with very high forest fire exposure,high sensitivity and low adaptive capacity for urgent targeted intervention and strategic planning to mitigate the impacts of forest fires.The results also revealed a set of critical indicators that contribute more significantly to forest fire vulnerability(e.g.,precipitation,elevation and factors related to biodiversity,human activity and economic reliance on forest resources).Our results provide insights that can inform policy-making,community engagement and environmental management strategies to mitigate the vulnerabilities associated with forest fires in the Hyrcanian forest.展开更多
Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca ...Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca lating urbanization and a dwindling rural populace in China,reconstructing rural settlements to enhance public service accessibility has become a fundamental strategy for achieving the SDGs in rural areas.However,few stud ies have examined the optimal methods for rural settlement reconstruction that ensure accessible and equitable public services while considering multiple existing facilities and service provisions.This paper focuses on rural settlement reconstruction in the context of the SDGs,employing an inverted MCLP-CC(maximal coverage loca tion problem for complementary coverage)model to identify optimal rural settlements and a rank-based method for their relocation.Conducted in Changyuan,a county-level city in Henan Province,China,this study observed significant enhancements in both accessibility and equity following rural settlement reconstruction by utilizing the MH3SFCA(modified Huff 3-step floating catchment area)and the spatial Lorenz curve method.Remarkably,these improvements were achieved without the addition of new facilities,with the accessibility increasing by 44.21%,4.97%,and 3.11%;Gini coefficients decreasing by 19.53%,1.64%,and 3.18%;Ricci-Schutz coef-ficients decreasing by 21.09%,2.09%,and 4.33%for educational,medical,and cultural and sports facilities,respectively.It indicated that rural settlement reconstruction can bolster the accessibility and equity of public ser-vices by leveraging existing facilities.This paper provides a new framework for stakeholders to better reconstruct rural settlements and promote sustainable development in rural areas in China.展开更多
A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the...A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the angle between the vehicle direction and the road segment direction and the road connectivity are discussed. Fuzzy rules for the distance, angle and connectivity are presented to calculate the matching reliability. 2 indicators for estimating the matching reliability are then derived, one is the lower limit of the reliability, and the other is the limit error of the difference between the maximal value and the second-maximal value of the reliability. A real-time map-matching system based on fuzzy logic is therefore developed. Using the real data of global positioning system(GIS) based navigation and geographic information system(GPS) based road map, the method is verified and the (results) prove the effectiveness of the proposed method.展开更多
AIM To perform a comprehensive review and provide an up-to-date synopsis of the incidence and trends of inflammatory bowel disease(IBD). METHODS We systematically searched the MEDLINE(source Pub Med), EMBASE and Cochr...AIM To perform a comprehensive review and provide an up-to-date synopsis of the incidence and trends of inflammatory bowel disease(IBD). METHODS We systematically searched the MEDLINE(source Pub Med), EMBASE and Cochrane Library databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines(period: 1985-2018) to identify studies reporting population-based data on the incidence of pediatriconset(< 19 years at diagnosis) IBD in full manuscripts. Two authors carried out screening and data extraction. Choropleth interactive maps and temporal trends were used to illustrate the international differences and incidences of and changes in IBD and subtypes.RESULTS In total, one hundred forty studies reporting data from 38 countries were considered in this review. The highest annual pediatric incidences of IBD were 23/100000 person-years in Europe, 15.2/100000 in North America, and 11.4/100000 in Asia/the Middle East and Oceania. The highest annual incidences of Crohn's disease(CD) were 13.9/100000 in North America and 12.3/100000 in Europe. The highest annual incidences of ulcerative colitis(UC) were 15.0/100000 in Europe and 10.6/100000 in North America. The highest annual incidences of IBD-unclassified(IBD-U) were 3.6/100000 in Europe and 2.1/100000 in North America. In the time-trend analyses, 67% of CD, 46% of UC and 11% of IBD-U studies reported an increasing incidence(P < 0.05). The risk of IBD is increasing among firstgeneration of migrant populations.CONCLUSION Globally, the incidence of IBD varies greatly by geographical areas. The steadily increasing incidence of pediatric IBD over time indicates its emergence as a global disease, suggesting that studies should investigate the environmental risk factors among pediatric cohorts.展开更多
Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. In this paper, the relationship between zenith tropospheric delays and the elevation and longitude of ...Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. In this paper, the relationship between zenith tropospheric delays and the elevation and longitude of stations is analyzed using the zenith tropospheric delay final products of International GNSS Service （IGS） stations from 2011. Two new models are proposed for estimating zenith tropospheric delays from regional CORS data without meteorological data. The proposed models are compared with the direct interpolation method and the remove-restore method using data from Guangxi CORS. The results show that the new models significantly improve the calculated precision. Finally, the root mean square （RMS） errors of the new models were used to estimate the surface precipitable water vapor （PWV） value at CORS station, which was determined to be less than 2 mm.展开更多
The prospects for expanding the mineral resource base in many countries are linked with the exploration of stranded sites localized at unexplored areas with complex natural and landscape conditions that make any groun...The prospects for expanding the mineral resource base in many countries are linked with the exploration of stranded sites localized at unexplored areas with complex natural and landscape conditions that make any ground survey,including magnetic prospecting,difficult and expensive.The current level of geology requires high-precision and large-scale data at the first stages of geological exploration.Since 2012,technologies of aeromagnetic surveying with unmanned aircraft vehicles(UAV)enter the market,but most of them are based on big fixed-wing UAV and do not allow to substantially increase the level of survey granularity compared with traditional aerial methods.To increase the scale of survey,it is necessary to reduce the altitude and speed of flight,for which the authors develop the methodical and technical solutions described in this article.To obtain data at altitudes of 5 m above the terrain even in a rugged relief,we created heavy multirotor UAVs that are stable in flight and may be used in a wide range of environmental conditions(even a moderate snowfall),and develop a special software to generate flight missions on the basis of digital elevation models.A UAV has special design to reduce magnetic interference of the flight platform;the magnetic sensor is hung below the aircraft.This technology was conducted in a considerable amount of magnetic surveys in the mountainous regions of East Siberia between 2014 and 2016.The results of the comparison between airborne and ground surveys are presented,which show that the sensitivity of the developed system in conjunction with low-altitude measurements can cover any geologically significant anomalies of the magnetic field.An unmanned survey is cheaper and more productive;the multirotor-based technologies may largely replace traditional ground magnetic exploration in scales of 1:10,000−1:1000.展开更多
The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） o...The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） of 0.53 in Well M1 and 0.55 in Wells H1/Hd1/Hd2, respectively. Comparing with vitrinite reflectance （Ro/%）, the OP features a dynamic range and can indicate the oil generation window more precisely. By using OP and other geochemical indices, the oil-source correlation is also conducted. It suggests that the oils in wells M1 and M2 are derived from the source rocks in situ. The mudstone in Huachang uplift is not the main source rocks for oils in this area, The OP is also a useful oil-source correlation parameter in some Tertiary lacustrine basins.展开更多
Current global urbanisation processes are leading to new forms of massive urban constellations. The conceptualisations and classifications of these, however, are often ambiguous, overlap or lag behind in scientific li...Current global urbanisation processes are leading to new forms of massive urban constellations. The conceptualisations and classifications of these, however, are often ambiguous, overlap or lag behind in scientific literature. This article examines whether there is a common denominator to define and delimitate–and ultimately map–these new dimensions of cityscapes. In an extensive literature review we analysed and juxtaposed some of the most common concepts such as megacity, megaregion or megalopolis. We observed that many concepts are abstract or unspecific, and for those concepts for which physical parameters exist, the parameters are neither properly defined nor used in standardised ways. While understandably concepts originate from various disciplines, the authors identify a need for more precise definition and use of parameters. We conclude that often, spatial patterns of large urban areas resemble each other considerably but the definitions vary so widely that these differences may surpass any inconsistencies in the spatial delimitation process. In other words, today we have tools such as earth observation data and Geographic Information Systems to parameterise if clear definitions are provided. This appears not to be the case. The limiting factor when delineating large urban areas seems to be a commonly agreed ontology.展开更多
Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has ...Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.展开更多
