Abstract
This study aims to examine the spatio-temporal urban expansion pattern and its impacts on green space variation as well as thermal behavior in Doon valley over the last two decades during 2000 and 2019. Landsat 5 and Landsat 8 images of February and May month of two study years 2000 and 2019 were used for the analysis. The land use change analysis revealed notable outgrowth of urbanization with 184% increase in Doon valley during 2000–2019. To examine the effects of locational factors on urban growth, relative Shannon entropy analysis was carried out based on two factors, i.e., distances from city center and roads. It was seen that all the roads and city center have witnessed consistent and higher urban spread in its surroundings with high relative entropy value more than 0.9. Further analysis shows that there was considerable loss of agriculture crop lands and fallow lands along the major roads and around city center. Forest area was mostly affected along the road towards Mussorie hill station (road 2) because of its hilly surroundings whereas in Subhash Nagar area (road 4), fallow land and cultivated land were mainly replaced by the development activities. Analysis was also carried out to assess the spatial-temporal distribution of land surface temperature (LST) and its changing dynamics with land covers. It revealed that LST has increased in all the land use types with overall increase of 1.86 °C and 8.62 °C in the months February and May, respectively, during the study period. It is also found that normalized difference vegetation index (NDVI) and LST are negatively correlated with R2 0.46 and 0.28 for the months February and May, respectively. However, the correlation between NDVI and LST was found highly significant with P value less than 0.01. Therefore, spatial and temporal changes of different land use types especially rapid urbanization at the cost of green spaces with rampant anthropogenic activities is one of the main factor for LST increase in the study area. Moreover, this temperature rise with ever-increasing anthropogenic activities is not a healthy indication for the hilly region like Doon Valley which may adversely affect the ecosystem stability and its resources as well. The study may be used as reference for future ecological and urban management studies and policies.
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Al-sharif, A. A., Pradhan, B., Shafri, H. Z. M., & Mansor, S. (2013). Spatio-temporal analysis of urban and population growths in Tripoli using remotely sensed data and GIS. Indian Journal of Science and Technology, 6(8), 5134–5142.
Amirtham, L., & Devadas, M. (2009). Analysis of land surface temperature and land use/land cover types using remote sensing imagery-a case in Chennai city, India. The Seventh International Conference on Urba.
Asselman, N. E. M., & Middelkoop, H. (1995). Floodplain sedimentation: quantities, patterns and processes. Earth Surface Processes and Landforms, 20(6), 481–499. https://doi.org/10.1002/esp.3290200602.
Barrera, F. D. L., & Henriquez, C. (2017). Vegetation cover change in growing urban agglomerations in Chile. Ecological Indicators, 81, 265–273.
Barsi, J. A., Schott, J. R., Hook, S. J., Raqueno, N. G., Markham, B. L., & Radocinski, R. G. (2014). Landsat-8 thermal infra red sensor (TIRS) vicarious radiometric calibration. Remote Sensing, 6(11), 11607–11626.
Benfield, F. K., Raimi, M. D., & Chen, D. D. (1999). Once there were greenfields: How urban sprawl is undermining America’s environment, economy and social fabric. Washington: The Natural Resources Defence Council.
Crutzen, P. J. (2004). New directions: the growing urban heat and pollution ‘island’ effect–impact on chemistry and climate. Atmospheric Environment, 38, 3539–3540.
Dar, I., Qadir, J., & Shukla, A. (2019). Estimation of LST from multi-sensor thermal remote sensing data and evaluating the influence of sensor characteristics. Annals of GIS, 25(3), 263–281.
Deka, J., Tripathi, O. P., & Khan, M. L. (2012). Urban growth trend analysis using Shannon entropy approach – a case study in north east India. International Journal of Geomatics and Geosciences, 2(4), 1062–1068.
Deosthali, V. (2000). Impacts of rapid urban growth on heat and moisture islands in Pune City, India. Atmospheric Environment, 34, 2745–2754.
Dutta, D., Rahman, A., & Kundu, A. (2015). Growth of Dehradun city: an application of linear spectral unmixing (LSU) technique using multi-temporal landsat satellite data sets. Remote Sensing Applications: Society and Environment, 1, 98–111. https://doi.org/10.1016/j.rsase.2015.07.001.
