Pub Date : 2019-01-01DOI: 10.4018/978-1-4666-9435-4.CH011
Lei Tong, Jun Zhou, S. Bai, Chengyuan Xu, Y. Qian, Yongsheng Gao, Zhihong Xu
Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil.
{"title":"Automatic Estimation of Soil Biochar Quantity via Hyperspectral Imaging","authors":"Lei Tong, Jun Zhou, S. Bai, Chengyuan Xu, Y. Qian, Yongsheng Gao, Zhihong Xu","doi":"10.4018/978-1-4666-9435-4.CH011","DOIUrl":"https://doi.org/10.4018/978-1-4666-9435-4.CH011","url":null,"abstract":"Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"30 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72959231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-2719-0.CH008
Jean-fiston Mikwa Ngamba, Ewango Corneille Ekokinya, C. N. Luwesi, Yves-Dady Botula Kahindo, Muhogwa Jean Marie, H. Seya
This study assessed the impact of human activities on deforestation and sustainability of water resources and livelihoods in the Congo Basin. It mainly aimed to assess forest degradation in the Yoko reserve from 1976 to 2015 and investigate the compatibility of Landsat imagery for forest monitoring. Digital Image processing for unsupervised classification was done using ENVI software while supervised classification was done by means of ArcGIS 10. Results show that forest landscape faced large scale human induced fragmentation over the last 40 years. If these trends continue, they will affect the sustainability of water resources and livelihoods in the Congo Basin of the Democratic Republic of Congo. Hence, policy makers need to look at key drivers and address impacts that may threaten the future of Hydrological Ecosystems Services, including water and land resources in the Congo Basin. Authorities have to apply an Integrated Management of Water, Land and Ecosystems.
{"title":"Multi-Temporal Landsat Remote Sensing for Forest Landscape Fragmentation Analysis in the Yoko Forest, Kisangani, DRC","authors":"Jean-fiston Mikwa Ngamba, Ewango Corneille Ekokinya, C. N. Luwesi, Yves-Dady Botula Kahindo, Muhogwa Jean Marie, H. Seya","doi":"10.4018/978-1-5225-2719-0.CH008","DOIUrl":"https://doi.org/10.4018/978-1-5225-2719-0.CH008","url":null,"abstract":"This study assessed the impact of human activities on deforestation and sustainability of water resources and livelihoods in the Congo Basin. It mainly aimed to assess forest degradation in the Yoko reserve from 1976 to 2015 and investigate the compatibility of Landsat imagery for forest monitoring. Digital Image processing for unsupervised classification was done using ENVI software while supervised classification was done by means of ArcGIS 10. Results show that forest landscape faced large scale human induced fragmentation over the last 40 years. If these trends continue, they will affect the sustainability of water resources and livelihoods in the Congo Basin of the Democratic Republic of Congo. Hence, policy makers need to look at key drivers and address impacts that may threaten the future of Hydrological Ecosystems Services, including water and land resources in the Congo Basin. Authorities have to apply an Integrated Management of Water, Land and Ecosystems.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"104 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80771090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-1715-3.CH012
Upasana Dutta
The agriculture sector is reeling under the pressures of population, land and water scarcity, diseases, disasters and the most challenging of them all, climate change. Although climate change is yet to be charged with affecting agriculture, but in recent years trends of change have been witnessed in various crop production, with a hint of climate's role in it. With the advent of technology, these trends have become easier to analyse and in certain cases predict too. Information Technology (ICT) tools like Geoinformatics are playing a profound role in the agriculture sector and is helping to understand and assess the various factors affecting the growth of crops along with finding out the alternative suitability parameters for better production and distribution. The main aim of this chapter on agro-geoinformatics is to look into this linkage between technology usage and better potato production during adverse conditions.
{"title":"Agro-Geoinformatics, Potato Cultivation, and Climate Change","authors":"Upasana Dutta","doi":"10.4018/978-1-5225-1715-3.CH012","DOIUrl":"https://doi.org/10.4018/978-1-5225-1715-3.CH012","url":null,"abstract":"The agriculture sector is reeling under the pressures of population, land and water scarcity, diseases, disasters and the most challenging of them all, climate change. Although climate change is yet to be charged with affecting agriculture, but in recent years trends of change have been witnessed in various crop production, with a hint of climate's role in it. With the advent of technology, these trends have become easier to analyse and in certain cases predict too. Information Technology (ICT) tools like Geoinformatics are playing a profound role in the agriculture sector and is helping to understand and assess the various factors affecting the growth of crops along with finding out the alternative suitability parameters for better production and distribution. The main aim of this chapter on agro-geoinformatics is to look into this linkage between technology usage and better potato production during adverse conditions.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"23 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90057306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch008
J. Dobson
Jerome E. Dobson, professor emeritus, University of Kansas; president of the American Geographical Society; and recipient of the 2014 James R. Anderson Medal of Honor in Applied Geography, discusses his career in the context of America's academic purge of geography. Highlights include his time as a Jefferson Science Fellow with the National Academies and U. S. Department of State. Dobson has been recognized with two lifetime achievement awards for his pioneering work in geographic information systems (GIS) and as Alumnus of 2013 at Reinhardt University. His contributions include the paradigm of automated geography, his instrumental role in originating the National Center for Geographic Information and Analysis, and his leadership of the LandScan Global Population Database, the de facto world standard for estimating populations at risk. His recent research includes testing a new system for mapping minefields; designing and promulgating the current world standard for cartographic representation of landmines, minefields, and mine actions; and leading six AGS Bowman Expeditions.
