This document discusses how geographic information systems (GIS) can be used to analyze the spread of invasive termite species in urban South Florida. Specifically, it provides two case studies: (1) A GIS spatial analysis showed that the Formosan subterranean termite and Asian subterranean termite were introduced through boat traffic. (2) An agent-based model within a GIS was used to simulate the natural dispersal of an arboreal invasive termite species in Dania Beach, Florida. The document provides an overview of GIS functionality for spatial analysis, modeling, and simulation that can help answer research questions about how invasive species invade and spread in new environments.
This document describes tools and methods for eco-geographical land characterization (ELC) mapping and characterization of plant genetic resource collecting sites. It discusses how ELC maps are developed by selecting important bioclimatic, geophysical, and edaphic variables through statistical analysis and clustering. It also describes how the Ecogeo tool can be used to characterize collecting sites based on geographic and environmental variables extracted from GIS data to build a characterization matrix for the sites.
INTEGRATED TECHNOLOGY OF DATA REMOTE SENSING AND GIS TECHNIQUES ASSESS THE LA...acijjournal
The present study focuses on the nature and pattern of urban expansion of Madurai city over its
surrounding region during the period from 2003 to 2013. Based on Its proximity to the Madurai city,
Preparation of various thematic data such Land use and Land cover using Land sat data. Create a land
use land cover map from satellite imagery using supervised classification. Find out the areas from the
classified data. The study is Based on secondary data, the satellite imagery has downloaded from GLCF
(Global Land Cover Facility) web site, for the study area (path101 row 67), the downloaded imagery
Subset using Imagery software to clip the study area. The clipped satellite imagery has Send to prepare the
land use and land cover map using supervised classification.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This paper presents a statistical model for predicting the locations of prehistoric mounds in Iowa based on environmental factors. The model uses 335 known mound locations and 640 random non-mound locations to analyze elevation, slope, relief, and distance to water. Histograms and statistical tests show the mound locations differ significantly from non-mound locations on these factors. A logistic regression model found all four environmental variables help explain differences between mound and non-mound areas. When tested on 818 independent mound sites, 72% were in the 10% of Iowa's area deemed most likely to contain mounds by the model, significantly better than chance.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This article explores using Landsat imagery and spectral mixture analysis to map licit and illicit artisanal and small-scale gold mining (ASM) in Madre de Dios, Peru. The study finds that ASM operations are difficult to detect using traditional classification methods due to their small size, but spectral mixture analysis can extract information from mixed pixels to map ASM. The results indicate that approximately 65% of all ASM activity in the study area occurs outside of legally permitted mining concessions, highlighting the prevalence of illicit mining. Mapping ASM using these remote sensing methods provides insights into the extent of environmental impacts from mineral extraction in the region.
IRJET- Land Use & Land Cover Change Detection using G.I.S. & Remote SensingIRJET Journal
This document discusses land use and land cover change detection in Vadodara, India between 1998 and 2008 using remote sensing and GIS techniques. Specifically, it analyzed Landsat satellite images from those two decades to map and classify land use, including built up area, vegetation, vacant land, and water bodies. The methodology involved image preprocessing like geometric correction and radiometric normalization. Images were then enhanced and classified using both supervised and unsupervised classification. Comparing the classified maps from 1998 and 2008 allowed analyzing changes in land use over that 10-year period and calculating the rate of land consumption. The study aimed to provide information to urban planners for predicting future growth and avoiding problems associated with rapid urbanization.
This document describes tools and methods for eco-geographical land characterization (ELC) mapping and characterization of plant genetic resource collecting sites. It discusses how ELC maps are developed by selecting important bioclimatic, geophysical, and edaphic variables through statistical analysis and clustering. It also describes how the Ecogeo tool can be used to characterize collecting sites based on geographic and environmental variables extracted from GIS data to build a characterization matrix for the sites.
INTEGRATED TECHNOLOGY OF DATA REMOTE SENSING AND GIS TECHNIQUES ASSESS THE LA...acijjournal
The present study focuses on the nature and pattern of urban expansion of Madurai city over its
surrounding region during the period from 2003 to 2013. Based on Its proximity to the Madurai city,
Preparation of various thematic data such Land use and Land cover using Land sat data. Create a land
use land cover map from satellite imagery using supervised classification. Find out the areas from the
classified data. The study is Based on secondary data, the satellite imagery has downloaded from GLCF
(Global Land Cover Facility) web site, for the study area (path101 row 67), the downloaded imagery
Subset using Imagery software to clip the study area. The clipped satellite imagery has Send to prepare the
land use and land cover map using supervised classification.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This paper presents a statistical model for predicting the locations of prehistoric mounds in Iowa based on environmental factors. The model uses 335 known mound locations and 640 random non-mound locations to analyze elevation, slope, relief, and distance to water. Histograms and statistical tests show the mound locations differ significantly from non-mound locations on these factors. A logistic regression model found all four environmental variables help explain differences between mound and non-mound areas. When tested on 818 independent mound sites, 72% were in the 10% of Iowa's area deemed most likely to contain mounds by the model, significantly better than chance.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This article explores using Landsat imagery and spectral mixture analysis to map licit and illicit artisanal and small-scale gold mining (ASM) in Madre de Dios, Peru. The study finds that ASM operations are difficult to detect using traditional classification methods due to their small size, but spectral mixture analysis can extract information from mixed pixels to map ASM. The results indicate that approximately 65% of all ASM activity in the study area occurs outside of legally permitted mining concessions, highlighting the prevalence of illicit mining. Mapping ASM using these remote sensing methods provides insights into the extent of environmental impacts from mineral extraction in the region.
IRJET- Land Use & Land Cover Change Detection using G.I.S. & Remote SensingIRJET Journal
This document discusses land use and land cover change detection in Vadodara, India between 1998 and 2008 using remote sensing and GIS techniques. Specifically, it analyzed Landsat satellite images from those two decades to map and classify land use, including built up area, vegetation, vacant land, and water bodies. The methodology involved image preprocessing like geometric correction and radiometric normalization. Images were then enhanced and classified using both supervised and unsupervised classification. Comparing the classified maps from 1998 and 2008 allowed analyzing changes in land use over that 10-year period and calculating the rate of land consumption. The study aimed to provide information to urban planners for predicting future growth and avoiding problems associated with rapid urbanization.
This document provides information about the proper uses of the prepositions "in", "on", and "at" as they relate to time and place. It explains that "in" is generally used for enclosed spaces and long periods of time, "on" is used for surfaces and specific days/dates, and "at" is used for precise times and points. Numerous examples are given to illustrate the different uses of each preposition in contexts involving locations, dates, times of day, activities, and states. At the end, an activity is included where the reader must choose the correct preposition to complete sentences about time and place.
18 June 2015 Rare Disease Site & Patient Recruitment KJAKevin J. Anderson
This document discusses challenges and approaches for site and patient recruitment in rare disease clinical studies. Key challenges include the rarity of diseases, difficulty finding patients and physicians, complex logistics, and vulnerable patient populations. Effective approaches involve casting a wide net globally, leveraging registries and advocacy groups, using medical informatics to identify sites, and hiring specialists to assist with outreach and education. Lessons learned emphasize starting recruitment efforts early, challenging site estimates, and ensuring multiple potential enrollment sites are identified for each patient.
La secuencia didáctica pretende que estudiantes de transición interpreten y analicen datos sobre animales y objetos en inglés de manera lúdica utilizando fichas, juegos y la herramienta Scratch. Las actividades incluyen identificar animales en una canción, organizar fichas de animales por cantidad, analizar la frecuencia de útiles escolares en grupos y subgrupos, y crear aplicaciones en Scratch para interpretar datos e incluir vocabulario en inglés. La evaluación es procesual a través de autoevaluación, coevaluación y
SlideShare es una herramienta en línea gratuita para compartir presentaciones. Se lanzó en 2006 y fue adquirida por LinkedIn en 2012. Los usuarios pueden subir documentos, presentaciones y videos de manera privada o pública. Proporciona funciones como comentarios, evaluaciones y conferencias en vivo. Para crear una cuenta, los usuarios completan un proceso de registro e inicio de sesión y luego pueden subir y compartir archivos en formatos como PDF, documentos de Word y presentaciones.
