Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.
Fonds National de la Recherche Scientifique (FNRS), Brussels, Belgium.
Sci Data. 2018 Oct 30;5:180227. doi: 10.1038/sdata.2018.227.
Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.
全球牲畜地理分布数据集对于农业社会经济学、食品安全、环境影响评估和流行病学等多个领域的应用至关重要。我们呈现了一个新版本的全球牲畜分布数据库(GLW3),反映了 2010 年最新编制和协调的国家以下层面牲畜分布数据。GLW3 以 0.083333 十进制度(赤道处约 10 公里)的空间分辨率,为每个土地像素提供了牛、水牛、马、绵羊、山羊、猪、鸡和鸭的全球种群密度。同时,还附有关于输入普查数据的年份、空间分辨率和来源的详细元数据。每种物种的分布都生成了两个版本。在第一个版本中,牲畜数量根据使用高分辨率空间协变量(dasymetric 加权)建立的统计模型在普查多边形内进行细分(dasymetric 加权)。在第二个版本中,动物数量在其普查多边形内均匀分布,具有相同的密度(面积加权),以提供与其他空间变量没有任何关联的空间数据层。