Jerome E. Dobson，堪萨斯大学名誉教授;美国地理学会会长;2014年詹姆斯·r·安德森应用地理荣誉勋章获得者，在美国地理学术清洗的背景下讨论了他的职业生涯。他的亮点包括他在国家科学院和美国国务院担任杰斐逊科学研究员的时间。Dobson因其在地理信息系统(GIS)方面的开创性工作和2013年莱因哈特大学(Reinhardt University)的校友身份，获得了两项终身成就奖。他的贡献包括自动化地理的范例，他在创建国家地理信息和分析中心方面发挥了重要作用，以及他领导的LandScan全球人口数据库，这是估计风险人口的事实上的世界标准。他最近的研究包括测试一个测绘雷区的新系统;设计和颁布目前的地雷、雷区和排雷行动地图表示世界标准;并领导了六次AGS鲍曼探险。
{"title":"Geography's Second Twilight","authors":"J. Dobson","doi":"10.4018/978-1-5225-7033-2.ch008","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch008","url":null,"abstract":"Jerome E. Dobson, professor emeritus, University of Kansas; president of the American Geographical Society; and recipient of the 2014 James R. Anderson Medal of Honor in Applied Geography, discusses his career in the context of America's academic purge of geography. Highlights include his time as a Jefferson Science Fellow with the National Academies and U. S. Department of State. Dobson has been recognized with two lifetime achievement awards for his pioneering work in geographic information systems (GIS) and as Alumnus of 2013 at Reinhardt University. His contributions include the paradigm of automated geography, his instrumental role in originating the National Center for Geographic Information and Analysis, and his leadership of the LandScan Global Population Database, the de facto world standard for estimating populations at risk. His recent research includes testing a new system for mapping minefields; designing and promulgating the current world standard for cartographic representation of landmines, minefields, and mine actions; and leading six AGS Bowman Expeditions.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"35 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85076029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch032
M. R. Boussema
In this chapter, the author presents a review of the GIS use during the research carried out during the past three decades dealing with land degradation. The objective is to assess the viability of applying GIS with different modes of remotely sensed data acquisition for quantifying land degradation in Tunisia. Various GIS based modelling approaches for soil erosion hazard assessment such as empirical and physical distributed are discussed. Five case studies are selected from several projects. They apply different methods for land degradation investigation at different scales using GIS and remotely sensed data. The research dealt mainly with: 1) The prediction of soil erosion at the regional level related to conservation techniques; 2) The quantification of soil erosion at the gully level based on GIS, digital photogrammetry and fieldwork; 3) The monitoring of gully erosion using GIS combined to images acquired by a non-metric digital camera on board a kite.
{"title":"GIS Use for Mapping Land Degradation","authors":"M. R. Boussema","doi":"10.4018/978-1-5225-7033-2.ch032","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch032","url":null,"abstract":"In this chapter, the author presents a review of the GIS use during the research carried out during the past three decades dealing with land degradation. The objective is to assess the viability of applying GIS with different modes of remotely sensed data acquisition for quantifying land degradation in Tunisia. Various GIS based modelling approaches for soil erosion hazard assessment such as empirical and physical distributed are discussed. Five case studies are selected from several projects. They apply different methods for land degradation investigation at different scales using GIS and remotely sensed data. The research dealt mainly with: 1) The prediction of soil erosion at the regional level related to conservation techniques; 2) The quantification of soil erosion at the gully level based on GIS, digital photogrammetry and fieldwork; 3) The monitoring of gully erosion using GIS combined to images acquired by a non-metric digital camera on board a kite.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"33 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76187583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-1814-3.CH010
M. T. Rahman
Immediately following a natural disaster, it is imperative to accurately assess the damages caused by the disaster for effective rescue and relief operations. Passive remote sensing imageries have been analyzed and used for over four decades for such assessments. However, they do have their limitations including inability to collect data during violent weather conditions, medium to low spatial resolution, and assessing areas and pixels on a damages/no damage basis. Recent advances in active remote sensing data collection methods can resolve some of these limitations. In this chapter, the basic theories and processing techniques of active remote sensing data is first discussed. It then provides some of the advantages and limitations of using active remote sensing data for disaster damage assessments. Finally, the chapter concludes by discussing how data from active sensors are used to assess damages from various types of natural disasters.
