CA-Markov Chain Analysis of Seasonal Land Surface Temperature and Land Use Land Cover Change Using Optical Multi-Temporal Satellite Data of Faisalabad, Pakistan

[1]  Onisimo Mutanga,et al.  Determining extreme heat vulnerability of Harare Metropolitan City using multispectral remote sensing and socio-economic data , 2018 .

[2]  A. Lenouo,et al.  Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO , 2015, Theoretical and Applied Climatology.

[3]  Ruci Wang,et al.  Scenario-based modelling for urban sustainability focusing on changes in cropland under rapid urbanization: A case study of Hangzhou from 1990 to 2035. , 2019, The Science of the total environment.

[4]  G. Mountrakis,et al.  Urban Growth Prediction: A Review of Computational Models and Human Perceptions , 2012 .

[5]  Hitomi Murakami,et al.  Monitoring Urban Spatial Growth in Harare Metropolitan Province, Zimbabwe , 2013 .

[6]  S. Shapiro,et al.  An Analysis of Variance Test for Normality (Complete Samples) , 1965 .

[7]  Hanqiu Xu.  Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[8]  B. Cohen.  Urban Growth in Developing Countries: A Review of Current Trends and a Caution Regarding Existing Forecasts , 2004 .

[9]  Xiaoling Chen,et al.  Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes , 2006 .

[10]  Bayes Ahmed,et al.  Modeling Urban Land Cover Growth Dynamics Using Multi-Temporal Satellite Images: A Case Study of Dhaka, Bangladesh , 2012, ISPRS Int. J. Geo Inf..

[11]  Bisheng Yang,et al.  Land surface temperature relation with normalized satellite indices for the estimation of spatio-temporal trends in temperature among various land use land cover classes of an arid Potohar region using Landsat data , 2019, Environmental Earth Sciences.

[12]  T. Mushore,et al.  Assessing the potential of integrated Landsat 8 thermal bands, with the traditional reflective bands and derived vegetation indices in classifying urban landscapes , 2017 .

[13]  D. Lu,et al.  Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States , 2007, Urban Ecosystems.

[14]  Jamal Jokar Arsanjani,et al.  ntegration of logistic regression , Markov chain and cellular automata odels to simulate urban expansion amal , 2012 .

[15]  D. Artis,et al.  Survey of emissivity variability in thermography of urban areas , 1982 .

[16]  Mariela Alfonzo,et al.  Euro What can we learn from existing research and from urban planning practice about how to support active living through active design in Chinese cities ? , 2013 .

[17]  S. K. McFeeters.  The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[18]  C. Nhemachena,et al.  Climate change adaptation for rural communities dependent on agriculture and tourism in marginal farming areas of the Hwange District, Zimbabwe. , 2014 .

[19]  P. Gong,et al.  Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data , 2002 .

[20]  Jay Gao,et al.  Use of normalized difference built-up index in automatically mapping urban areas from TM imagery , 2003 .

[21]  Manoj K. Jha,et al.  MODELING OF FUTURE LAND COVER LAND USE CHANGE IN NORTH CAROLINA USING MARKOV CHAIN AND CELLULAR AUTOMATA MODEL , 2014 .

[22]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[23]  Peter Hoffmann,et al.  A statistical model for the urban heat island and its application to a climate change scenario , 2012 .

[24]  Anthony J. Ratkowski,et al.  Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi- and hyperspectral imagery , 2005 .

[25]  Ugur Avdan,et al.  Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data , 2016, J. Sensors.

[26]  K. Aaviksoo,et al.  Simulating vegetation dynamics and land use in a mire landscape using a Markov model , 1995 .

[27]  G. Jia,et al.  Influence of land use change on urban heat island derived from multi‐sensor data , 2010 .

[28]  Nektarios Chrysoulakis,et al.  Using midday surface temperature to estimate Cooling Degree-Days from NOAA-AVHRR thermal infrared data: An application for Athens, Greece , 2006 .

[29]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[30]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[31]  Yikalo H. Araya,et al.  Analysis and Modeling of Urban Land Cover Change in Setúbal and Sesimbra, Portugal , 2010, Remote. Sens..

[32]  D. Mazvimavi.  Investigating changes over time of annual rainfall in Zimbabwe , 2010 .

[34]  T. S. Saitoh,et al.  Modeling and simulation of the Tokyo urban heat island , 1996 .

[35]  G. Gutman,et al.  The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models , 1998 .

[36]  Onisimo Mutanga,et al.  Exploiting machine learning algorithms for tree species classification in a semiarid woodland using RapidEye image , 2013 .

[37]  Keechoo Choi,et al.  Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh , 2013, Remote. Sens..

[38]  F. Lindsay,et al.  Dynamics of urban growth in the Washington DC metropolitan area, 1973-1996, from Landsat observations , 2000 .

[39]  G. Ramos-Fernández,et al.  Biodiversity conservation, traditional agriculture and ecotourism: Land cover/land use change projections for a natural protected area in the northeastern Yucatan Peninsula, Mexico , 2007 .

[40]  Onisimo Mutanga,et al.  Prediction of future urban surface temperatures using medium resolution satellite data in Harare metropolitan city, Zimbabwe , 2017 .

[41]  A. Huete,et al.  A feedback based modification of the NDVI to minimize canopy background and atmospheric noise , 1995 .

[42]  E. Omran.  Detection of Land-Use and Surface Temperature Change at Different Resolutions , 2012 .

[43]  Perumal Balakrishnan,et al.  Change analysis of land use/land cover and modelling urban growth in Greater Doha, Qatar , 2015, Ann. GIS.

[44]  H. Keshtkar,et al.  A spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models , 2016, Modeling Earth Systems and Environment.