Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelengt...Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.展开更多
The advancement of effective spatial planning to support sustainable development and interregional cooperation has become an issue of serious concern for regional authorities.Spatial planning research helps to identif...The advancement of effective spatial planning to support sustainable development and interregional cooperation has become an issue of serious concern for regional authorities.Spatial planning research helps to identify economic clusters and analyze their changing spatial patterns,which is important for understanding regional economic space dynamics and poten-tial inter-regional cooperation.To support decision-makers in the development of efficient plans of spatial development encompassing the identification of the best-suited territories,a combined Geographic Information System(GIS)based approach to interpret qualitatively expressed multiple socio-economic scenarios in quantitative map-based terms of graded suitability,and a formalized approach to the socio-economic evaluation of the territory is offered.Based on GIS technology coupled with integrated cellular automata decision analysis techniques,the study provides a method that performs socio-economic assessment of the study area according to the generated scenarios of regional spatial and socio-economic development.The proposed method is applied to Primorsky and Khabarovsk Krais,located in the Russian Far East.Socio-economic scenarios of spatial development initiated by investors and regional authorities were assessed and evaluated.The generated socio-economic scenar-ios illustrate how the unified set of spatial and socio-economic variables can be linked and used to gain insights into inter-regional socio-economic and spatial development.The application results demonstrate the advantage of the proposed method in identifying the best-suited unit areas for targeted regional development.展开更多
We sketch Friedrich Ackermann’s research program following the concept of Imre Lakatos,with some historical key developments in the theory and application of aerotriangulation and image matching.The research program,...We sketch Friedrich Ackermann’s research program following the concept of Imre Lakatos,with some historical key developments in the theory and application of aerotriangulation and image matching.The research program,with its core being statistical estimation theory,has decisively influenced photogrammetry since the 60s,is still fully alive,and a challenge for today’s methods of image interpretation.We describe(1)Lakatos’concept of a scientific research program,with its negative and positive heuristics and(2)Ackermann’s research program,clearly made explicit in his PhD,with its mathematical model,the ability to predict theoretical precision and reliability,the potential of analyzing rigorous and approximate method,and the role of testing.The development of aerotriangulation,later augmented by image matching techniques,is closely connected to Ackermann’s successful attempts to integrate basic research and practical applications.展开更多
Mangroves are woody plant communities that appear in tropical and subtropical regions,mainly in intertidal zones along the coastlines.Despite their considerable benefits to humans and the surrounding environment,their...Mangroves are woody plant communities that appear in tropical and subtropical regions,mainly in intertidal zones along the coastlines.Despite their considerable benefits to humans and the surrounding environment,their existence is threatened by anthropogenic activities and natural drivers.Accordingly,it is vital to conduct efficient efforts to increase mangrove plantations by identifying suitable locations.These efforts are required to support conservation and plantation practices and lower the mortality rate of seedlings.Therefore,identifying ecologically potential areas for plantation practices is mandatory to ensure a higher success rate.This study aimed to identify suitable locations for mangrove plantations along the southern coastal frontiers of Hormozgan,Iran.To this end,we applied a hybrid Fuzzy-DEMATEL-ANP(FDANP)model as a Multi-Criteria Decision Making(MCDM)approach to determine the relative importance of different criteria,combined with geospatial and remote sensing data.In this regard,ten relevant sources of environmental criteria,including meteorological,topographical,and geomorphological,were used in the modeling.The statistical evaluation demonstrated the high potential of the developed approach for suitable location identification.Based on the final results,6.10%and 20.80%of the study area were classified as very-high suitable and very-low suitable areas.The obtained values can elucidate the path for decision-makers and managers for better conservation and plantation planning.Moreover,the utility of charge-free remote sensing data allows cost-effective implementation of such an approach for other regions by interested researchers and governing organizations.展开更多
This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were proce...This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were processed.Reference samples were scrutinized using the Continuous Change Detection and Classification(CCDC)algorithm to identify spectrally unchanged samples.These spectrally unchanged samples were subsequently employed as training data within an object-based Random Forest(RF)model to generate wetland maps from 1984 to 2021.Subsequently,a change analysis was conducted to calculate the loss and gain of different wetland types.Overall,it was observed that approximately 45%(184,434 km^(2))and 55%(220,778 km^(2))of the entire study area are covered by wetland and non-wetland categories,respectively.It was also observed that 2.46%(12,495 km^(2))of the study area was changed during 40 years.Overall,there was a decline in the Bog and Fen classes,while the Marsh,Swamp,Forest,Grassland/Shrubland,Cropland,and Barren classes had an increase.Finally,the wetland gain and loss were 6,793 km^(2)and 5,701 km^(2),respectively.This study demonstrated that the use of Landsat data,along with advanced machine learning and GEE,could provide valuable assistance for wetland classification and change studies.展开更多
Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth.Spread modeling,which is one of the most helpful analyses in the geographic inform...Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth.Spread modeling,which is one of the most helpful analyses in the geographic information system(GIS),plays a prominent role in meeting this objective.This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata(CA)modeling.Therefore,artificial intelligence tools such as adaptive neuro-fuzzy inference system(ANFIS)and genetic algorithm(GA)were used in accordance with the objectives of knowledge discovery and optimization.Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization.We focused on the estimation of forest fire growth as an important case study for decision makers.A two-dimensional cellular representation of the combustion of heterogeneous fuel types and density on non-flat terrain were successfully linked with dynamic wind and slope impact.The validation of the simulation on experimental data indicated a relatively realistic head-fire shape.Further investigations showed that the results obtained using the dynamic controlling with GA in the absence of static modeling with ANFIS were unacceptable.展开更多
With growing demand on multi-purpose or multi-modal navigation,the route calculation needs to traverse semantically enriched road networks for different transportation modes.Currently,operational route planning algori...With growing demand on multi-purpose or multi-modal navigation,the route calculation needs to traverse semantically enriched road networks for different transportation modes.Currently,operational route planning algorithms reveal rather limited performances or their potential for comprehensive applications are constrained by the unavailable or insufficient interoperation among the under-lying geo-data that are separately maintained in different spatial databases.To overcome this limitation,a novel approach has been proposed to integrate the routing-relevant information from different data sources,which involves three processes:(1)automatic matching to identify the corresponding road objects between different datasets;(2)interaction to refine the automatic matching result;and(3)transferring the routing-relevant information from one data-set to another.In process(1),the Delimited Stroke Oriented algorithm is employed to achieve the automatic data matching between different datasets,which has revealed a high matching rate and certainty.However uncertain matching problems occur in areas where topological conditions are too complicated or inconsistent.The remaining unmatched or wrongly matched objects are treated in process(2),with the help of a series of interaction tools.On the basis of refined matching results after the interaction,process(3)is dedicated to automatic integration of the routing-relevant information from different data sources.展开更多
To support the monitoring and reporting processes during imple-mentation of the Sustainable Development Goals,well-developed,commonly recognized Earth observations and geospatial data,methods,innovations,committed pro...To support the monitoring and reporting processes during imple-mentation of the Sustainable Development Goals,well-developed,commonly recognized Earth observations and geospatial data,methods,innovations,committed professionals,and strong sus-tainability policies are necessary.This article informs the readers on the Earth observation and geoinformation developments and innovations,and on the engagement of profession,academy and governance to support implementation of the Sustainable Development Goals in Hungary.Description,analyses and critical assessments are given on the elements selected from Hungarian sustainable-oriented Earth observation and geospatial novelties:(a)Working Group for Sustainable Development mission and national sustainabilitypolicy,(b)international partnerships,domestic activities and achievements,(c)status of the professional education,(d)spatial databases and services to support implementation of the sustain-able development,(e)a case study on the internationally recog-nized soil geoinformation system,(f)national Earth Observation Information System and perspectives of its applications for mon-itoring the sustainability.The article conclusion strongly advises the Hungarian realization of(a)institutionalization of the Earth observation and geospatial tools and capacity for sustainable development,(b)their use in integration with statistical data,(c)establishment of national spatial information infrastructure and(d)development and spreading of the use of big data.展开更多
The advent of information and communication technology and the Internet of Things have led our society toward a digital era.The proliferation of personal computers,smartphones,intelligent autonomous sensors,and pervas...The advent of information and communication technology and the Internet of Things have led our society toward a digital era.The proliferation of personal computers,smartphones,intelligent autonomous sensors,and pervasive network interactions with individuals have gradually shifted human activities from offline to online and from in person to virtual.This transformation has brought a series of challenges in a variety of fields,such as the dilemma of placelessness,some aspects of timelessness(no time relevance),and the changing relevance of distance in the field of geographic information science(GIScience).In the last two decades,“cyber thinking”in GIScience has received significant attention from different perspectives.For instance,human activities in“cyberspace”need to be reconsidered when coupled with the geographic space to observe the first law of geography.展开更多
基金supported by the Shanghai Industrial Collaborative Innovation Fund(HCXBCY-2021-001)the Academy of Finland(349229)。
文摘Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.
