格式化牲畜密度数据库和哈萨克斯坦的空间趋势
Venkatesh Kolluru1, Ranjeet John2,3, Sakshi Saraf3
1Department of Sustainability and Environment, University of South Dakota, Vermillion, SD, 57069, USA. Venkatesh.Kolluru@coyotes.usd.edu.
Scientific data
|November 29, 2023
概括
哈萨克斯坦的高分辨率牲畜密度地图显示了中南部和东南部地区的关键热点. 这些数据对于了解牲畜对生态系统和疾病传播的影响至关重要.
科学领域:
- 环境科学 环境科学
- 农业科学 农业科学
- 地理空间分析是什么
背景情况:
- 牲畜养殖对于亚洲干旱地区的生计至关重要,但增加牲畜密度 (LSKD) 会带来生态和健康风险.
- 现有的牲畜数据缺乏高分辨率的空间分布,阻碍了有效的管理和研究.
- 了解牲畜密度对于生态系统健康,气候变化适应和疾病预防至关重要.
研究的目的:
- 为哈萨克斯坦的马,绵羊和山羊开发一个高分辨率 (1公里) 格式化牲畜密度数据库.
- 分析2000-2019年期间牲畜密度的空间分布和时间变化.
- 为了更好地缩小数据,确定影响牲畜分布的因素.
主要方法:
- 采用随机森林 (RF) 回归建模来创建网格化牲畜密度数据库.
- 综合植被代理,气候,社会经济,地形和近距离变量.
- 利用了地区级人口普查数据,使用人口密度和夜间灯光等因素进行缩小.
主要成果:
- 在哈萨克斯坦中南部和东南部确定了高密度牲畜热点.
- 在北部和西北部地区观察到中密集群.
- 证明了人口密度,靠近定居点,夜间灯光和温度在缩小牲畜数据中的有效性.
结论:
- 开发的高分辨率网格畜牧数据库为哈萨克斯坦的畜牧分布提供了关键的见解.
- 这个资源将支持利益相关者,研究人员,土地管理者和政策制定者在区域和国家规划方面.
- 这些发现强调了综合数据和建模对于有效的畜牧管理和环境管理的重要性.
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