1. رضاییراد، هادی. (1396). تحلیل اثرات برنامهریزی کالبدی بر تعادل انرژی در نواحی شهر تهران، رساله دکتری، دانشگاه تربیت مدرس، تهران.
2. رضاییراد، هادی، و رفیعیان، مجتبی (1396). روندیابی تغییرات حرارتی سطوح نواحی شهر تهران، نشریه علمی- پژوهشی پژوهشهای محیط زیست، 8 (16):176-167.
3. رفیعیان، مجتبی و رضاییراد، هادی (1396). سنجش اثرات سبزینگی گیاهی در تحولات فضایی شدت جزیره حرارتی سطح کلانشهر تهران با استفاده از تصاویر ماهوارهای LANDSAT8 و ASTER، نشریه علمی- پژوهشی تحلیل فضایی مخاطرات محیطی، 4 (3):1-16.
4. Bhang, K. J., & Park, S. S. (2009). Evaluation of the surface temperature variation with surface settings on the urban heat island in Seoul, Korea, using Landsat-7 ETM+ and SPOT. IEEE Geoscience and Remote Sensing Letters, 6(4), 708-712. [
DOI:10.1109/LGRS.2009.2023825]
5. Bobrinskaya, M. (2012). Remote sensing for analysis of relationships between land cover and land surface temperature in ten megacities.
6. Collatz, G. J., Bounoua, L., Los, S. O., Randall, D. A., Fung, I. Y., & Sellers, P. J. (2000). A mechanism for the influence of vegetation on the response of the diurnal temperature range to changing climate. Geophysical Research Letters, 27(20), 3381-3384. [
DOI:10.1029/1999GL010947]
7. Gartland, L. M. (2012). Heat islands: understanding and mitigating heat in urban areas. Routledge. [
DOI:10.4324/9781849771559]
8. Guillevic, P. C., Privette, J. L., Coudert, B., Palecki, M. A., Demarty, J., Ottlé, C., & Augustine, J. A. (2012). Land Surface Temperature product validation using NOAA's surface climate observation networks-Scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS). Remote Sensing of Environment, 124, 282-298. [
DOI:10.1016/j.rse.2012.05.004]
9. Huang, C., Goward, S. N., Masek, J. G., Thomas, N., Zhu, Z., & Vogelmann, J. E. (2010). An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sensing of Environment, 114(1), 183-198. [
DOI:10.1016/j.rse.2009.08.017]
10. Kerr, Y. H., Lagouarde, J. P., Nerry, F., & Ottlé, C. (2004). Land surface temperature retrieval techniques and applications: Case of the AVHRR. In Thermal remote sensing in land surface processing (pp. 33-109). CRC Press. [
DOI:10.1201/9780203502174-c3]
11. Li, H. (2016). Pavement materials for heat island mitigation. Science Direct, 79-96. [
DOI:10.1016/B978-0-12-803476-7.00005-2]
12. Markham, B. L., Storey, J. C., Williams, D. L., & Irons, J. R. (2004). Landsat sensor performance: history and current status. IEEE transactions on geoscience and remote sensing, 42(12), 2691-2694. [
DOI:10.1109/TGRS.2004.840720]
13. Meng, Q. Y., Spector, D., Colome, S., & Turpin, B. (2009). Determinants of indoor and personal exposure to PM2. 5 of indoor and outdoor origin during the RIOPA study. Atmospheric Environment, 43(36), 5750-5758. [
DOI:10.1016/j.atmosenv.2009.07.066] [
PMID] [
]
14. Moran, M. S., Scott, R. L., Keefer, T. O., Emmerich, W. E., Hernandez, M., Nearing, G. S., ... & O'Neill, P. E. (2009). Partitioning evapotranspiration in semiarid grassland and shrubland ecosystems using time series of soil surface temperature. agricultural and forest meteorology, 149(1), 59-72. [
DOI:10.1016/j.agrformet.2008.07.004]
15. Niu, C. Y., Musa, A., & Liu, Y. (2015). Analysis of soil moisture condition under different land uses in the arid region of Horqin sandy land, northern China. Solid Earth, 6(4), 1157-1167. [
DOI:10.5194/se-6-1157-2015]
16. Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly journal of the royal meteorological society, 108(455), 1-24.