Reflected signals from global navigation satellite systems（GNSSs） have been widely acknowledged as an important remote sensing tool for retrieving sea surface wind speeds.The power of GNSS reflectometry（GNSS-R）sig...Reflected signals from global navigation satellite systems（GNSSs） have been widely acknowledged as an important remote sensing tool for retrieving sea surface wind speeds.The power of GNSS reflectometry（GNSS-R）signals can be mapped in delay chips and Doppler frequency space to generate delay Doppler power maps（DDMs）,whose characteristics are related to sea surface roughness and can be used to retrieve wind speeds.However,the bistatic radar cross section（BRCS）,which is strongly related to the sea surface roughness,is extensively used in radar.Therefore,a bistatic radar cross section（BRCS） map with a modified BRCS equation in a GNSS-R application is introduced.On the BRCS map,three observables are proposed to represent the sea surface roughness to establish a relationship with the sea surface wind speed.Airborne Hurricane Dennis（2005） GNSS-R data are then used.More than 16 000 BRCS maps are generated to establish GMFs of the three observables.Finally,the proposed model and classic one-dimensional delay waveform（DW） matching methods are compared,and the proposed model demonstrates a better performance for the high wind speed retrievals.展开更多
The contents of nitrogen and organic carbon in an agricultural soil were analyzed using reflectance measurements （n = 52） performed with an ASD FieldSpee-Ⅱ spectroradiometer. For parameter prediction, empirical mod...The contents of nitrogen and organic carbon in an agricultural soil were analyzed using reflectance measurements （n = 52） performed with an ASD FieldSpee-Ⅱ spectroradiometer. For parameter prediction, empirical models based on partial least squares （PLS） regression were defined from the measured reflectance spectra （0.4 to 2.4 μm）. Here, reliable estimates were obtained for nitrogen content, but prediction accuracy was only moderate for organic carbon. For nitrogen, the real spatial pattern of within-field variability was reproduced with high accuracy. The results indicate the potential of this method as a quick screening tool for the spatial assessment of nitrogen and organic carbon, and therefore an appropriate alternative to time- and cost-intensive chemical analysis in the laboratory.展开更多
The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas.The objectives are:(1)to test the applicability of UAV visible a...The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas.The objectives are:(1)to test the applicability of UAV visible an near-infrared(VNIR)and geometrical data based on Z values of point dense cloud(PDC)raster to separate forest species and dead trees in the study area;(2)to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling;and(3)to explore the possibility of the qualitative classification of spruce health indicators.Analysis based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir,and for identification of dead tree category.Separation between common beech and fir was distinguished by the object-oriented image analysis.NDVI was able to identify the presence of key indicators of spruce health,such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation,while stem damage by peeling was identified at the significance margin.The results contributed to improving separation of coniferous(spruce and fir)tree species based on VNIR and PDC raster UAV data,and newly demonstrated the potential of NDVI for qualitative classification of spruce trees.The proposed methodology can be applicable for monitoring of spruce health condition in the local forest sites.展开更多
文摘This paper discusses the role of Geoinformatics as a new scientific discipline designed for handling of geospatial information.Depending on the scientific background of the people involved in shaping the emerging discipline,emphasis may be placed on different aspects of Geoinformatics.Applications and developments may address geoscientific,spatial planning,or computer science related matters.The scientific field of Geoinformatics encompasses the acquisition and storing of geospatial data,the modelling and presentation of spatial information,geoscientific analyses and spatial planning,and the development of algorithms and geospatial database systems.It is the position of the author that these tools from Geoinformatics are necessary to bridge the gap between Digital Earth models and the real world with its real-world problems(‘connecting through location’).It is,however,crucial that Geoinformatics represents a coherent integrated approach to the acquisition,storage,analysis,modeling,presentation,and dissemination of geo-processes and not a patchwork solution of unconnected fields of activity.Geoinformatics is as such not a part of Geography,Surveying,or Computer Science,but a new self-contained scientific discipline.The current paper highlights international and national trends of the discipline and presents a number of Geoinformatics initiatives.The research and teaching activities of the newly formed Institute for Geoinformatics and Remote Sensing(IGF)at the University of Osnabrueck serve as an example for these initiatives.All these developments have lead to the long overdue formation of a scientific‘Society for Geoinformatics’(German:Gesellschaft fu¨r Geoinformatik-GfGI)in Germany.
