geoinformation systems is not an easy task. The following sections will discuss
approaches to identify and manage land parcel information in agro-geoinformation
system for different scales.
9.3 Managing Land Parcel Information
in Agro-Geoinformation Systems for Local
Governments, Agencies, and Companies
Unlike land parcel data collection, which is a labor- and time-intensive process, the
challenges of land parcel management come from its data volume and complexity.
Land parcel generated tremendous amount of digital data including footprint and
other attached attributes. As a result, many land parcel information is organized at
local governments, agencies, and companies (National Research Council 2007).
Many land parcel information was transferred from physical storage to digital
archive with the development of desktop computer and GIS software. Most land
parcel information are stored in vector data model, which is a superior data model,
than raster to represent features with discrete boundaries. However, vector data may
consume more storage space than other data model due to its complicated feature and
precise boundary representation, especially for desktop computers.
There are few techniques widely used for managing land parcel information in
agro-geoinformation systems. The size of parcel dataset could be reduced by simplifying polygon boundaries. For example, ESRI provides tools to allow user to
smooth polygons by reducing/repositioning edge points (ESRI 2014). Firstly, the
method, which reduces land parcel data size and increases performance by losing the
detail of land parcel footprints, lowers spatial accuracy of land parcel too. Secondly,
land parcels could be divided into two groups: agricultural and nonagricultural.
Information about nonagricultural land parcels could be discarded in agrogeoinformation systems and only keep agricultural land parcels to save space and
processing power. For example, a mask layer could be produced to define an area
with agricultural activities (Boryan and Yang 2012). To add an agricultural mask
layer is a simple but efficient way to reduce land parcel data size in agrogeoinformation data management.
In addition to reducing the size of land parcel dataset, land parcel for agriculture
could be tagged in land administration systems; thus these tagged land parcels could
be linked with agro-geoinformation systems. The first approach requires the integration of land parcel dataset and agro-geoinformation systems. However, it is hard
to integrate two datasets since land parcel information is dynamically changing. The
second approach was introduced to minimize the effort from data modification by
using standardized structure (Inan et al. 2010). This approach is more flexible during
the collaboration between multiple agencies such as the states within the European
Union. However, it requires a large effort from local agencies that are collecting and
building land parcel systems. Local government, agencies, and companies may not
9 Land Parcel Identification
167
approaches to identify and manage land parcel information in agro-geoinformation
system for different scales.
9.3 Managing Land Parcel Information
in Agro-Geoinformation Systems for Local
Governments, Agencies, and Companies
Unlike land parcel data collection, which is a labor- and time-intensive process, the
challenges of land parcel management come from its data volume and complexity.
Land parcel generated tremendous amount of digital data including footprint and
other attached attributes. As a result, many land parcel information is organized at
local governments, agencies, and companies (National Research Council 2007).
Many land parcel information was transferred from physical storage to digital
archive with the development of desktop computer and GIS software. Most land
parcel information are stored in vector data model, which is a superior data model,
than raster to represent features with discrete boundaries. However, vector data may
consume more storage space than other data model due to its complicated feature and
precise boundary representation, especially for desktop computers.
There are few techniques widely used for managing land parcel information in
agro-geoinformation systems. The size of parcel dataset could be reduced by simplifying polygon boundaries. For example, ESRI provides tools to allow user to
smooth polygons by reducing/repositioning edge points (ESRI 2014). Firstly, the
method, which reduces land parcel data size and increases performance by losing the
detail of land parcel footprints, lowers spatial accuracy of land parcel too. Secondly,
land parcels could be divided into two groups: agricultural and nonagricultural.
Information about nonagricultural land parcels could be discarded in agrogeoinformation systems and only keep agricultural land parcels to save space and
processing power. For example, a mask layer could be produced to define an area
with agricultural activities (Boryan and Yang 2012). To add an agricultural mask
layer is a simple but efficient way to reduce land parcel data size in agrogeoinformation data management.
In addition to reducing the size of land parcel dataset, land parcel for agriculture
could be tagged in land administration systems; thus these tagged land parcels could
be linked with agro-geoinformation systems. The first approach requires the integration of land parcel dataset and agro-geoinformation systems. However, it is hard
to integrate two datasets since land parcel information is dynamically changing. The
second approach was introduced to minimize the effort from data modification by
using standardized structure (Inan et al. 2010). This approach is more flexible during
the collaboration between multiple agencies such as the states within the European
Union. However, it requires a large effort from local agencies that are collecting and
building land parcel systems. Local government, agencies, and companies may not
9 Land Parcel Identification
167