Chapter 9
Land Parcel Identification
Li Lin and Chen Zhang
Abstract Land parcel is the finest unit to describe the location, boundary, and
ownership in land management. Land survey is the most popular way to identify
land parcel in the history of land management. However, land parcel survey come
with huge financial cost while the accuracy of the survey is not acceptable for many
applications such as agricultural management. The development of Remote Sensing
and Geographic Information System (GIS) introduced a novel way of collecting,
storing, and analyzing agricultural land parcel information. This study discusses
agricultural land parcel identification and management approaches from local to
global level. In most countries, local authorities are responsible for the collection and
storage of land parcel information. For this reason, the aggregation of land parcel
information from various authorities’ datasets becomes critical in large-scale agricultural management activities. However, agencies and nations develop land parcel
databases differently, and these databases are often not interoperable. This study also
summarizes the state-of-art approaches to reduce friction in land parcel database
integration across the globe. The study concludes that international standards and
corporations between organizations are essential to the management of land parcel
information in agro-geoinformation systems.
Keywords Land parcel · Agricultural management · Agro-geoinformation systems ·
Remote sensing · GIS · Interoperability · Web-services
9.1 Introduction
Land plays one of the most significant roles in the history of human beings. It is the
fundamental of many other developments such as agricultural production and
urbanization (United Nations 1976). Within the science of location, land
L. Lin (*) · C. Zhang
George Mason University, Fairfax, VA, USA
e-mail: llin2@masonlive.gmu.edu; czhang11@masonlive.gmu.edu
© Springer Nature Switzerland AG 2021
L. Di, B. Üstündağ (eds.), Agro-geoinformatics, Springer Remote Sensing/
Photogrammetry, https://doi.org/10.1007/978-3-030-66387-2_9
163
Land Parcel Identification
Li Lin and Chen Zhang
Abstract Land parcel is the finest unit to describe the location, boundary, and
ownership in land management. Land survey is the most popular way to identify
land parcel in the history of land management. However, land parcel survey come
with huge financial cost while the accuracy of the survey is not acceptable for many
applications such as agricultural management. The development of Remote Sensing
and Geographic Information System (GIS) introduced a novel way of collecting,
storing, and analyzing agricultural land parcel information. This study discusses
agricultural land parcel identification and management approaches from local to
global level. In most countries, local authorities are responsible for the collection and
storage of land parcel information. For this reason, the aggregation of land parcel
information from various authorities’ datasets becomes critical in large-scale agricultural management activities. However, agencies and nations develop land parcel
databases differently, and these databases are often not interoperable. This study also
summarizes the state-of-art approaches to reduce friction in land parcel database
integration across the globe. The study concludes that international standards and
corporations between organizations are essential to the management of land parcel
information in agro-geoinformation systems.
Keywords Land parcel · Agricultural management · Agro-geoinformation systems ·
Remote sensing · GIS · Interoperability · Web-services
9.1 Introduction
Land plays one of the most significant roles in the history of human beings. It is the
fundamental of many other developments such as agricultural production and
urbanization (United Nations 1976). Within the science of location, land
L. Lin (*) · C. Zhang
George Mason University, Fairfax, VA, USA
e-mail: llin2@masonlive.gmu.edu; czhang11@masonlive.gmu.edu
© Springer Nature Switzerland AG 2021
L. Di, B. Üstündağ (eds.), Agro-geoinformatics, Springer Remote Sensing/
Photogrammetry, https://doi.org/10.1007/978-3-030-66387-2_9
163