Spatial Aspects of Poverty and Inequality

Spatial analysis of poverty and inequality requires powerful technology, serving as the only means to accurately classify places based on the wealth they possess. The utility of technology spans various activities, with climate analysis as an exemplar. The evaluation of disasters related to climate change or weather shifts and natural events like earthquakes demands advanced technology. Tools such as Remote Sensors are instrumental in discovering intricate details about different places. As proposed by Herold et al., hidden aspects about regions or places can be unraveled using technologies like satellite imagery and remote sensing (2003).

These tools facilitate an insight into places based on the affordability of basic needs for all citizens, and clarifying the percentage of the population living above the poverty line. Any complexities that require assistance affirm the need for highly sophisticated techniques, tools, and methods. Research through technology reveals substantial information about places or regions in a country (Engstrom et al., 2016). It uncovers the relationships between or among different places. This can be accomplished by employing technology that gauges how close or far country locations are. However, it’s important to note that poverty or inequality cannot be measured by looking at building structures alone.

Engstrom contends that data obtained from satellites is instrumental for conducting research as it lays the foundation for decisions regarding poverty in different country locations, playing a crucial role in combating poverty in diverse regional parts of a country (Engstrom, 2018). Besides, Engstrom et al. accentuate that the significance of technology has been vindicated in the fight against poverty, resulting in a balance of wealth among individuals located in various areas of a country. It’s notable that not all countries regularly conduct surveys or research to determine poverty levels in different locations. In such countries, the importance of research on significant areas like poverty, population dynamics, and economic conditions is often overlooked. Elvidge articulates that satellite data can prove instrumental in identifying and reducing poverty (2009).

Satellite data can be utilized to classify places based on the age of existing building structures, distinguishing between old or recently constructed ones. Indicators of poverty levels can also be derived from the area’s extent of industrialization and urbanization. This method focuses on discernable, physical materials present in the area. According to Hansen et al. (2000), through remote sensing, researchers have gleaned valuable insights about places, including Buraydah. Morikawa (2014) affirms that remote sensing enables comprehensive categorization of income across different locations, identifies developed or underdeveloped areas, considers industries, and detects natural resources. Researchers, especially those focusing on geographical areas, as discussed by Champion, exploit advanced satellite data and imagery for spatial analysis of places in efficient ways (1999). Hence, numerous technologies can be deployed to professionally analyze places.

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