Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Bước chân không gian-thời gian của urban hóa tại Surat, Thành phố Kim cương của Ấn Độ (1990–2009)
Tóm tắt
Đô thị hóa là một hiện tượng phổ biến, đặc biệt nổi bật ở các quốc gia đang phát triển. Mở rộng đô thị liên quan đến việc chuyển đổi đất từ các bề mặt đất ẩm ướt có thực vật sang các bề mặt đất không thấm nước và thiếu ẩm. Những biến đổi về đất đô thị làm thay đổi các tham số sinh lý một cách thúc đẩy sự phát triển của các đảo nhiệt và suy giảm sức khỏe môi trường. Nghiên cứu này phân tích mối quan hệ giữa các biến môi trường khác nhau bằng cách sử dụng dữ liệu viễn thám để nghiên cứu dấu vết không gian-thời gian của đô thị hóa ở thành phố Surat. Dữ liệu vệ tinh Landsat Thematic Mapper được sử dụng kết hợp với các kỹ thuật địa lý không gian để nghiên cứu đô thị hóa và sự tương quan giữa các tham số sinh lý do vệ tinh thu được, bao gồm: Chỉ số Chênh lệch Thực vật Nh normalized (NDVI), Chỉ số Chênh lệch Đô thị Nh normalized (NDBI), Chỉ số Chênh lệch Nước Nh normalized (NDWI), Chỉ số Chênh lệch Khô cằn Nh normalized (NDBI), NDWI đã sửa đổi và nhiệt độ bề mặt đất (LST). Sử dụng phân loại cây quyết định phân cấp, việc sử dụng đất và lớp phủ được chuẩn bị với độ chính xác là 90,4 % (kappa = 0,88) cho năm 1990 và 85 % (kappa = 0,81) cho năm 2009. Kết quả cho thấy thành phố đã mở rộng hơn 42,75 km2 trong vòng một thập kỷ, và những thay đổi này dẫn đến việc gia tăng nhiệt độ bề mặt. Ví dụ, sự chuyển đổi từ thực vật sang xây dựng đã dẫn đến sự tăng nhiệt độ bề mặt đất là 5,5 ± 2,6 °C, từ thực vật sang đất bỏ hoang là 6,7 ± 3 °C, từ đất bỏ hoang sang xây dựng là 3,5 ± 2,9 °C và từ xây dựng sang xây dựng dày đặc là 5,3 ± 2,8 °C. Đã thực hiện lập hồ sơ hướng cho LST để nghiên cứu các mô hình không gian của LST trong và xung quanh thành phố Surat. Sự xuất hiện của hai đỉnh LST mới cho năm 2009 được quan sát trong các hồ sơ N-S và NE-SW.
Từ khóa
#đô thị hóa #nhiệt độ bề mặt đất #viễn thám #sinh lý đô thị #biến đổi sử dụng đất #SuratTài liệu tham khảo
Alberti, M. (2005). The effects of urban patterns on ecosystem function. International Regional Science Review, 28, 168–192.
Amiri, R., Weng, Q., Alimohammadi, A., & Alavipanah, S. K. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113, 2606–2617.
Anyamba, A., & Tucker, C. J. (2005). Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003. Journal of Arid Environments, 63, 596–614.
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holtslag, A. A. M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. Journal of Hydrology, 212–213, 198–212.
Baur, B., & Baur, A. (1993). Climatic warming due to thermal radiation from an urban area as possible cause for the local extinction of a land snail. Applied Ecology, 30, 333–340.
Bolund, P., & Hunhammar, S. (1999). Ecosystem services in urban areas. Ecological Economics, 29, 293–301.
Bridhikitti, A., & Overcamp, T. J. (2012). Estimation of Southeast Asian rice paddy areas with different ecosystems from moderate-resolution satellite imagery. Agriculture, Ecosystems and Environment, 146, 113–120.
Brun, S. E., & Band, L. E. (2000). Simulating runoff behavior in an urbanizing watershed. Computers, Environment and Urban Systems, 24, 5–22.
Buyantuyev, A., & Wu, J. (2012). Urbanization diversifies land surface phenology in arid environments: interactions among vegetation, climatic variation, and land use pattern in the Phoenix metropolitan region, USA. Landscape and Urban Planning, 105, 149–159.
Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62, 241–252.
Census of India (2011). Government of India.
Chen, J. (2007). Rapid urbanization in China: a real challenge to soil protection and food security. Catena, 69, 1–15.
Chen, X.-L., Zhao, H.-M., Li, P.-X., & Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104, 133–146.
Delgado-V, C. A., & French, K. (2012). Parasite-bird interaction in urban areas: Current evidence and emerging questions. Landscape and urban planning, 105, 5–14.
Essa, W., et al. (2012). Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation, 19, 163–172.
Gabor, P., & Jombach, S. (2009). The relationship between the biological activity and the land surface temperature in Budapest. Applied Ecology and Environmental Research, 7, 241–251.
Gallo, K. P., Tarpley, J. D., Mcnab, A. L., & Karl, T. R. (1995). Assessment of urban heat islands: a satellite perspective. Atmospheric Research, 37, 37–43.
Gao, B. (1996). NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.
Gillies, R. R., et al. (1997). A verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature. International Journal of Remote Sensing, 18, 3145–3166.
Goetz, S. J. (1997). Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site. International Journal of Remote Sensing, 18, 71–94.
Huang, S. L., Yeh, C. T., & Chang, L. F. (2010). The transition to an urbanizing world and the demand for natural resources. Current Opinion in Environmental Sustainability, 2(3), 136–143
Jackson, T. J., et al. (2004). Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sensing of Environment, 92, 475–482.
Jiang, J., & Tian, G. (2010). Analysis of the impact of land use/land cover change on land surface temperature with remote sensing. Procedia Environmental Sciences, 2, 571–575.
Jong, R., et al. (2011). Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment, 115, 692–702.
Joshi, P. K., Bairawa, B. M., Sharma, R., & Sinha, V. S. P. (2011). Assessing urbanization patterns over India using temporal DMSP-OLS night time satellite data. Current Science, 100, 1479–1482.
Julien, Y., & Sobrino, J. A. (2009). The Yearly Land Cover Dynamics (YLCD) method: an analysis of global vegetation from NDVI and LST parameters. Remote Sensing of Environment, 113, 329–334.
Julien, Y., Sobrino, J. A., & Verhoef, W. (2006). Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999. Remote Sensing of Environment, 103, 43–55.
Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423, 528–531.
Kaushal, S., et al. (2008). Interaction between urbanisation and climate variability amplifies watershed nitrate export in Maryland. Environmental Science and Technology, 42, 5872–5878.
Li, Z., & Fox, J. M. (2012). Mapping rubber tree growth in mainland Southeast Asia using time-series MODIS 250 m NDVI and statistical data. Applied Geography, 32, 420–432.
Liu, L., & Zhang, Y. (2011). Urban heat island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sensing, 3, 1535–1552.
Ma, Y., Kuang, Y., & Huang, N. (2010). Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery. International Journal of Applied Earth Observation and Geoinformation, 12, 110–118.
Maki, M., Ishiahra, M., & Tamura, M. (2004). Estimation of leaf water status to monitor the risk of forest fires by using remotely sensed data. Remote Sensing of Environment, 90, 441–450.
Maxwell, S. K., & Sylvester, K. M. (2012). Identification of “ever-cropped” land (1984–2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study. Remote Sensing of Environment, 121, 186–195.
Mckinney, M. L. (2006). Urbanization as a major cause of biotic homogenization. Biological Conservation, 127, 247–260.
Nasipuri, P., & Chatterjee, A. (2009). Land use around Maithon reservoir: a study from high-resolution ASTER data. Current Science, 97, 25–27.
Ng, C. N., Xie, Y. J., & Yu, X. J. (2011). Measuring the spatio-temporal variation of habitat isolation due to rapid urbanization: a case study of the Shenzhen River cross-boundary catchment, China. Landscape and Urban Planning, 103, 44–54.
Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization. International Journal of Remote Sensing, 19, 1663–1681.
Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365.
Pu, R., Gong, P., Michishita, R., & Sasagawa, T. (2006). Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval. Remote Sensing of Environment, 104, 211–225.
Punia, M., Joshi, P. K., & Porwal, M. C. (2011). Decision tree classification of land use land cover for Delhi, India using IRS-P6 AWiFS data. Expert Systems with Applications, 38, 5577–5583.
