An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption l...An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.展开更多
Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster...Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.展开更多
Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-...Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the surface features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the proposed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.展开更多
How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classif...How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.展开更多
In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a visi...In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a vision-language aligning paradigm for RSIC to jointly represent vision and language. First, a new RSIC dataset DIOR-Captions is built for augmenting object detection in optical remote(DIOR) sensing images dataset with manually annotated Chinese and English contents. Second, a Vision-Language aligning model with Cross-modal Attention(VLCA) is presented to generate accurate and abundant bilingual descriptions for remote sensing images. Third, a crossmodal learning network is introduced to address the problem of visual-lingual alignment. Notably, VLCA is also applied to end-toend Chinese captions generation by using the pre-training language model of Chinese. The experiments are carried out with various baselines to validate VLCA on the proposed dataset. The results demonstrate that the proposed algorithm is more descriptive and informative than existing algorithms in producing captions.展开更多
Since the complication of monitoring and evaluating the problems about the transgenic expression and its impacts on the receptor in the transgenic crop breeding and other relevant evaluated works,the authors in the pr...Since the complication of monitoring and evaluating the problems about the transgenic expression and its impacts on the receptor in the transgenic crop breeding and other relevant evaluated works,the authors in the present work tried to assess the differences of spectral parameters of the transgenic rice in contrast with its parent group quantitatively and qualitatively,fulfilling the growth monitoring of the transgenic samples.The spectral parameters(spectral morphological characteristics and indices) chosen are highly related to internal or external stresses to the receipts,and thus could be applied as indicators of biophysical or biochemical processes changes of plant.By ASD portable field spectroradiometer with high-density probe,fine foliar spectra of 8 groups were obtained.By analyzing spectral angle and continuum removal,the spectral morphological differences and their locations of sample spectra were found which could be as auxiliary priori knowledge for quantitative analysis.By investigating spectral indices of the samples,the quantitative differences of spectra were revealed about foliar chlorophyll a+b and carotenoid content.In this study both the spectral differences between transgenic and parent groups and among transgenic groups were investigated.The results show that hyperspectral technique is promising and a helpful auxiliary tool in the study of monitoring the transgenic crop and other relevant researches.By this technique,quantitative and qualitative results of sample spectra could be provided as prior knowledge,as certain orientation,for laboratory professional advanced transgenic breeding study.展开更多
The working principle of radio remote controlling of construction machinery should be that signals of the radio wave from the transmitter obtained in the receiver were controlled and then changed into electronic analo...The working principle of radio remote controlling of construction machinery should be that signals of the radio wave from the transmitter obtained in the receiver were controlled and then changed into electronic analog or digital signals which can be used to drive different actuators and mechanisms of the vehicle.The vehicle could be acted by following the controlling instructions sent by the operator.The best operation mode of construction machinery is suitable not only to manual operating but also to remote controlling in the same vehicle.The design methods of the hydraulic system used for the radio remote controlling of construction machinery are discussed.The design methods of hydraulic circuits for the actuators controlled by solenoid on-off type valves,hydro-electronic multi-way proportional valves,closed loop proportional servo driver or three-way proportional reducing valves are discussed in detail (with real example).The design methods of the power shift transmission of electro-hydraulic controlling,the devices of braking and the directional streering are discussed in this paper.展开更多
Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received ...Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.展开更多
The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the...The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the quality of the training datasets. However, real-world data is not perfect and often suffers from noise. This paper gives an overview of noise filtering methods. Firstly, the types of noise and the consequences of class noise on machine learning are presented. Secondly, class noise handling methods at both the data level and the algorithm level are introduced. Then ensemble-based class noise handling methods including class noise removal, correction, and noise robust ensemble learners are presented. Finally, a summary of existing data-cleaning techniques is given.展开更多
A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decom...A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.展开更多
Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characterist...Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.展开更多
