تحلیل تغییرات پوشش زمین در اثر آتش سوزی جنگل های زاگرس با استفاده از ماشین بردار پشتیبانی (SVM) و تاثیر آن بر دمای سطح زمین (LST) و شاخص های طیفی NDWI، NDSI، NDVI و MIDII (منطقه مورد مطالعه: جنگل های کوه خائیز گچساران)

Abbott, K. N., Leblon, B., Staples, G. C., MacLean, D. A., & Alexander, M. E. (2007). Fire danger monitoring using RADARSAT-1 over northern boreal forests. International Journal of Remote Sensing, 28(6), 1317–1338.

Abdollahi, M., Islam, T., Gupta, A., & Hassan, Q. K. (2018). An advanced forest fire danger forecasting system: integration of remote sensing and historical sources of ignition data. Remote Sensing, 10, 923.

Allgöwer, B., Carlson, J. D., & van Wagtendonk, J. W. (2003). Introduction to fire danger rating and remote sensing – Will remote sensing enhance wildland fire danger rating? In E. Chuvieco (Ed.), Wildland Fire Danger Estimation and Mapping - The Role of Remote Sensing Data (pp. 1–19). World Scientific.

Allen, D. E., Singh, B. P., & Dalal, R. C. (2011). Soil health indicators under climate change: A review of current knowledge. In B. P. Singh (Ed.), Soil Health and Climate Change (pp. 25–35). Springer.

Bajocco, S., Guglietta, D., & Ricotta, C. (2015). Modeling fire occurrence at regional scale: does vegetation phenology matter? European Journal of Remote Sensing, 48, 763–775.

Bonn, F. J., & O'Neill, N. T. (1993). Thermal infrared remote sensing of soils: evolution, trends, and perspectives. Remote Sensing Review, 7, 281–302.

Carlson, J. D., & Burgan, R. E. (2003). Review of users’ needs in operational fire danger estimation: The Oklahoma example. International Journal of Remote Sensing, 24, 1601–1620.

Ceccato, P., Flasse, S., & Grégoire, J. M. (2002). Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications. Remote Sensing of Environment, 82, 198–207.

Chowdhury, E. H., & Hassan, Q. K. (2015a). Operational perspective of remote sensing-based forest fire danger forecasting systems. ISPRS Journal of Photogrammetry and Remote Sensing, 104, 224–236.

Chuvieco, E. (2003). Wildland Fire Danger Estimation and Mapping. World Scientific.

De Groot, W. J., & Flannigan, M. D. (2014). Climate change and early warning systems for wildland fire. In A. Singh & Z. Zommers (Eds.), Reducing Disaster: Early Warning Systems for Climate Change (pp. 127–151). Springer.

Deeming, J. E., Burgan, R. E., & Cohen, J. D. (1977). The National Fire Danger Rating System - 1978. Ogden.

Dousset, B., & Gourmelon, F. (2003). Satellite multi-sensor data analysis of urban surface temperatures and land cover. ISPRS Journal of Photogrammetry and Remote Sensing, 58, 43–54.

Ermida, S. L., Soares, P., Mantas, V., Göttsche, F. M., & Trigo, I. F. (2020). Google Earth Engine open-source code for land surface temperature estimation from the Landsat series. Remote Sensing, 12(1471), 21p.

Fall, S., Niyogi, D., Gluhovsky, A., Pielke Sr, R. A., Kalnay, E., Rochon, G. (2010). Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis. International Journal of Climatology, 30(13), 1980–1993.

Feizizadeh, B., Blaschke, T., Nazmfar, H., Akbari, E., & Kohbanani, H. R. (2013). Monitoring land surface temperature relationship to land use/land cover from satellite imagery in Maraqeh County, Iran. Journal of Environmental Planning and Management, 56, 1290–1315.

Fernandez-Guisuraga, J. M., Suárez-Seoane, S., Calvo, L. (2021). Radiative transfer modeling to measure fire impact and forest engineering resilience in short-term. ISPRS Journal of Photogrammetry and Remote Sensing, 176, 30–41.

