Geospatial data is data related to specific locations on the surface of the earth. It provides information about the relationship between variables and shows patterns and trends. This kind of data can benefit the environment, nature, and business when applied correctly.
Geospatial Data and Analysis at a Glance
The term “Geospatial” refers to information about objects, events, or other features on the Earth. The data incorporates coordinate and other information with temporary information or in a certain time.
In other cases, data can be used to provide short-term statistics like earthquakes or tsunamis, as well as dynamic data like vehicle movement and the spread of infectious disease. By using spatial analysis, time and location can be added to traditional data types as well as visualizing it.
Several data visualizations are map, graphic, statistics, and cartogram, which shows historical changes and the recent time. The context edition makes the visualization more comprehensive.
The outcome of data visualization is a readable pattern and picture. It allows companies to make a fast and accurate decision. Geospatial data refers to the geographical information.
There are two types of spatial data namely vector data and raster data. Vector data consists of points, lines, and polygons that represent features such as property, city, road, hill, or water.
Uses vector data to visualize houses with a point, roads with a line, and polygons for the whole city. On the other hand, raster data takes the form of a pixel or grid identified by rows and columns. Raster data provides more complex images like portrait or satellite images.
Aside from vector and raster data, some spatial data are census data, data, device, and social media data. Things that are posted on social media can be valuable data for data scientists to identify the latest trends.
The Implementation of Geospatial Data
Many industries have benefited from spatial data and analysis. They can be used by the government, researchers, companies, and other parties for specific purposes.
To be able to perform spatial data analysis we need special software to visualize the desired visualization. Below is the implementation of spatial analysis.
Government
By using spatial analysis, the government can gain insights about health, disease, and weather. In pandemic situations, for example, spatial analysis is capable of showing the spread of disease in a particular area.
In addition, spatial analysis can also map affected locations when disaster hits. As a result, governments are able to make quick, informed, and data-driven decisions.
Electricity
The analysis can predict better risk of electrical disturbance. It assists in optimizing electricity maintenance schedules and the employees work based on those schedules.
Insurance companies
With spatial analysis, insurance companies are able to estimate the risk. Customers will be notified before the problem occurs, resulting in better efficiency.
Banking and financial services
Banks or financial institutions that offer loan services may improve the method of credit scoring. In addition, spatial data can be used to reduce poor credit loans by showing where loans with bad credit or problems are located.
Food Companies
Companies focused on food industries can use spatial analysis to give better responses for their customers. Companies are able to encourage better quality to suit customers’ demand and ensure that the products are available in the right locations.
Transportation Companies
Transportation industries will get many benefits by implementing spatial analysis. The outcome assists companies in finding the fastest route. It also helps evaluate the potential for road development. There are many advantages that can be used by companies to improve their business.
The technology today allows spatial data analysis to be performed more easily than ever before. Companies only need to partner with spatial analysis providers.
Get to Know Geospatial Tools
We need certain tools and techniques to analyze spatial data. Performing analysis using manual methods and normal computer applications is not feasible due to the length of time it takes.
Geospatial technology refers to technologies that collect, store, and manage geographic information.
It’s important for companies to have technology that is able to perform data analysis. Here are some tools used in spatial analysis.
Big data tools
To begin with, the spatial data set is quite small and can easily be analyzed with a simple SQL. In recent years, the acquisition and management of big data has become profitable thanks to the emergence of data science and machine learning.
Big data technology is needed to manage the data, several companies such as Google and AWS provide big data software.
Sensor evolution
To collect data from various places, it is necessary to use sensors that gather spatial information. As a result of the smartphone revolution, we were able to store this kind of data.
And then the technology has flourished to the internet-of-things, sensors like Tile and Amazon Echo are strong enough to transmit the data needed. This trend will continue to grow and there will be more data collected from many places.
Cloud migration
From companies to governments to SME’s to developers, cloud technology has revolutionized the way spatial data is used to offer value to customers.
The use of state-of-the art technology is needed to manage complex spatial data. Popular programming languages such as Python are also used for spatial data since it is able to accommodate vector and raster data.
Xarray and Fiona are programs that can run vector data, while Fiona and Geopandas are able to handle raster data. The management of data is becoming easier along with the advancement of technology. However, there are also challenges that companies may face when they want to use spatial data.
Companies may struggle in managing existing data if technology is implemented incorrectly. Many companies have difficulty to profit from spatial data.
Before analyzing, spatial data needs to be collected. The amount of data can be massive, and poor results may provide unneeded insight for companies. Aside from collecting data, it also needs good data management.
In several companies, data management challenges have forced the data scientists to clean the spatial data. Companies also need to understand how to perform data management with existing tools.
Performing spatial data analysis requires a certain level of expertise, and there are only a few employees who have that capability. As an alternative to hiring a spatial data analyst, companies can partner with companies that offer spatial data analysis services.
Discover the real market for your products with LOKASI Intelligence
Many industries can benefit from geospatial analysis such as business, health, finance and so on. In business sectors, companies use geospatial analysis to identify their real target market.
It is important to comprehend target marketing because it helps distribute products so that customers can easily obtain them, allowing companies to increase revenue.
LOKASI Intelligence is a platform that integrates GIS software, spatial big data, and spatial analysis by using Artificial Intelligence and Machine Learning.
Some data that you can find in this platform are demography such as female or male, ages, incomes, married status, education,and religion. Aside from that, this platform provides social economic status data, point of interest, and more.
Those data will then be used to perform analysis and the outcome will provide the information which stores that have good performance and high revenue. Through the results, companies can determine if they are targeting the right market or not.
In addition, LOKASI can also assist companies to find potential locations for their goods to increase their revenue.
Find out more about how we help businesses to grow their business by contacting [email protected] or Whatsapp at 087777977731.