Ⅰ. Introduction Over the past two decades, microwave remote sensing has evolved into a focal point in the remote sensing area. This is due to the fact that in microwave band, we can acquire physical parameters about ...Ⅰ. Introduction Over the past two decades, microwave remote sensing has evolved into a focal point in the remote sensing area. This is due to the fact that in microwave band, we can acquire physical parameters about ocean, terrain and atmosphere on all weather condition. Research and application work about the aerial passive micro wave remote sensors has been done at Changchun Institute of Geography since 1973, under the unitary planning of Academia Sinica. Microwave radiometers of six freqency bands have been developed. Numerous remote sensing experiments were carried out, and large amount of scientific data were accumulated. Recently, theoretical models have展开更多
Majority of the population of Sri Lanka does not have modern pipe-born water system especially in rural areas.They depend entirely on deep hand pump tube wells and shallow dug wells for their domestic water requiremen...Majority of the population of Sri Lanka does not have modern pipe-born water system especially in rural areas.They depend entirely on deep hand pump tube wells and shallow dug wells for their domestic water requirements.Most of the shallow dug wells in the dry zone of Sri Lanka go dry during the dry period. So construction of tube wells increasing very rapidly in the dry zone of Sri Lanka.Groundwater potential zone maps are the most essential tool for locating tube wells.Arial photographs,Geographical Information Systems(GIS) data and satellite images have展开更多
Our goal is to map the different geological features using satellite remotely sensed images of Cyprus acquired both from Landsat5/7 TM/ETM+,ASTER and Quickbird sensors.We want to distinguish such features on the basis...Our goal is to map the different geological features using satellite remotely sensed images of Cyprus acquired both from Landsat5/7 TM/ETM+,ASTER and Quickbird sensors.We want to distinguish such features on the basis of their spectral characteristics.Detailed reflectance spectra have been acquired using the SVC HR-1024 field spectroradiometer.This spectral information with results of a field visit has been used to determine how to process the spectra using image data. Other goals of this study are to explore the differences between the map arrived through image processing and展开更多
With the wide application of information technologi es , Internet-based remote diagnosis (IRD) of plant will surely become the main se rvice mode of corporations in the future. Therefore, it has received a great dea l...With the wide application of information technologi es , Internet-based remote diagnosis (IRD) of plant will surely become the main se rvice mode of corporations in the future. Therefore, it has received a great dea l recognition from academia and the industry. The IRD technology, which is based upon database, computer, and network technologies is the focus of correlative r esearch all over the world. Although some scientific institutions have developed primary IRD systems, their functions are quite narrow with many shortcomings. I n short, the standard of remote diagnosis has not been created, in particula r the network manufacture and diagnostic resources cannot be shared extensiv ely, so the systemic open character has not been developed enough to create the efficiency and the scope of the existing remote diagnostic systems. Aimed at improving the limitations mentioned above, in this paper we try to develop Web -CORBA open remote diagnosis architecture over the Internet, which is based on the existing troubleshooting software. We have designed and realized the general -purpose data interface of the software and some Java applets functional module s. Thereby the software’s open character and application field get widened. Our current research is focused on building the remote intelligent diagnosis center on the basis of the Web-CORBA architecture. Some basic functions have been app lied. Further, we put forward the project of combining the enterprise interior d iagnostic system to the remote diagnosis center, and make a study of building th e remote diagnosis object network architecture. The open remote diagnostic syste m based on Internet offers many advantages. Also, with the CORBA distributed obj ect technology, the distributed diagnostic resources can be connected as a coope rative diagnosis object system, in order that all the resources can be shared to the full extent, and the advanced diagnostic technique can be applied as soon a s possible. This is the inevitable trend of the diagnostic technology.展开更多
In this paper, a new progress in scattering measurement of ocean surface wind vector using a space borne scanning scatterometer (CNSCAT) has been described. The CNSCAT developed during the past five years in the labor...In this paper, a new progress in scattering measurement of ocean surface wind vector using a space borne scanning scatterometer (CNSCAT) has been described. The CNSCAT developed during the past five years in the laboratory for Microwave Remote Sensing and Information Technology (MIRIT), CSSAR,The Chinese Academy of Sciences, will be launched in early next decade. This paper also discussed CNSCAT system design, system calibration and some theoretical analysis.展开更多
C/N ratio of crops is an important input parameter of ecological model.Contamination stress will change the ecological parameters of crops,such as chlorophyll content and C/N ratio.Quite a few scholars chose the persp...C/N ratio of crops is an important input parameter of ecological model.Contamination stress will change the ecological parameters of crops,such as chlorophyll content and C/N ratio.Quite a few scholars chose the perspective of chlorophyll content inversion by remote sensing and build models of heavy metal contamination of remote sensing.But research on spectral stress response of C/N ratio is still blank.展开更多
文摘An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.
