通过结合NPP-VIIRS类数据集和Sentinel-2图像,精确地在建成区域进行GDP空间化和分析
Zijun Chen1,2, Wanning Wang1, Haolin Zong1
1College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, China.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
这项研究使用卫星数据精确地空间化和分析了建筑地区的二级和三级行业 (GDP23) 的国内生产总值. 调查结果揭示了城市规划和可持续发展的关键模式和转折点.
科学领域:
- 遥感 遥感 遥感 遥感
- 地理空间分析是什么
- 城市经济学城市经济学
背景情况:
- 区域社会经济地位通过空间化二级和三级行业的国内生产总值 (GDP23) 来有效地描绘.
- 现有的GDP空间化方法主要使用夜间光线数据,仅限于使用多源遥感的建筑区域.
- 在城市环境中,GDP23的精确空间化对于理解区域发展动态至关重要.
研究的目的:
- 精确地空间化和分析GDP23在中国齐博市建成区内的变化模式.
- 将NPP-VIIRS类型和Sentinel-2数据结合起来,以进行增强的GDP23映射.
- 评估遥感数据和机器学习对城市经济分析的有效性.
主要方法:
- 使用了Sentinel-2多光谱图像和NPP-VIIRS类数据集超过六年.
- 在PIE-Engine云平台上使用随机森林 (RF) 分类方法来提取建筑区.
- 构建了GDP23的空间化模型,使用夜间光大小和全面的夜间光指数.
主要成果:
- 射频分类在建地开采中实现了高精度 (>0.90),区间的扩张率各不相同.
- 综合性夜间照明指数有效地显示了建筑地区的GDP23 (R2=0.82),模拟错误很低 (<1%).
- 2018年被确定为GDP的转折点23,中区显示最大的下降 (-52.36%).
- 张甸区的高GDP比例最高23 (>9%),而其他地区主要显示低GDP23 (<60%).
结论:
- 这项研究开创了使用集成遥感数据集在建成地区精确的GDP23的空间化和分析.
- 这些发现为优化城市规划和实施可持续发展政策提供了有价值的参考资料.
- 该方法表明了结合多来源遥感数据以进行详细的城市社会经济分析的潜力.
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