Improving small watersheds socioeconomic indicators with nighttime light satellite data to support water management decisions

Rossano Belladona; Tiago De Vargas; Ana Paula Dalcin; Augusto Pedro Stefanon; Guilherme Fernandes Marques

doi:10.26848/rbgf.v16.3.p1436-1449

Autores/as

Rossano Belladona Federal University of Rio Grande do Sul, IPH, Porto Alegre, RS, Brazil https://orcid.org/0000-0003-2806-6629
Tiago De Vargas Federal University of Rio Grande do Sul, IPH, Porto Alegre, RS, Brazil https://orcid.org/0000-0003-2205-8708
Ana Paula Dalcin Federal University of Rio Grande do Sul, IPH, Porto Alegre, RS, Brazil https://orcid.org/0000-0001-9871-7373
Augusto Pedro Stefanon Serviço Autônomo Municipal de Água e Esgoto (SAMAE), Caxias do Sul, RS, Brazil https://orcid.org/0000-0003-1956-2524
Guilherme Fernandes Marques Federal University of Rio Grande do Sul, IPH, Porto Alegre, RS, Brazil https://orcid.org/0000-0003-0543-6279

DOI:

https://doi.org/10.26848/rbgf.v16.3.p1436-1449

Palabras clave:

GDP, Population, Job, Nighttime light, Water resources management

Resumen

Small watersheds lack socioeconomic data. These data are essential in land use decision-making and in water resources management, especially when determining its economic value. In order to contribute to filling this notable gap, this study presents an approach to estimate this type of information for small watersheds (from 5 to 100 km²), applying nighttime light (NTL) satellite images and available socioeconomic records from larger locale. Three socioeconomic indicators were chosen to test the method: Gross Domestic Product, population and jobs. The relationship between these three socioeconomic indicators and the radiance quantified from the NTL images was acquired through simple regression analysis applied at the 497 municipalities of the State of Rio Grande do Sul (RS), southern Brazil. The polynomial fit equations presented the best Coefficient of Determination, being further submitted to validation by using data from 50 municipalities of the neighboring State of Santa Catarina. The validation showed a very good estimation performance. The validated equations were used to estimate these socioeconomic indicators for small watersheds located in the municipality of Caxias do Sul, RS, in three different years: 2011, 2014 and 2018. Findings indicate that this novel application of NTL for estimating socioeconomic data can be a helpful tool towards land use and water resources management of small watersheds.

Keywords: GDP, population, job, nighttime light, water resources management.

Estimando indicadores socioeconômicos de pequenas bacias hidrográficas através de imagens noturnas de satélite no apoio à gestão dos recursos hídricos

R E S U M O

Há falta de dados socioeconômicos para pequenas bacias hidrográficas. Esses dados são fundamentais para a tomada de decisões na gestão dos recursos hídricos, principalmente na determinação do seu valor econômico. Para contribuir em preencher essa lacuna, este estudo apresenta um método para estimar esse tipo de informação para pequenas bacias hidrográficas (de 5 a 100 km²), aplicando imagens noturnas de satélite e dados socioeconômicos disponíveis de regiões maiores. Três indicadores socioeconômicos foram selecionados para testar o método: Produto Interno Bruto (PIB), população e emprego. A relação entre esses três indicadores e a radiância quantificada nas imagens noturnas foi obtida por meio de análise de regressão simples aplicada nos 497 municípios do Estado do Rio Grande do Sul (RS). As equações do ajuste polinomial apresentaram o melhor Coeficiente de Determinação, sendo posteriormente submetidas à validação com dados de 50 municípios localizados no Estado de Santa Catarina. A validação mostrou um desempenho de estimação muito bom. As equações validadas foram usadas para estimar esses indicadores socioeconômicos para pequenas bacias hidrográficas localizadas no município de Caxias do Sul, RS, em três anos distintos: 2011, 2014 e 2018. Os resultados indicam que esta nova aplicação de imagens noturnas de satélite para estimar dados socioeconômicos pode ser uma ferramenta útil para a gestão do uso do solo e dos recursos hídricos de pequenas bacias hidrográficas.

Palavras-chave: PIB, população, emprego, luz noturna, gestão dos recursos hídricos.

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