{"title":"Applications of Active Remote Sensing Technologies for Natural Disaster Damage Assessments","authors":"M. T. Rahman","doi":"10.4018/978-1-5225-1814-3.CH010","DOIUrl":"https://doi.org/10.4018/978-1-5225-1814-3.CH010","url":null,"abstract":"Immediately following a natural disaster, it is imperative to accurately assess the damages caused by the disaster for effective rescue and relief operations. Passive remote sensing imageries have been analyzed and used for over four decades for such assessments. However, they do have their limitations including inability to collect data during violent weather conditions, medium to low spatial resolution, and assessing areas and pixels on a damages/no damage basis. Recent advances in active remote sensing data collection methods can resolve some of these limitations. In this chapter, the basic theories and processing techniques of active remote sensing data is first discussed. It then provides some of the advantages and limitations of using active remote sensing data for disaster damage assessments. Finally, the chapter concludes by discussing how data from active sensors are used to assess damages from various types of natural disasters.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"22 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83911149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch025
S. Nagarajan
The utilization of relative shading size of a picture to extricate the vegetation of a study range Vellore, Tamilnadu, India was proposed. This novel hereditary based calculation utilizes the pixel guide of every picture and tries to figure out the ranges using so as to fit the right determination for vegetation Biomass the hereditary based methodology. The simplicity of execution permits any further changes to the calculation in future. Capable picture handling component permitted improved control of picture A Google Programming interface was utilized to concentrate and yield picture. It permitted simple augmentation of the work to any demographic range. The proposed calculation is superior to anything some present day devices as it is taking into account singular pixel values as opposed to layers. All the more vitally, no pre-meaning of the picture or layer is needed. Pixel control permits blending the effectively utilized procedures with other more up to date picture handling strategies that would prompt a more far reaching and multi-useful calculation. The advances utilized are between operable and can be kept as a steady stage for further up degree. The calculation does endure in computational speed and can be upgraded by utilizing better equipment offices. Parallel registering may be another choice to accelerate the handling of free pixels. Certain area methodologies can be utilized to upgrade honing of picture and better limits.
{"title":"Genetic-Based Estimation of Biomass Using Geographical Information System","authors":"S. Nagarajan","doi":"10.4018/978-1-5225-7033-2.ch025","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch025","url":null,"abstract":"The utilization of relative shading size of a picture to extricate the vegetation of a study range Vellore, Tamilnadu, India was proposed. This novel hereditary based calculation utilizes the pixel guide of every picture and tries to figure out the ranges using so as to fit the right determination for vegetation Biomass the hereditary based methodology. The simplicity of execution permits any further changes to the calculation in future. Capable picture handling component permitted improved control of picture A Google Programming interface was utilized to concentrate and yield picture. It permitted simple augmentation of the work to any demographic range. The proposed calculation is superior to anything some present day devices as it is taking into account singular pixel values as opposed to layers. All the more vitally, no pre-meaning of the picture or layer is needed. Pixel control permits blending the effectively utilized procedures with other more up to date picture handling strategies that would prompt a more far reaching and multi-useful calculation. The advances utilized are between operable and can be kept as a steady stage for further up degree. The calculation does endure in computational speed and can be upgraded by utilizing better equipment offices. Parallel registering may be another choice to accelerate the handling of free pixels. Certain area methodologies can be utilized to upgrade honing of picture and better limits.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"3 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88442137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-1683-5.CH005
P. Srivastava, S. Suman, S. Pandey
The monitoring of urban cover is very important for the planner, management, governmental and non-governmental organizations for optimizing the use of urban resources and minimizing the environmental losses. The study here aims at analyzing the changes that occurred in urban green cover over a time span of 1991-2001 using multi-date Landsat satellite images data over the Varanasi district, India and its relation to demographical changes. The Support Vector Machines (SVMs) classifier has been used for image classification. The urbanization indicators such as Land Consumption Ratio (LCR) and Land Absorption Coefficient (LAC) were also used in order to understand the changes in urban cover and population dynamics. All the analysis indicates significant changes in the urban cover values with increasing population at both spatial and temporal scale.