Purevdorj, T., Tateishi, R., Ishiyama, T., & Honda, Y. (1998). Relationships between percent vegetation cover and vegetation indices. International Journal of Remote Sensing, 19, 3519–3535.
Qin, Z., Karnieli, A., & Berliner, P. (2001). A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel–Egypt border region. International Journal of Remote Sensing, 22, 3719–3746.
Raynolds, M. K., Comiso, J. C., Walker, D. A., & Verbyla, D. (2008). Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sensing of Environment, 112, 1884–1894.
Sandholt, I., Rasmussen, K., & Anderson, J. (2002). A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79, 213–224.
Schott, J. R., et al. (2001). Caliberation of Landsat thermal data and application to water resource studies. Remote Sensing of Environment, 78, 108–117.
Schwarz, N., Schlink, U., Franck, U., & Grobmann, K. (2012). Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators—an application for the city of Leipzig (Germany). Ecological Indicators, 18, 693–704.
Scolozzi, R., & Geneletti, D. (2012). A multi-scale qualitative approach to assess the impact of urbanization on natural habitats and their connectivity. Environmental Impact Assessment Review, 36, 9–22.
Serrano, L., et al. (2000). Deriving water content of chaparral vegetation from AVIRIS data. Remote Sensing of Environment, 74, 570–581.
Son, N. T., et al. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417–427.
Souch, C., & Grimmond, S. (2006). Applied climatology: urban climate. Progress in Physical Geography, 30, 270–279.
Stehman, S. V. (1996). Estimation of Kappa coefficient and its variance using stratified random sampling. Photogrammetric Engineering and Remote Sensing, 26, 401–407.
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 Sciences, 59, 1047–1055.
Surat Municipal Corporation (2011). Surat Municipal Corporation, http://www.suratmunicipal.org [Online]. Surat Municipal Corporation. Accessed 27 July 2012.
Tan, J., et al. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. International Journal of Biometeorology, 54, 75–84.
Taubenböck, H., et al. (2009). Urbanization in India—spatiotemporal analysis using remote sensing data. Computers, Environment and Urban Systems, 33, 179–188.
Threlfall, C. G., Law, B., & Banks, P. B. (2012). Sensitivity of insectivorous bats to urbanization: implications for suburban conservation planning. Biological Conservation, 146, 41–52.
Uddin, S., et al. (2010). A remote sensing classification for land-cover changes and micro-climate in Kuwait. International Journal of Sustainable Development and Planning, 5, 367–377.
UN. (2010). World Urbanisation Prospects—The 2009 Revision. New York: Department of Economic and Social Affairs, Population Division.
Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote Sensing of Environment, 86, 370–384.
Weiss, J. L., Gutzler, D. S., Coonrod, J. E. A., & Dahm, C. N. (2004). Long-term vegetation monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal of Arid Environments, 58, 249–272.
Weng, Q., Lu, D., & Schubring, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89, 467–483.
Wenhui, K. (2012). Spatio-temporal patterns of intra-urban land use change in Beijing, China Between 1984 and 2008. Chinese Geographical Sciences, 22, 210–220.
Wentz, E. A., et al. (2008). Expert system classification of urban land use/cover for Delhi, India. International Journal of Remote Sensing, 29(15), 4405–4427.
Whitford, V., Ennos, A. R., & Handley, J. F. (2001). “City form and natural process”—indicators for the ecological performance of urban areas and their application to Merseyside, UK. Landscape and Urban Planning, 57, 91–103.
Xiao, H., & Weng, Q. (2007). The impact of land use and land cover changes on land surface temperature in a karst area of China. Journal of Environmental Management, 85, 245–257.
Xiao, R., et al. (2008). Land surface temperature variation and major factors in Beijing, China. Photogrammetric Engineering and Remote Sensing, 74, 451–481.
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, 375–386.
Zha, Y., Gao, J., & Ni, S. (2003). Use of normalised difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583–594.
Zhang, Y., Odeh, I. O. A., & Han, C. (2009). Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 11, 256–264.
Zhou, L., et al. (2004). Evidence for a significant urbanization effect on climate in China. PNAS Geophysics, 101, 9540–9544.
Zhou, W., Huang, G., & Cadenasso, M. L. (2011). Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landscape and Urban Planning, 102(1), 54–63.