Wetlands are important natural resources due to their numerous ecological services.Consequently,identifying their locations and extents is imperative.The stability,repeatability,cost-effectiveness,multi-scale coverage...Wetlands are important natural resources due to their numerous ecological services.Consequently,identifying their locations and extents is imperative.The stability,repeatability,cost-effectiveness,multi-scale coverage,and proper spatial resolution imagery of satellites provide a valuable opportunity for their use in various large-scale applications,such as provincial wetland mapping.To do so,it is required to(1)process and classify big geo data(i.e.a large amount of satellite datasets)in a time-and computationally-efficient approach and(2)collect a large amount of field samples.In this study,Google Earth Engine(GEE)and machine learning algorithms were utilized to process thousands of remote sensing images and produce provincial wetland inventory maps of the three Canadian provinces of Manitoba,Quebec,and Newfoundland and Labrador(NL).Additionally,using GEE,a generalized supervised classification method is proposed to produce a regional wetland map from a large area(e.g.,a province)when lacking field samples.In fact,using the field data from only Manitoba and assuming that all wetlands in Canada have similar characteristics,the wetland maps were generated for the other two provinces.The overall classification accuracies for Manitoba,Quebec,and NL were 84%,78%,and 82%,respectively,indicating the high potential of the proposed method for aiding provincial wetland inventory systems.展开更多
1 Key concepts underpinning geo-data science Geoinformatics and Geomathematics Computers have been used for data collection,management,analysis,and transmission in geoscience for about 70 years since the 1950s (Merria...1 Key concepts underpinning geo-data science Geoinformatics and Geomathematics Computers have been used for data collection,management,analysis,and transmission in geoscience for about 70 years since the 1950s (Merriam,2001;2004).The term geoinformatics is widely used to describe such activities.In real-world practices,researchers in both geography and geoscience are using the term geoinformatics.展开更多
Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can pro...Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can provide a new and flexible hardware design environment,but its applications in observation instruments of earth-quake precursor are rare. The present paper introduces in detail the realization of a networked geo-electrical meter by applying the low price,high reliability embedded PC104 industrial computer.展开更多
鉴于数据提供者与数据需求者之间的矛盾是促使W ebG IS产生、发展的直接动力,为此围绕着在W eb环境下如何以3维空间可视化方式来实现地理空间数据共享与互操作的问题,以X3D/XML数据流作为不同结构的地理空间数据之间联系的桥梁,建立了...鉴于数据提供者与数据需求者之间的矛盾是促使W ebG IS产生、发展的直接动力,为此围绕着在W eb环境下如何以3维空间可视化方式来实现地理空间数据共享与互操作的问题,以X3D/XML数据流作为不同结构的地理空间数据之间联系的桥梁,建立了一种新的组件式W ebG IS体系结构———Geo-SD SH IP(Geo-Spatial DataSharing and Hand ling Integrated P latform)。为了更好地阐述基于X3D/XML的组件式3维W ebG IS平台的有效性、可行性,首先对Geo-SD SH IP体系结构组成及其特点进行了深入的阐述,并给出了Geo-SD SH IP体系结构框架图;接着,详细介绍了基于X3D/XML的Geo-SD SH IP体系结构中各组件实现的关键技术,如W eb-3D虚拟地理场景的创建、用VC++.Net和ArcOb jects来构建X3D/XML数据转换组件和G IS空间分析组件,以及用VC++.Net结合OpenGL图形函数库来实现X3D/XML数据解析组件等;最后,举例说明了Geo-SD SH IP体系结构的数据转换服务请求/响应过程、数据需求服务请求/响应过程,并通过在国家自然基金项目和中国科学院知识创新工程重要方向性项目中的成功应用,证明了Geo-SD SH IP体系结构的有效性和可行性。展开更多
基金supported by the Canada Centre for Mapping and Earth Observation of Natural Resources Canada(NRCan).
文摘Wetlands are important natural resources due to their numerous ecological services.Consequently,identifying their locations and extents is imperative.The stability,repeatability,cost-effectiveness,multi-scale coverage,and proper spatial resolution imagery of satellites provide a valuable opportunity for their use in various large-scale applications,such as provincial wetland mapping.To do so,it is required to(1)process and classify big geo data(i.e.a large amount of satellite datasets)in a time-and computationally-efficient approach and(2)collect a large amount of field samples.In this study,Google Earth Engine(GEE)and machine learning algorithms were utilized to process thousands of remote sensing images and produce provincial wetland inventory maps of the three Canadian provinces of Manitoba,Quebec,and Newfoundland and Labrador(NL).Additionally,using GEE,a generalized supervised classification method is proposed to produce a regional wetland map from a large area(e.g.,a province)when lacking field samples.In fact,using the field data from only Manitoba and assuming that all wetlands in Canada have similar characteristics,the wetland maps were generated for the other two provinces.The overall classification accuracies for Manitoba,Quebec,and NL were 84%,78%,and 82%,respectively,indicating the high potential of the proposed method for aiding provincial wetland inventory systems.
基金supported by the National Science Foundation (Grant No.1815526).
文摘1 Key concepts underpinning geo-data science Geoinformatics and Geomathematics Computers have been used for data collection,management,analysis,and transmission in geoscience for about 70 years since the 1950s (Merriam,2001;2004).The term geoinformatics is widely used to describe such activities.In real-world practices,researchers in both geography and geoscience are using the term geoinformatics.
基金"The Study of ELF Receiver"from Ministry of Science and Technology (2001BA601B03-01-03).
文摘Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can provide a new and flexible hardware design environment,but its applications in observation instruments of earth-quake precursor are rare. The present paper introduces in detail the realization of a networked geo-electrical meter by applying the low price,high reliability embedded PC104 industrial computer.
文摘鉴于数据提供者与数据需求者之间的矛盾是促使W ebG IS产生、发展的直接动力,为此围绕着在W eb环境下如何以3维空间可视化方式来实现地理空间数据共享与互操作的问题,以X3D/XML数据流作为不同结构的地理空间数据之间联系的桥梁,建立了一种新的组件式W ebG IS体系结构———Geo-SD SH IP(Geo-Spatial DataSharing and Hand ling Integrated P latform)。为了更好地阐述基于X3D/XML的组件式3维W ebG IS平台的有效性、可行性,首先对Geo-SD SH IP体系结构组成及其特点进行了深入的阐述,并给出了Geo-SD SH IP体系结构框架图;接着,详细介绍了基于X3D/XML的Geo-SD SH IP体系结构中各组件实现的关键技术,如W eb-3D虚拟地理场景的创建、用VC++.Net和ArcOb jects来构建X3D/XML数据转换组件和G IS空间分析组件,以及用VC++.Net结合OpenGL图形函数库来实现X3D/XML数据解析组件等;最后,举例说明了Geo-SD SH IP体系结构的数据转换服务请求/响应过程、数据需求服务请求/响应过程,并通过在国家自然基金项目和中国科学院知识创新工程重要方向性项目中的成功应用,证明了Geo-SD SH IP体系结构的有效性和可行性。