https://doi.org/10.1256/smsqj.45501 [
DOI:10.1002/qj.49710845502]
17. Oke, T. R. (2002). Boundary layer climates. Routledge. [
DOI:10.4324/9780203407219] [
]
18. Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). Remotely sensed surface parameters governing urban climate change. Int. J. Remote Sens, 19, 1663-1681. [
DOI:10.1080/014311698215171]
19. Pitman, A. J., Avila, F. B., Abramowitz, G., Wang, Y. P., Phipps, S. J., & de Noblet-Ducoudré, N. (2011). Importance of background climate in determining impact of land-cover change on regional climate. Nature Climate Change, 1(9), 472-475. [
DOI:10.1038/nclimate1294]
20. Rajeshwari, A., & Mani, N. D. (2014). Estimation of land surface temperature of Dindigul district using Landsat 8 data. International journal of research in engineering and technology, 3(5), 122-126. [
DOI:10.15623/ijret.2014.0305025]
21. RezaeiRad, H., & Afzali, N. (2021). Measuring effects of building orientation and vegetation on thermal comfort by ENVI-Met (Case Study: Maslak Area, Istanbul).
22. RezaeiRad, H., & Afzali, N. (2024). The Role of City Information Modelling (CIM) in Evaluating the Spatial Correlation Between Vegetation Index Changes and Heat Island Severity in the Last Two Decades in Tehran Metropolis. In City Information Modelling (pp. 111-138). Singapore: Springer Nature Singapore. [
DOI:10.1007/978-981-99-9014-6_7]
23. RezaeiRad, H., & Rafieiana, M. (2016). Evaluating The Effects of High rise building On Urban Heat Island by Sky View Factor: A case study of Narmak neighborhood, Tehran. Naqshejahan- Basic studies and New Technologies of Architecture and Planning, 5(4), 13-22.
24. RezaeiRad, H., & Rafieyan, M. (2017). Estimating the spatial-temporal Changes in intensity of the heat island in Tehran Metropolitan by Using ASTER and Landsat8 Satellite Images. Regional Planning, 7(27), 47-60.
25. RezaeiRad, H., Rafieian, M., & Sozer, H. (2019). Evaluating the effects of increasing of building height on land surface temperature. International Journal Of Urban Management And Energy Sustainability, 1(1), 37-42.
26. Roy, D. P., Wulder, M. A., Loveland, T. R., Woodcock, C. E., Allen, R. G., Anderson, M. C., ... & Zhu, Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote sensing of Environment, 145, 154-172. [
DOI:10.1016/j.rse.2014.02.001]
27. Shukla, J., & Mintz, Y. (1982). Influence of land-surface evapotranspiration on the earth's climate. Science, 215(4539), 1498-1501. [
DOI:10.1126/science.215.4539.1498] [
PMID]
28. Skelhorn, C. P. (2013). A fine scale assessment of urban greenspace impacts on microclimate and building energy in Manchester. The University of Manchester (United Kingdom).
