The spatial distribution of cropland is an important input to many applications including food security monitoring and economic land use modeling. Global land cover maps derived from remote sensing are one source of c...The spatial distribution of cropland is an important input to many applications including food security monitoring and economic land use modeling. Global land cover maps derived from remote sensing are one source of cropland but they are currently not accurate enough in the cropland domain to meet the needs of the user community. Moreover, when compared with one another, these land cover products show large areas of spatial disagreement, which makes the choice very difficult regarding which land cover product to use. This paper takes an entirely different approach to mapping cropland, using crowdsourcing of Google Earth imagery via tools in Geo-Wiki. Using sample data generated by a crowdsourcing campaign for the collection of the degree of cultivation and settlement in Ethiopia, a cropland map was created using simple inverse distance weighted interpolation. The map was validated using data from the GOFC-GOLD validation portal and an independent crowdsourced dataset from Geo-Wiki. The results show that the crowdsourced cropland map for Ethiopia has a higher overall accuracy than the individual global land cover products for this country. Such an approach has great potential for mapping cropland in other countries where such data do not currently exist. Not only is the approach inexpensive but the data can be collected over a very short period of time using an existing network of volunteers.展开更多
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 incr...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,to-pography,and relatively static soil properties,such as soil texture,depth,and mineralogy.Future mod-ules 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 discus-sion of how this system can be used to help distinguish between meteorological and edaphic drought.展开更多
文摘The spatial distribution of cropland is an important input to many applications including food security monitoring and economic land use modeling. Global land cover maps derived from remote sensing are one source of cropland but they are currently not accurate enough in the cropland domain to meet the needs of the user community. Moreover, when compared with one another, these land cover products show large areas of spatial disagreement, which makes the choice very difficult regarding which land cover product to use. This paper takes an entirely different approach to mapping cropland, using crowdsourcing of Google Earth imagery via tools in Geo-Wiki. Using sample data generated by a crowdsourcing campaign for the collection of the degree of cultivation and settlement in Ethiopia, a cropland map was created using simple inverse distance weighted interpolation. The map was validated using data from the GOFC-GOLD validation portal and an independent crowdsourced dataset from Geo-Wiki. The results show that the crowdsourced cropland map for Ethiopia has a higher overall accuracy than the individual global land cover products for this country. Such an approach has great potential for mapping cropland in other countries where such data do not currently exist. Not only is the approach inexpensive but the data can be collected over a very short period of time using an existing network of volunteers.
文摘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,to-pography,and relatively static soil properties,such as soil texture,depth,and mineralogy.Future mod-ules 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 discus-sion of how this system can be used to help distinguish between meteorological and edaphic drought.