Flannigan, M. D., Wotton, B. M., Marshall, G. A., de Groot, W. J., Johnston, J., Jurko, N., & Cantin, A. S. (2016). Fuel moisture sensitivity to temperature and precipitation: climate change implications. Climate Change, 134, 59–71.

Gao, B.-C. (1996). NDWI - A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.

Gunes, A. E., & Kovel, J. P. (2000). Using GIS in emergency management operations. Journal of Urban Planning and Development, 126, 136–149.

Hillel, D. (2004). Introduction to Environmental Soil Physics. Elsevier Academic Press.

Huesca, M., Litago, J., Merino-de-Miguel, S., Cicuendez-López-Ocaña, V., Palacios-Orueta, A. (2014). Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models. International Journal of Applied Earth Observation and Geoinformation, 26, 363–376.

Hunt, E. R., Li, L., Yilmaz, M. T., & Jackson, T. J. (2011). Comparison of vegetation water contents derived from shortwave-infrared and passive-microwave sensors over central Iowa. Remote Sensing of Environment, 115, 2376–2383.

Jensen, J. R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective. Pearson Prentice Hall.

Leblon, B., San-Miguel-Ayanz, J., Bourgeau-Chavez, L., & Kong, M. (2016). Remote sensing of wildfires. In N. Baghdadi & M. Zribi (Eds.), Land Surface Remote Sensing (pp. 55–95). Elsevier.

Li, Z., Tang, B., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A. (2013). Satellite-Derived Land Surface Temperature: Current Status and Perspectives. Remote Sensing of Environment, 131, 14–37.

Madeira, N. J. (1993). Etude Quantitative des Relations Constituants Minéralogiques-Réflectance Diffuse des Latosols Brésiliens: Application à l'utilisation Pédologique des Données Satellitaires TM (Région de Brasilia); Pierre et Marie Curie Université.

Manzo-Delgado, L., Aguirre-Gómez, R., & Álvarez, R. (2004). Multitemporal analysis of land surface temperature using NOAA-AVHRR: preliminary relationships between climatic anomalies and forest fires. International Journal of Remote Sensing, 25, 4417–4424.

Mao, D., Wang, Z., Luo, L., & Ren, C. (2012). Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation, 18, 528–536.

Matin, M. A., Chitale, V. S., Murthy, M. S. R., Uddin, K., Bajracharya, B., & Pradhan, S. (2017). Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information systems, and historical fire data. International Journal of Wildland Fire, 26, 276–286.

McArthur, A. G. (1967). Fire behavior in Eucalypt forests. Canberra: Australia Forestry and Timber Bureau.

McFeeters, S. K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17, 1425–1432.

Mhawej, M., Faour, G., Adjizian-Gerard, J. (2015). Wildfire likelihood’s elements: A literature review. Challenges, 6, 282–293.

Miller, C., & Ager, A. A. (2013). A review of recent advances in risk analysis for wildfire management. International Journal of Wildland Fire, 22, 1–14.

Minas, J. P., Hearne, J. W., & Handmer, J. W. (2012). A review of operations research methods applicable to wildfire management. International Journal of Wildland Fire, 21, 189–196.

Mohamed Shaluf, I. (2008). Technological disaster stages and management. Disaster Prevention and Management: An International Journal, 17, 114–126.

Ndossi, M. I., & Avdan, U. (2016). Application of open source coding technologies in the production of Land Surface Temperature (LST) maps from Landsat. A PyQGIS Plugin. Remote Sensing, 8, 31 p.

Noble, I. R., Bary, G. A. V., & Gill, A. M. (1980). McArthur's fire-danger meters are expressed as equations. Austral Ecology, 5, 201–203.

Nolan, R. H., Resco de Dios, V., Boer, M. M., Caccamo, G., Goulden, M. L., & Bradstock, R. A. (2016). Predicting dead fine fuel moisture at regional scales using vapor pressure deficit from MODIS and gridded weather data. Remote Sensing of Environment, 174, 100–108.