29. Sobrino, J. A., Caselles, V., & Coll, C. (1993). Theoretical split-window algorithms for determining the actual surface temperature. Il Nuovo Cimento C, 16, 219-236. [
DOI:10.1007/BF02524225]
30. Sun, J. (2011). Parameter estimation of coupled water and energy balance models based on stationarity constraints of soil moisture and temperature. Boston University. [
DOI:10.1029/2010WR009293]
31. Svensson, M. K., & Eliasson, I. (2002). Diurnal air temperatures in built-up areas in relation to urban planning. Landscape and urban planning, 61(1), 37-54. [
DOI:10.1016/S0169-2046(02)00076-2]
32. Tan, J., Zheng, Y., Tang, X., Guo, C., Li, L., Song, G., ... & Chen, H. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. International journal of biometeorology, 54, 75-84. [
DOI:10.1007/s00484-009-0256-x] [
PMID]
33. Tran, N., Powell, B., Marks, H., West, R., & Kvasnak, A. (2009). Strategies for design and construction of high-reflectance asphalt pavements. Transportation Research Record, 2098(1), 124-130. [
DOI:10.3141/2098-13]
34. Voogt, J. (2006). How researchers measure urban heat islands. In United States Environmental Protection Agency (EPA), state and local climate and energy program, heat island effect, urban heat island webcasts and conference calls.
35. Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote sensing of environment, 86(3), 370-384. [
DOI:10.1016/S0034-4257(03)00079-8]
36. Weng, Q., Fu, P., & Gao, F. (2014). Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data. Remote sensing of environment, 145, 55-67. [
DOI:10.1016/j.rse.2014.02.003]
37. Yang, X., Zhao, L., Bruse, M., & Meng, Q. (2013). Evaluation of a microclimate model for predicting the thermal behavior of different ground surfaces. Building and Environment, 60, 93-104. [
DOI:10.1016/j.buildenv.2012.11.008]
38. Yuan, F., & Bauer, M. E. (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of environment, 106(3), 375-386. [
DOI:10.1016/j.rse.2006.09.003]
39. Zareie, S., Khosravi, H., & Nasiri, A. (2016). Derivation of land surface temperature from Landsat Thematic Mapper (TM) sensor data and analysing relation between land use changes and surface temperature. Solid Earth. Discuss, 1-15. [
DOI:10.5194/se-2016-22] [
]
40. Zhou, Y., & Ren, G. (2011). Change in extreme temperature event frequency over mainland China, 1961− 2008. Climate Research, 50(2-3), 125-139. [
DOI:10.3354/cr01053]
41.
42. رضاییراد، هادی. (1396). تحلیل اثرات برنامهریزی کالبدی بر تعادل انرژی در نواحی شهر تهران، رساله دکتری، دانشگاه تربیت مدرس، تهران.
43. رضاییراد، هادی، و رفیعیان، مجتبی (1396). روندیابی تغییرات حرارتی سطوح نواحی شهر تهران، نشریه علمی- پژوهشی پژوهشهای محیط زیست، 8 (16):176-167.
44. رفیعیان، مجتبی و رضاییراد، هادی (1396). سنجش اثرات سبزینگی گیاهی در تحولات فضایی شدت جزیره حرارتی سطح کلانشهر تهران با استفاده از تصاویر ماهوارهای LANDSAT8 و ASTER، نشریه علمی- پژوهشی تحلیل فضایی مخاطرات محیطی، 4 (3):1-16.
45. Bhang, K. J., & Park, S. S. (2009). Evaluation of the surface temperature variation with surface settings on the urban heat island in Seoul, Korea, using Landsat-7 ETM+ and SPOT. IEEE Geoscience and Remote Sensing Letters, 6(4), 708-712. [
DOI:10.1109/LGRS.2009.2023825]
46. Bobrinskaya, M. (2012). Remote sensing for analysis of relationships between land cover and land surface temperature in ten megacities.
