Document Type : Original Article
Authors
1 Assistant Prof., Dep. of Nature Engineering, Collage of Agriculture and Natural Resources of Darab, Shiraz University
2 Associate Prof., Dep. of Geography, Faculty of Economics, Management and Social Sciences, Shiraz University
Abstract
Keywords
Arzani, H., Kabuli, S.H., Nikkhah, A. & Jalili, A., 2004, Introduction of the Most Important Indicators for Determining the Nutritional Value of Pasture Plants, Journal of Natural Resources of Iran, 57(4), PP. 777-791.
Balogun, A.L., Yekeen, S.T., Pradhan, B. & Althuwaynee, O.F., 2020, Spatio-Temporal Analysis of Oil Spill Impact and Recovery Pattern of Coastal Vegetation and Wetland Using Multispectral Satellite Landsat 8-OLI Imagery and Machine Learning Models, Remote Sensing, 12(7), P. 1225.
Calera, A., Martínez, C. & Melia, J., 2001, A Procedure for Obtaining Green Plant Cover: Relation to NDVI in a Case Study for Barley, International Journal of Remote Sensing, 22(17), PP. 3357-3362.
Carreño-Conde, F., Sipols, AE., deBlas, CS. & Mostaza-Colado, D.A., 2021, Forecast Model Applied to Monitor Crops Dynamics Using Vegetation Indices (Ndvi), Applied Sciences, 11(4), PP. 1859300-307.
Cho, M.A., Skidmore, A., Corsi, F., Wieren, S.E.V. & Sobhan, I., 2007, Estimation of Green Grass/Herb Biomass from Airborne Hyperspectral Imagery Using Spectral Indices and Partial Least Squares Regression, International Journal of Applied Earth Observation and Geoinformation, 9, PP. 414-424.
Cohen, W.B., Maiersperger, T.K., Gower, S.T. & Turner, D.P., 2003, An Improved Strategy for Regression of Biophysical Variables and Landsat ETM+ Data, Remote Sensing of Environment, 84, PP. 561-571.
Daghestani, M., 2018, Application of Remote Sensing in Forest Management, First Regional Geomatic Conference, Islamshahr.
Ding, Z., Hu, X., Wan, Y., Wang, S. & Gao, B., 2016, Removal of Lead, Copper, Cadmium, Zinc, and Nickel from Aqueous Solutions by Alkali-Modified Biochar: Batch and Column Tests, Journal of Industrial and Engineering Chemistry, 33, PP. 239-245.
Eidvidge, C.D., 2007, Visible and Near Infrared Reflectance Charactristics of Dry Plant Materials, International Journal of Remote Sensing, 11(10), PP. 1775-1795.
Eitel, J.U.H., Gessler, P.E., Smith, A.M.S. & Robberecht, R., 2006, Suitability of Existing and Novel Spectral Indices to Remotely Detect Water Stress in Populus spp, Forest Ecology and Management, 229, PP. 170-182.
Fensholt, R. & Sandholt, I., 2003, Derivation of a Shortwave Infrared Water Stress Index from MODIS Near-and Shortwave Infrared Data in a Semiarid Environment, Remote Sensing of Environment, 87(1), PP. 111-121.
ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
Ferwerda, J.G., Skidmore, A.K. & Mutanga, O., 2005, Nitrogen Detection with Hyper-spectral Normalized Ratio Indices across Multiple Plant Species, International Journal of Remote Sensing, 26, PP. 4083-4095.
Gholizadeh, A. & Kopačková, V., 2019, Detecting Vegetation Stress as a Soil Contamination Proxy: A Review of Optical Proximal and Remote Sensing Techniques, International Journal of Environmental Science and Technology, 16(5), PP. 2511-2524.
Gitelson, A.A., Kaufman, Y.J., Stark, R. & Rundquist, D., 2002, Novel Algorithms for Remote Estimation of Vegetation Fraction, Remote Sensing of Environment, 80(1), PP. 76-87.
Goldsmith, F.B., 1991, Monitoring for Conservation and Ecology, Chapman & Hall, 275P.
Hansen, P.M. & Schjoerring, J.K., 2003, Reflectance Measurement of Canopy Biomass and Nitrogen Status in Wheat Crops Using Normalized Difference Vegetation Indices and Partial Least Squares Regression, Remote Sensing Environ, 86, PP. 542-553.
