High resolution satellite images are rich source of geospatial information. Nowadays, these images contain finest spectral and spatial information of ground realities in different electromagnetic spectrum. Many image ...High resolution satellite images are rich source of geospatial information. Nowadays, these images contain finest spectral and spatial information of ground realities in different electromagnetic spectrum. Many image processing softwares, algorithms and techniques are available to extract such information from these images. Multi spectral as well as panchromatic (PAN) high resolution satellite images are missing, one important information, regarding ground features and realities that information is attribute information which is not directly available in high resolution satellite images. From very first day, this information used to be collected through indirect ways using GPS, digitizing, geo-coding, geo tagging, field survey and many other techniques. Our real world has vertical labels for ground observer to identify and use this information. These vertical labels are present in form of names, logos, icons, symbols and numbers. These vertical labels ease us to work in real world. Satellites are unable to read these labels due to their vertical orientation. Making satellite/aerial imagery rich of attribute information, we have the possibility to design our world accordingly. Just like vertical labels we can also place real physical horizontal label for space sensors, to make this information directly available in high resolution satellite/aerial imagery. This work is about possibilities of such techniques and methods.展开更多
In this research, a content-based image retrieval (CBIR) system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern (LBP) texture ...In this research, a content-based image retrieval (CBIR) system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern (LBP) texture feature and a block based scheme. The query and database images are divided into equally sized blocks, from which LBP histograms are extracted. The block histograms are then compared by using the Chi-square distance. Experimental results show that the LBP representation provides a powerful tool for high resolution satellite images (HRSI) retrieval.展开更多
Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational ...Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution(2 m) urban land-cover map(Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer’s accuracies and user’s accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level.Compared with the existing medium-resolution land-cover/use datasets(at a 30-m resolution), HiULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.展开更多
The central concept of precision agriculture is to manage within-field soil and crop growth variability for more efficient use of farming inputs. Remote sensing has been an integral part of precision agriculture since...The central concept of precision agriculture is to manage within-field soil and crop growth variability for more efficient use of farming inputs. Remote sensing has been an integral part of precision agriculture since the farming technology started developing in the mid to late 1980 s. Various types of remote sensors carried on groundbased platforms, manned aircraft, satellites, and more recently, unmanned aircraft have been used for precision agriculture applications. Original satellite sensors, such as Landsat and SPOT, have commonly been used for agricultural applications over large geographic areas since the 1970 s, but they have limited use for precision agriculture because of their relatively coarse spatial resolution and long revisit time. Recent developments in high resolution satellite sensors have significantly narrowed the gap in spatial resolution between satellite imagery and airborne imagery. Since the first high resolution satellite sensor IKONOS was launched in 1999, numerous commercial high resolution satellite sensors have become available. These imaging sensors not only provide images with high spatial resolution, but can also repeatedly view the same target area. The high revisit frequency and fast data turnaround time, combined with their relatively large aerial coverage, make high resolution satellite sensors attractive for many applications,including precision agriculture. This article will provide an overview of commercially available high resolution satellite sensors that have been used or have potential for precision agriculture. The applications of these sensors for precision agriculture are reviewed and application examples based on the studies conducted by the author and his collaborators are provided to illustrate how high resolution satellite imagery has been used for crop identification, crop yield variability mapping and pest management. Some challenges and future directions on the use of high resolution satellite sensors and other types of remote sensors for precision agriculture are discussed.展开更多
This paper presents the studies of the refining of IKONOS-2 RPC, the transform of the datum, the mode of the control point distribution and the method of IKONOS stereo triangulation, so that IKONOS imagery can be used...This paper presents the studies of the refining of IKONOS-2 RPC, the transform of the datum, the mode of the control point distribution and the method of IKONOS stereo triangulation, so that IKONOS imagery can be used to collect the precise geospatial data and produce the large scale map.The transform between the IKONOS-2 image space and the national coordinate system based on the RPC have been developed, and the results of block adjustment with various control schemes in a practical project near Himalayas have been examined and analysed. The encouraging results of high positioning accuracy have been obtained.展开更多
文摘High resolution satellite images are rich source of geospatial information. Nowadays, these images contain finest spectral and spatial information of ground realities in different electromagnetic spectrum. Many image processing softwares, algorithms and techniques are available to extract such information from these images. Multi spectral as well as panchromatic (PAN) high resolution satellite images are missing, one important information, regarding ground features and realities that information is attribute information which is not directly available in high resolution satellite images. From very first day, this information used to be collected through indirect ways using GPS, digitizing, geo-coding, geo tagging, field survey and many other techniques. Our real world has vertical labels for ground observer to identify and use this information. These vertical labels are present in form of names, logos, icons, symbols and numbers. These vertical labels ease us to work in real world. Satellites are unable to read these labels due to their vertical orientation. Making satellite/aerial imagery rich of attribute information, we have the possibility to design our world accordingly. Just like vertical labels we can also place real physical horizontal label for space sensors, to make this information directly available in high resolution satellite/aerial imagery. This work is about possibilities of such techniques and methods.
