Conference Agenda

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Session Overview
05-03: Using Remotely Sensed Data to Improve Land Use Efficiency
Wednesday, 22/Mar/2017:
8:30am - 10:00am

Session Chair: Guido Lemoine, European Commission, DG Joint Research Centre, Italy
Location: MC 2-800


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Tools for Improving Land Tenure Project Outcomes with Through Mobile Access to Land Management Information with the Global Land-Potential Knowledge System (LandPKS)

Jeffrey Herrick1, Ioana Bouvier2, Jason Karl1, Brian King2, Jason Neff3

1USDA-ARS, United States of America; 2USAID, United States of America; 3University of Colorado @ Boulder, United States of America

Securing land tenure is often a necessary but rarely sufficient requirement for long-term sustainability of agricultural production and rural communities. To maintain and increase its value, land must be managed within its sustainable potential. This paper reviews the challenges of determining the potential of specific land types (soil+topography+climate), and accessing relevant information and knowledge necessary for management. It describes the global Land-Potential Knowledge System (LandPKS), which is addressing these challenges described by providing soil-specific knowledge and information through mobile apps and cloud-computing. This system can also be used to more equitably allocate land based on its sustainable production potential. The free apps are currently being used to inventory and monitor the impacts of several rangeland restoration and management projects. By the end of 2017 they will provide users with relative potential production and soil erosion risk under several management scenarios, including annual cropping. The system is completely open, and all data are available on a data portal and through APIs. User inputs are used to increase the precision of soil identification using a simple icon-based interface supported by short embedded video clips. Future versions will provide soil-specific management information from new (including user-generated) and existing knowledge-bases.


Utilizing unmanned aerial vehicles (UAVs) in the agricultural sector

Sungyeop Kim

LX Korea Land and Geospatial Informatix Corporation, Korea, Republic of (South Korea)

Although there has been substantial technical advancement with respect to the exploi-tation and analysis of imagery and geospatial information during the last few decades, little attention has been given to the potential for geospatial methods to collect accurate data in agriculture and evaluate it. With this in mind, the present paper has shed light on the effective utilization of Unmanned Aerial Vehicle (UAV) in the agricultural sector by introducing a state-of-the-art geospatial information system; that is, the Korean Land Change Monitoring System (KLCMS). Moreover, this paper reports on two main applications of KLCMS to the agricultural environment in South Korea.

First, with a periodic monitoring, a state-owned land information system can decline the rate of the occupation without permission on state-owned lands, imposing property taxes on the use of them. Furthermore, a management system for supply and demand of agricultural products can precisely estimate crop areas by using images from UAVs, which would forecast yields of farm products.

In conclusion, these utilizations might contribute to suggesting feasible solutions for sustainable agriculture and rural development in South Korea as well as further develop-ing countries.


A Space-time Analysis Approach to Tackle Some Emerging Environmental Issues

Soe Myint, Chuyuan Wang, Asif Ishtiaque

Arizona State University, United States of America

Our planet has been experiencing significant changes in global population, urbanization, energy use, food security, water use, climate, and atmospheric conditions since the last few decades. These changes are emerging along with the rapid growth of spatiotemporal climate, environment, socio-economic, atmospheric and advanced analysis approaches. The integrative space-time system of geographic information science offers a unique and effective framework to investigate spatial-temporal processes and interactions in a wide range of environmental applications for informed decision-making. This trend is further enhanced by the growing availability of high temporal resolution data, computational performance of space-time concepts, and emerging data-intensive or big data-driven science. Especially with regards to remotely sensed image analysis spatio-temporal method has received attention since high temporal resolution MODIS was launched into Earth orbit by NASA in 1999. This paper attempts to demonstrate if and how spatial-temporal image analysis can be employed to tackle some emerging environmental issues in connection to evidence-based sustainable land management. Example applications include (1) Environmental concerns of deforestation in Myanmar; (2) Spatio-temporal modeling of the urban heat island in the Phoenix metropolitan area: Land use change implications; and (3) Examining the ecosystem health and sustainability of the world’s largest mangrove forest.


A Cost-Effective Approach to Meeting Data Needs for Multi-Purpose Land Governance in Africa

Marc Levy, Markus Walsh

Earth Institute, Columbia University, United States of America

Demands on land governance in Africa have grown faster than supply. In addition to the traditional purposes of access and property rights, processes of land governance in Africa are now increasingly expected to play a role in carbon management, regulation of land degradation, biodiversity protection, provision of food security, protection of indigenous rights, conflict management, population movement and resettlement, disease control, and sustainable water management. We build on the Africa Soil Information Service (AfSIS) to identify the principles that can guarantee a cost-effective, scalable approach to meeting land governance data needs. 1) blending of official and unofficial data sources, 2) select investment in “club goods” that fill critical data needs more effectively than public good or private investments (for example, investment in high-capacity infrared and x-ray spectroscopy), 3) specification of land-governance data requirements around decision-support needs, 4) willingness to provide data in probabilistic terms, 5) creation of public-private data partnerships, 6) open-data architectures that extend principles of openness to sample frames, collection algorithms, estimation procedures, and fitness-for-purpose evaluations. We illustrate how such principles have made a difference in specific settings in Africa, and utilize quantitative evidence to demonstrate how the principles provide more value at lower cost than conventional approaches.


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