47. Collatz, G. J., Bounoua, L., Los, S. O., Randall, D. A., Fung, I. Y., & Sellers, P. J. (2000). A mechanism for the influence of vegetation on the response of the diurnal temperature range to changing climate. Geophysical Research Letters, 27(20), 3381-3384. [
DOI:10.1029/1999GL010947]
48. Gartland, L. M. (2012). Heat islands: understanding and mitigating heat in urban areas. Routledge. [
DOI:10.4324/9781849771559]
49. Guillevic, P. C., Privette, J. L., Coudert, B., Palecki, M. A., Demarty, J., Ottlé, C., & Augustine, J. A. (2012). Land Surface Temperature product validation using NOAA's surface climate observation networks-Scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS). Remote Sensing of Environment, 124, 282-298. [
DOI:10.1016/j.rse.2012.05.004]
50. Huang, C., Goward, S. N., Masek, J. G., Thomas, N., Zhu, Z., & Vogelmann, J. E. (2010). An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sensing of Environment, 114(1), 183-198. [
DOI:10.1016/j.rse.2009.08.017]
51. Kerr, Y. H., Lagouarde, J. P., Nerry, F., & Ottlé, C. (2004). Land surface temperature retrieval techniques and applications: Case of the AVHRR. In Thermal remote sensing in land surface processing (pp. 33-109). CRC Press. [
DOI:10.1201/9780203502174-c3]
52. Li, H. (2016). Pavement materials for heat island mitigation. Science Direct, 79-96. [
DOI:10.1016/B978-0-12-803476-7.00005-2]
53. Markham, B. L., Storey, J. C., Williams, D. L., & Irons, J. R. (2004). Landsat sensor performance: history and current status. IEEE transactions on geoscience and remote sensing, 42(12), 2691-2694. [
DOI:10.1109/TGRS.2004.840720]
54. Meng, Q. Y., Spector, D., Colome, S., & Turpin, B. (2009). Determinants of indoor and personal exposure to PM2. 5 of indoor and outdoor origin during the RIOPA study. Atmospheric Environment, 43(36), 5750-5758. [
DOI:10.1016/j.atmosenv.2009.07.066] [
PMID] [
]
55. Moran, M. S., Scott, R. L., Keefer, T. O., Emmerich, W. E., Hernandez, M., Nearing, G. S., ... & O'Neill, P. E. (2009). Partitioning evapotranspiration in semiarid grassland and shrubland ecosystems using time series of soil surface temperature. agricultural and forest meteorology, 149(1), 59-72. [
DOI:10.1016/j.agrformet.2008.07.004]
56. Niu, C. Y., Musa, A., & Liu, Y. (2015). Analysis of soil moisture condition under different land uses in the arid region of Horqin sandy land, northern China. Solid Earth, 6(4), 1157-1167. [
DOI:10.5194/se-6-1157-2015]
57. Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly journal of the royal meteorological society, 108(455), 1-24.
https://doi.org/10.1256/smsqj.45501 [
DOI:10.1002/qj.49710845502]
58. Oke, T. R. (2002). Boundary layer climates. Routledge. [
DOI:10.4324/9780203407219] [
]
59. Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). Remotely sensed surface parameters governing urban climate change. Int. J. Remote Sens, 19, 1663-1681. [
DOI:10.1080/014311698215171]
60. Pitman, A. J., Avila, F. B., Abramowitz, G., Wang, Y. P., Phipps, S. J., & de Noblet-Ducoudré, N. (2011). Importance of background climate in determining impact of land-cover change on regional climate. Nature Climate Change, 1(9), 472-475. [
DOI:10.1038/nclimate1294]
61. Rajeshwari, A., & Mani, N. D. (2014). Estimation of land surface temperature of Dindigul district using Landsat 8 data. International journal of research in engineering and technology, 3(5), 122-126. [
DOI:10.15623/ijret.2014.0305025]
62. RezaeiRad, H., & Afzali, N. (2021). Measuring effects of building orientation and vegetation on thermal comfort by ENVI-Met (Case Study: Maslak Area, Istanbul).
63. RezaeiRad, H., & Afzali, N. (2024). The Role of City Information Modelling (CIM) in Evaluating the Spatial Correlation Between Vegetation Index Changes and Heat Island Severity in the Last Two Decades in Tehran Metropolis. In City Information Modelling (pp. 111-138). Singapore: Springer Nature Singapore. [
DOI:10.1007/978-981-99-9014-6_7]
64. RezaeiRad, H., & Rafieiana, M. (2016). Evaluating The Effects of High rise building On Urban Heat Island by Sky View Factor: A case study of Narmak neighborhood, Tehran. Naqshejahan- Basic studies and New Technologies of Architecture and Planning, 5(4), 13-22.
