We construct a population dynamic model that accounts for the versatility of begomovirus populati... more We construct a population dynamic model that accounts for the versatility of begomovirus populations and demonstrates the emergent patterns of population dynamics that can cause massive virus epidemics. Such epidemics appear mostly on large-scale cultivation areas of a similar set of crop plants under intensive cultivation. The model explains how the combination of intensive farming practices for cash crop farming create an ideal platform for begomovirus epidemics through their interplay with the structural properties of begomovirus clusters. Alternative cropping patterns are proposed to reduce the impact of massive begomovirus epidemics.
In preparation for participation in funding mechanisms established under the United Nations' fram... more In preparation for participation in funding mechanisms established under the United Nations' framework for reducing emissions from deforestation and forest degradation (REDD+), the Government of Nepal has developed a sub-national reference level (RL) for the 12 districts of Terai Arc Landscape (TAL) in partnership with the WWF-Nepal, WWF-US and Arbonaut Ltd., Finland. The reference level was established using LiDAR–Assisted Multisource Programme (LAMP), an innovative effort that utilizes existing national forest and survey data, field sampling, satellite imagery, and airborne LiDAR data to measure deforestation and forest degradation, regrowth and maintenance of forests, and the resulting emissions and sequestration of CO 2 in the project districts for the period 1999–2011. This effort was designed to create a sub-national RL that meets the highest international standards for integrity and transparency and followed closely the guidelines of the Methodological Framework (MF) defined by the Forest Carbon Partnership Facility (FCPF) at the World Bank and Guidelines defined by Intergovernmental Panel on Climate Change (IPCC).The present analysis shows that during the 12-year period between 1999 and 2011 a net total of 52,245,991 tons CO 2 (tCO 2 e) was emitted from the forest sector in the TAL, an average emission of 4,353,833 tons CO 2 e per year. The results presented here reflect the first iteration of the TAL RL and a major milestone in an ongoing process that will further refine and improve the RL in the months ahead based on external review and input and additional field verification and data analysis.
Nowadays it is possible to identify and visualize your location using only a mobile terminal, suc... more Nowadays it is possible to identify and visualize your location using only a mobile terminal, such as a cellular phone or a pocket computer. The applications of mobile location services are very diverse, and most providers offer only technology rather than business or a ready solution. Yet operators must see at least one compelling end-user service that can be built upon such a technical foundation. Here we present such a service based on GeoMessaging and Mobile Map Imaging, which is ready for immediate adoption. GeoMessaging adds location information to the messages sent by people using SMS, WAP or e-mail services, and puts special emphasis on user-created location-related content.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Conference Proceedings IT IS-ITAB '99. Joint Meeting. Second International Workshop On the Telemedical Information Society (IT IS '99)/Second IEEE EMBS International Workshop on Information Technology Applications in Biomedicine (ITAB '99) (Cat. No.99TH, 1999
Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orinat... more Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orination that may reside in several different locations, be of many different modalities, and adapt automatically to ncw informiltion, A particularly important source of mcdical informution are medical imagcs nowadays mostly stored in DICOM datu bases. We present and demonstrate an integrated system that allows Web-bascd access to DICOM imagcs from the Virtual Mcdical Worlds interface, and provides for semi-automatic incorporation of new image information jnto the VMW template, as soon as the imagcs are entered into the DICOM data base.
In this paper, we consider the problem of unsupervised clustering (vector quantization) of multid... more In this paper, we consider the problem of unsupervised clustering (vector quantization) of multidimensional numerical data. We propose a new method for determining an optimal number of clusters in the data set. The method is based on parametric modeling of the quantization error. The model parameter can be treated as the effective dimensionality of the data set. The proposed method was tested with artificial and real numerical data sets and the results of the experiments demonstrate empirically not only the effectiveness of the method but its ability to cope with difficult cases where other known methods fail.