Horler, D.N.H., Dockray, M. & Barber, J., 1983, The Red Edge of Plant Leaf Reflectance, International Journal of Remote Sensing, 4, PP. 273-288.
Hubbard, S.S., Schmutz, M., Balde, A., Falco, N., Peruzzo, L., Dafflon, B., Léger, E. & Wu, Y., 2021, Estimation of Soil Classes and their Relationship to Grapevine Vigor in a Bordeaux Vineyard: Advancing the Practical Joint Use of Electromagnetic Induction (EMI) and NDVI Datasets for Precision Viticulture, Precision Agriculture, PP. 1-24.
Huete, A.R., 1988, A Soil-Adjusted Vegetation Index (SAVI), Remote Sensing of Environment, 25(3), PP. 295-309.
Jimoh, W.L.O. & Mohammed, M.I., 2012, Assessment of Cadmium and Lead in Soil and Tomatoes Grown in Irrigated Farmland of the Kaduna Metropolis Nigeria, Research Journal of Environmental and Earth Sciences, 4(1), PP. 55-59.
Kerle, N., Janssen, L.L. & Huurneman, G.C., 2004, Principles of Remote Sensing, ITC, Educational Textbook Series, 2, P. 250.
Lu, R.K., 1999, Analytical Methods for Soil Agrochemistry, Chinese Agricultural Science and Technology Publishing, House, Beijing.
Milton, N.M., Ager, C.M., Eiswerth, B.A. & Power, M.S., 1990, Arsenic- and Selenium-Induced Changes in Spectral Reflectance and Morphology of Soybean Plants, Remote Sensing of Environment, 30, PP. 263-269.
Muchuweti, M., Birkett, J.W., Chinyanga, E., Zvauya , R., Scrimshaw, M.D. & Lester, J.N., 2006, Heavy Metal Content of Vegetables Irrigated with Mixtures of Wastewater and Sewage Sludge in Zimbabwe: Implications for Human Health, Agriculture, Ecosystems and Environment, 112, PP. 41-48.
Mobarki, Hoda & Ataian, taktom., 2015, The use of remote sensing data in advance knowledge of the integrated management of pests and diseases, The first research congress on the application of modern sciences in geographical studies of Iran, https://civilica.com/doc/451450.
Næsset, E., Bollandsås, O.M. & Gobakken, T., 2005, Comparing Regression Methods in Estimation of Biophysical Properties of Forest Stands from Two Different Inventories Using Laser Scanner Data, Remote Sens. Environ, 94, PP. 541-553.
O'neill, P.E., Chauhan, N.S. & Jackson, T.J., 1996, Use of Active and Passive Microwave Remote Sensing for Soil Moisture Estimation through Corn, International Journal of Remote Sensing, 17(10), PP. 1851-1865.
Rouse, J.W., Haas, R.H., Schell, J.A. & Deering, D.W., 1974, Monitoring Vegetation Systems in the Great Plains with ERTS, NASA Special Publication, 351(1974), P. 309.
Seelig, H.D., Hoehn, A., Stodieck, L.S., Klaus, D.M., Adams Iii, W.W. & Emery, W.J., 2008, Relations of Remote Sensing Leaf Water Indices to Leaf Water Thickness in Cowpea, Bean, and Sugarbeet Plants, Remote Sensing of Environment, 112, PP. 445-455.
Tavakli, M., Safaian, N. & Shukri, M., 2014, Investigating the Importance and Role of Classification of Plants in the Assessment of Pasture Capacity, the third national conference on pasture and pasture management of Iran, Karaj.
Wójtowicz, M., Wójtowicz, A. & Piekarczyk, J., 2016, Application of Remote Sensing Methods in Agriculture, Communications in Biometry and Crop Science, 11, PP. 31-50.
Wylie, B.K., Meyer, D.J., Tieszen, L.L. & Mannel, S., 2002, Satellite Mapping of Surface Biophysical Parameters at the Biome Scale over the North American Grasslands: A Case Study, Remote Sensing of Environment, 79(2-3), PP. 266-278.
Yavari, S.M. & Qaderi, F., 2020, Determination of Thermal Pollution of Water Resources Caused by Neka Power Plant through Processing Satellite Imagery, Environment, Development and Sustainability, 22(3), PP. 1953-1975.