How can you tell if the nearest drinking water source is safe? What would be the agriculture yield this year, factoring in all the variables? How can we identify the optimum location for a rural healthcare facility? We can follow conventional approaches to look for the answers, but if we need a consistent, timely and cost-effective solution, we must take the help of what is known as Remotely-Sensed (RS) data. Analysing RS and geospatial data has become the latest innovation in data generation. RS data comprises the images taken by satellites and UAVs (Unmanned Aerial Vehicle) that can be processed and modified to obtain critical information. The enormous scope of this unique source of intelligence has amazed stakeholders from science, technology, geology and policymaking alike. The easy-to-access nature of such data is unfurling new avenues of opportunity every day. In the last several years, it has made its foray into the monitoring and evaluation of development goals advocated by the United Nations (UN).

Assessing the outcomes of the Millennium Development Goals (MDGs), the UN came up with the Sustainable Development Goals (SDGs) in September 2015. These goals underscore a triple bottom line approach of human wellbeing by integrating agreed synergies and trade-offs among economic development, environmental sustainability and social inclusion, adopted by world leaders and development partners. This time around, the objectives are much broader in scope, with 17 goals and 169 target areas. One compelling dimension of the SDGs is keeping in mind "the health of the Earth" while pursuing development goals. This makes the implementation and monitoring part all the more complex.

Collecting data continuously and on a significant scale is the basis of success in achieving these goals. That is where the whole initiative faces a considerable challenge. Development experts believe that conducting the census every ten years is not enough to detect the latent yet critical changes in socioeconomic indicators. Along with this regular practice, every country must portray an accurate and consistent picture of the indicators. According to estimates, it could cost up to USD 253 billion to monitor socioeconomic targets through household survey data on a broad scale for the entire lifetime of the SDGs.

The application of RS data can play a critical role here. There are several Earth Observation (EO) satellite programmes like Landsat by NASA and Sentinel by ESA (the space agencies of the USA and European Union) that provide free access to high-resolution images and a wide variety of updated information. A developing country could save a ton of money and time and still extract relevant insight out of these data. With the recent development in big data analysis assisted by state-of-the-art software and cheap computing power, satellite images can aid in detecting suitable agricultural land or safe water sources, predicting floods and volcanic eruptions, or managing evacuation in a wildfire or cyclone.

RS data could provide more specific recommendations suitable for targeted SDG interventions and local execution as well. As the methods of data collection from census and yearly surveys are different from country to country, RS data could support a standardised platform for analyses and policy suggestions. It can help solve the perpetual problem of infrequent and insufficient conventional data sources. These compelling features of RS data in measuring development factors has recently caught the attention of the UN's High-Level Political Forum to kickstart a conversation on "Data for Sustainable Development".

So how exactly can RS data help achieve the SDGs? The UN Statistics Division estimated that approximately 20 percent of the SDG indicators could be translated and determined either through direct use of geospatial data itself or through integration with other statistical data. Indonesia has been using a GIS-based poverty map as a tool to detect inequality and disparity within the country. Many of their social protection programmes are hinged on such data. Geospatial analysis could further offer intelligence on the precise level of irrigation, fertilisers, pesticides and seeds required for optimum yield. The Indian state of Kerala has been analysing satellite images for making accurate agricultural decisions. Vietnam has also been using RS data to fight arsenic contamination and land subsidence issues in the Mekong delta. Many countries from Africa are applying satellite imagery to institute a substantive healthcare system like finding the optimum location of healthcare facilities, predicting patterns and distribution of diseases, monitoring the quality of air, and identifying sources of safe drinking water.

RS data can also be applied to track and control unbridled urbanisation, deforestation and desertification. South American countries are benefitting exceptionally in the battle against illegal cutting and land-grabbing as they turn actionable insights out of satellite imagery. Countries that bank heavily on the blue economy utilise bathymetric data from satellites and sensors. They can take practical measures to maximise fishing output. These data also help predict the contamination of the river and sea by analysing the colour and texture of the surface water. One geospatial study projects that the entire coastal region of Bangladesh could drown if the sea level rises 18 inches due to global warming. It would affect more than 15 million people. RS data could help to formulate a secure and robust relocation programme for them if necessary.

The potential for applying GIS data in the development sector of Bangladesh is enormous. Being a signatory of the SDG protocol, Bangladesh must take advantage of this technology to keep up with monitoring and evaluating the indicators. For example, India has its programmes for auditing and assessing SDGs promoted by the Indian Space Research Organization (ISRO). As Bangladesh has already entered into the prestigious league of flying its own satellites, it is high time to move forward with new satellites equipped with sophisticated sensors and cameras. The Prime Minister recently mentioned in a speech that we must ensure the optimum use of land and resources to fight the economic fallout from the pandemic. Cutting edge geospatial and big data analysis, and state-of-the-art facilities for space and geo sciences, hold the key to this end.

Tanvir Kabir is a Science-Technology-Public Policy Analyst, and a member of the Bangladesh Foreign Service as Senior Assistant Secretary. Iftekhairul Islam is a PhD Candidate in Public Policy at The University of Texas at Dallas. Emails: [email protected], [email protected]. The views expressed here do not necessarily represent the views of the Ministry of Foreign Affairs or the Government of Bangladesh.