基金supported by the National Key Research and Development Program of China(2020YFC1512304).
文摘Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.
基金supported by the National Natural Science Foundation of China(61172127)the Natural Science Foundation of Anhui Province(1408085MF121)
文摘Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the surface features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the proposed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.
基金supported by the National Natural Science Foundation of China(U1435220)
文摘How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.
基金supported by the National Natural Science Foundation of China (61702528,61806212)。
文摘In the field of satellite imagery, remote sensing image captioning(RSIC) is a hot topic with the challenge of overfitting and difficulty of image and text alignment. To address these issues, this paper proposes a vision-language aligning paradigm for RSIC to jointly represent vision and language. First, a new RSIC dataset DIOR-Captions is built for augmenting object detection in optical remote(DIOR) sensing images dataset with manually annotated Chinese and English contents. Second, a Vision-Language aligning model with Cross-modal Attention(VLCA) is presented to generate accurate and abundant bilingual descriptions for remote sensing images. Third, a crossmodal learning network is introduced to address the problem of visual-lingual alignment. Notably, VLCA is also applied to end-toend Chinese captions generation by using the pre-training language model of Chinese. The experiments are carried out with various baselines to validate VLCA on the proposed dataset. The results demonstrate that the proposed algorithm is more descriptive and informative than existing algorithms in producing captions.
基金supported by The Research Grants Council,Hong Kong:Competitive Earmarked Research Grant,No.461907
文摘Since the complication of monitoring and evaluating the problems about the transgenic expression and its impacts on the receptor in the transgenic crop breeding and other relevant evaluated works,the authors in the present work tried to assess the differences of spectral parameters of the transgenic rice in contrast with its parent group quantitatively and qualitatively,fulfilling the growth monitoring of the transgenic samples.The spectral parameters(spectral morphological characteristics and indices) chosen are highly related to internal or external stresses to the receipts,and thus could be applied as indicators of biophysical or biochemical processes changes of plant.By ASD portable field spectroradiometer with high-density probe,fine foliar spectra of 8 groups were obtained.By analyzing spectral angle and continuum removal,the spectral morphological differences and their locations of sample spectra were found which could be as auxiliary priori knowledge for quantitative analysis.By investigating spectral indices of the samples,the quantitative differences of spectra were revealed about foliar chlorophyll a+b and carotenoid content.In this study both the spectral differences between transgenic and parent groups and among transgenic groups were investigated.The results show that hyperspectral technique is promising and a helpful auxiliary tool in the study of monitoring the transgenic crop and other relevant researches.By this technique,quantitative and qualitative results of sample spectra could be provided as prior knowledge,as certain orientation,for laboratory professional advanced transgenic breeding study.
文摘The working principle of radio remote controlling of construction machinery should be that signals of the radio wave from the transmitter obtained in the receiver were controlled and then changed into electronic analog or digital signals which can be used to drive different actuators and mechanisms of the vehicle.The vehicle could be acted by following the controlling instructions sent by the operator.The best operation mode of construction machinery is suitable not only to manual operating but also to remote controlling in the same vehicle.The design methods of the hydraulic system used for the radio remote controlling of construction machinery are discussed.The design methods of hydraulic circuits for the actuators controlled by solenoid on-off type valves,hydro-electronic multi-way proportional valves,closed loop proportional servo driver or three-way proportional reducing valves are discussed in detail (with real example).The design methods of the power shift transmission of electro-hydraulic controlling,the devices of braking and the directional streering are discussed in this paper.
基金supported by Changwon National University in 2009-2010
文摘Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.
基金supported by the National Natural Science Foundation of China (62201438,61772397,12005169)the Basic Research Program of Natural Sciences of Shaanxi Province (2021JC-23)+2 种基金Yulin Science and Technology Bureau Science and Technology Development Special Project (CXY-2020-094)Shaanxi Forestry Science and Technology Innovation Key Project (SXLK2022-02-8)the Project of Shaanxi F ederation of Social Sciences (2022HZ1759)。
文摘The development of image classification is one of the most important research topics in remote sensing. The prediction accuracy depends not only on the appropriate choice of the machine learning method but also on the quality of the training datasets. However, real-world data is not perfect and often suffers from noise. This paper gives an overview of noise filtering methods. Firstly, the types of noise and the consequences of class noise on machine learning are presented. Secondly, class noise handling methods at both the data level and the algorithm level are introduced. Then ensemble-based class noise handling methods including class noise removal, correction, and noise robust ensemble learners are presented. Finally, a summary of existing data-cleaning techniques is given.