基金supported by the Ministry of Science and Higher Education of Russia[grant number 075-15-2020-804].
文摘The advancement of effective spatial planning to support sustainable development and interregional cooperation has become an issue of serious concern for regional authorities.Spatial planning research helps to identify economic clusters and analyze their changing spatial patterns,which is important for understanding regional economic space dynamics and poten-tial inter-regional cooperation.To support decision-makers in the development of efficient plans of spatial development encompassing the identification of the best-suited territories,a combined Geographic Information System(GIS)based approach to interpret qualitatively expressed multiple socio-economic scenarios in quantitative map-based terms of graded suitability,and a formalized approach to the socio-economic evaluation of the territory is offered.Based on GIS technology coupled with integrated cellular automata decision analysis techniques,the study provides a method that performs socio-economic assessment of the study area according to the generated scenarios of regional spatial and socio-economic development.The proposed method is applied to Primorsky and Khabarovsk Krais,located in the Russian Far East.Socio-economic scenarios of spatial development initiated by investors and regional authorities were assessed and evaluated.The generated socio-economic scenar-ios illustrate how the unified set of spatial and socio-economic variables can be linked and used to gain insights into inter-regional socio-economic and spatial development.The application results demonstrate the advantage of the proposed method in identifying the best-suited unit areas for targeted regional development.
文摘We sketch Friedrich Ackermann’s research program following the concept of Imre Lakatos,with some historical key developments in the theory and application of aerotriangulation and image matching.The research program,with its core being statistical estimation theory,has decisively influenced photogrammetry since the 60s,is still fully alive,and a challenge for today’s methods of image interpretation.We describe(1)Lakatos’concept of a scientific research program,with its negative and positive heuristics and(2)Ackermann’s research program,clearly made explicit in his PhD,with its mathematical model,the ability to predict theoretical precision and reliability,the potential of analyzing rigorous and approximate method,and the role of testing.The development of aerotriangulation,later augmented by image matching techniques,is closely connected to Ackermann’s successful attempts to integrate basic research and practical applications.
基金funded by Erasmus+ICM programme for a 3-month and 5-month stay at Lund University,Lund,Sweden,and thank the European Union.
文摘Mangroves are woody plant communities that appear in tropical and subtropical regions,mainly in intertidal zones along the coastlines.Despite their considerable benefits to humans and the surrounding environment,their existence is threatened by anthropogenic activities and natural drivers.Accordingly,it is vital to conduct efficient efforts to increase mangrove plantations by identifying suitable locations.These efforts are required to support conservation and plantation practices and lower the mortality rate of seedlings.Therefore,identifying ecologically potential areas for plantation practices is mandatory to ensure a higher success rate.This study aimed to identify suitable locations for mangrove plantations along the southern coastal frontiers of Hormozgan,Iran.To this end,we applied a hybrid Fuzzy-DEMATEL-ANP(FDANP)model as a Multi-Criteria Decision Making(MCDM)approach to determine the relative importance of different criteria,combined with geospatial and remote sensing data.In this regard,ten relevant sources of environmental criteria,including meteorological,topographical,and geomorphological,were used in the modeling.The statistical evaluation demonstrated the high potential of the developed approach for suitable location identification.Based on the final results,6.10%and 20.80%of the study area were classified as very-high suitable and very-low suitable areas.The obtained values can elucidate the path for decision-makers and managers for better conservation and plantation planning.Moreover,the utility of charge-free remote sensing data allows cost-effective implementation of such an approach for other regions by interested researchers and governing organizations.