O documento discute a obrigatoriedade do Ensino Fundamental no Brasil. Ele explica que a obrigatoriedade foi estabelecida por leis de 1961 e 1996 para assegurar uma formação comum e desenvolver a capacidade crítica e pensamento dos estudantes. No entanto, a qualidade do ensino nem sempre atendeu esses objetivos.
Comunicado. 40 por ciento de padecimientos atendidos son por cáncerprensa AMIS
El 40% de las enfermedades cubiertas por las aseguradoras mexicanas corresponden al tratamiento de cáncer y tumores, siendo el grupo de edad con mayor frecuencia entre 51 y 64 años. Las estadísticas muestran que el 45% de personas entre 51-64 años usaron su seguro médico para cubrir cáncer, mientras que el 39% y 37% de personas entre 31-50 años y mayores de 65 años respectivamente también presentaron cáncer. Los tres casos de cáncer más costosos fueron un tumor maligno de piel, huesos y méd
El documento es un currículum vitae de Carlos Maximiliano Rosas Arraiano, un arquitecto argentino. Detalla su información personal y de contacto, educación, idiomas, habilidades con software, actividades académicas y de formación, cursos de especialización, y trabajos realizados como diseñador urbano para la Fundación CEPA desde 2003 hasta la actualidad en varios proyectos en Argentina, Uruguay, Brasil y México.
1) Equalizer matching involves finding the power spectrum of an example audio, then multiplying the input audio's magnitude spectrogram by a filter matching the example's power spectrum.
2) Noise matching involves denoising the input and example separately, then recombining their clean and noise components using the original signal-to-noise ratio.
3) Reverberation matching uses convolutive non-negative matrix factorization to decompose the input into a dry sound and reverb kernel, and convolve the estimated dry input with the example's reverb kernel.
The mayor of Kasa-vubu district in Kinshasa, Democratic Republic of Congo has authorized the registration of the non-denominational not-for-profit organization FONDATION NSIESI - NFDP.C/ONG/ASBL. Based on an investigation by the district's Rural Development Service, the mayor confirmed that the organization is headquartered at 42 Avenue de la Force Publique in Kasa-vubu district. In accordance with the DRC constitution and Act 004 of 2001 on not-for-profit organizations, the mayor has authorized the organization to operate within his jurisdiction from its headquarters address. However, the organization's activities must not violate public order or current legislation.
NSJ EnviroSciences provides a reference letter for Meagan and Andrew Clarkson's application to become a Mould Remediation Specialist. The letter details that NSJ has processed over 101 jobs for AMC Ozone Treatment in the last 2 years, with no failed remediation jobs. It commends Meagan and Andrew for their professional commitment and physical effort on remediation works. NSJ also appreciates how Meagan and Andrew readily confer on problem jobs and share context to help NSJ better advise them.
Este documento presenta diversas estrategias metodológicas para la enseñanza y el aprendizaje, entre ellas: preguntas orientadoras, cuadros sinópticos, matrices de clasificación, mapas conceptuales, debates, foros, talleres y estudios de caso. El objetivo es ofrecer herramientas que permitan organizar y comprender mejor la información, desarrollar el pensamiento crítico y favorecer la participación activa de los estudiantes.
Habitat models: Predicting Sebastes presence in the Del Monte ShalebedsLisa Jensen
The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures.
Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries.
Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity.
This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds.
Self-organzing maps in Earth Observation Data Cube AnalysisLorena Santos
Earth Observation (EO) Data Cubes infrastructures model
analysis-ready data generated from remote sensing images as multidimensional cubes (space, time and properties), especially for satellite image time series analysis. These infrastructures take advantage of big data technologies and methods to store, process and analyze the big amount of Earth observation satellite images freely available nowadays. Recently, EO Data Cubes infrastructures and satellite image time series analysis
have brought new opportunities and challenges for the Land Use and Cover Change (LUCC) monitoring over large areas. LUCC have caused a great impact on tropical ecosystems, increasing global greenhouse gases emissions and reducing the planet’s biodiversity. This paper presents the
utility of Self-Organizing Maps (SOM) neural network method in the
process to extract LUCC information from EO Data Cubes infrastructures, using image time series analysis. Most classification techniques to create LUCC maps from satellite image time series are based on supervised learning methods. In this context, SOM is used as a method to assess land use and cover samples and to evaluate which spectral bands and vegetation indexes are best suitable for the separability of land use and cover classes. A case study is described in this work and shows the potential of SOM in this application
The effectiveness of methods and algorithms for detecting and isolating facto...IJECEIAES
This article discusses a large number of textural features and integral transformations for the analysis of texture-type images. It also discusses the description and analysis of the features of applying existing methods for segmenting texture areas in images and determining the advantages and disadvantages of these methods and the problems that arise in the segmentation of texture areas in images. The purpose of the ongoing research is to use methods and determine the effectiveness of methods for the analysis of aerospace images, which are a combination of textural regions of natural origin and artificial objects. Currently, the automation of the processing of aerospace information, in particular images of the earth’s surface, remains an urgent task. The main goal is to develop models and methods for more efficient use of information technologies for the analysis of multispectral texture-type images in the developed algorithms. The article proposes a comprehensive approach to these issues, that is, the consideration of a large number of textural features by integral transformation to eventually create algorithms and programs applicable to solving a wide class of problems in agriculture.
Radar and optical remote sensing data evaluation and fusion; a case study for...rsmahabir
The recent increase in the availability of spaceborne radar in different wavelengths with multiple polarisations provides new opportunities for land surface analysis. This research effort explored how different radar data, and derived texture values, indepen- dently and in combination with optical imagery influence land cover/use classification accuracies for a study site in Washington, DC, USA. Two spaceborne radar images, Radarsat-2L-band and Palsar C-band quad-polarised radar, were registered with Aster optical data for this study. Traditional methods of classification were applied to various components and combinations of this data set, and overall and class-specific thematic accuracies obtained for comparison. The results for the two despeckled radar data sets were quite different, with Radarsat-2 obtaining an overall accuracy of 59% and Palsar 77%, while that of the optical Aster was 90%. Combining the original radar and a variance texture measure increased the accuracy of Radarsat-2 to 71% but that of Palsar only to 78%. One of the sensor fusions of optical and radar obtained an accuracy of 93%. For this location, radar by itself does not obtain classification accuracies as high as optical data, but fusion with optical imagery provides better overall thematic accuracy than the optical independently, and results in some useful improvements on a class-by-class basis. For those regions with high cloud cover, quad polarisation radar can independently provide viable results but it may be wavelength-dependent.
The Matrix Effects Natural Resources Remote Scanningsolarsonics
The document describes a technology called The Matrix Effect that utilizes holographic principles, string theory, and solar sonic frequencies to identify natural resources and other substances through their unique molecular signatures. It can potentially be used for natural resource exploration, DNA imaging, asteroid defense, energy production, forensics, anti-aging, and more. Further development is needed, including custom automation software and higher resolution imaging technology, to fully realize the possibilities of this technology.
Ascendency As An Ecological Indicator A Case Study Of Estuarine Pulse Eutrop...Sheila Sinclair
This document summarizes a case study examining estuarine eutrophication using ecological network analysis and the concept of ascendency. Three sampling stations were selected along a gradient of eutrophication in the southern arm of the Mondego estuary in Portugal. Network analyses were conducted on food webs constructed for each station. The analyses quantified trophic exchanges, biomass, and energy flows to develop ecological budgets. The study aimed to test if the network concept of ascendency accurately tracked changes in community structure along the known eutrophication gradient.