文摘The use of AI technologies in remote sensing(RS)tasks has been the focus of many individuals in both the professional and academic domains.Having more accessible interfaces and tools that allow people of little or no experience to intuitively interact with RS data of multiple formats is a potential provided by this integration.However,the use of AI and AI agents to help automate RS-related tasks is still in its infancy stage,with some frameworks and interfaces built on top of well-known vision language models(VLM)such as GPT-4,segment anything model(SAM),and grounding DINO.These tools do promise and draw guidelines on the potentials and limitations of existing solutions concerning the use of said models.In this work,the state of the art AI foundation models(FM)are reviewed and used in a multi-modal manner to ingest RS imagery input and perform zero-shot object detection using natural language.The natural language input is then used to define the classes or labels the model should look for,then,both inputs are fed to the pipeline.The pipeline presented in this work makes up for the shortcomings of the general knowledge FMs by stacking pre-processing and post-processing applications on top of the FMs;these applications include tiling to produce uniform patches of the original image for faster detection,outlier rejection of redundant bounding boxes using statistical and machine learning methods.The pipeline was tested with UAV,aerial and satellite images taken over multiple areas.The accuracy for the semantic segmentation showed improvement from the original 64%to approximately 80%-99%by utilizing the pipeline and techniques proposed in this work.GitHub Repository:MohanadDiab/LangRS.
基金funded by the European Commission,CINEA Horizon Europe project no.101081307“Towards Sustainable Land-Use in the Context of Climate Change and Biodiversity in Europe(Europe-LAND)”。
文摘Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the operation of such farming from 16/17th century till 1945,many changes in land use/land cover and landscape at all occurred,which are generally evaluated positively.Turbulent events including political,economic and social changes and the displacement of the German-speaking population associated with them in the mid-20th century rapidly ended this development,causing significant landscape changes,such as the abandonment of agricultural land and succession,afforestation,expansion of the alpine tree line,reduction of diversity.The aim of our study is to evaluate changes of land cover(forests,dwarf pine,grasslands,other areas)from 1936/1946 till 2021,secondary succession and driving forces of change for selected meadow enclaves in the Krkonose Mountains and the Hruby Jeseník Mountains after the decline of mountain chalet farming since the middle of 20th century.We used remote sensing methods(aerial imagery)and field research(dendrochronology and comparative photography)to detect the land use/land cover changes in the selected study areas in the Krkono?e Mountains and the Hruby Jeseník Mountains.We documented the process of the succession,which occurred almost immediately after the end of farming,peaking about 10–20 years later,with an earlier start in the Hruby Jeseník Mountains.The succession led to the significant change of land use/land cover and these processes were similar in both mountain ranges.The largest changes were a decrease in grasslands by 62%–64%and an increase in forest area by 33%–40%for both study areas.The abandonment of land is the main consequence of a crucial political driving forces(displacement of German-speaking population)in the Krkono?e Mountains and the Hruby Jeseník Mountains.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number RI-44-0456.
文摘This study explores the integration of Synthetic Aperture Radar(SAR)imagery with deep learning and metaheuristic feature optimization techniques for enhanced oil spill detection.This study proposes a novel hybrid approach for oil spill detection.The introduced approach integrates deep transfer learning with the metaheuristic Binary Harris Hawk optimization(BHHO)and Principal Component Analysis(PCA)for improved feature extraction and selection from input SAR imagery.Feature transfer learning of the MobileNet convolutional neural network was employed to extract deep features from the SAR images.The BHHO and PCA algorithms were implemented to identify subsets of optimal features from the entire feature dataset extracted by MobileNet.A supplemented hybrid feature set was constructed from the PCA and BHHO-generated features.It was used as input for oil spill detection using the logistic regression supervised machine learning classification algorithm.Several feature set combinations were implemented to test the classification performance of the logistic regression classifier in comparison to that of the proposed hybrid feature set.Results indicate that the highest oil spill detection accuracy of 99.2%has been achieved using the logistic regression classification algorithm,with integrated feature input from subsets identified using the PCA and the BHHO feature selection techniques.The proposed method yielded a statistically significant improvement in the classification performance of the used machine learning model.The significance of our study lies in its unique integration of deep learning with optimized feature selection,unlike other published studies,to enhance oil spill detection accuracy.
基金the National Natural Science Foundation of China(NSFC 31761143002,NSFC 3207178)China Postdoctoral Science Foundation(2022M710405)the National Forest and Grassland Genetic Recourse(No.2005DKA21003).
文摘The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.
基金funding provided by University of Natural Resources and Life Sciences Vienna(BOKU).
文摘The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regeneration cycle.This study aims to identify the indicators influencing forest fire vulnerability and compare maps of forest fire susceptibility that are based on the Intergovernmental Panel on Climate Change tripartite model,with a focus on the vulnerable Hyrcanian forest region in Golestan Province,northern Iran,where forest fires have caused considerable economic losses.On the basis of expert opinions and a literature review,we used geographic information systems,remote sensing and machine learning techniques to select and weigh 30 biophysical,environmental and socioeconomic indicators that affect forest fire vulnerability in the study area.These indicators were rigorously normalized,weighted and amalgamated into a comprehensive forest fire vulnerability index to analyze forest exposure,sensitivity and adaptive capacity.We thus identified and mapped areas with very high forest fire exposure,high sensitivity and low adaptive capacity for urgent targeted intervention and strategic planning to mitigate the impacts of forest fires.The results also revealed a set of critical indicators that contribute more significantly to forest fire vulnerability(e.g.,precipitation,elevation and factors related to biodiversity,human activity and economic reliance on forest resources).Our results provide insights that can inform policy-making,community engagement and environmental management strategies to mitigate the vulnerabilities associated with forest fires in the Hyrcanian forest.
基金funded by the National Nat-ural Science Foundation of China(Grants No.42371433,U2443214)National Key Project of High-Resolution Earth Observation System of China(Grant No.80Y50G19900122/23)Foundation of Key Laboratory of Soil andWater Conservation on the Loess Plateau ofMinistry ofWater Resources(Grant No.WSCLP202301).
文摘Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca lating urbanization and a dwindling rural populace in China,reconstructing rural settlements to enhance public service accessibility has become a fundamental strategy for achieving the SDGs in rural areas.However,few stud ies have examined the optimal methods for rural settlement reconstruction that ensure accessible and equitable public services while considering multiple existing facilities and service provisions.This paper focuses on rural settlement reconstruction in the context of the SDGs,employing an inverted MCLP-CC(maximal coverage loca tion problem for complementary coverage)model to identify optimal rural settlements and a rank-based method for their relocation.Conducted in Changyuan,a county-level city in Henan Province,China,this study observed significant enhancements in both accessibility and equity following rural settlement reconstruction by utilizing the MH3SFCA(modified Huff 3-step floating catchment area)and the spatial Lorenz curve method.Remarkably,these improvements were achieved without the addition of new facilities,with the accessibility increasing by 44.21%,4.97%,and 3.11%;Gini coefficients decreasing by 19.53%,1.64%,and 3.18%;Ricci-Schutz coef-ficients decreasing by 21.09%,2.09%,and 4.33%for educational,medical,and cultural and sports facilities,respectively.It indicated that rural settlement reconstruction can bolster the accessibility and equity of public ser-vices by leveraging existing facilities.This paper provides a new framework for stakeholders to better reconstruct rural settlements and promote sustainable development in rural areas in China.
基金Projects(40301043 and 40171078) supported by the National Natural Science Foundation of China
文摘A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the angle between the vehicle direction and the road segment direction and the road connectivity are discussed. Fuzzy rules for the distance, angle and connectivity are presented to calculate the matching reliability. 2 indicators for estimating the matching reliability are then derived, one is the lower limit of the reliability, and the other is the limit error of the difference between the maximal value and the second-maximal value of the reliability. A real-time map-matching system based on fuzzy logic is therefore developed. Using the real data of global positioning system(GIS) based navigation and geographic information system(GPS) based road map, the method is verified and the (results) prove the effectiveness of the proposed method.
基金Supported by the“On Our Own Feet Movement-P?áteléstonozky”-Endowment Programand Research Project Progress Q-39
文摘AIM To perform a comprehensive review and provide an up-to-date synopsis of the incidence and trends of inflammatory bowel disease(IBD). METHODS We systematically searched the MEDLINE(source Pub Med), EMBASE and Cochrane Library databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines(period: 1985-2018) to identify studies reporting population-based data on the incidence of pediatriconset(< 19 years at diagnosis) IBD in full manuscripts. Two authors carried out screening and data extraction. Choropleth interactive maps and temporal trends were used to illustrate the international differences and incidences of and changes in IBD and subtypes.RESULTS In total, one hundred forty studies reporting data from 38 countries were considered in this review. The highest annual pediatric incidences of IBD were 23/100000 person-years in Europe, 15.2/100000 in North America, and 11.4/100000 in Asia/the Middle East and Oceania. The highest annual incidences of Crohn's disease(CD) were 13.9/100000 in North America and 12.3/100000 in Europe. The highest annual incidences of ulcerative colitis(UC) were 15.0/100000 in Europe and 10.6/100000 in North America. The highest annual incidences of IBD-unclassified(IBD-U) were 3.6/100000 in Europe and 2.1/100000 in North America. In the time-trend analyses, 67% of CD, 46% of UC and 11% of IBD-U studies reported an increasing incidence(P < 0.05). The risk of IBD is increasing among firstgeneration of migrant populations.CONCLUSION Globally, the incidence of IBD varies greatly by geographical areas. The steadily increasing incidence of pediatric IBD over time indicates its emergence as a global disease, suggesting that studies should investigate the environmental risk factors among pediatric cohorts.
基金supported by the National Natural Foundation of China(4106400141071294)+1 种基金the Natural Science Foundation of Guangxi(2012GXNSFAA053183)Guangxi Key Laboratory of Spatial Information and Geomatics(1103108-06)
文摘Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. In this paper, the relationship between zenith tropospheric delays and the elevation and longitude of stations is analyzed using the zenith tropospheric delay final products of International GNSS Service （IGS） stations from 2011. Two new models are proposed for estimating zenith tropospheric delays from regional CORS data without meteorological data. The proposed models are compared with the direct interpolation method and the remove-restore method using data from Guangxi CORS. The results show that the new models significantly improve the calculated precision. Finally, the root mean square （RMS） errors of the new models were used to estimate the surface precipitable water vapor （PWV） value at CORS station, which was determined to be less than 2 mm.
基金This work was supported by the Council on grants of the President of the Russian Federation[Grant Number MK-3608.2018.5].
文摘The prospects for expanding the mineral resource base in many countries are linked with the exploration of stranded sites localized at unexplored areas with complex natural and landscape conditions that make any ground survey,including magnetic prospecting,difficult and expensive.The current level of geology requires high-precision and large-scale data at the first stages of geological exploration.Since 2012,technologies of aeromagnetic surveying with unmanned aircraft vehicles(UAV)enter the market,but most of them are based on big fixed-wing UAV and do not allow to substantially increase the level of survey granularity compared with traditional aerial methods.To increase the scale of survey,it is necessary to reduce the altitude and speed of flight,for which the authors develop the methodical and technical solutions described in this article.To obtain data at altitudes of 5 m above the terrain even in a rugged relief,we created heavy multirotor UAVs that are stable in flight and may be used in a wide range of environmental conditions(even a moderate snowfall),and develop a special software to generate flight missions on the basis of digital elevation models.A UAV has special design to reduce magnetic interference of the flight platform;the magnetic sensor is hung below the aircraft.This technology was conducted in a considerable amount of magnetic surveys in the mountainous regions of East Siberia between 2014 and 2016.The results of the comparison between airborne and ground surveys are presented,which show that the sensitivity of the developed system in conjunction with low-altitude measurements can cover any geologically significant anomalies of the magnetic field.An unmanned survey is cheaper and more productive;the multirotor-based technologies may largely replace traditional ground magnetic exploration in scales of 1:10,000−1:1000.
基金supported by the Natural Science Foundation of China(Grant No.40672093)CNPC Innovation Fund(07El001)the ESS-China Hydrocarbon Geosciences Collaboration Project under Natural Resources Canada's International Opportunities Program.
文摘The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） of 0.53 in Well M1 and 0.55 in Wells H1/Hd1/Hd2, respectively. Comparing with vitrinite reflectance （Ro/%）, the OP features a dynamic range and can indicate the oil generation window more precisely. By using OP and other geochemical indices, the oil-source correlation is also conducted. It suggests that the oils in wells M1 and M2 are derived from the source rocks in situ. The mudstone in Huachang uplift is not the main source rocks for oils in this area, The OP is also a useful oil-source correlation parameter in some Tertiary lacustrine basins.
