Assessment of urban green space dynamics influencing the surface urban heat stress using advanced geospatial techniques

Urban areas are mostly heterogeneous due to settlements and vegetation including forests, water bodies and many other land use and land cover (LULC) classes. Due to the overwhelming population pressure, urbanization, industrial works and transportation systems, urban areas have been suffering from a deficiency of green spaces, which leads to an increase in the variation of temperature in urban areas. This study investigates the conceptual framework design towards urban green space (UGS) and thermal variability over Kolkata and Howrah city using advanced remote sensing (RS) and geospatial methods. The low green space is located in the highly built-up area, which is influenced by thermal variations. Therefore, the heat stress index showed a high area located within the central, north, northwestern and some parts of the southern areas. The vegetated areas decreased by 8.62% during the ten years studied and the other land uses increased by 11.23%. The relationship between land surface temperature (LST) and the normalized difference vegetation index (NDVI) showed significant changes with R2 values between 0.48 (2010) and 0.23 (2020), respectively. The correlation among the LST and the normalized difference built-up index (NDBI) showed a notable level of change with R2 values between 0.38 (2010) and 0.61 (2020), respectively. The results are expected to contribute significantly towards urban development and planning, policymaking and support for key stakeholders responsible for the sustainable urban planning procedures and processes

Identification of the Groundwater Potential Recharge Zones Using MCDM Models: Full Consistency Method (FUCOM), Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)

In arid and semi-arid regions, groundwater is considered being the most available natural resources for different water use. However, it is being limited in quantity. As such, its sustainable development and managementent depends on based on various criteria (e.g. climatic conditions, scale, aquifer properties, etc.). This study presents three multi-criteria index approaches (Analytic Hierarchy Process (AHP), Best–Worst Method (BWM), and Full Consistency Method (FUCOM) to classify groundwater potential maps in the Sarakhs Plain in North-east Iran. In this study, 10 parameters (layers) that affect groundwater potential recharge mapping (GPRM) are used using ArcGIS10.2. These layers includeground surface elevation, surface slope, aspect, relative slope position (RSP), plan curvature, topographic wetness index (TWI), terrain ruggedness index (TRI), drainage density, landuse, and lithology. These layers and their features were assigned properweights based on the conceptual frameworks of AHP, BWM, and FUCOM techniques, and then using a weighted overlay summation process (WOSP), final maps of groundwater potential in Sarakhs plain are obtained. The developed groundwater potential maps are classified into four classes, including low, medium, high, and very-high. The results show that among the 10 driving parameters, land use, and lithology have the highest importance and the surface slope has the lowest importance in the mapping of groundwater potential recharge. The best groundwater potential zones are concentrated in northeast and southeast, central parts, and a few parts in the areas of the western regionof the Sarakhs plain due to its nearly gentle slopes with quaternary alluvial and agriculture land and lower drainage density. The obtained results are of high value for decision-makers in the Sarakhs plain in specific and for entire Iran in general to apply sustainable groundwater utilization plans

Artificial intelligence models for suspended river sediment prediction : state-of-the art, modeling framework appraisal, and proposed future research directions

202303 bcwwVersion of RecordSelf-fundedPublishe

ESICM LIVES 2016: part two : Milan, Italy. 1-5 October 2016.

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