A thirst for development: mapping water stress using night‐time stable lights as predictors of province‐level water stress in China

Xiaojun You, Kyle M Monahan
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引用次数: 1

Abstract

Given the rapid development within China, the inequality of available water resources has been increasingly of interest. Current methods for assessing water stress are inadequate for province-scale rapid monitoring. A more responsive indicator at a finer scale is needed to understand the distribution of water stress in China. This paper selected Defense Meteorological Satellite Program Operational Line-scan System night-time stable lights as a proxy for water stress at the province level in China from 2004 to 2012, as night-time lights are closely linked with population density, electricity consumption and other social, economic and environmental indicators associated with water stress. The linear regression results showed the intensity of night-time lights can serve as a predictive tool to assess water stress across provinces with an R2 from 0.797 to 0.854. The model worked especially well in some regions, such as East China, North China and South West China. Nonetheless, confounding factors interfered with the predictive relationship, including population density, level of economic development, natural resource endowment and industrial structures, etc. The model was not greatly improved by building a multi-variable linear regression including agricultural and industrial indicators. A straightforward predictor of water stress using remotely sensed data was developed.
对发展的渴望:利用夜间稳定灯作为中国省级水资源压力预测指标绘制水资源压力图
随着中国经济的快速发展,水资源分配不均问题日益引起人们的关注。目前评估水资源压力的方法不足以进行省级规模的快速监测。要了解中国水资源压力的分布情况,需要一个更灵敏、更精细的指标。由于夜间照明与人口密度、用电量等与水资源压力相关的社会、经济和环境指标密切相关,本文选择国防气象卫星计划运行线扫描系统夜间稳定灯作为2004 - 2012年中国省级水资源压力的代表。线性回归结果表明,夜间照明强度可以作为各省水资源压力的预测工具,R2在0.797 ~ 0.854之间。这种模式在华东、华北和西南等地区尤为有效。人口密度、经济发展水平、自然资源禀赋、产业结构等混杂因素对预测关系有干扰作用。通过建立包括农业和工业指标在内的多变量线性回归,模型并没有得到很大的改进。开发了一种利用遥感数据直接预测水分胁迫的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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