文摘Current global urbanisation processes are leading to new forms of massive urban constellations. The conceptualisations and classifications of these, however, are often ambiguous, overlap or lag behind in scientific literature. This article examines whether there is a common denominator to define and delimitate–and ultimately map–these new dimensions of cityscapes. In an extensive literature review we analysed and juxtaposed some of the most common concepts such as megacity, megaregion or megalopolis. We observed that many concepts are abstract or unspecific, and for those concepts for which physical parameters exist, the parameters are neither properly defined nor used in standardised ways. While understandably concepts originate from various disciplines, the authors identify a need for more precise definition and use of parameters. We conclude that often, spatial patterns of large urban areas resemble each other considerably but the definitions vary so widely that these differences may surpass any inconsistencies in the spatial delimitation process. In other words, today we have tools such as earth observation data and Geographic Information Systems to parameterise if clear definitions are provided. This appears not to be the case. The limiting factor when delineating large urban areas seems to be a commonly agreed ontology.
基金This study was funded by the Korea Meteorological Administration Research and Development Program(KMI2017-9060)the National Research Foundation of Korea funded by the Korea government(NRF-2018M1A3A3A02066008)+1 种基金In addition,the ALOS-2 PALSAR-2 data used in this study are owned by the Japan Aerospace Exploration Agency(JAXA)and were provided through the JAXA’s ALOS-2 research program(RA4,PI No.1412)The GPS data were provided by the Geospatial Information Authority of Japan.
文摘Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.
基金The National Natural Science Foundation of China under contract No.41371355the Director Fund Project of Institute of Remote Sensing and Digital Earth of CAS under contract No.Y6SJ0600CX
文摘Reflected signals from global navigation satellite systems（GNSSs） have been widely acknowledged as an important remote sensing tool for retrieving sea surface wind speeds.The power of GNSS reflectometry（GNSS-R）signals can be mapped in delay chips and Doppler frequency space to generate delay Doppler power maps（DDMs）,whose characteristics are related to sea surface roughness and can be used to retrieve wind speeds.However,the bistatic radar cross section（BRCS）,which is strongly related to the sea surface roughness,is extensively used in radar.Therefore,a bistatic radar cross section（BRCS） map with a modified BRCS equation in a GNSS-R application is introduced.On the BRCS map,three observables are proposed to represent the sea surface roughness to establish a relationship with the sea surface wind speed.Airborne Hurricane Dennis（2005） GNSS-R data are then used.More than 16 000 BRCS maps are generated to establish GMFs of the three observables.Finally,the proposed model and classic one-dimensional delay waveform（DW） matching methods are compared,and the proposed model demonstrates a better performance for the high wind speed retrievals.
文摘The contents of nitrogen and organic carbon in an agricultural soil were analyzed using reflectance measurements （n = 52） performed with an ASD FieldSpee-Ⅱ spectroradiometer. For parameter prediction, empirical models based on partial least squares （PLS） regression were defined from the measured reflectance spectra （0.4 to 2.4 μm）. Here, reliable estimates were obtained for nitrogen content, but prediction accuracy was only moderate for organic carbon. For nitrogen, the real spatial pattern of within-field variability was reproduced with high accuracy. The results indicate the potential of this method as a quick screening tool for the spatial assessment of nitrogen and organic carbon, and therefore an appropriate alternative to time- and cost-intensive chemical analysis in the laboratory.
基金This work was supported by the Ministry of Education,Youth and Sports of the Czech Republic within the National Programme for Sustainability I[grant number LO1415]partly by EEA Grants if Iceland,Liechtenstein and Norway[grant number EHP-CZ02-OV-1-019-2014].
文摘The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas.The objectives are:(1)to test the applicability of UAV visible an near-infrared(VNIR)and geometrical data based on Z values of point dense cloud(PDC)raster to separate forest species and dead trees in the study area;(2)to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling;and(3)to explore the possibility of the qualitative classification of spruce health indicators.Analysis based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir,and for identification of dead tree category.Separation between common beech and fir was distinguished by the object-oriented image analysis.NDVI was able to identify the presence of key indicators of spruce health,such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation,while stem damage by peeling was identified at the significance margin.The results contributed to improving separation of coniferous(spruce and fir)tree species based on VNIR and PDC raster UAV data,and newly demonstrated the potential of NDVI for qualitative classification of spruce trees.The proposed methodology can be applicable for monitoring of spruce health condition in the local forest sites.