This paper considers the problem of unsupervised segmentation and approximation of digital curves... more This paper considers the problem of unsupervised segmentation and approximation of digital curves and trajectories with a set of geometrical primitives (model functions). An algorithm is proposed based on a parameterized model of the Rate-Distortion curve. The multiplicative cost function is then derived from the model. By analyzing the minimum of the cost function, a solution is defined that produces the best possible balance between the number of segments and the approximation error. The proposed algorithm was tested for polygonal approximation and multi-model approximation (circular arcs and line segments for digital curves, and polynomials for trajectory). The algorithm demonstrated its efficiency in comparisons with known methods with a heuristic cost function. The proposed method can additionally be used for segmentation and approximation of signals and time series.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Extracting digital elevation models (DTMs) from LiDAR data under forest canopy is a challenging t... more Extracting digital elevation models (DTMs) from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5 m to over 10 m.
Participatory forest monitoring has been promoted as a means to engage local forest-dependent com... more Participatory forest monitoring has been promoted as a means to engage local forest-dependent communities in concrete climate mitigation activities as it brings a sense of ownership to the communities and hence increases the likelihood of success of forest preservation measures. However, sceptics of this approach argue that local community forest members will not easily attain the level of technical proficiency that accurate monitoring needs. Thus it is interesting to establish if local communities can attain such a level of technical proficiency. This paper addresses this issue by assessing the robustness of biomass estimation models based on air-borne laser data using models calibrated with two different field sample designs namely, field data gathered by professional forester teams and field data collected by local communities trained by professional foresters in two study sites in Nepal. The aim is to find if the two field sample data sets can give similar results (LiDAR models) and whether the data can be combined and used together in estimating biomass. Results show that even though the sampling designs and principles of both field campaigns were different, they produced equivalent regression models based on LiDAR data. This was successful in one of the sites (Gorkha). At the other site (Chitwan), however, major discrepancies remained in model-based estimates that used different field sample data sets. This discrepancy can be attributed to the complex terrain and dense forest in the site which makes it difficult to obtain an accurate digital elevation model (DTM) from LiDAR data, and neither set of data produced satisfactory results. Field sample data produced by professional foresters and field sample data produced by professionally trained communities can be used together without affecting prediction performance provided that the correlation between LiDAR predictors and biomass estimates is good enough.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Conference Proceedings IT IS-ITAB '99. Joint Meeting. Second International Workshop On the Telemedical Information Society (IT IS '99)/Second IEEE EMBS International Workshop on Information Technology Applications in Biomedicine (ITAB '99) (Cat. No.99TH, 1999
Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orinat... more Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orination that may reside in several different locations, be of many different modalities, and adapt automatically to ncw informiltion, A particularly important source of mcdical informution are medical imagcs nowadays mostly stored in DICOM datu bases. We present and demonstrate an integrated system that allows Web-bascd access to DICOM imagcs from the Virtual Mcdical Worlds interface, and provides for semi-automatic incorporation of new image information jnto the VMW template, as soon as the imagcs are entered into the DICOM data base.
This paper considers the problem of unsupervised segmentation and approximation of digital curves... more This paper considers the problem of unsupervised segmentation and approximation of digital curves and trajectories with a set of geometrical primitives (model functions). An algorithm is proposed based on a parameterized model of the Rate-Distortion curve. The multiplicative cost function is then derived from the model. By analyzing the minimum of the cost function, a solution is defined that produces the best possible balance between the number of segments and the approximation error. The proposed algorithm was tested for polygonal approximation and multi-model approximation (circular arcs and line segments for digital curves, and polynomials for trajectory). The algorithm demonstrated its efficiency in comparisons with known methods with a heuristic cost function. The proposed method can additionally be used for segmentation and approximation of signals and time series.
We construct a population dynamic model that accounts for the versatility of begomovirus populati... more We construct a population dynamic model that accounts for the versatility of begomovirus populations and demonstrates the emergent patterns of population dynamics that can cause massive virus epidemics. Such epidemics appear mostly on large-scale cultivation areas of a similar set of crop plants under intensive cultivation. The model explains how the combination of intensive farming practices for cash crop farming create an ideal platform for begomovirus epidemics through their interplay with the structural properties of begomovirus clusters. Alternative cropping patterns are proposed to reduce the impact of massive begomovirus epidemics.