El-Raey, M., Fouda, Y., & Gal, P. (2000). GIS for environmental assessment of the impacts of urban encroachment on Rosetta region, Egypt. Environmental Monitoring and Assessment, 60(2), 217–233. https://doi.org/10.1023/A:1006195006898.
Fung, T., & Ledrew, E. (1987). Application of principal components analysis to change detection. Photogrammetric Engineering and Remote Sensing, 53(12), 1649–1658.
Gillespie, A. R., Rokugawa, S., Matsunaga, T., Cothern, J. S., Hook, S. J., & Kahle, A. B. (1998). A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36, 1113–1126.
Grimm, N. B., Morgan, G. J., Pickett, S. T., & Redman, C. L. (2000). Integrated approaches to long-term studies of urban ecological systems. Bioscience, 50(7), 571–584.
Gupta, K. (2013). Unprecedented growth of Dehradun urban area: a spatio-temporal analysis. International Journal of Advanced Remote Sensing GIS and Geography, 1, 47–56.
Hathout, S. (2002). The use of GIS for monitoring and predicting urban growth in East and West St Paul, Winnipeg, Manitoba, Canada. Journal of Environmental Management, 66(3), 229–238.
Hayes, D. J., & Sader, S. A. (2001). Change detection techniques for monitoring forest clearing and vegetation regrowth in a tropical moist forest. Photogrammetric Engineering and Remote Sensing, 67(9), 1067–1075.
Hedblom, M., & Söderström, B. (2008). Woodlands across Swedish urban gradients: Status, structure and management implications. Landscape and Urban Planning, 84(1), 62–73. https://doi.org/10.1016/j.landurbplan.2007.06.007.
Hoffhine-Wilson, E. F., & Sader, S. A. (2002). Detection of forest type using multiple dates of Landsat TM imagery. Remote Sensing of Environment, 80, 385–396.
Hudak, A. T., & Wessman, C. A. (1998). Textural analysis of historical aerial photography to characterize woody plant encroachment in South African Savanna. Remote Sensing of Environment, 66(3), 317–330. https://doi.org/10.1016/S0034-4257(98)00078-9.
Ioannis, M., & Meliadis, M. (2011). Multi-temporal Landsat image classification and change analysis of land cover/use in the prefecture of Thessaloiniki, Greece. Proceeding of the IAEES, 1(1), 15–25.
Jana, C., Alam, N. M., Shrimali, S. S., Kumar, G., Ghosh, B. N., & Mishra, P. K. (2015). Rainfall extremity in Doon valley of Uttarakhand - reorienting agricultural management. International Journal of Agricultural and Statistical Sciences, 11(2), 425431.
Jat, M. K., Garg, P. K., & Khare, D. (2007). Monitoring and modeling urban sprawl using remote sensing and GIS techniques. International Journal of Applied Earth Observation and Geoinformation, 10, 26–43.
Jha, C. S., Dutt, C. B. S., & Bawa, K. S. (2000). Deforestations and land use changes in Western Ghats, India. Current Science, 79, 231–237.
Jimenez-Munoz, J. C., & Sobrino, J. A. (2003). A generalized single-channel method for retrieving landsurface temperature from remote sensing data. Journal of Geophysical Research, 108, 4688–4694.
Kaufmann, R. K., Seto, K. C., Shneider, A., Liu, Z., Zhou, L., & Wang, W. (2007). Climate response to rapid urban growth: Evidence of human-induced precipitation deficit. Journal of Climate, 20, 2299–2306.
Kim, Y. H., & Baik, J. J. (2004). Spatial and temporal structure of the urban heat island in Seoul. Journal of Applied Meteorology, 44, 591–605.
Kumar, J. A. V., Pathan, S. K., & Bhanderi, R. J. (2007). Spatio-temporal analysis for monitoring urban growth–a case study of Indore city. Journal of the Indian Society of Remote Sensing, 35(1), 11–20.
