REVIEW PAPER Enhanced Adaptive Technique for Surface Temperature Variability Analysis Deepak Kumar 1 • Tavishi Tewary 2 • Sulochana Shekhar 3 Received: 12 July 2016 / Accepted: 13 December 2017 Ó Shiraz University 2018 Abstract The concerns of global warming effect have elevated the global inclination to interpret the mystery of surface temperature variations with respect to various aspects. Surface temperature (ST) plays a role as most substantial parameter in any environment. The effort attempts to present the satellite image processing methods for utilizing the state-of-the-art- enhanced adaptive technique (AET) to illustrate the spatial variability of ST. These methods can be helpful in computing the spatial variability at macro- to micro-scales. Therefore, spatial variability through AET was explored to demonstrate spatial scattering of surface temperatures. The outcomes seemingly revealed the aggregation and dispersion of spatial thermal configuration at the test area. The current work also presented the approach for assimilation of spatial variability information as a powerful reliable instrument to monitor the thermal dynamics within the region. Keywords Adaptive  Enhanced  Global  Spatial  Surface  Temperature 1 Introduction The rapid expansion in urban development in countries like India is enduring as one of the key issues of worldwide changes affecting the physical dimensions of cities leading to several changes in their landscape (Urban et al. 2007). It has become the most powerful and visible anthropogenic strength that has fet- ched vital deviations in urban land cover and landscape pattern around the country (Moonen et al. 2012). In this regard, many studies were conducted by the various researchers across the nation including (Dontree 2010) and surface temperature (ST) was considered as a significant indicator for the study of several models on the earth surface interactions at local and global scale. Normally, ST is derived from thermal infrared data supplied by band 6 of the Enhanced Thematic Mapper plus (ETM?) sensor onboard the Landsat 7 satellite through various algorithms (viz. single-channel methods, split-window tech- nique and multi-angle methods). ST retrieval also depends on the atmospheric effects, the exact amount of emissivity factor and quality of radiation data, including thermal infrared band spectral response function, signal to noise, power, and precision of radiometric calibration separation (Li 2004). In the current study, an effort has been taken to utilize the ST for the study of ST with the help of state-of-the-art method termed enhanced adaptive technique (AET). Similarly, other quantities improved the study to deliver a set of quantitative parameters for enu- merating the spatial variability at macro- to micro-scales. 2 Materials and Methods 2.1 Study Area The current study has been carried out at Kalaburagi city (formerly known as Gulbarga City) located in the northern & Deepak Kumar deepakdeo2003@gmail.com; dkumar12@amity.edu Tavishi Tewary tavu.tavishi@gmail.com Sulochana Shekhar sulogis@gmail.com 1 Amity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Sector 125, Gautam Buddha Nagar, Noida, Uttar Pradesh 201303, India 2 Amity Business School (ABS), Amity University, Sector 125, Gautam Buddha Nagar, Noida, Uttar Pradesh 201303, India 3 School of Earth Sciences, Central University of Tamil Nadu, Neelakudi Campus, Kangalancherry Post, Thiruvarur, Tamil Nadu 610005, India 123 Iran J Sci Technol Trans Sci https://doi.org/10.1007/s40995-017-0469-5