18.1 Introduction
With the rapid development of sensor and data technologies, the volume of Earth
Observation (EO) data collection has been expanded exponentially. Meanwhile, the
EO data need to be managed and analyzed by human society or information systems
have increased from terabyte level to exabyte level; these data are tremendously
diverse in terms of format, sensor, heterogeneity, quality, etc. In the agricultural
field, plenty of agricultural data also have been captured and preserved by agricultural government agencies, organizations, industries, and individuals, which require
further processing and mining.
Agricultural information such as crop condition is extremely significant to
knowledgeable decision and policy making for agricultural product markets, food
price, food security, and economic prosperity. Agriculture disaster monitoring such
as flood, drought, and plague has a crucial influence on global agricultural sustainable development and farming industry. In order to maximize the utilization of the
agro-geoinformation, geospatial data and service technologies could play the most
important role for agricultural data planning, collection, curation, transformation,
analysis, dissemination, cataloging, discovery, access, mining, visualization, quality
control, privacy, provenance, and long-term preservation.
Geospatial Web services enable users to leverage distributed geospatial data and
computing resources from the third-party geospatial applications through the network and to automate geospatial data integration and analysis (Zhao 2010). Compared with the portal manner, geospatial Web service is a more efficient and flexible
manner to make multi-machine interactions possible. Standard-based geospatial
Web services technologies (e.g., OGC Web service) have been widely adopted in
accessing, managing, and analyzing data and information for agriculture and environmental monitoring (Yue et al. 2010; Han et al. 2012; Hu et al. 2015; Di et al.
2016). However, the effectiveness and efficiency issues of the agricultural data
discovery, access, and processing still exist; therefore, it cannot meet the increasing
needs of the concerned agencies. For example, the huge volume, large spatial
coverage, and high temporal resolution cropland raster data still present a big
challenge to achieve the near-real-time (NRT) on-demand analysis, visualization,
and dissemination (Han et al. 2014a).
This chapter discusses how to design and implement standard-based geospatial
Web services for the discovery, access, and management of agricultural data interactively at a diverse geographic level. The agricultural data categories and life cycle
are discussed. Emphatically, the architecture of geospatial service, implementation
of service functionalities, and standardization are demonstrated. The solution of the
agricultural data retrieval efficiency is proposed.
386
L. Hu et al.
With the rapid development of sensor and data technologies, the volume of Earth
Observation (EO) data collection has been expanded exponentially. Meanwhile, the
EO data need to be managed and analyzed by human society or information systems
have increased from terabyte level to exabyte level; these data are tremendously
diverse in terms of format, sensor, heterogeneity, quality, etc. In the agricultural
field, plenty of agricultural data also have been captured and preserved by agricultural government agencies, organizations, industries, and individuals, which require
further processing and mining.
Agricultural information such as crop condition is extremely significant to
knowledgeable decision and policy making for agricultural product markets, food
price, food security, and economic prosperity. Agriculture disaster monitoring such
as flood, drought, and plague has a crucial influence on global agricultural sustainable development and farming industry. In order to maximize the utilization of the
agro-geoinformation, geospatial data and service technologies could play the most
important role for agricultural data planning, collection, curation, transformation,
analysis, dissemination, cataloging, discovery, access, mining, visualization, quality
control, privacy, provenance, and long-term preservation.
Geospatial Web services enable users to leverage distributed geospatial data and
computing resources from the third-party geospatial applications through the network and to automate geospatial data integration and analysis (Zhao 2010). Compared with the portal manner, geospatial Web service is a more efficient and flexible
manner to make multi-machine interactions possible. Standard-based geospatial
Web services technologies (e.g., OGC Web service) have been widely adopted in
accessing, managing, and analyzing data and information for agriculture and environmental monitoring (Yue et al. 2010; Han et al. 2012; Hu et al. 2015; Di et al.
2016). However, the effectiveness and efficiency issues of the agricultural data
discovery, access, and processing still exist; therefore, it cannot meet the increasing
needs of the concerned agencies. For example, the huge volume, large spatial
coverage, and high temporal resolution cropland raster data still present a big
challenge to achieve the near-real-time (NRT) on-demand analysis, visualization,
and dissemination (Han et al. 2014a).
This chapter discusses how to design and implement standard-based geospatial
Web services for the discovery, access, and management of agricultural data interactively at a diverse geographic level. The agricultural data categories and life cycle
are discussed. Emphatically, the architecture of geospatial service, implementation
of service functionalities, and standardization are demonstrated. The solution of the
agricultural data retrieval efficiency is proposed.
386
L. Hu et al.