A comprehensive comparison of the original forms of biogeography based optimi...ijscai
Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and one of meta-heuristic algorithms. This technique is based on an old mathematical study that explains the geographical distribution of biological organisms. The first original form of BBO was introduced in 2008 and known as a partial migration based BBO. After three months, BBO was re-introduced again with additional three other forms and known as single, simplified partial, and simplified single migration based BBOs. Then a lot of modifications and hybridizations were employed to boost-up the performance of BBO and solve its weak exploration. However, the literature lacks the explanations and the reasons on which the modifications of the BBO forms are based on. This paper tries to clarify this issue by making a comparison between the four original BBO algorithms through 23 benchmark functions with different dimensions and complexities. The final judgment is confirmed by evaluating the performance based on the effect of the problem’s dimensions, the side constraints and the population size. The results show that both single and simplified single migration based BBOs are faster, but have less performance as compared to the others. The comparison between the partial and the simplified partial migration based BBOs shows that the preference depends on the population size, problem’s complexity and dimensions, and the values of the upper and lower side constraints. The partial migration model wins when these factors, except the population size, are increased, and vice versa for the simplified partial migration model. The results can be used as a foundation and a first step of modification for enhancing any proposed modification on BBO including the existing modifications that are described in literature.
This document provides information about the proper uses of the prepositions "in", "on", and "at" as they relate to time and place. It explains that "in" is generally used for enclosed spaces and long periods of time, "on" is used for surfaces and specific days/dates, and "at" is used for precise times and points. Numerous examples are given to illustrate the different uses of each preposition in contexts involving locations, dates, times of day, activities, and states. At the end, an activity is included where the reader must choose the correct preposition to complete sentences about time and place.
18 June 2015 Rare Disease Site & Patient Recruitment KJAKevin J. Anderson
This document discusses challenges and approaches for site and patient recruitment in rare disease clinical studies. Key challenges include the rarity of diseases, difficulty finding patients and physicians, complex logistics, and vulnerable patient populations. Effective approaches involve casting a wide net globally, leveraging registries and advocacy groups, using medical informatics to identify sites, and hiring specialists to assist with outreach and education. Lessons learned emphasize starting recruitment efforts early, challenging site estimates, and ensuring multiple potential enrollment sites are identified for each patient.
La secuencia didáctica pretende que estudiantes de transición interpreten y analicen datos sobre animales y objetos en inglés de manera lúdica utilizando fichas, juegos y la herramienta Scratch. Las actividades incluyen identificar animales en una canción, organizar fichas de animales por cantidad, analizar la frecuencia de útiles escolares en grupos y subgrupos, y crear aplicaciones en Scratch para interpretar datos e incluir vocabulario en inglés. La evaluación es procesual a través de autoevaluación, coevaluación y
SlideShare es una herramienta en línea gratuita para compartir presentaciones. Se lanzó en 2006 y fue adquirida por LinkedIn en 2012. Los usuarios pueden subir documentos, presentaciones y videos de manera privada o pública. Proporciona funciones como comentarios, evaluaciones y conferencias en vivo. Para crear una cuenta, los usuarios completan un proceso de registro e inicio de sesión y luego pueden subir y compartir archivos en formatos como PDF, documentos de Word y presentaciones.
O documento discute a obrigatoriedade do Ensino Fundamental no Brasil. Ele explica que a obrigatoriedade foi estabelecida por leis de 1961 e 1996 para assegurar uma formação comum e desenvolver a capacidade crítica e pensamento dos estudantes. No entanto, a qualidade do ensino nem sempre atendeu esses objetivos.
Comunicado. 40 por ciento de padecimientos atendidos son por cáncerprensa AMIS
El 40% de las enfermedades cubiertas por las aseguradoras mexicanas corresponden al tratamiento de cáncer y tumores, siendo el grupo de edad con mayor frecuencia entre 51 y 64 años. Las estadísticas muestran que el 45% de personas entre 51-64 años usaron su seguro médico para cubrir cáncer, mientras que el 39% y 37% de personas entre 31-50 años y mayores de 65 años respectivamente también presentaron cáncer. Los tres casos de cáncer más costosos fueron un tumor maligno de piel, huesos y méd
El documento es un currículum vitae de Carlos Maximiliano Rosas Arraiano, un arquitecto argentino. Detalla su información personal y de contacto, educación, idiomas, habilidades con software, actividades académicas y de formación, cursos de especialización, y trabajos realizados como diseñador urbano para la Fundación CEPA desde 2003 hasta la actualidad en varios proyectos en Argentina, Uruguay, Brasil y México.
1) Equalizer matching involves finding the power spectrum of an example audio, then multiplying the input audio's magnitude spectrogram by a filter matching the example's power spectrum.
2) Noise matching involves denoising the input and example separately, then recombining their clean and noise components using the original signal-to-noise ratio.
3) Reverberation matching uses convolutive non-negative matrix factorization to decompose the input into a dry sound and reverb kernel, and convolve the estimated dry input with the example's reverb kernel.
The mayor of Kasa-vubu district in Kinshasa, Democratic Republic of Congo has authorized the registration of the non-denominational not-for-profit organization FONDATION NSIESI - NFDP.C/ONG/ASBL. Based on an investigation by the district's Rural Development Service, the mayor confirmed that the organization is headquartered at 42 Avenue de la Force Publique in Kasa-vubu district. In accordance with the DRC constitution and Act 004 of 2001 on not-for-profit organizations, the mayor has authorized the organization to operate within his jurisdiction from its headquarters address. However, the organization's activities must not violate public order or current legislation.
NSJ EnviroSciences provides a reference letter for Meagan and Andrew Clarkson's application to become a Mould Remediation Specialist. The letter details that NSJ has processed over 101 jobs for AMC Ozone Treatment in the last 2 years, with no failed remediation jobs. It commends Meagan and Andrew for their professional commitment and physical effort on remediation works. NSJ also appreciates how Meagan and Andrew readily confer on problem jobs and share context to help NSJ better advise them.
Este documento presenta diversas estrategias metodológicas para la enseñanza y el aprendizaje, entre ellas: preguntas orientadoras, cuadros sinópticos, matrices de clasificación, mapas conceptuales, debates, foros, talleres y estudios de caso. El objetivo es ofrecer herramientas que permitan organizar y comprender mejor la información, desarrollar el pensamiento crítico y favorecer la participación activa de los estudiantes.
Habitat models: Predicting Sebastes presence in the Del Monte ShalebedsLisa Jensen
The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures.
Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries.
Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity.
This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds.
Self-organzing maps in Earth Observation Data Cube AnalysisLorena Santos
Earth Observation (EO) Data Cubes infrastructures model
analysis-ready data generated from remote sensing images as multidimensional cubes (space, time and properties), especially for satellite image time series analysis. These infrastructures take advantage of big data technologies and methods to store, process and analyze the big amount of Earth observation satellite images freely available nowadays. Recently, EO Data Cubes infrastructures and satellite image time series analysis
have brought new opportunities and challenges for the Land Use and Cover Change (LUCC) monitoring over large areas. LUCC have caused a great impact on tropical ecosystems, increasing global greenhouse gases emissions and reducing the planet’s biodiversity. This paper presents the
utility of Self-Organizing Maps (SOM) neural network method in the
process to extract LUCC information from EO Data Cubes infrastructures, using image time series analysis. Most classification techniques to create LUCC maps from satellite image time series are based on supervised learning methods. In this context, SOM is used as a method to assess land use and cover samples and to evaluate which spectral bands and vegetation indexes are best suitable for the separability of land use and cover classes. A case study is described in this work and shows the potential of SOM in this application
The effectiveness of methods and algorithms for detecting and isolating facto...IJECEIAES
This article discusses a large number of textural features and integral transformations for the analysis of texture-type images. It also discusses the description and analysis of the features of applying existing methods for segmenting texture areas in images and determining the advantages and disadvantages of these methods and the problems that arise in the segmentation of texture areas in images. The purpose of the ongoing research is to use methods and determine the effectiveness of methods for the analysis of aerospace images, which are a combination of textural regions of natural origin and artificial objects. Currently, the automation of the processing of aerospace information, in particular images of the earth’s surface, remains an urgent task. The main goal is to develop models and methods for more efficient use of information technologies for the analysis of multispectral texture-type images in the developed algorithms. The article proposes a comprehensive approach to these issues, that is, the consideration of a large number of textural features by integral transformation to eventually create algorithms and programs applicable to solving a wide class of problems in agriculture.
