Next Article in Journal
CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity
Previous Article in Journal
Remote Sensing-Based Mapping of Senescent Leaf C:N Ratio in the Sundarbans Reserved Forest Using Machine Learning Techniques
Open AccessArticle

Geospatial Assessment of Water-Migration Scenarios in the Context of Sustainable Development Goals (SDGs) 6, 11, and 16

1
United Nations University, Institute for Water, Health and Environment, Hamilton, ON L8P 0A1, Canada
2
School of Geography and Earth Science, McMaster University, Hamilton, ON L8S 4L8, Canada
3
Department of Geography, University of Northern British Columbia, Prince George, BC V2N 4Z9, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(9), 1376; https://doi.org/10.3390/rs12091376
Received: 16 December 2019 / Revised: 18 April 2020 / Accepted: 22 April 2020 / Published: 27 April 2020
(This article belongs to the Special Issue Monitoring Sustainable Development Goals)
Communities and countries around the world are gearing up efforts to implement the 2030 Agenda goals and targets. In this paper, the water and migration scenarios are explained with a focus on Sustainable Development Goals (SDGs) 6 (water-related), 11 (urbanization), and 16 (peace and political stability). The study has two phases. The first phase illustrates the application of geospatial data and tools to assess the water-migration interlinkages (nexus) by employing a case study approach. Three case studies, Lake Chad, the Aral Sea region, and the Nile Delta, representing various geographic and socio-political settings, were selected to perform the multitemporal analysis. For this analysis, a mixed toolset framework that combined algorithmic functions of digital image processing, the Landsat sensor data, and applied a geographic information system (GIS) platform was adopted. How water-related events directly or indirectly trigger human migration is described using spatial indicators such as water spread and the extent of urban sprawl. Additionally, the geospatial outputs were analyzed in tandem with the climate variables such as temperature, precipitation data, and socio-economic variables such as population trends and migration patterns. Overall, the three case studies examined how water and climate crisis scenarios influence migration at a local and regional scale. The second phase showcases global-scale analysis based on the Global Conflict Risk Index (GCRI). This indicator reflects on the risks and conflicts with environmental, social, and political aspects and comments on the connection of these dimensions with migration. Together, the two phases of this paper provide an understanding ofthe interplay of water-related events on migration by applying the geospatial assessment and a proxy global index. Additionally, the paper reiterates that such an understanding can serve to establish facts and create evidence to inform sustainable development planning and decision making, particularly with regard to SDGs 6, 11, and 16. Targets such as 6.4 (managing water stress), 6.5 (transboundary challenges) and, 11.B (adaptation and resilience planning) can benefit from the knowledge generated by this geospatial exercise. For example, the high GCRI values for the African region speak to SDG targets 11.B (integrated policies/plans) and 16.7 (decision support systems for peaceful societies). Two key highlights from the synthesis: (a) migration and urbanization are closely interconnected, and (b) the impact of water and climate crisis is comparatively high for rural-urban migration due to the considerable dependence of rural communities on nature-based livelihoods. In conclusion, geospatial analysis is an important tool to study the interlinkages between water and migration. The paper presents a novel perspective toward widening the scope of remote sensing data and GIS toward the implementation of the SDG Agenda. View Full-Text
Keywords: water; migration; Landsat; GIS; Sustainable Development Goals 6; 11; 16; interlinkages; scenarios water; migration; Landsat; GIS; Sustainable Development Goals 6; 11; 16; interlinkages; scenarios
Show Figures

Graphical abstract

MDPI and ACS Style

Nagabhatla, N.; Brahmbhatt, R. Geospatial Assessment of Water-Migration Scenarios in the Context of Sustainable Development Goals (SDGs) 6, 11, and 16. Remote Sens. 2020, 12, 1376.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop