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    Google Earth Engine(GEE)——全球范围内不同作物的无机肥(简称化肥)使用量

    按作物和国家划分的全球化肥使用情况 了解国家、地区和全球范围内不同作物的无机肥(简称化肥)使用量是化肥消费分析和需求预测的重要组成部分。由于难以收集,处理和验证也很费时,所以很少有关于作物用肥(FUBC)的良好信息。为了填补这一空白,1992年,根据联合国粮食及农业组织(FAO)、国际肥料开发中心(IFDC)和国际肥料协会(IFA)联合进行的专家调查,发表了1990/1991年期间的第一份全球FUBC报告。此后,类似的专家调查在主要化肥消费国每两到四年进行并公布一次。自2008年以来,IFA领导了这些工作,据我们所知,这仍然是全球唯一可获得的关于FUBC的数据集。这个数据集包括IFA进行的调查的数据(CSV格式),代表2017-18年的情况,以及所有历史上的FUBC数据的整理。前言 – 床长人工智能教程

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    Google Earth Engine——全球摩擦面列举了北纬85度和南纬60度之间的所有陆地像素在2015年的名义年的陆地迁移速度。

    This global friction surface enumerates land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for a nominal year 2015. This map was produced through a collaboration between the University of Oxford Malaria Atlas Project (MAP), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands. The underlying datasets used to produce the map include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce this “friction surface”, a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel, with the fastest travel mode intersecting the pixel being used to determine the speed of travel in that pixel (with some exceptions such as national boundaries, which have the effect of imposing a travel time penalty). This map represents the travel speed from this allocation process, expressed in units of minutes required to travel one meter. It forms the underlying dataset behind the global accessibility map described in the referenced paper.

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