Radar and optical remote sensing data evaluation and fusion; a case study for...rsmahabir
The recent increase in the availability of spaceborne radar in different wavelengths with multiple polarisations provides new opportunities for land surface analysis. This research effort explored how different radar data, and derived texture values, indepen- dently and in combination with optical imagery influence land cover/use classification accuracies for a study site in Washington, DC, USA. Two spaceborne radar images, Radarsat-2L-band and Palsar C-band quad-polarised radar, were registered with Aster optical data for this study. Traditional methods of classification were applied to various components and combinations of this data set, and overall and class-specific thematic accuracies obtained for comparison. The results for the two despeckled radar data sets were quite different, with Radarsat-2 obtaining an overall accuracy of 59% and Palsar 77%, while that of the optical Aster was 90%. Combining the original radar and a variance texture measure increased the accuracy of Radarsat-2 to 71% but that of Palsar only to 78%. One of the sensor fusions of optical and radar obtained an accuracy of 93%. For this location, radar by itself does not obtain classification accuracies as high as optical data, but fusion with optical imagery provides better overall thematic accuracy than the optical independently, and results in some useful improvements on a class-by-class basis. For those regions with high cloud cover, quad polarisation radar can independently provide viable results but it may be wavelength-dependent.
The Matrix Effects Natural Resources Remote Scanningsolarsonics
The document describes a technology called The Matrix Effect that utilizes holographic principles, string theory, and solar sonic frequencies to identify natural resources and other substances through their unique molecular signatures. It can potentially be used for natural resource exploration, DNA imaging, asteroid defense, energy production, forensics, anti-aging, and more. Further development is needed, including custom automation software and higher resolution imaging technology, to fully realize the possibilities of this technology.
Ascendency As An Ecological Indicator A Case Study Of Estuarine Pulse Eutrop...Sheila Sinclair
This document summarizes a case study examining estuarine eutrophication using ecological network analysis and the concept of ascendency. Three sampling stations were selected along a gradient of eutrophication in the southern arm of the Mondego estuary in Portugal. Network analyses were conducted on food webs constructed for each station. The analyses quantified trophic exchanges, biomass, and energy flows to develop ecological budgets. The study aimed to test if the network concept of ascendency accurately tracked changes in community structure along the known eutrophication gradient.
A comprehensive comparison of the original forms of biogeography based optimi...ijscai
Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and one of meta-heuristic algorithms. This technique is based on an old mathematical study that explains the geographical distribution of biological organisms. The first original form of BBO was introduced in 2008 and known as a partial migration based BBO. After three months, BBO was re-introduced again with additional three other forms and known as single, simplified partial, and simplified single migration based BBOs. Then a lot of modifications and hybridizations were employed to boost-up the performance of BBO and solve its weak exploration. However, the literature lacks the explanations and the reasons on which the modifications of the BBO forms are based on. This paper tries to clarify this issue by making a comparison between the four original BBO algorithms through 23 benchmark functions with different dimensions and complexities. The final judgment is confirmed by evaluating the performance based on the effect of the problem’s dimensions, the side constraints and the population size. The results show that both single and simplified single migration based BBOs are faster, but have less performance as compared to the others. The comparison between the partial and the simplified partial migration based BBOs shows that the preference depends on the population size, problem’s complexity and dimensions, and the values of the upper and lower side constraints. The partial migration model wins when these factors, except the population size, are increased, and vice versa for the simplified partial migration model. The results can be used as a foundation and a first step of modification for enhancing any proposed modification on BBO including the existing modifications that are described in literature.
During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased
to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time
slice. To address this problem, several seismic facies classification algorithms including k-means, self-organizing
maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural
networks have been successfully used to extract features of geologic interest from multiple volumes. Although
well documented in the literature, the terminology and complexity of these algorithms may bewilder the average
seismic interpreter, and few papers have applied these competing methods to the same data volume. We have
reviewed six commonly used algorithms and applied them to a single 3D seismic data volume acquired over the
Canterbury Basin, offshore New Zealand, where one of the main objectives was to differentiate the architectural
elements of a turbidite system. Not surprisingly, the most important parameter in this analysis was the choice of
the correct input attributes, which in turn depended on careful pattern recognition by the interpreter. We found
that supervised learning methods provided accurate estimates of the desired seismic facies, whereas unsupervised
learning methods also highlighted features that might otherwise be overlooked.
Geographers at Clark University and Clark Labs in Worcester, Massachusetts, use geographic information system (GIS)
and image processing computer software to produce images that help them understand the impact of humans on the Earth. A spring 2016 exhibit by J. Ronald Eastman, professor of geography and director of Clark Labs, highlights some of these images. The exhibit is sponsored by Clark University's Higgins School of Humanities and Clark Labs.
CLUSTER DETECTION SCHEMES IN SPATIO TEMPORAL NETWORKSIJDKP
A spatiotemporal challenge can be portrayed as an inquiry that has no short of what one spatial and one
momentary property. The spatial properties are region and geometry of the inquiry. The transient property
is timestamp or time interval for which the challenge is real. The spatio fleeting inquiry as a general rule
contains spatial, common and topical or non-spatial properties. Instances of such inquiries are moving
auto, forest fire, and earth shake. Spatiotemporal educational accumulations essentially find changing
estimations of spatial and topical attributes over a time allotment. Spatio transient bunching is a procedure
of collection articles in view of their spatial and worldly similitude. It is generally new sub-field of
information mining which increased high notoriety particularly in geographic data sciences because of the
inescapability of a wide range of area based or ecological gadgets that record position, time or/and
natural properties of a protest or set of articles progressively. As a result, distinctive sorts and a lot of
spatio-transient information got to be distinctly accessible that acquaint new difficulties with information
examination and require novel ways to deal with learning revelation.
This document summarizes a study of polygonal fault systems in the Dutch offshore region of the North Sea using 3D seismic data. The analysis identified polygonal fault networks at the Mid Miocene Unconformity, characterized by small-scale, densely packed normal faults arranged in a random, polygonal pattern. Seismic attributes like similarity and curvature were computed to enhance visualization of the fault systems, showing they are most prominent in the northwest, southwest, and northeast parts of the study area and exhibit a range of orientations with a major east-west trend. The polygonal fault systems likely played a role in fluid migration and reservoir architecture in this region.
This study tested the feasibility of using classification tree analysis (CTA) on high resolution aerial imagery and linear spectral unmixing (LSU) on Landsat TM data to map the distribution of invasive flowering rush in the Ottawa National Wildlife Refuge wetlands in Ohio. CTA was used to classify the aerial imagery and derive endmembers, which were then input into LSU to estimate sub-pixel abundances from the Landsat imagery. Validation showed the aerial imagery results were slightly better than the Landsat results at mapping flowering rush. Overall, both methods showed promise for predicting flowering rush distribution but require further research using different datasets and modeling techniques.
This document provides an overview of different types of orbits used for satellites, including low Earth orbit (LEO), medium Earth orbit (MEO), geostationary orbit (GEO), and highly elliptical orbit (HEO). It discusses the advantages and disadvantages of each orbit type, as well as their applications. Specific orbits like LEO are discussed in more detail, including factors like altitude and advantages like lower latency for communication satellites. The document also examines space debris and the increasing threat it poses to operational satellites from collisions. It notes there are over 20,000 pieces of debris larger than 10cm tracked in Earth's orbit.
