The United Nations acknowledges that action in one of the 17 Sustainable Development Goals (SDGs) will impact outcomes in others and that development should interact the social, economic, and environmental sustainability. Many countries have prioritized goals and targets based on their current progress and the prosperity of their people. This article focused on SDG 6: Clean water and sanitation, especially the first two (6.1 and 6.2) out of eight targets. The author has considered SDG 6, a critical goal to focus on and achieve in Tirunelveli city municipal corporation. The study area is situated in the Tirunelveli district of Tamil Nadu, India's southernmost state. Citizen science (CS), also known as community science, has emerged as an effective method of collecting data and supporting a wide range of indicators from the SDG targets. The objective of this article is to utilize the benefit of the CS approach for monitoring the targets 6.1 and 6.2 pertained to drinking water and sanitation facilities respectively in the study area. The activities suggested for this SDG 6 CS project were framing the core question, identification of citizen scientists, data analysis, and action plan. College students, ward councilors, and community volunteers, referred to as three categories of citizen scientists, will collect household data for all 55 wards in the study area. The value of the collected data to various government agencies and monitoring organizations is also discussed.
The world has changed dramatically in the last two decades due to human intervention at regional and global levels. The fates of humanity and our planet are in our hands. Governments, international agencies, the corporate sector, and individuals must work together to shift away from unsustainable practices. The U.N. General Assembly endorsed the 2030 agenda for Sustainable Development, which comprises 17 Sustainable Development Goals (SDGs). Several published research supports SDG strategies in the last 5 years. Despite initial efforts, the U.N. declared that the world is not really on pace to achieve most SDG targets. Geographic information system (GIS) has been identified as an effective tool in accessing, monitoring, and achieving goals that have 15 years lifespan. This paper presents a systematic review of published articles that combined GIS and SDG in their research. Because these 17 goals include 169 targets, the assessment may be more difficult if all the goals were addressed. This study focused only on “SDG 6: Clean water and sanitation” literature. Google scholar was used to find the most relevant 25 studies. The variable attributes like SDG target addressed, study area, monitoring and improving strategies dealt, the particularity of GIS were analyzed in the literature review through content analysis. The systematic review has found that target 6.1 received enormous attention, and the inverse distance weightage (IDW) interpolation tool from the geostatistical analysis toolset was widely employed in the monitoring stage.
The United Nations (U.N.) has declared the present decade a “decade of action” to accelerate the phase of 17 Sustainable Development Goals (SDGs) endorsed in 2015. These 17 goals are intended to protect the earth's environment, eradicate poverty and inequality, and guarantee that everyone lives in peace, harmony, and prosperity. Target 11.1 for safe and affordable housing from SDG 11: Sustainable cities and community is a crucial target for most developing nations. This target addresses the slums and informal settlements, which indicate inequalities in the urbanized city. The proportion of the population living in slum dwellings and informal settlements was the indicator to measure the achievement level of the target. The study area to assess the target is Tirunelveli City municipal corporation from southern India. The field survey was conducted in all 55 wards to locate and count the population of slums and informal settlements and to map the spatial variation of target scores among the wards. The spatial assessment was performed by comparing the attributes of population density and land use classes (water, built area, and bare land) with the achievement score of target 11.1 for each ward. With an overall score of 90.08, this city has no significant relation with population density (R2 = 0.07) and relevant land use classes (R2 = 0.05) at the ward level. The spatial tool, weighted mean centre, has concluded that slum settlements appeared randomly and dispersed throughout Tirunelveli without any pattern.
United Nations has announced the current decade as a 'decade of action' to deliver the 2030 agenda successfully. The 17 Sustainable Development Goals (SDG) achievement level of all the nations varies. Almost 70% of the world's population is expected to settle in the urban region by 2050. So SDG 11, the goal of developing a resilient and sustainable city, was focused on in the study. Since the targets of each goal are interrelated to others, the progress in each goal will also reflect on the achievement scores of different goals. An attempt was made in this study to develop a model to predict the achievement status of SDG 11 based on the performance of the country's related goals. The Random Forest machine learning algorithm was used in developing the prediction model with the KNIME analytics platform, which attained overall prediction accuracy up to 83.67%.
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