Kumari, B., Tayyab, M., Salman, S., Mallick, J., Khan, M. F., & Rahman, A. (2018). Satellite-driven land surface temperature (LST) using Landsat 5, 7 (TM/ETM+ SLC) and Landsat 8 (OLI/TIRS) data and its association with built-up and green cover over urban Delhi, India. Remote Sensing in Earth Systems Sciences, 1, 63–78. https://doi.org/10.1007/s41976-018-0004-2.
Landsberg, H. E. (1981). The urban climate. New York: Academic.
Li, J. (2006). Estimating land surface temperature from Landsat-5 TM. Remote Sensing Technological Application, 21, 322–326.
Li, Y., Zhao, M., Motesharrei, S., Mu, Q., Kalnay, E., & Li, S. (2015). Local cooling and warming effects of forests based on satellite observations. Nature Communications, 6, 6603. https://doi.org/10.1038/ncomms7603.
Liu, C., & Li, Y. (2018). Spatio-temporal features of urban heat island and its relationship with land use/cover in mountainous city: a case study in Chongqing. Sustainability, 10, 1943. https://doi.org/10.3390/su10061943.
Long, H., Wum, X., Wangm, W., & Dong, G. (2008). Analysis of urban-rural land-use change during 1995-2006 and its policy dimensional driving forces in Chongqing, China. Sensors, 8(2), 681–699. https://doi.org/10.3390/s8020681.
Lu, Y., Feng, P., Shen, C., & Sun, J. (2009). Urban heat island in summer of Nanjing based on TM data. In Proceedings of 2009 Joint Urban Remote Sensing Event (pp. 1–5). Shanghai, China.
Maktav, D., Erbek, F., & Jürgens, C. (2005). Remote sensing of urban areas. International Journal of Remote Sensing, 26(4), 655–659. https://doi.org/10.1080/01431160512331316469.
Malik, M. S., & Shukla, J. P. (2018). Retrieving of land surface temperature using thermal remote sensing and GIS techniques in Kandaihimmat watershed, Hoshangabad, Madhya Pradesh. Journal of the Geological Society of India, 92(3), 298–304. https://doi.org/10.1007/s12594-018-1010-y.
Mallupattu, P. K., & Reddy, J. D. S. (2013). Analysis of land use/land cover changes using remote sensing data and GIS at an urban area, Tirupati, India. The Scientific World Journal. https://doi.org/10.1155/2013/268623.
Markham, B. L., & Barker, J. L. (1985). Spectral characterization of the LANDSAT thematic mapper sensors. International Journal of Remote Sensing, 6, 697–716. https://doi.org/10.1080/01431168508948492.
Martinuzzi, S., Gould, W. A., & González, O. M. R. (2007). Land development, land use, and urban sprawl in Puerto Rico integrating remote sensing and population census data. Landscape and Urban Planning, 79(3–4), 288–297.
Mas, J. F. (1999). Monitoring land-cover changes: a comparison of change detection techniques. International Journal of Remote Sensing, 20, 139–152. https://doi.org/10.1080/014311699213659.
Mishra, P. K., Rai, A., & Rai, S. C. (2019). Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India. The Egyptian Journal of Remote Sensing and Space Science. https://doi.org/10.1016/j.ejrs.2019.02.001.
Omran, E. S. E. (2012). Detection of land-use and surface temperature change at different resolutions. Journal of Geographic Information System, 4, 189–203.
Pathan, S., Shukla, V., Patel, R., Patel, B., & Mehta, K. (1991). Urban land use mapping: a case study of Ahmedabad city and its environs. Journal of the Indian Society of Remote Sensing, 19(2), 95–112.
Pourghasemi, H. R., Mohammadi, M., & Pradhan, B. (2012). Landslide susceptibility mapping using index of entropy and conditional probability models at Safarood Basin, Iran. Catena, 97, 71–84. https://doi.org/10.1016/j.catena.2012.05.005.
Qin, Z., Zhang, M., Amon, K., & Pedro, B. (2001). Mono-window algorithm for retrieving land surface temperature from Landsat TM 6 data. Acta Geographica Sinica, 56, 456–466.