APPLICATION OF SPATIOTEMPORAL ASSOCIATION RULES ON SOLAR DATA TO SUPPORT SPAC...IJDKP
This summarizes a research paper that proposes a new algorithm called MiTSAI to extract Thematic Spatiotemporal Association Rules (TSARs) from solar Satellite Image Time Series (SITS) in order to better understand solar data and support space weather forecasting. MiTSAI considers both the visual features and semantic information of solar images. Experimental results validated that MiTSAI can extract new and interesting patterns compared to existing algorithms.
M. cribraria was initially detected in Georgia in 2009 and has since spread rapidly throughout the Southeastern US. Researchers theorized this spread may have occurred via attaching to moving surfaces like automobiles ("hitchhiking"). This study tested this theory by examining M. cribraria's ability to attach to surfaces in a wind tunnel. The results showed the insects could remain attached for an average of 591 seconds, equivalent to potentially traveling 5.6 miles. While there was variation, this provides support that "hitchhiking" may explain the insect's rapid dispersal following its initial detection. However, more research is needed to better understand attachment times under different conditions.
Estimation of diffuse solar radiation in the south of cameroonAlexander Decker
This document presents a study that developed models to estimate monthly mean daily diffuse solar radiation for locations in southern Cameroon between 2°N and 5°N latitude. It analyzed monthly mean daily data on global and diffuse solar radiation from 1985-2005 for five cities. Linear and quadratic regression models were developed relating diffuse fraction to clearness index. The proposed models were compared to existing models from Liu and Jordan, Page, Iqbal, and Erbs, finding the proposed models had better statistical performance and agreement with observed values. The study concludes the developed models can reliably estimate diffuse solar radiation for locations in southern Cameroon.
This summarizes a document about change detection techniques in remote sensing for analyzing land use and land cover changes. Remote sensing using aerial photographs and satellite imagery allows efficient monitoring of land cover changes compared to traditional field surveys. Change detection involves identifying transformations of land cover types over time and space using multi-temporal remote sensing data. Common techniques include comparing imagery from Landsat, QuickBird and other satellite sensors to detect changes in agriculture, deforestation, urban growth and other human and natural impacts on the earth's surface.
This document describes a study that used remote sensing and GIS techniques to assess land use and land cover changes in Madurai City, India between 2003 and 2008. Satellite imagery from 2003 and 2008 was analyzed using supervised classification to create land use/land cover maps for each time period. A change detection analysis was then conducted to identify changes between the two time periods. The results showed an 18% increase in built-up land and a 14.2% increase in crop land, while mixed built-up land and vacant land decreased. The study concluded that the urban area of Madurai City increased significantly from 2003 to 2008.
Rhizostoma optimization algorithm and its application in different real-world...IJECEIAES
In last decade, numerous meta-heuristic algorithms have been proposed for dealing the complexity and difficulty of numerical optimization problems in the realworld which is growing continuously recently, but only a few algorithms have caught researchers’ attention. In this study, a new swarm-based meta-heuristic algorithm called Rhizostoma optimization algorithm (ROA) is proposed for solving the optimization problems based on simulating the social movement of Rhizostoma octopus (barrel jellyfish) in the ocean. ROA is intended to mitigate the two optimization problems of trapping in local optima and slow convergence. ROA is proposed with three different movement strategies (simulated annealing (SA), fast simulated annealing (FSA), and Levy walk (LW)) and tested with 23 standard mathematical benchmark functions, two classical engineering problems, and various real-world datasets including three widely used datasets to predict the students’ performance. Comparing the ROA algorithm with the latest meta-heuristic optimization algorithms and a recent published research proves that ROA is a very competitive algorithm with a high ability in optimization performance with respect to local optima avoidance, the speed of convergence and the exploration/exploitation balance rate, as it is effectively applicable for performing optimization tasks.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
1. Florida Entomological Society is collaborating with JSTOR to digitize, preserve and extend access to The Florida Entomologist.
http://www.jstor.org
THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS FOR ANALYZING INFESTATIONS AND
SPREAD OF INVASIVE TERMITES (ISOPTERA: RHINOTERMITIDAE AND TERMITIDAE) IN URBAN
SOUTH FLORIDA
Author(s): Hartwig H. Hochmair, Francesco Tonini and Rudolf H. Scheffrahn
Source: The Florida Entomologist, Vol. 96, No. 3 (September, 2013), pp. 746-755
Published by: Florida Entomological Society
Stable URL: http://www.jstor.org/stable/23609383
Accessed: 04-12-2015 03:16 UTC
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2. 746 Florida Entomologist 96(3) September 2013
THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS FOR ANALYZING
INFESTATIONS AND SPREAD OF INVASIVE TERMITES (ISOPTERA:
RHINOTERMITIDAE AND TERMITIDAE) IN URBAN SOUTH FLORIDA5
Hartwig H. Hochmair", Francesco Tonini and Rudolf H. Scheffrahn
University of Florida, Fort Lauderdale Research and Education Center, 3205 College Avenue,
Davie, Florida, U.S.A. 33314
*Corresponding author; E-mail: hhhochmair@ufl.edu
Summarized from a presentation and discussions at the "Native or Invasive - Florida Harbors Everyone"
Symposium at the Annual Meeting of the Florida Entomological Society, 24 July 2012, Jupiter, Florida.
Supplementary material for this article in Florida Entomologist 96(3) (2013) is online
at http://purl.fcla.edu/fcla/entomologist/browse
Abstract
The ability to manage geospatial data has made Geographic Information Systems (GIS) an
important tool for a wide range of applications over the past decades, including manage
ment of natural resources, analysis of wildlife movement, ecological niche modeling, or land
records management. This paper illustrates, using invasive termite species as examples,
how GIS can assist in identifying their potential sources of infestations and model their
spread in urban South Florida. The first case study shows that the Formosan subterranean
termite, Coptoterm.es formosanus Shiraki, and the Asian subterranean termite, Coptotermes
gestroi (Wasmann) (Isoptera: Rhinotermitidae), were introduced into and dispersed across
South Florida by sailboats and yachts. The second case study shows an agent-based model to
simulate the natural spread of Nasutitermes corniger (Motschulsky) (Isoptera: Termitidae)
in Dania Beach, Florida. This paper provides an overview of basic functionalities in GIS and
demonstrates how they can be customized for advanced modeling and simulation.
Key Words: Spatial analysis, GIS functionality, modeling, South Florida, exotic termites
Resumen
La capacidad de manejar datos geoespaciales ha hecho de los Sistemas de Información Geo
gráfica (SIG) una herramienta importante para una amplia gama de aplicaciones en las
últimas décadas, incluyendo el manejo de los recursos naturales, análisis de movimiento
de la fauna, modelos de nichos ecológicos, o manejo de los registros de terrenos. Se ilustra,
utilizando especies invasoras de termitas como ejemplos, cómo el SIG puede ayudar a identi
ficar las posibles fuentes de infestación y modelar su diseminación en las zonas urbanas del
sur de la Florida. El primer caso de estudio muestra que la termita subterránea de Formo
sa, Coptotermes formosanus Shiraki y la termita subterránea asiática, Coptotermes gestroi
(Wasmann) (Isoptera: Rhinotermitidae), fueron introducidas y dispersadas en todo el sur de
la Florida por medio de los barcos veleros y yates. El segundo caso de estudio muestra un
modelo basado en agentes para simular la diseminación natural de Nasutitermes corniger
(Motschulsky) (Isoptera: Termitidae) en Dania Beach, Florida. Este documento provee una
visión global de las funciones básicas de SIG y demuestra la forma como puede ser adaptado
para producir modelos azanzados y simulaciones.
