On the potential of Google Street View for environmental waste quantification in urban Africa: An assessment of bias in spatial coverage
On the potential of Google Street View for environmental waste quantification in urban Africa: An assessment of bias in spatial coverage
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DOI：
10.1080/27658511.2023.2251799
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发表时间：
2023-08
影响因子：
2.3
通讯作者：
Farouk Umar;Josephine Amoah;Moses Asamoah;M. Dzodzomenyo;Chidinma Igwenagu;L. Okotto;J. Okotto-Okotto-J.-Okotto-Okotto-1419527485;Peter J. Shaw;Jim A. Wright
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文献类型：
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作者：
Farouk Umar;Josephine Amoah;Moses Asamoah;M. Dzodzomenyo;Chidinma Igwenagu;L. Okotto;J. Okotto-Okotto-J.-Okotto-Okotto-1419527485;Peter J. Shaw;Jim A. Wright
如果目前的消费和废物收集趋势继续下去，预计发展中国家城市的生活废物将大量增加，这将威胁到生态系统的健康。谷歌街景（GSV）图像已被用于量化高收入国家的城市环境废物。GSV在其他地方的可用性正在增加，但其覆盖范围是可变的。本研究的目的是评估偏见的时空GSV覆盖相对于环境废物在两个案例研究城市。一项环境调查分别通过95个和81个样带测量了加纳大阿克拉和肯尼亚基苏穆的环境废物。通过多水平回归，计算和比较了具有完全、部分和无GSV覆盖的样带的环境废物的六个汇总指标。多水平回归表明，与没有GSV覆盖的样带，分散的废物密度没有显着差异。然而，这两个城市有显着较低的垃圾焚烧密度沿着样带GSV覆盖（4.3与24.2燃烧点/公顷的基苏穆; 1.7与13.6站点/公顷的大阿克拉）相比，那些没有街景的大型垃圾堆密度显着较低的基苏穆样带街景覆盖（1.4与11.5站点/公顷）。由于部分图像覆盖，GSV图像分析可能会低估废物燃烧密度等废物指标。因此，今后利用全球标准价值量化非洲城市废物指标的研究应纠正覆盖面偏差。
ABSTRACT Mismanaged domestic waste threatens ecosystem health, with substantial increases predicted from developing country cities if current consumption and waste service collection trends continue. Google Street View (GSV) imagery has been used to quantify urban environmental waste in high-income countries. GSV availability is increasing elsewhere, but its coverage is variable. This study aims to evaluate bias in spatiotemporal GSV coverage relative to environmental waste in two case study cities. An environmental survey measured environmental waste in Greater Accra, Ghana and Kisumu, Kenya via 95 and 81 transects, respectively. Six summary metrics of environmental waste were calculated and compared for transects with full, partial, and no GSV coverage via multi-level regression. Multi-level regression indicated no significant differences in scattered waste density for transects with versus without GSV coverage. However, both cities had significantly lower waste burning densities along transects with GSV coverage (4.3 versus 24.2 burning sites/Ha in Kisumu; 1.7 versus 13.6 sites/Ha for Greater Accra) compared to those without Street View density of large waste piles was significantly lower in Kisumu transects with Street View coverage (1.4 versus 11.5 sites/Ha). Because of partial imagery coverage, GSV imagery analysis is likely to under-estimate waste indicators such as waste burning density. Future studies using GSV to quantify waste indicators in African cities should therefore correct for coverage bias.