文摘This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were processed.Reference samples were scrutinized using the Continuous Change Detection and Classification(CCDC)algorithm to identify spectrally unchanged samples.These spectrally unchanged samples were subsequently employed as training data within an object-based Random Forest(RF)model to generate wetland maps from 1984 to 2021.Subsequently,a change analysis was conducted to calculate the loss and gain of different wetland types.Overall,it was observed that approximately 45%(184,434 km^(2))and 55%(220,778 km^(2))of the entire study area are covered by wetland and non-wetland categories,respectively.It was also observed that 2.46%(12,495 km^(2))of the study area was changed during 40 years.Overall,there was a decline in the Bog and Fen classes,while the Marsh,Swamp,Forest,Grassland/Shrubland,Cropland,and Barren classes had an increase.Finally,the wetland gain and loss were 6,793 km^(2)and 5,701 km^(2),respectively.This study demonstrated that the use of Landsat data,along with advanced machine learning and GEE,could provide valuable assistance for wetland classification and change studies.
文摘Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth.Spread modeling,which is one of the most helpful analyses in the geographic information system(GIS),plays a prominent role in meeting this objective.This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata(CA)modeling.Therefore,artificial intelligence tools such as adaptive neuro-fuzzy inference system(ANFIS)and genetic algorithm(GA)were used in accordance with the objectives of knowledge discovery and optimization.Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization.We focused on the estimation of forest fire growth as an important case study for decision makers.A two-dimensional cellular representation of the combustion of heterogeneous fuel types and density on non-flat terrain were successfully linked with dynamic wind and slope impact.The validation of the simulation on experimental data indicated a relatively realistic head-fire shape.Further investigations showed that the results obtained using the dynamic controlling with GA in the absence of static modeling with ANFIS were unacceptable.
文摘With growing demand on multi-purpose or multi-modal navigation,the route calculation needs to traverse semantically enriched road networks for different transportation modes.Currently,operational route planning algorithms reveal rather limited performances or their potential for comprehensive applications are constrained by the unavailable or insufficient interoperation among the under-lying geo-data that are separately maintained in different spatial databases.To overcome this limitation,a novel approach has been proposed to integrate the routing-relevant information from different data sources,which involves three processes:(1)automatic matching to identify the corresponding road objects between different datasets;(2)interaction to refine the automatic matching result;and(3)transferring the routing-relevant information from one data-set to another.In process(1),the Delimited Stroke Oriented algorithm is employed to achieve the automatic data matching between different datasets,which has revealed a high matching rate and certainty.However uncertain matching problems occur in areas where topological conditions are too complicated or inconsistent.The remaining unmatched or wrongly matched objects are treated in process(2),with the help of a series of interaction tools.On the basis of refined matching results after the interaction,process(3)is dedicated to automatic integration of the routing-relevant information from different data sources.
文摘To support the monitoring and reporting processes during imple-mentation of the Sustainable Development Goals,well-developed,commonly recognized Earth observations and geospatial data,methods,innovations,committed professionals,and strong sus-tainability policies are necessary.This article informs the readers on the Earth observation and geoinformation developments and innovations,and on the engagement of profession,academy and governance to support implementation of the Sustainable Development Goals in Hungary.Description,analyses and critical assessments are given on the elements selected from Hungarian sustainable-oriented Earth observation and geospatial novelties:(a)Working Group for Sustainable Development mission and national sustainabilitypolicy,(b)international partnerships,domestic activities and achievements,(c)status of the professional education,(d)spatial databases and services to support implementation of the sustain-able development,(e)a case study on the internationally recog-nized soil geoinformation system,(f)national Earth Observation Information System and perspectives of its applications for mon-itoring the sustainability.The article conclusion strongly advises the Hungarian realization of(a)institutionalization of the Earth observation and geospatial tools and capacity for sustainable development,(b)their use in integration with statistical data,(c)establishment of national spatial information infrastructure and(d)development and spreading of the use of big data.
文摘The advent of information and communication technology and the Internet of Things have led our society toward a digital era.The proliferation of personal computers,smartphones,intelligent autonomous sensors,and pervasive network interactions with individuals have gradually shifted human activities from offline to online and from in person to virtual.This transformation has brought a series of challenges in a variety of fields,such as the dilemma of placelessness,some aspects of timelessness(no time relevance),and the changing relevance of distance in the field of geographic information science(GIScience).In the last two decades,“cyber thinking”in GIScience has received significant attention from different perspectives.For instance,human activities in“cyberspace”need to be reconsidered when coupled with the geographic space to observe the first law of geography.