Palabras Clave: análisis espacial, funcionalidad GIS, modelos, sur de la Florida, termitas
exóticas
Termites are destructive insect pests which
cause billions of US dollars in structural damage
and control within the United States alone (Su &
Scheffrahn 1998). Worldwide, more than a dozen
exotic termite species have become established
(Evans 2011), of which 6 can be found in Florida
(Scheffrahn et al. 2002). Typical research ques
tions related to invasive species are: (Ql) How
did non-native species invade and establish non
endemic populations? (Q2) How fast do invasive
species disperse without human assistance with
in a new environment? In the case of termites,
maritime transport has long been suspected to be
responsible for the transport and nonendemic es
tablishment of numerous termite species across
ocean barriers (Gay 1967; Scheffrahn et al. 2009).
Two invasive termites, the Formosan subterra
nean termite (FST), Coptotermes formosanus Shi
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3. Hochmair et al.: Geographie Information Systems for Analyzing Termite Invasions 747
raki (Isoptera: Rhinotermitidae), and the Asian
subterranean termite (AST), Coptotermes gestroi
(Wasmann), are now well-established pests in
urban South Florida. The paper by Hochmair &
Scheffrahn (2010) illustrates how a Geographic
Information System (GIS) was utilized to show
with spatial analysis that these two invasive spe
cies were introduced through boat traffic. In a
second example herein, we demonstrate how GIS
functions together with an agent-based model
simulate the natural dispersal of an arboreal in
vasive termite, Nasutitermes corniger (Isoptera:
Termitidae), in Dania Beach, Florida. The focus
of this paper is on describing how a GIS can be
used to run spatial analyses in order to answer
the aforementioned research questions.
Geographic Information Systems
A GIS comprises an integrated suite of soft
ware components containing (1) a data manage
ment system, (2) a mapping system for display
and interaction with maps, and (3) a spatial anal
ysis and modeling system (Longley et al. 2011). It
uses georeferenced data, that is, having unique
location information, such as postal addresses, or
point coordinates. Geovisualization is used to ex
plore, analyze, and present spatial data, however,
a GIS mapping system also supports on-screen
digitizing of spatial features on top of background
maps. Point, line, and polygon object features are
often displayed over a base map, e.g. a satellite
image, which can be provided through a Web
mapping service within the GIS. Geovisualization
often involves a map projection, which is a pro
cess that transforms the spherical Earth's surface
into a plane (Slocum et al. 2005). The resultant
map allows use of a Euclidean coordinate system
with Eastings and Northings instead of geograph
ic coordinates with longitude and latitude. This
simplifies the computation of distance, direction,
and area compared to spherical geometry.
A raster dataset represents geographic fea
tures by dividing the Earth into discrete square
or rectangular cells laid out in a grid. Cells, also
called pixels, are arranged in rows and columns,
and each cell has a value that is used to represent
some characteristic of that location. Resampling
of both background maps and raster dataseis in
general is necessary whenever raster data must
be transformed to another coordinate grid system
or the cell size between input and output raster
changes, like in the case of registering remotely
sensed data to a ground coordinate system. Dur
ing this process cell values in the new grid are
filled with cell values derived from the original
grid using a resampling technique. Resampling is
also necessary in the context of map projections.
Let us assume that a background image (Fig. 1)
is provided in Albers Equal Area Conic projection
for North America, as shown to the left. The im
age has a pixel resolution of approximately one
meter, and Eastings and Northings are given in
meters. Let us further assume that the GIS uses
the Universal Transverse Mercator (UTM) projec
tion (Zone 17) to display the image together with
other data layers. For this task, the background
image needs to be re-projected to UTM. The con
version between these 2 projected grids is done
through different sets of equations, where pro
jected coordinates are converted to geographical
coordinates. For the output image in UTM pro
jection, pixel brightness values need to be deter
mined for each pixel from the input image (Albers
projection). Since there is no direct one-to-one re
lationship between pixels of the input and output
image, the output image often requires a value
from a location of the input pixel grid that does
not fall neatly on a cell center. This is illustrated
in a zoomed portion of the images, shown with a
highlighted grid cell as an example (lower right
portion of Fig. 1), where the brightness value of a
pixel in the pool area is sought (yellow dot). Using
mapping equations, the point coordinate of that
cell center in the output image can be converted
back to the point coordinates in the coordinate
system of the input image (dashed arrow), giv
ing the position indicated by the brown dot. Since
the brown dot in the input image is not on a cell
center, a mechanism for determining the bright
ness value from neighboring cells is used. This
mechanism is called intensity interpolation and
is the core of resampling techniques (solid arrow).
Widely used interpolation methods include the
nearest neighbor interpolation, the bilinear inter
polation, or the cubic convolution (Jensen 2005).
GIS Analysis
Two conceptual schemas are used to represent
the Earth, which are (i) discrete object view and
(ii) continuous-field view. Both schemas have im
plications on the GIS data models used for GIS
analysis. In the discrete object view the world
is empty except where occupied by stationary
or moving objects with well-defined boundaries,
including lakes, roads, buildings, or animals.
While this schema works for many everyday ap
plications, it becomes difficult to provide defini
tions for all kinds of objects to be mapped, e.g.
to distinguish between a hill and a mountain. In
the discrete object view geographic objects are de
fined by their dimensionality and represented in
the GIS as a vector data model. The vector data
model uses points and their x-, y- coordinates to
construct polygons (for area-like objects such as
counties), lines (for linear features such as roads),
and zero-dimensional points (such as termite
infested boats). In the continuous-field view, the
world is described by a number of variables where
each variable can be measured at every position
on Earth. This conceptual scheme is realized as
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4. 748 Florida Entomologist 96(3) September 2013
North pole
Meridian of Greenwich
(A=0°)
Geographic coordinates
. (latitude cp,longitude A.)
Inverse mapping
Equator (<p=o-)/ / ^
Forward mapping
equations J / equations
8
Albers Equal Area Conic Projection UTM Projection, Zone 17
P(1267124.62,-1117636.81) P(369591.65,3280806.30)
1266900 1267000 1267100 1267200 369300 369400 369500 369600
280900H
280800
280700
280600
Convert coordinate of cell center ^
iC id in output image to inputimage g g
<n S coordinate system 2 2
¥ ¥ ¥ ¥X X x x
y=-1117636.18 y=3280806.80
d"
" " "
"O
y=-1117637.18 —y=3280805.80
Brightness value through resampling
Input image Output image
Fig. 1. Re-projection of a 1-m resolution aerial image between Albers Equal Area Conic projection and UTM
projection (Zone 17) using geographic coordinates as an intermediate step. Resampling is used to fill pixel values
in the output image through pixel values derived from the input image.
raster data in a GIS, where a surface is overlaid
with a raster grid that has attributes assigned to
its cells, such as elevation or land cover class.
The large number of spatial analysis functions
in a GIS can be divided into (1) analyses based
on a single location, and (2) analyses based on
distance between separate places (Longley et al.
2011). The first group compares different proper
ties of the same place and calculates relationships
and correlations between them. For example, this
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5. Hochmair et al.: Geographie Information Systems for Analyzing Termite Invasions 749
includes the analysis of attribute tables, spatial
joins, point-in-polygon operations, polygon over
lays (such as Union and Erase), and raster analy
sis. The Union operation creates a new layer of
vector polygons (called coverage) by overlaying
two input polygon coverages. The resultant cov
erage contains the combined polygons and attri
butes of both input coverages. The Erase opera
tion removes the part inside of the first coverage
which is covered by the outline of the overlaid
coverage. The second group of analysis functions
includes the measurement of distances between
points, buffering, cluster detection, computation
of autocorrelation, density estimation, and spa
tial interpolation. All these methods can be com
bined into more complex tasks both in the raster
and vector data model. One example is surface
analysis, which includes the computation of both
slope and aspect of a surface grid cell, finding the
least cost path between two grid cells, delineation
of watersheds, or determining viewsheds (a view
shed is an area of land or water that is visible to
the human eye from a fixed vintage point) based on
topography. Another example is network analysis
which includes routing and logistics problems in
transportation networks, such as optimizing the
routing of delivery trucks. Observation of social
insect behavior has allowed computer scientists
and engineers to improve network based optimi
zation algorithms, such as the Travelling Sales
man Problem which consists of finding the short
est tour between a given set of cities visiting each
city once only and ending at the starting point.
This problem has been tackled by the use of arti
ficial pheromones (with a decay of the pheromone
concentration over time) that artificial ants use
to mark travelled paths along completed routes.
This approach has been adopted from ant colony
behavior, where ants use pheromones during for
aging for food to collectively discover the shortest
path between nest and food source (Bonabeau et
al. 2000). A GIS provides sampling tools for spa
tial statistical testing, e.g., generating random
points within a pre-defined area (de Smith et al.
2010).
GIS Modeling
A GIS can also be used to create and visual
ize dynamic simulation models. A simulation
shows the evolution of the phenomenon of inter
est through time and may involve multiple sub
processes. Dynamic modeling allows scientists to
experiment with policy options and what-if sce
narios. It also allows them to implement ideas
about the behavior to the world (Longley et al.
2011). Typical case study applications include:
Planning for emergency evacuations, e.g. in the
case of hurricanes or wildfires; urban growth sce
narios and its impact on food resources and en
vironment; assessment of the effect of planning
policies on deforestation area; modeling competi
tion for canopy space in forest ecosystems for bet
ter informed silvicultural prescriptions.
Widely used model types include: (a) analytical
models, e.g. diffusion-type processes, which use
differential equations (Holmes et al. 1994); (b)
agent-based models (ABM) (Judson 1994), a.k.a.
individual based models (IBM), which study the
fate and movement of single individuals using
both physiological and behavioral rules; (c) land
scape models (Mladenoff 2004), which consider
each cell as group of individuals; and (d) cellular
automata models (Ermentrout & Edelstein-Kesh
et 1993), which represent the surface of the earth
as a raster where each cell has a fixed number of
states that change through transition rules based
on each cell's neighborhood.
Since these models are usually more complex
than what is provided through standard GIS
functionality, they need to be implemented from
scratch or through customization of existing func
tions. Customization is the process of modifying
GIS software through adding new functionality,
embedding GIS functions to other applications,
or creating specific-purpose applications (Longley
et al. 2011). Numerous programming languages,
such as C, C++, C#, Java, or Python are avail
able for customizing both desktop GIS software
and Web GIS applications (Zaragozi et al. 2012;
Zandbergen 2013). Integrated development en
vironments (IDEs) combine various software de
velopment tools, including a visual programming
language, an editor, and a debugger. To support
customization, a vendor must expose details on
the software's functionality to the developers. A
key feature of such software components is that
they have well-defined programming interfaces
that allow the functionality to be called by pro
gramming tools in an IDE. One example is ESRI's
ArcObjects model and all its functionality which
can be accessed through any programming lan
guage that supports the Microsoft Component
Object Model (COM), such as VB.NET, C#, C++,
or Java. The R programming language for statis
tical computing (R Development Core Team 2012)
has recently improved its spatial functionalities
and added a package called RPYGeo providing ac
cess to most of ESRI's ArcGIS geoprocessing tools
fromwithin R. Within the ArcGIS software suite,
customization can also be done with the Model
Builder. This allows the user to build a customized
workflow of geoprocessing operations from exist
ing tools using a graphical interface. The same can
also be accomplished by using Python scripting.
Finally, geospatial analyses and a number of im
age processing tasks can also be carried out using
either open source software, e.g. R, GRASS GIS,
SAGA GIS, or GeoDa, or proprietary software, e.g.
Matlab, SAS, ENVI, or ERDAS. These software
platforms typically exchange data through com
mon GIS formats, such as shapefiles or geotiffs.
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6. 750 Florida Entomologist 96(3) September 2013
Materials and Methods
For enhanced clarity, the figures in this report
are also displayed online in color in supplemen
tary material for this article in Florida Entomolo
gist 96(3) (2013) at http://purl.fcla.edu/fcla/ento
mologist/browse.
Termite Samples
All termite samples used for analysis in the
two case studies are preserved in 85% ethanol
and are deposited in the University of Florida ter
mite collection at the Fort Lauderdale Research and
Education Center in Davie, Florida. Samples were
collected by operatives in the pest control industry
and property owners and submitted to R.H.S. The
collection database records contain among other
data the genus and species, geographic latitude and
longitude of the termite infestation, collection date,
and collecting conditions. For the analysis of the
first case study, samples were used with collection
dates ranging from Apr 1996 to Mar 2009 for AST,
and from May 1990 to Jul 2008 for FST. For that
study, termite samples were externally submitted
for identification and location georeferencing, but
no additional field surveys were conducted.
For the second case study, collection dates of used
samples for N. corniger ranged between Jan 2003
and Feb 2012. From early 2003 until early 2011, a
previously delineated area was targeted for a de
liberate eradication campaign of this invasive pest.
Sample locations were recorded in the field using a
GPS device and later imported into a database. The
surveyed area covered around 200 acres (81 ha).
In 2012, new infestations were found in areas that
were not surveyed since 2005 due to cancellation of
project funding, providing some insight into the dy
namics of natural dispersal.
Case Study 1: Infestation Source Analysis
The first GIS example comes from a study
that compares the distances between 190 terres
trial point records for FST (first infestation reported
1980 in Broward County), 177 records for AST (first
discovered 1996 in Miami), and random points loca
tions in the surrounding urban areas to the near
est marine dockage (Hochmair & Scheffrahn 2010).
The hypothesis is that both species are significantly
closer to potential infested boat locations, i.e., ma
rine docks, than random points in these urban ar
eas. It is further hypothesized that a larger median
distance between FST infestations and proximal
dockage can be observed than for AST.
Using the ArcGIS software suite and as depicted
in Fig. 2, the two point sets of termite sightings were
first projected from geographic to UTM coordinates.
Next, the study region was tessellated (i.e., divided
into non-overlapping squares), where squares con
taining a dockage location, assessed through a back
ground image on the screen, were marked as having
a dock. Then a random point pattern in urban areas
was generated. Urban areas as defined by the U.S.
Census Bureau were utilized. Urban areas can be
split into two categories, which are Urbanized Area
(UA) and Urban Cluster (UC) (U.S. Census Bureau
2002). Only those UA and UC polygons for which at
least one termite collection was recorded, serve as
the reference area for the generation of a spatially
random point pattern. Finally, for each point in both
termite point sets and the random point set the clos
est dock location (i.e., the nearest center of a square
dock polygon) was identified and the straight line
distance determined. These last 2 steps were ac
complished through the Spatial Join function in the
GIS.
Case Study 2: Spread Model
The second case study combines GIS functional
ity with a computer simulation (Fig. 3) that uses an
individual based model to predict the dispersal ofN.
corniger. A sample of 189 termite sightings between
Jan and Apr 2003 in Dania Beach, FL (Tonini 2013)
was used as the starting point for the simulation
which was run for 10 yr between 2003 and 2012.
The simulation algorithm is realized through a set
of R functions that implement an individual based
model (IBM) for natural termite dispersal. The
model considers a variety of biological parameters,
such as overall survival rates of alates, mean dis
persal flight distance, age of colony maturity, and
maximum density of colonies per hectare. Before
the simulation, ArcGIS was used to determine ar
eas suitable for the establishment of a new colony.
A Union overlay operation (Fig. 3A) was applied to
polygon coverages showing hydrographic features,
buffered roads, airport runways, and agricultural
fields, which gave an unsuitable area coverage. By
means of the Erase operation (Fig. 3B), this cover
age was converted to a suitable area coverage, which
was utilized in the simulation (Fig. 3C). While over
lay functions in ArcGIS provided the suitable area
polygon layer, a set of R packages (libraries), includ
ing 'sp', 'spatstat', 'rgdal', and 'raster', was used in
order to carry out further basic geoprocessing op
erations in preparation for the simulation. These in
cluded point-in-polygon overlays (to make sure that
termite colonies do not fall within unsuitable habi
tat), the creation of a reference simulation grid over
the study area (to control the maximum density of
termite colonies), point-to-raster conversions (to
represent the approximate area covered by one or
more colonies based on the aforementioned simula
tion grid), and raster overlays (to count the number
of times a given pixel was occupied after 100 Monte
Carlo simulations).