Oliveira, S., Laneve, G., Fusilli, L., Eftychidis, G., Nunes, A., Lourenço, L., Sebastián-López, A. (2017). A common approach to foster prevention and recovery of forest fires in Mediterranean Europe. In B. Fuerst-Bjeliš (Ed.), Mediterranean Identities - Environment, Society, Culture (pp. 337–361). IntechOpen.

Pal, S., & Ziaul, S. K. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban center. Egyptian Journal of Remote Sensing and Space Sciences, 20(1), 125–145.

Pan, J., Wang, W., & Li, J. (2016). Building probabilistic models of fire occurrence and fire risk zoning using logistic regression in Shanxi Province, China. Natural Hazards, 81, 1879–1899.

Rogers, A. S., & Kearney, M. S. (2004). Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices. International Journal of Remote Sensing, 25(12), 2317–2335.

Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite-1 Symposium, NASA SP-351 I, 309–317.

Ruffault, J., Martin-StPaul, N., Pimont, F., & Dupuy, J. L. (2018). How well do meteorological drought indices predict live fuel moisture content (LFMC)? An assessment for wildfire research and operations in Mediterranean ecosystems. Agricultural and Forest Meteorology, 262, 391–401.

Sabins, F. F. (1996). Remote Sensing: Principles and Interpretation (3rd ed.). W.H. Freeman and Company.

San-Miguel-Ayanz, J., Schulte, E., Schmuck, G., Camia, A., Strobl, P., Liberta, G., Giovando, C., Boca, R., Sedano, F., Kempeneers, P., McInerney, D., Whitmore, C., de Oliveira, S. S., Rodrigues, M., Durrant, T., Corti, P., Oehler, F., Vilar, L., & Amatulli, G. (2012). Comprehensive monitoring of wildfires in Europe: The European Forest Fire Information System (EFFIS). In J. Tiefenbacher (Ed.), Approaches to Managing Disaster - Assessing Hazards, Emergencies and Disaster Impacts (pp. 87–108). InTech.

Sayão, V. M., Demattê, J. A. M., Bedin, L. G., Nanni, M. R., Rizzo, R. (2018). Satellite land surface temperature and reflectance related to soil attributes. Geoderma, 325, 125–140.

Sirca, C., Salis, M., Arca, B., Duce, P., & Spano, D. (2018). Assessing the performance of fire danger indexes in a Mediterranean area. iForest - Biogeosciences and Forestry, 11, 563–571.

Slingsby, J. A., Moncrieff, G. R., & Wilson, A. M. (2020). Near-real-time forecasting and change detection for an open ecosystem with complex natural dynamics. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 15–25.

Sobrino, J. A., & Raissouni, N. (2000). Toward remote sensing methods for land cover dynamic monitoring: Application to Morocco. International Journal of Remote Sensing, 21(2), 353–366.

Song, X., Hansen, M. C., Stehman, S. V., Potapov, P. V., Tyukavina, A., Vermote, E. F., & Townshend, J. R. (2018). Global land change from 1982 to 2016. Nature, 560, 639–643.

Thompson, M. P., Haas, J. R., Gilbertson-Day, J. W., Scott, J. H., Langowski, P., Bowne, E., & Calkin, D. E. (2015). Development and application of a geospatial wildfire exposure and risk calculation tool. Environmental Modelling & Software, 63, 61–72.

Tran, D. X., Pla, F., Latorre-Carmona, P., Myint, S. W., Caetano, M., Kieu, H. V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119–132.

USGS. (2016). Landsat 5 (L5) data users handbook. LSDS-1574 Version. Retrieved from https://landsat.usgs.gov/documents/ on March 1, 2019.

Van Wagner, C. E. (1977). Conditions for the start and spread of crown fire. Canadian Journal of Forest Research, 7, 23–34.

Vezzani, F. M., & Mielniczuk, J. (2009). Uma visão sobre qualidade do solo. Revista Brasileira de Ciência do Solo, Viçosa, 33(4), 743–755.

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, 467–548.

Yu, B., Chen, F., Li, B., Wang, L., Wu, M. (2017). Fire risk prediction using remotely sensed products: a case of Cambodia. Photogrammetric Engineering & Remote Sensing, 83, 19–25.