65. RezaeiRad, H., & Rafieyan, M. (2017). Estimating the spatial-temporal Changes in intensity of the heat island in Tehran Metropolitan by Using ASTER and Landsat8 Satellite Images. Regional Planning, 7(27), 47-60.
66. RezaeiRad, H., Rafieian, M., & Sozer, H. (2019). Evaluating the effects of increasing of building height on land surface temperature. International Journal Of Urban Management And Energy Sustainability, 1(1), 37-42.
67. Roy, D. P., Wulder, M. A., Loveland, T. R., Woodcock, C. E., Allen, R. G., Anderson, M. C., ... & Zhu, Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote sensing of Environment, 145, 154-172. [
DOI:10.1016/j.rse.2014.02.001]
68. Shukla, J., & Mintz, Y. (1982). Influence of land-surface evapotranspiration on the earth's climate. Science, 215(4539), 1498-1501. [
DOI:10.1126/science.215.4539.1498] [
PMID]
69. Skelhorn, C. P. (2013). A fine scale assessment of urban greenspace impacts on microclimate and building energy in Manchester. The University of Manchester (United Kingdom).
70. Sobrino, J. A., Caselles, V., & Coll, C. (1993). Theoretical split-window algorithms for determining the actual surface temperature. Il Nuovo Cimento C, 16, 219-236. [
DOI:10.1007/BF02524225]
71. Sun, J. (2011). Parameter estimation of coupled water and energy balance models based on stationarity constraints of soil moisture and temperature. Boston University. [
DOI:10.1029/2010WR009293]
72. Svensson, M. K., & Eliasson, I. (2002). Diurnal air temperatures in built-up areas in relation to urban planning. Landscape and urban planning, 61(1), 37-54. [
DOI:10.1016/S0169-2046(02)00076-2]
73. Tan, J., Zheng, Y., Tang, X., Guo, C., Li, L., Song, G., ... & Chen, H. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. International journal of biometeorology, 54, 75-84. [
DOI:10.1007/s00484-009-0256-x] [
PMID]
74. Tran, N., Powell, B., Marks, H., West, R., & Kvasnak, A. (2009). Strategies for design and construction of high-reflectance asphalt pavements. Transportation Research Record, 2098(1), 124-130. [
DOI:10.3141/2098-13]
75. Voogt, J. (2006). How researchers measure urban heat islands. In United States Environmental Protection Agency (EPA), state and local climate and energy program, heat island effect, urban heat island webcasts and conference calls.
76. Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote sensing of environment, 86(3), 370-384. [
DOI:10.1016/S0034-4257(03)00079-8]
77. Weng, Q., Fu, P., & Gao, F. (2014). Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data. Remote sensing of environment, 145, 55-67. [
DOI:10.1016/j.rse.2014.02.003]
78. Yang, X., Zhao, L., Bruse, M., & Meng, Q. (2013). Evaluation of a microclimate model for predicting the thermal behavior of different ground surfaces. Building and Environment, 60, 93-104. [
DOI:10.1016/j.buildenv.2012.11.008]
79. Yuan, F., & Bauer, M. E. (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of environment, 106(3), 375-386. [
DOI:10.1016/j.rse.2006.09.003]
80. Zareie, S., Khosravi, H., & Nasiri, A. (2016). Derivation of land surface temperature from Landsat Thematic Mapper (TM) sensor data and analysing relation between land use changes and surface temperature. Solid Earth. Discuss, 1-15. [
DOI:10.5194/se-2016-22] [
]
81. Zhou, Y., & Ren, G. (2011). Change in extreme temperature event frequency over mainland China, 1961− 2008. Climate Research, 50(2-3), 125-139. [
DOI:10.3354/cr01053]