To assess the sensitivity of the model with re
spect to model parameters, the simulation was
run with one or two alternative values for each
parameter, giving a total of 12 alternative model
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7. Hochmair et al.: Geographie Information Systems for Analyzing Termite Invasions 751
A
Projection,
11=1* % Si | coordinates | | coordinates mapping
gestroi ,
<
, ,
1
,
OBJECTID* county longitude latitude POINT X POINT_Y
157 PalmBeach -80.0658 26 77755 592870.9723 2962138.3724
► 158 PalmBeach -80.06255 26.78207 593190.3884 2962641.4063
159 PalmBeach -80.05439 26.78069 594002.7415 2962494 5582
160 PalmBeach -80.05748 26.7732 593701.6981 2961662.6499
161 PalmBeach -80.05327 26.77347 594120.0402 2961695.6652
B
^ B random 1000
O AST
• FST
Dock identified
Digitizing,
random points
Spatial join
Fig. 2. GIS operations involved in distance analysis of termite collection sites and random points to nearest
dockage: A) Point coordinate conversion from geographic to UTM coordinates; B) Digitize dock locations and gener
ate random point pattern in urban areas; C) Determine distance to nearest dockage through Spatial Join function,
as illustrated for selected termite and random points.
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8. 752 Florida Entomologist 96(3) September 2013
Hydrography
10m Road Buffer
"" 4r
Union
AirportRunways
Unsuitable Area
Agricultural Fields
I
i
'
5
Erase
Area Extent Unsuitable Area Suitable Area
Suitable Area
> wmmmmmmKwmKWBKSiMmmmmmmmmmumam
2003 Collection Sites
•": "=e7
2012 Prediction
Data Input Simulation Model Result
Fig. 3. Spatial analysis functions supporting termite spread model: A) Union overlay to determine unsuitable
area; B) Erase operation to identify suitable area; C) Suitable area coverage together with 2003 termite collection
sites used as input for spread model in R, with mapped model result to the right.
realizations in addition to the baseline simula
tion. The uncertainty associated with the outcome
of a stochastic simulation was estimated through
the Monte Carlo technique and 100 simulation
runs. The GIS mapped the simulation result of
the baseline model for 2012 on a background im
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9. Hochmair et al.: Geographie Information Systems for Analyzing Termite Invasions 753
age provided through a Web service (Fig. 3C),
illustrating the spread of termite colonies from
original points of infestation. Yellow, orange, and
red cells indicate the >0%, >=50%, and 100% oc
cupancy envelopes, respectively. The 100% occu
pancy envelope groups areas that are predicted as
infested by all runs.
Statistical Analysis
Case study 1 resulted in three sets of distanc
es which are Euclidean (straight line) distances
to the nearest dockage for FST, AST, and the
random points, respectively. A one-sample Kol
mogorov Smirnov test indicated that distances in
each set were not normally distributed. Therefore
the non-parametric Mann-Whitney U test was
used to compare median distances between the
three distance sets.
Data analysis in case study 2 had two goals.
The first goal was to validate the model fitness
by comparing the predicted infested area for 2012
with actually observed infestation data occurring
up to 2012. The predicted area was visualized
through visualization of >0%, >=50%, and 100%
occupancy envelopes resulting from a Monte
Carlo simulation. This was visually compared to
74 new infestation sightings in 2012, all ofwhich
were found in previously Insecticide-untreated
areas. The second goal was to conduct a sensitiv
ity analysis for 12 alternative model realizations
in addition to the baseline simulation to assess
the effect of model parameters on predicted in
fested area. The sensitivity analysis comprises
relative and absolute growth rates in infested
area compared to the base line model for a given
year between 2004 and 2012, and also a compari
son of total predicted infested area for the differ
ent years.
Results
Case Study 1: Infestation Analysis
Table 1 provides the descriptive statistics for
distances associated with the 3 point patterns.
Mann-Whitney U tests showed that the median
distances to nearest docks associated with AST
and FST, respectively, were significantly smaller
than for the random point set (p < 0.0001, 2-tailed
forAST and FST), indicating that AST and FST
are significantly closer to potential infested boat
locations, i.e., marine docks, than random points
in considered urban areas. A Mann-Whitney U
test further showed that observed median dis
tances to nearest docks were significantly smaller
forAST than forFST (p < 0.0001, 2-tailed). Since
FST was discovered in Florida about two decades
before AST, larger median distances for FST than
for AST can be expected if assuming that these
two invasive termite species were first establish
ing near boat dockage, and with later generations,
colonizing areas further away. In summary, sta
tistical comparison of median distances provides
strong evidence that the two exotic termite spe
cies were introduced and spread by boat in South
Florida. A more detailed discussion of analysis
results can be found in (Hochmair & Scheffrahn
2010).
Case Study 2: Spread Model
To validate the simulation model, the locations
of newly infested sites from 2012 were compared
to the occupancy envelopes which are based on
2003 sample sites as initial infestation points.
Fig. 4A shows the infested areas predicted by
the baseline simulation model with in all three
occupancy envelopes (Tonini 2013). The 100%
occupancy envelope overlaps well with the 2012
sighted collection points, while the > 0% and >=
50% envelopes overestimate termite spread.
Sensitivity analysis (Fig. 4B) found that the
prediction model was most sensitive to the fol
lowing parameters: Number of alates generated
by a colony over the colony's lifetime, survival
rate of alates, maximum mating pheromone at
traction distance, and mean dispersal flight dis
tance. Only small effects were observed for the
following parameters: prevalence of male alates
in the colony, age of first production of alates,
density of colonies/ha. While the solid line in Fig.
4B indicates the predicted infested area when
using a parameter baseline value of 200 m for
mean flight distance of alates, the dashed lines
show the effect on the predicted infested area
when changing this parameter to 100 m and 300
m (Tonini 2013). The results of this stochastic
individual-based simulation model provide a
means for regulatory agencies to anticipate pos
sible areas of infestation. It must be noted that
Table l. Distance of land-based infestations of Coptotermes gestroi and Coptotermes formosanus to
NEAREST MARINE DOCKS (IN METERS).
AST (C. gestroi) FST (C. formosanus) Random
Mean 709 2719 7914
Standard deviation 849 3882 6173
Median 405 1382 6796
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11. Hochmair et al.: Geographie Information Systems for Analyzing Termite Invasions 755
dispersal of the West Indian drywood termite. Biol.
Invasions 11: 787-799.
Slocum, T. A., McMaster, R. B., Kessler, F. C., and
HOWARD, H. H. 2005. Thematic Cartography and
Geographic Visualization, Prentice Hall, Upper Sad
dle River, NJ.
Su, N.-Y., AND SCHEFFRAHN, R. H. 1998. A review of
subterranean termite control practices and pros
pects for integrated pest management programmes.
Integ. Pest Mgt. Rev. 3: 1-13.
Tonini, F., Hochmair, H. H., Scheffrahn, R. H., and
Deangelis, D. L. 2013. Simulating the spread of an
invasive termite in an urban environment using a
stocastic individual-based model. Environ. Entornó
lo. 42: 412-423.
U.S. CENSUS bureau (2002). Federal Register Notices
for Census 2000 Urban Area Criteria. Retrieved
07/26/2013 from http://www.census.gov/geo/refer
ence/pdfs/fedreg/ua_2k.pdf
ZANDBERGEN, P. A. 2013. Python Scripting for ArcGIS,
ESRI Press, Redlands, CA.
Zaragozí, B., Belda, A., Linares, J., Martínez-Pérez,
J. E., Navarro, J. T., and Esparza, J. 2012. A free
and open source programming library for landscape
metrics calculations. Environ. Modelling & Software
31: 131-140.
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