support, food and security analysis, and policymaking and implementing (Pierce and
Clay 2007). It is vital to advance our knowledge in these fields through the continued
development of new GIS and related technologies to build sustainable agricultural
production systems (Wilson 1999).
GIS provide advanced technologies at multiple scales ranging from field level to
globe level due to its numerous advantages such as generating updated information
efficiently (Boryan et al. 2011), providing timely input data for crop yield and
pollution models (Luzio et al. 2004), preparing tables and maps for specific agricultural practices (Chau et al. 2013), and developing decision support system for
disseminating geospatial cropland data (Han et al. 2012). Finding a way to synthesize out data, knowledge, and technologies in agricultural application is important
for the continued development of new GIS functions and related tools to build a
more sustainable agricultural production system. The availability of big data has
provided unprecedented opportunities for advancing new knowledge in predictive
decision and data-supported innovation in agriculture. In October 2016, the US
National Institute of Food and Agriculture (NIFA) embarked on the Food and
Agriculture Cyberinformatics and Tools (FACT) initiative to identify the frontiers
and future of data in agriculture on the existing US government-wide effects and
investments in big data. To achieve this, NIFA envisions a future for agriculture that
is connected, data-driven, personalized, and sustainable. This provides new opportunities and challenges for the GIS and agricultural communities.
3.2 GIS: The Geospatial Approach
GIS is a system designed to capture, store, manipulate, analyze, manage, and present
spatial or geographic data (Longley et al. 2005). It integrates hardware, software, and
data for displaying, analyzing, and managing all forms of geospatial information
(Parthasarathy 2010). Spatial data are commonly stored in layers that might depict
environment or topography elements. Nowadays, GIS is an essential tool for combining multiple spatial data such as satellite and map information sources in spatial
models to simulate the interactions of complex natural and human systems. There
has been some debate about the definition of GIS, either as a narrow technological
term (Devine and Field 1986) or a wider perspective (Carter 1989). Dickinson and
Calkins (1988) define GIS from the three key components: GIS technology including hardware and software; GIS database to store geographical and related data; and
GIS infrastructure as staff, facilities, and supporting elements. All of these early
definitions have expressed a common feature that GIS are systems that deal with
geographical information and data (Maguire 1991).
The relationship between GIS and other information systems, including
computer-aided design, cartography, database management, and remote sensing
system, is important in comprehensively understanding GIS (Fig. 3.1). Newell and
Theriault (1990) suggested that GIS as a subset or superset of these systems and
defined “any system that capable of putting a map on the screen as GIS.” Although
26
J. Tang
Clay 2007). It is vital to advance our knowledge in these fields through the continued
development of new GIS and related technologies to build sustainable agricultural
production systems (Wilson 1999).
GIS provide advanced technologies at multiple scales ranging from field level to
globe level due to its numerous advantages such as generating updated information
efficiently (Boryan et al. 2011), providing timely input data for crop yield and
pollution models (Luzio et al. 2004), preparing tables and maps for specific agricultural practices (Chau et al. 2013), and developing decision support system for
disseminating geospatial cropland data (Han et al. 2012). Finding a way to synthesize out data, knowledge, and technologies in agricultural application is important
for the continued development of new GIS functions and related tools to build a
more sustainable agricultural production system. The availability of big data has
provided unprecedented opportunities for advancing new knowledge in predictive
decision and data-supported innovation in agriculture. In October 2016, the US
National Institute of Food and Agriculture (NIFA) embarked on the Food and
Agriculture Cyberinformatics and Tools (FACT) initiative to identify the frontiers
and future of data in agriculture on the existing US government-wide effects and
investments in big data. To achieve this, NIFA envisions a future for agriculture that
is connected, data-driven, personalized, and sustainable. This provides new opportunities and challenges for the GIS and agricultural communities.
3.2 GIS: The Geospatial Approach
GIS is a system designed to capture, store, manipulate, analyze, manage, and present
spatial or geographic data (Longley et al. 2005). It integrates hardware, software, and
data for displaying, analyzing, and managing all forms of geospatial information
(Parthasarathy 2010). Spatial data are commonly stored in layers that might depict
environment or topography elements. Nowadays, GIS is an essential tool for combining multiple spatial data such as satellite and map information sources in spatial
models to simulate the interactions of complex natural and human systems. There
has been some debate about the definition of GIS, either as a narrow technological
term (Devine and Field 1986) or a wider perspective (Carter 1989). Dickinson and
Calkins (1988) define GIS from the three key components: GIS technology including hardware and software; GIS database to store geographical and related data; and
GIS infrastructure as staff, facilities, and supporting elements. All of these early
definitions have expressed a common feature that GIS are systems that deal with
geographical information and data (Maguire 1991).
The relationship between GIS and other information systems, including
computer-aided design, cartography, database management, and remote sensing
system, is important in comprehensively understanding GIS (Fig. 3.1). Newell and
Theriault (1990) suggested that GIS as a subset or superset of these systems and
defined “any system that capable of putting a map on the screen as GIS.” Although
26
J. Tang