The Land‐Potential Knowledge System (LandPKS): mobile apps and collaboration for optimizing climate change investments. Issue 3 (24th March 2016)

• Record Type: Journal Article
• Authors: Herrick, Jeffrey E.; Beh, Adam; Barrios, Edmundo; Bouvier, Ioana; Coetzee, Marina; Dent, David; Elias, Emile; Hengl, Tomislav; Karl, Jason W.; Liniger, Hanspeter; Matuszak, John; Neff, Jason C.; Ndungu, Lilian Wangui; Obersteiner, Michael; Shepherd, Keith D.; Urama, Kevin C.; van den Bosch, Rik; Webb, Nicholas P.
• Is Part Of: Ecosystem health and sustainability. Volume 2:Issue 3(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-03-24
• Subjects: agriculture -- analytics -- crowdsourcing -- expert systems -- extension -- knowledge management -- land evaluation -- land‐use planning -- mobile apps -- sustainability -- sustainable land management; Ecosystem health -- Periodicals; Environmental health -- Periodicals; Environmental policy -- Periodicals; Environmental engineering -- Periodicals; Environmental ethics -- Periodicals; Ecosystem management -- Periodicals; Ecosystem management; Environmental engineering; Environmental ethics; Environmental health; Environmental policy; Periodicals; 577
• DOI: 10.1002/ehs2.1209
• Languages: English
• ISSNs: 2096-4129

Abstract

Abstract: Massive investments in climate change mitigation and adaptation are projected during coming decades. Many of these investments will seek to modify how land is managed. The return on both types of investments can be increased through an understanding of land potential: the potential of the land to support primary production and ecosystem services, and its resilience. A Land‐Potential Knowledge System (LandPKS) is being developed and implemented to provide individual users with point‐based estimates of land potential based on the integration of simple, geo‐tagged user inputs with cloud‐based information and knowledge. This system will rely on mobile phones for knowledge and information exchange, and use cloud computing to integrate, interpret, and access relevant knowledge and information, including local knowledge about land with similar potential. The system will initially provide management options based on long‐term land potential, which depends on climate, topography, and relatively static soil properties, such as soil texture, depth, and mineralogy. Future modules will provide more specific management information based on the status of relatively dynamic soil properties such as organic matter and nutrient content, and of weather. The paper includes a discussion of how this system can be used to help distinguish between meteorological and edaphic drought.