{"title":"Monitoring Changes in Urban Cover Using Landsat Satellite Images and Demographical Information","authors":"P. Srivastava, S. Suman, S. Pandey","doi":"10.4018/978-1-5225-1683-5.CH005","DOIUrl":"https://doi.org/10.4018/978-1-5225-1683-5.CH005","url":null,"abstract":"The monitoring of urban cover is very important for the planner, management, governmental and non-governmental organizations for optimizing the use of urban resources and minimizing the environmental losses. The study here aims at analyzing the changes that occurred in urban green cover over a time span of 1991-2001 using multi-date Landsat satellite images data over the Varanasi district, India and its relation to demographical changes. The Support Vector Machines (SVMs) classifier has been used for image classification. The urbanization indicators such as Land Consumption Ratio (LCR) and Land Absorption Coefficient (LAC) were also used in order to understand the changes in urban cover and population dynamics. All the analysis indicates significant changes in the urban cover values with increasing population at both spatial and temporal scale.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"13 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88804738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-1814-3.CH004
G. Gienko, M. Govorov
Researchers worldwide use remotely sensed imagery in their projects, in both the social and natural sciences. However, users often encounter difficulties working with satellite images and aerial photographs, as image interpretation requires specific experience and skills. The best way to acquire these skills is to go into the field, identify your location in an overhead image, observe the landscape, and find corresponding features in the overhead image. In many cases, personal observations could be substituted by using terrestrial photographs taken from the ground with conventional cameras. This chapter discusses the value of terrestrial photographs as a substitute for field observations, elaborates on issues of data collection, and presents results of experimental estimation of the effectiveness of the use of terrestrial ground truth photographs for interpretation of remotely sensed imagery. The chapter introduces the concept of GeoTruth – a web-based collaborative framework for collection, storing and distribution of ground truth terrestrial photographs and corresponding metadata.
{"title":"Improving the Efficiency of Image Interpretation Using Ground Truth Terrestrial Photographs","authors":"G. Gienko, M. Govorov","doi":"10.4018/978-1-5225-1814-3.CH004","DOIUrl":"https://doi.org/10.4018/978-1-5225-1814-3.CH004","url":null,"abstract":"Researchers worldwide use remotely sensed imagery in their projects, in both the social and natural sciences. However, users often encounter difficulties working with satellite images and aerial photographs, as image interpretation requires specific experience and skills. The best way to acquire these skills is to go into the field, identify your location in an overhead image, observe the landscape, and find corresponding features in the overhead image. In many cases, personal observations could be substituted by using terrestrial photographs taken from the ground with conventional cameras. This chapter discusses the value of terrestrial photographs as a substitute for field observations, elaborates on issues of data collection, and presents results of experimental estimation of the effectiveness of the use of terrestrial ground truth photographs for interpretation of remotely sensed imagery. The chapter introduces the concept of GeoTruth – a web-based collaborative framework for collection, storing and distribution of ground truth terrestrial photographs and corresponding metadata.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"40 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86543395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch077
Xihuang Sun, Peng Liu, Yan Ma, Dingsheng Liu, Yechao Sun
The explosion of data and the increase in processing complexity, together with the increasing needs of real-time processing and concurrent data access, make remote sensing data streaming processing a wide research area to study. This paper introduces current situation of remote sensing data processing and how timely remote sensing data processing can help build future smart cities. Current research on remote sensing data streaming is also introduced where the three typical and open-source stream processing frameworks are introduced. This paper also discusses some design concerns for remote sensing data streaming processing systems, such as data model and transmission, system model, programming interfaces, storage management, availability, etc. Finally, this research specifically addresses some of the challenges of remote sensing data streaming processing, such as scalability, fault tolerance, consistency, load balancing and throughput.
{"title":"Streaming Remote Sensing Data Processing for the Future Smart Cities","authors":"Xihuang Sun, Peng Liu, Yan Ma, Dingsheng Liu, Yechao Sun","doi":"10.4018/978-1-5225-7033-2.ch077","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch077","url":null,"abstract":"The explosion of data and the increase in processing complexity, together with the increasing needs of real-time processing and concurrent data access, make remote sensing data streaming processing a wide research area to study. This paper introduces current situation of remote sensing data processing and how timely remote sensing data processing can help build future smart cities. Current research on remote sensing data streaming is also introduced where the three typical and open-source stream processing frameworks are introduced. This paper also discusses some design concerns for remote sensing data streaming processing systems, such as data model and transmission, system model, programming interfaces, storage management, availability, etc. Finally, this research specifically addresses some of the challenges of remote sensing data streaming processing, such as scalability, fault tolerance, consistency, load balancing and throughput.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":"73 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89897567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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