In preparation for participation in funding mechanisms established under the United Nations' fram... more In preparation for participation in funding mechanisms established under the United Nations' framework for reducing emissions from deforestation and forest degradation (REDD+), the Government of Nepal has developed a sub-national reference level (RL) for the 12 districts of Terai Arc Landscape (TAL) in partnership with the WWF-Nepal, WWF-US and Arbonaut Ltd., Finland. The reference level was established using LiDAR–Assisted Multisource Programme (LAMP), an innovative effort that utilizes existing national forest and survey data, field sampling, satellite imagery, and airborne LiDAR data to measure deforestation and forest degradation, regrowth and maintenance of forests, and the resulting emissions and sequestration of CO 2 in the project districts for the period 1999–2011. This effort was designed to create a sub-national RL that meets the highest international standards for integrity and transparency and followed closely the guidelines of the Methodological Framework (MF) defined by the Forest Carbon Partnership Facility (FCPF) at the World Bank and Guidelines defined by Intergovernmental Panel on Climate Change (IPCC).The present analysis shows that during the 12-year period between 1999 and 2011 a net total of 52,245,991 tons CO 2 (tCO 2 e) was emitted from the forest sector in the TAL, an average emission of 4,353,833 tons CO 2 e per year. The results presented here reflect the first iteration of the TAL RL and a major milestone in an ongoing process that will further refine and improve the RL in the months ahead based on external review and input and additional field verification and data analysis.
Nowadays it is possible to identify and visualize your location using only a mobile terminal, suc... more Nowadays it is possible to identify and visualize your location using only a mobile terminal, such as a cellular phone or a pocket computer. The applications of mobile location services are very diverse, and most providers offer only technology rather than business or a ready solution. Yet operators must see at least one compelling end-user service that can be built upon such a technical foundation. Here we present such a service based on GeoMessaging and Mobile Map Imaging, which is ready for immediate adoption. GeoMessaging adds location information to the messages sent by people using SMS, WAP or e-mail services, and puts special emphasis on user-created location-related content.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Conference Proceedings IT IS-ITAB '99. Joint Meeting. Second International Workshop On the Telemedical Information Society (IT IS '99)/Second IEEE EMBS International Workshop on Information Technology Applications in Biomedicine (ITAB '99) (Cat. No.99TH, 1999
Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orinat... more Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orination that may reside in several different locations, be of many different modalities, and adapt automatically to ncw informiltion, A particularly important source of mcdical informution are medical imagcs nowadays mostly stored in DICOM datu bases. We present and demonstrate an integrated system that allows Web-bascd access to DICOM imagcs from the Virtual Mcdical Worlds interface, and provides for semi-automatic incorporation of new image information jnto the VMW template, as soon as the imagcs are entered into the DICOM data base.
In this paper, we consider the problem of unsupervised clustering (vector quantization) of multid... more In this paper, we consider the problem of unsupervised clustering (vector quantization) of multidimensional numerical data. We propose a new method for determining an optimal number of clusters in the data set. The method is based on parametric modeling of the quantization error. The model parameter can be treated as the effective dimensionality of the data set. The proposed method was tested with artificial and real numerical data sets and the results of the experiments demonstrate empirically not only the effectiveness of the method but its ability to cope with difficult cases where other known methods fail.
This paper considers the problem of unsupervised segmentation and approximation of digital curves... more This paper considers the problem of unsupervised segmentation and approximation of digital curves and trajectories with a set of geometrical primitives (model functions). An algorithm is proposed based on a parameterized model of the Rate-Distortion curve. The multiplicative cost function is then derived from the model. By analyzing the minimum of the cost function, a solution is defined that produces the best possible balance between the number of segments and the approximation error. The proposed algorithm was tested for polygonal approximation and multi-model approximation (circular arcs and line segments for digital curves, and polynomials for trajectory). The algorithm demonstrated its efficiency in comparisons with known methods with a heuristic cost function. The proposed method can additionally be used for segmentation and approximation of signals and time series.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Extracting digital elevation models (DTMs) from LiDAR data under forest canopy is a challenging t... more Extracting digital elevation models (DTMs) from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5 m to over 10 m.