Rajendran, P., & Mani, K. (2015). Estimation of spatial variability of land surface temperature using Landsat 8 imagery. The International Journal Of Engineering And Science, 4(11), 19–23.
Sharma, K., & Jalan, S. (2013). Change assessment of urban green spaces of Dehradun city using image derived parameters. Transactions of the Institute of Indian Geographers, 35, 63–74.
Singh, P., & Khanduri, K. (2011). Land use and land cover change detection through remote sensing & GIS technology: case study of Pathankot and DharKalan tehsils, Punjab. International Journal of Geomatics and Geosciences, 1, 839–846.
Singh, O., Arya, P., & Chaudhary, B. S. (2013a). On rising temperature trends at Dehradun in Doon valley of Uttarakhand, India. Journal of Earth System Science, 122(3), 613–622.
Singh, A., Singh, S., Garg, P. K., & Khanduri, K. (2013b). Land use and land cover change detection: a comparative approach using post classification change matrix and discriminate function change detection methodology of Allahabad City. International Journal of Current Engineering and Technology, 3, 142–148.
Sobrino, J. A., Li, Z. L., Stoll, M. P., & Becker, F. (1996). Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data. International Journal of Remote Sensing, 1996(17), 2089–2114.
Stathopoulou, M., & Cartalis, C. (2007). Daytime urban heat islands from Landsat ETM+ and Corine land cover data: an application to major cities in Greece. Solar Energy, 81(3), 358–368.
Sudhira, H., Ramachandra, T., & Jagadish, K. (2004). Urban sprawl: metrics, dynamics and modelling using GIS. International Journal of Applied Earth Observation and Geoinformation, 5(1), 29–39. https://doi.org/10.1016/j.jag.2003.08.002.
Sun, D., & Kafatos, M. (2007). Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America. Geophysical Research Letters, 34, L24406. https://doi.org/10.1029/2007GL031485.
Sun, Q., Tan, J., & Xu, Y. (2010). An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta region in South China. Environmental Earth Science, 59, 1047–1055.
Suzanchi, K., & Kaur, R. (2011). Land use land cover change in National Capital Region of India: a remote sensing & GIS based two decadal spatial-temporal analyses. Procedia - Social and Behavioral Sciences, 21, 212–221. https://doi.org/10.1016/j.sbspro.2011.07.044.
Tiwari, K., & Khanduri, K. (2011). Land use / land cover changes detection in Doon valley (Dehradun Tehsil), Uttarakhand: using GIS & remote sensing technique. International Journal of Geomatics and Geosciences, 2, 34–41.
Weng, Q. (2001). A remote sensing – GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 22(10), 1999–2014. https://doi.org/10.1080/713860788.
Weng, Q. H., Lu, D. S., & Schubring, J. (2004). Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467–483.
Yang, J., & Qiu, J. (1996). The empirical expressions of the relation between precipitable water and groundwater vapor pressure for some areas in China. Scientia Atmospherica Sinica, 20, 620–626.
Yeh, A. G. O., & Li, X. (1998). Principal component analysis of stacked multi-temporal images for the monitoring of rapid urban expansion in the Pearl River. International Journal of Remote Sensing, 19(8), 501–1518. https://doi.org/10.1080/014311698215315.
Yeh, A. G. O., & Xia, L. (2001). Measurement and monitoring of urban sprawl in a rapidly growing region using entropy. Photogrammetric Engineering and Remote Sensing, 67(1), 83–90.
Zhang, Y. (2006). Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect. Journal of Remote Sensing, 10, 789–797.
Zhou, X., & Wang, Y. C. (2011). Spatial–temporal dynamics of urban green space in response to rapid urbanization and greening policies. Landscape and Urban Planning, 100(3), 268–277.
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The authors wish to thank the Director, ICAR-Indian Institute of Soil and Water Conservation (IISWC), Dehradun, for providing financial assistance for this study.
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Jana, C., Mandal, D., Shrimali, S.S. et al. Assessment of urban growth effects on green space and surface temperature in Doon Valley, Uttarakhand, India. Environ Monit Assess 192, 257 (2020). https://doi.org/10.1007/s10661-020-8184-7
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DOI: https://doi.org/10.1007/s10661-020-8184-7