Generating global crop distribution maps: from census to grid

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

英文文献：Generating global crop distribution maps: from census to grid
英文文献作者：You, Liangzhi,Wood, Stanley,Wood-Sichra, Ulrike
英文文献摘要：
In order to evaluate food security, technology potential and the environmental impacts of production in a strategic and regional context, it is critical to have reliable information on the spatial distribution and coincidence of people, agricultural production, and environmental services. This paper proposes a spatial allocation model for generating highly disaggregated, crop-specific production data by a triangulation of any and all relevant background and partial information. This includes national or sub-national crop production statistics, satellite data on land cover, maps of irrigated areas, biophysical crop suitability assessments, population density, secondary data on irrigation and rainfed production systems, cropping intensity, and crop prices. This information is compiled and integrated to generate "prior" estimates of the spatial distribution of individual crops. Priors are then submitted to an optimization model that uses cross-entropy principles and area and production accounting constraints to simultaneously allocate crops into the individual pixels of a GIS database. The result for each pixel (notionally of any size, but typically from 25 to 100 square km) is the area and production of each crop produced, split by the shares grown under irrigated, high-input rainfed, low-input rainfed conditions (each with distinct yield levels). Tested in Latin America and sub-Saharan Africa, the spatial allocation model is applied here to generate a global distribution of crop area and production for 20 major crops (wheat, rice, maize, barley, millet, sorghum, potato, sweet potato, cassava and yams, plantain and banana, soybean, dry beans, other pulse, sugar cane, sugar beets, coffee, cotton, other fibres, groundnuts, and other oil crops). The detailed spatial datasets represent a truly unique and extremely rich platform for exploring the social, economic and environmental consequences of agricultural production in a strategic policy context.

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