Participatory forest monitoring has been promoted as a means to engage local forest-dependent com... more Participatory forest monitoring has been promoted as a means to engage local forest-dependent communities in concrete climate mitigation activities as it brings a sense of ownership to the communities and hence increases the likelihood of success of forest preservation measures. However, sceptics of this approach argue that local community forest members will not easily attain the level of technical proficiency that accurate monitoring needs. Thus it is interesting to establish if local communities can attain such a level of technical proficiency. This paper addresses this issue by assessing the robustness of biomass estimation models based on air-borne laser data using models calibrated with two different field sample designs namely, field data gathered by professional forester teams and field data collected by local communities trained by professional foresters in two study sites in Nepal. The aim is to find if the two field sample data sets can give similar results (LiDAR models) and whether the data can be combined and used together in estimating biomass. Results show that even though the sampling designs and principles of both field campaigns were different, they produced equivalent regression models based on LiDAR data. This was successful in one of the sites (Gorkha). At the other site (Chitwan), however, major discrepancies remained in model-based estimates that used different field sample data sets. This discrepancy can be attributed to the complex terrain and dense forest in the site which makes it difficult to obtain an accurate digital elevation model (DTM) from LiDAR data, and neither set of data produced satisfactory results. Field sample data produced by professional foresters and field sample data produced by professionally trained communities can be used together without affecting prediction performance provided that the correlation between LiDAR predictors and biomass estimates is good enough.
ISPRS Journal of Photogrammetry and Remote Sensing, 2015
Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing E... more Measuring, Reporting and Verification (MRV) systems of the United Nations programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) aim to provide robust and reliable data on carbon credits over large areas. Multitemporal satellite mosaics are often the only cost-effective remote sensing data that allow such coverage. Although a number of methods for producing mosaics has been proposed, most of them are dependent on the order in which tiles to normalized are presented to the algorithm and suffer from loss of input scenes' variance which can substantially reduce the carbon credits. In this study we propose a variance-preserving mosaic (VPM) algorithm that considers all images at the same time, minimizes overall error of the normalization and aims to preserve average variance of input images. We have compared the presented method with a popular relative normalization algorithm commonly used nowadays. The proposed algorithm allows to avoid iterative pair-wise normalization, results in visually uniform mosaics while maintaining also the original image variance. Ó
Conference Proceedings IT IS-ITAB '99. Joint Meeting. Second International Workshop On the Telemedical Information Society (IT IS '99)/Second IEEE EMBS International Workshop on Information Technology Applications in Biomedicine (ITAB '99) (Cat. No.99TH, 1999
Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orinat... more Virtual Medical Worlds (VMW) reprcscnts a new standard for integrating together medical in€orination that may reside in several different locations, be of many different modalities, and adapt automatically to ncw informiltion, A particularly important source of mcdical informution are medical imagcs nowadays mostly stored in DICOM datu bases. We present and demonstrate an integrated system that allows Web-bascd access to DICOM imagcs from the Virtual Mcdical Worlds interface, and provides for semi-automatic incorporation of new image information jnto the VMW template, as soon as the imagcs are entered into the DICOM data base.
This paper considers the problem of unsupervised segmentation and approximation of digital curves... more This paper considers the problem of unsupervised segmentation and approximation of digital curves and trajectories with a set of geometrical primitives (model functions). An algorithm is proposed based on a parameterized model of the Rate-Distortion curve. The multiplicative cost function is then derived from the model. By analyzing the minimum of the cost function, a solution is defined that produces the best possible balance between the number of segments and the approximation error. The proposed algorithm was tested for polygonal approximation and multi-model approximation (circular arcs and line segments for digital curves, and polynomials for trajectory). The algorithm demonstrated its efficiency in comparisons with known methods with a heuristic cost function. The proposed method can additionally be used for segmentation and approximation of signals and time series.
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Papers by T. Kauranne