Andersson M., Milberg P., Bergman K.O. (2011): Low pre-death growth rates of oak (Quercus robur L.) – Is oak death a long-term process induced by dry years? Annals of Forest Science, 68: 159–168. Azizi G., Miri M., Mohamadi H., Pourhashemi M. (2015): Analysis of relationship between forest decline and precipitation changes in Ilam province. Iranian Journal of Forest and Poplar Research, 23: 502–515. (in Persian) Bannari A., Asalhi H., Teillet P.M. (2002): Transformed difference vegetation index (TDVI) for vegetation cover mapping. In: Proceedings of the Geoscience and Remote Sensing Symposium, Toronto, June 24–28, 2002: 3053–3055.Batten G. D. (1998): Plant analysis using near infrared reflectance spectroscopy: the potential and the limitations. Australian Journal of Experimental Agriculture, 38, 697- https://doi.org/10.1071/EA97146Boegh Eva, Soegaard H., Broge N., Hasager C.B., Jensen N.O., Schelde K., Thomsen A. (2002): Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture. Remote Sensing of Environment, 81, 179-193 https://doi.org/10.1016/S0034-4257(01)00342-XCRIPPEN R (1990): Calculating the vegetation index faster. Remote Sensing of Environment, 34, 71-73 https://doi.org/10.1016/0034-4257(90)90085-ZFoley William J., McIlwee Allen, Lawler Ivan, Aragones Lem, Woolnough Andrew P., Berding Nils (1998): Ecological applications of near infrared reflectance spectroscopy - a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia, 116, 293-305 https://doi.org/10.1007/s004420050591Gitelson Anatoly A., Merzlyak Mark N. (1998): Remote sensing of chlorophyll concentration in higher plant leaves. Advances in Space Research, 22, 689-692 https://doi.org/10.1016/S0273-1177(97)01133-2Haboudane D (2004): Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sensing of Environment, 90, 337-352 https://doi.org/10.1016/j.rse.2003.12.013 Hosseinzadeh J., Pourhashemi M. (2015): An investigation on the relationship between crown indices and the severity of oak forests decline in Ilam. Iranian Journal of Forest, 7: 57–66. (in Persian)Huete A.R (1988): A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25, 295-309 https://doi.org/10.1016/0034-4257(88)90106-XHuete A, Didan K, Miura T, Rodriguez E.P, Gao X, Ferreira L.G (2002): Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195-213 https://doi.org/10.1016/S0034-4257(02)00096-2 IPCC (2014): Climate Change 2014 – Impacts, Adaptation, and Vulnerability: Part A: Global and Sectoral Aspects. Cambridge, Cambridge University Press: 1140. Kauth R., Thomas G. (1976): The tasseled cap – a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. In: Swain P.H., Morrison D.B. (eds): Proceedings of the Symposium of Machine Processing of Remotely-Sensed Data, West Lafayette, June 29–July 1, 1976: 441–451. Lobell D.B., Asner G.P. (2003): Hyperion studies of crop stress in Mexico. In: Proceedings of the 12th Annual JPL Airborne Earth Science Workshop, Pasadena, Feb 24–28, 2003: 1–6. Morgan R.S., Rahim I.S., El-Hady M.A. (2015): A comparison of classification techniques for the land use/land cover classification. Global Advanced Research Journal of Agricultural Science, 4: 810–818.Prieto-Recio Cristina, Martín-García Jorge, Bravo Felipe, Diez Julio J. (2015): Unravelling the associations between climate, soil properties and forest management in Pinus pinaster decline in the Iberian Peninsula. Forest Ecology and Management, 356, 74-83 https://doi.org/10.1016/j.foreco.2015.07.033Rondeaux Geneviève, Steven Michael, Baret Frédéric (1996): Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55, 95-107 https://doi.org/10.1016/0034-4257(95)00186-7Roujean Jean-Louis, Breon François-Marie (1995): Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment, 51, 375-384 https://doi.org/10.1016/0034-4257(94)00114-3 Rouse J.W., Haas R.H., Schell J.A., Deering D.W. (1973): Monitoring vegetation systems in the Great Plains with ERTS. In: Freden S.C., Mercanti E.P., Becker M.A. (eds): Third Earth Resources Technology Satellite-1 Symposium. Volume 1: Technical Presentations, Section A, Washington, D.C., Dec 10–14, 1973: 309–317.Safari Amir, Sohrabi Hormoz, Powell Scott (2018): Comparison of satellite-based estimates of aboveground biomass in coppice oak forests using parametric, semiparametric, and nonparametric modeling methods. Journal of Applied Remote Sensing, 12, 1- https://doi.org/10.1117/1.JRS.12.046026Safari Amir, Sohrabi Hormoz, Powell Scott, Shataee Shaban (2017): A comparative assessment of multi-temporal Landsat 8 and machine learning algorithms for estimating aboveground carbon stock in coppice oak forests. International Journal of Remote Sensing, 38, 6407-6432 https://doi.org/10.1080/01431161.2017.1356488 Sagheb Talebi K., Sajedi T., Pourhashemi M. (2014): Forests of Iran: A Treasure from the Past, a Hope for the Future. Dordrecht, Springer Netherlands: 152.Sallé A., Nageleisen L.-M., Lieutier F. (2014): Bark and wood boring insects involved in oak declines in Europe: Current knowledge and future prospects in a context of climate change. Forest Ecology and Management, 328, 79-93 https://doi.org/10.1016/j.foreco.2014.05.027Sripada Ravi P., Heiniger Ronnie W., White Jeffrey G., Meijer Alan D. (2006): Aerial Color Infrared Photography for Determining Early In-Season Nitrogen Requirements in Corn. Agronomy Journal, 98, 968- https://doi.org/10.2134/agronj2005.0200Thiele Jan C., Nuske Robert S., Ahrends Bernd, Panferov Oleg, Albert Matthias, Staupendahl Kai, Junghans Udo, Jansen Martin, Saborowski Joachim (2017): Climate change impact assessment—A simulation experiment with Norway spruce for a forest district in Central Europe. Ecological Modelling, 346, 30-47 https://doi.org/10.1016/j.ecolmodel.2016.11.013Tucker Compton J. (1979): Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127-150 https://doi.org/10.1016/0034-4257(79)90013-0Ustuner Mustafa, Sanli Fusun Balik, Dixon Barnali (2017): Application of Support Vector Machines for Landuse Classification Using High-Resolution RapidEye Images: A Sensitivity Analysis. European Journal of Remote Sensing, 48, 403-422 https://doi.org/10.5721/EuJRS20154823Xu Hanqiu (2007): Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27, 3025-3033 https://doi.org/10.1080/01431160600589179ZANDEBASIRI M (2017): EVALUATING EXISTING STRATEGIES IN ENVIRONMENTAL CRISIS OF ZAGROS FORESTS OF IRAN. Applied Ecology and Environmental Research, 15, 621-632 https://doi.org/10.15666/aeer/1503_621632