be motivated to do the enhancement since they may not see the benefit (Library of
Congress 2011).
As desktop computer became one of the most common and cost-efficient ways to
process and store data, many local governments, agencies, and companies used it to
store and analyze land parcel data for agricultural studies. Multiple approaches were
used in managing land parcel information in agro-geoinformation applications
including simplifying data complexities, discarding land parcels which are unrelated
with agriculture, and linking land parcel dataset with agro-geoinformation systems
by tagging agricultural land parcels. The methods discussed above are widely used
in desktop applications. However, they do have limitations, which are commonly
existing in desktop computers, such as the balance of reduction in spatial and
temporal accuracy. The following chapters will be discussing ways to facilitate
these problems for the larger regions.
9.4 Managing Land Parcel Information
in Agro-Geoinformation Systems at State and National
Levels
Spatial information plays important roles when conducting research. For a long time,
scientists found that location is the key to some aggregated phenomena. Regional
geographers conduct research by finding similar patterns within a region of study
(Hartshorne 1939). However, one single county is too small for scientists to find
meaningful patterns. Scientists, especially agricultural experts, work on regional
scales: one state or several states. It requires the aggregation of local land parcel
information which is not easy for few reasons: (1) inconsistent data collection leads
to result incomparable; (2) nonstandardized data storage brings difficulty in the
collaboration between land parcel datasets.
Land parcel data is collected by various agencies including private companies,
and the methods of data collection were not standardized among different counties.
For example, surveys on farmers could be used to evaluate agricultural condition for
land parcels, but the result may lead to uncertainties if the survey was conducted
independently across counties. Moreover, counties may have various methods to
collect land parcel data. Many land parcel data were collected at various
nonstandardized methods due to the nature of using desktop computer and the lack
of the requirement of collaboration between other counties or states. All these
inconsistent land parcel identification approaches bring difficulties in managing
land parcel data in agro-geoinformation systems.
Land parcel identification in EU was one of many successful cases. The Common
Agricultural Policy (CAP) from the EU needed aggregated land parcel data for
distributing aids to farmers. Scientists developed a standardized land parcel identification system to collect and manage land parcel. It is a standardized system which
manages land parcel information and is widely used in the European Union (EU) to
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L. Lin and C. Zhang
Congress 2011).
As desktop computer became one of the most common and cost-efficient ways to
process and store data, many local governments, agencies, and companies used it to
store and analyze land parcel data for agricultural studies. Multiple approaches were
used in managing land parcel information in agro-geoinformation applications
including simplifying data complexities, discarding land parcels which are unrelated
with agriculture, and linking land parcel dataset with agro-geoinformation systems
by tagging agricultural land parcels. The methods discussed above are widely used
in desktop applications. However, they do have limitations, which are commonly
existing in desktop computers, such as the balance of reduction in spatial and
temporal accuracy. The following chapters will be discussing ways to facilitate
these problems for the larger regions.
9.4 Managing Land Parcel Information
in Agro-Geoinformation Systems at State and National
Levels
Spatial information plays important roles when conducting research. For a long time,
scientists found that location is the key to some aggregated phenomena. Regional
geographers conduct research by finding similar patterns within a region of study
(Hartshorne 1939). However, one single county is too small for scientists to find
meaningful patterns. Scientists, especially agricultural experts, work on regional
scales: one state or several states. It requires the aggregation of local land parcel
information which is not easy for few reasons: (1) inconsistent data collection leads
to result incomparable; (2) nonstandardized data storage brings difficulty in the
collaboration between land parcel datasets.
Land parcel data is collected by various agencies including private companies,
and the methods of data collection were not standardized among different counties.
For example, surveys on farmers could be used to evaluate agricultural condition for
land parcels, but the result may lead to uncertainties if the survey was conducted
independently across counties. Moreover, counties may have various methods to
collect land parcel data. Many land parcel data were collected at various
nonstandardized methods due to the nature of using desktop computer and the lack
of the requirement of collaboration between other counties or states. All these
inconsistent land parcel identification approaches bring difficulties in managing
land parcel data in agro-geoinformation systems.
Land parcel identification in EU was one of many successful cases. The Common
Agricultural Policy (CAP) from the EU needed aggregated land parcel data for
distributing aids to farmers. Scientists developed a standardized land parcel identification system to collect and manage land parcel. It is a standardized system which
manages land parcel information and is widely used in the European Union (EU) to
168
L. Lin and C. Zhang