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Crop Calendar Dataset

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DataONE2014-09-25 更新2024-06-27 收录
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https://search.dataone.org/view/Crop_Calendar_Dataset.xml
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This data set is the result of digitizing and georeferencing existing observations of crop planting and harvesting dates. Climate statistics (e.g., the average temperature at which planting occurs in each region) were derived by merging the crop calendar maps with monthly climatologies from CRU. The gridded maps of planting dates, harvesting dates, etc., for 19 crops are available at two different resolutions (5 minute and 0.5 degree), and in two different formats (netCDF and ArcINFO ASCII). For each region where there is a crop calendar observation, investigators applied that observation to every grid cell in the region (i.e., a simple paint-by-number approach). This dataset is described in the following publication: Sacks, W.J., D. Deryng, J.A. Foley, and N. Ramankutty (2010). Crop planting dates: an analysis of global patterns. Global Ecology and Biogeography 19, 607-620. DOI: 10.1111/j.1466-8238.2010.00551.x If you download this dataset, please email the PI to let him know how our data are being used. He can keep you informed of any updates to the dataset. Also see the MIRCA2000 data set [at http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html and http://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=10015] which contains much of the same crop calendar data as this data set, but in a different format.

本数据集是对现有作物播种与收获日期观测数据进行数字化与地理配准后的成果。气候统计量(如各区域播种时的平均气温)通过将作物日历地图与CRU的月均气候数据集融合得到。 涵盖19种作物的播种日期、收获日期等网格化地图,提供两种空间分辨率(5分与0.5度)以及两种存储格式(netCDF与ArcINFO ASCII)。针对存在作物日历观测数据的区域,研究人员将该观测数据直接应用于区域内的所有网格单元,即采用简易的数字填色式赋值方法。 本数据集的详细说明见于如下文献: Sacks WJ、Deryng D、Foley JA、Ramankutty N(2010)。作物播种日期:全球格局分析。全球生态学与生物地理学(Global Ecology and Biogeography),19卷:607-620。DOI: 10.1111/j.1466-8238.2010.00551.x 若您下载本数据集,请发送邮件告知项目负责人(Principal Investigator,PI)您的数据使用用途,他将为您同步数据集的相关更新信息。 另可参考MIRCA2000数据集(链接:http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html 及 http://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=10015),该数据集包含与本数据集大量重合的作物日历数据,但采用了不同的存储格式。
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2014-11-17
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