文摘A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.
基金Project(2006BAB01A06) supported by the National Science and Technology Pillar Program Project during the 11th Five-Year Plan PeriodProject(1212010761503) supported by Land and Resources Investigation Project
文摘Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.
文摘Ⅰ. Introduction Over the past two decades, microwave remote sensing has evolved into a focal point in the remote sensing area. This is due to the fact that in microwave band, we can acquire physical parameters about ocean, terrain and atmosphere on all weather condition. Research and application work about the aerial passive micro wave remote sensors has been done at Changchun Institute of Geography since 1973, under the unitary planning of Academia Sinica. Microwave radiometers of six freqency bands have been developed. Numerous remote sensing experiments were carried out, and large amount of scientific data were accumulated. Recently, theoretical models have
文摘Majority of the population of Sri Lanka does not have modern pipe-born water system especially in rural areas.They depend entirely on deep hand pump tube wells and shallow dug wells for their domestic water requirements.Most of the shallow dug wells in the dry zone of Sri Lanka go dry during the dry period. So construction of tube wells increasing very rapidly in the dry zone of Sri Lanka.Groundwater potential zone maps are the most essential tool for locating tube wells.Arial photographs,Geographical Information Systems(GIS) data and satellite images have
文摘Our goal is to map the different geological features using satellite remotely sensed images of Cyprus acquired both from Landsat5/7 TM/ETM+,ASTER and Quickbird sensors.We want to distinguish such features on the basis of their spectral characteristics.Detailed reflectance spectra have been acquired using the SVC HR-1024 field spectroradiometer.This spectral information with results of a field visit has been used to determine how to process the spectra using image data. Other goals of this study are to explore the differences between the map arrived through image processing and
文摘With the wide application of information technologi es , Internet-based remote diagnosis (IRD) of plant will surely become the main se rvice mode of corporations in the future. Therefore, it has received a great dea l recognition from academia and the industry. The IRD technology, which is based upon database, computer, and network technologies is the focus of correlative r esearch all over the world. Although some scientific institutions have developed primary IRD systems, their functions are quite narrow with many shortcomings. I n short, the standard of remote diagnosis has not been created, in particula r the network manufacture and diagnostic resources cannot be shared extensiv ely, so the systemic open character has not been developed enough to create the efficiency and the scope of the existing remote diagnostic systems. Aimed at improving the limitations mentioned above, in this paper we try to develop Web -CORBA open remote diagnosis architecture over the Internet, which is based on the existing troubleshooting software. We have designed and realized the general -purpose data interface of the software and some Java applets functional module s. Thereby the software’s open character and application field get widened. Our current research is focused on building the remote intelligent diagnosis center on the basis of the Web-CORBA architecture. Some basic functions have been app lied. Further, we put forward the project of combining the enterprise interior d iagnostic system to the remote diagnosis center, and make a study of building th e remote diagnosis object network architecture. The open remote diagnostic syste m based on Internet offers many advantages. Also, with the CORBA distributed obj ect technology, the distributed diagnostic resources can be connected as a coope rative diagnosis object system, in order that all the resources can be shared to the full extent, and the advanced diagnostic technique can be applied as soon a s possible. This is the inevitable trend of the diagnostic technology.
文摘In this paper, a new progress in scattering measurement of ocean surface wind vector using a space borne scanning scatterometer (CNSCAT) has been described. The CNSCAT developed during the past five years in the laboratory for Microwave Remote Sensing and Information Technology (MIRIT), CSSAR,The Chinese Academy of Sciences, will be launched in early next decade. This paper also discussed CNSCAT system design, system calibration and some theoretical analysis.
文摘C/N ratio of crops is an important input parameter of ecological model.Contamination stress will change the ecological parameters of crops,such as chlorophyll content and C/N ratio.Quite a few scholars chose the perspective of chlorophyll content inversion by remote sensing and build models of heavy metal contamination of remote sensing.But research on spectral stress response of C/N ratio is still blank.
