Shedding light on local development: Unveiling spatial dynamics from infrastructure implementation through nighttime lights in the Nacala corridor, Mozambique

IF 3.8 Q2 ENVIRONMENTAL SCIENCES
Ricardo Gellert Paris , Andreas Rienow
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Abstract

The increased use of nighttime lights (NTL) to assess infrastructure implementation and socioeconomic development highlights the potential of this open data source, often used as a proxy indicator of economic dynamics. Many studies focus on supra-national levels and the quantification of light emissions, generating assumptions regarding development. However, fewer studies address the characterization of socio-spatial dynamics at the local level. This research analyses the Nacala corridor in Mozambique, aiming to challenge the assumption that increasing NTL levels equals local development. We qualify and contextualize the types of activities identified by nighttime light anomalies. Using data cubes with 10-year seasonal NTL emissions, we identified anomalies in the time series of 17 out of 74 settlements and subsequently analyzed them with very high-resolution images. Among these settlements, we identified soil extraction, quarrying, or industries in 13 cases. Finally, we compared the results with household surveys indicating that during the period, the population had no significant increase in access to energy. We conclude that the NTL time series can effectively portray infrastructure-driven activities, such as surface mining and industry, in the context of the Corridor. However, the assumption that local development is linked with an increase in NTL in non-urbanized areas can be misleading without qualitative analysis. The activities that are the source of radiance can be illicit, not socially adopted, economically concentrated, and/or environmentally harmful.
照亮地方发展:通过莫桑比克纳卡拉走廊夜间灯光揭示基础设施实施的空间动态
越来越多地使用夜间灯光(NTL)来评估基础设施的实施情况和社会经济发展,这凸显了这一开放数据源的潜力,它通常被用作经济动态的替代指标。许多研究侧重于超国家层面和光排放的量化,从而产生有关发展的假设。然而,较少研究涉及地方层面的社会空间动态特征。本研究分析了莫桑比克的纳卡拉走廊,旨在对 "提高非物质文化遗产水平等于地方发展 "这一假设提出质疑。我们对夜间光线异常所确定的活动类型进行了定性和背景分析。通过使用包含 10 年季节性非甲烷总烃排放量的数据立方体,我们在 74 个居民点中的 17 个居民点的时间序列中发现了异常现象,并随后使用高分辨率图像对其进行了分析。在这些居民点中,我们发现了 13 个土壤采掘、采石或工业点。最后,我们将结果与家庭调查进行了比较,结果表明,在此期间,居民获得能源的机会没有显著增加。我们的结论是,在走廊的背景下,NTL 时间序列可以有效地描述基础设施驱动的活动,如地表采矿和工业。但是,如果不进行定性分析,就认为当地发展与非城市化地区非地表水排放量的增加有关,可能会产生误导。作为辐射源的活动可能是非法的、未被社会采纳的、经济上集中的和/或对环境有害的。
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来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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