Abstract
Abstract. The socioeconomic data, such as household income, is an important indicator of people’s well-being. However, due to the limited resource in many developing countries such as Thailand, the data obtained from household income surveys are often incomplete. As a result, the annual household survey usually contains a gap at the municipality household level. In this study, we aim to quantify the household income with K-NN imputation models at the sub-district level using satellite imageries and geospatial data as proxies to socioeconomic indicators. We examined the role of satellite and geospatial data in household income estimation, applied the K-NN imputation methods to estimate the missing income data by using various geographical and statistical variables, and quantified how these data improved the accuracy of sub-district household income estimation. Our results illustrated a significant correlation between sub-district household income and geographical data extracted from day-night satellite data, such as night light intensity (r = 0.53), urban density (r = 0.44), residential area (r = 0.68), urban area (r = 0.64), and statistical data as well as household expenditure (r = 0.97). These can be used to improve the socioeconomic indicators’ estimation as well as household income in sub-district level. The income imputation from geographical data perform better result than purely statistical variables. Especially, the night light intensity can infer the wealth of people living in large scale areas, while day-time satellite images can be interpreted for land use and land cover also implying socioeconomic status. Such socioeconomic proxy from space provides spatially explicit information in further study.
Highlights
Since 1992, the sustainable development concepts had been adopted by more than 178 countries
We studied the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor dataset from National Oceanic and Atmospheric Administration (NOAA) which has been released since May 2012
We examined the role of satellite imageries and geospatial data as proxies to socioeconomic indicators in household income imputation models
Summary
Since 1992, the sustainable development concepts had been adopted by more than 178 countries. The development of Thailand’s mega project, the Eastern Economic Corridor (EEC), is framed under the Sustainable Development Goals (SDGs) and required intensive socioeconomic information for the decision making of high-level policymakers. The socioeconomic data such as household income is an important indicator of people’s well-being to eliminate poverty (SDG-1). The annual household survey has been done in most areas, the survey does not always cover the municipal area This problem often leads to a lack of understanding of the economic and sociological standing of people who live in outbound areas. The limited socioeconomic data can cause difficulty in implementing the national polices as well as disinteresting the vendors to stimulate economic growth
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