文摘In this research, a content-based image retrieval (CBIR) system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern (LBP) texture feature and a block based scheme. The query and database images are divided into equally sized blocks, from which LBP histograms are extracted. The block histograms are then compared by using the Chi-square distance. Experimental results show that the LBP representation provides a powerful tool for high resolution satellite images (HRSI) retrieval.
基金supported by the National Natural Science Foundation of China (41771360 and 41971295)the National Program for Support of Top-notch Young Professionals, the Hubei Provincial Natural Science Foundation of China (2017CFA029)the National Key Resarch & Development Program of China (2016YFB0501403)。
文摘Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution(2 m) urban land-cover map(Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer’s accuracies and user’s accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level.Compared with the existing medium-resolution land-cover/use datasets(at a 30-m resolution), HiULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.
文摘The central concept of precision agriculture is to manage within-field soil and crop growth variability for more efficient use of farming inputs. Remote sensing has been an integral part of precision agriculture since the farming technology started developing in the mid to late 1980 s. Various types of remote sensors carried on groundbased platforms, manned aircraft, satellites, and more recently, unmanned aircraft have been used for precision agriculture applications. Original satellite sensors, such as Landsat and SPOT, have commonly been used for agricultural applications over large geographic areas since the 1970 s, but they have limited use for precision agriculture because of their relatively coarse spatial resolution and long revisit time. Recent developments in high resolution satellite sensors have significantly narrowed the gap in spatial resolution between satellite imagery and airborne imagery. Since the first high resolution satellite sensor IKONOS was launched in 1999, numerous commercial high resolution satellite sensors have become available. These imaging sensors not only provide images with high spatial resolution, but can also repeatedly view the same target area. The high revisit frequency and fast data turnaround time, combined with their relatively large aerial coverage, make high resolution satellite sensors attractive for many applications,including precision agriculture. This article will provide an overview of commercially available high resolution satellite sensors that have been used or have potential for precision agriculture. The applications of these sensors for precision agriculture are reviewed and application examples based on the studies conducted by the author and his collaborators are provided to illustrate how high resolution satellite imagery has been used for crop identification, crop yield variability mapping and pest management. Some challenges and future directions on the use of high resolution satellite sensors and other types of remote sensors for precision agriculture are discussed.
基金Funded by the Western Region Transport Development Science and Technology Program (No.2002 318 0050).
文摘This paper presents the studies of the refining of IKONOS-2 RPC, the transform of the datum, the mode of the control point distribution and the method of IKONOS stereo triangulation, so that IKONOS imagery can be used to collect the precise geospatial data and produce the large scale map.The transform between the IKONOS-2 image space and the national coordinate system based on the RPC have been developed, and the results of block adjustment with various control schemes in a practical project near Himalayas have been examined and analysed. The encouraging results of high positioning accuracy have been obtained.