Advancement Through Research
Pests and diseases can cause a variety of reactions in plants. In recent years, boxwood dieback has become one of the essential concerns of practitioners and natural resources managers in Iran. Dieback is one of the boxwood diseases whose symptoms include sudden and severe yellowing, browning, spotting, withering, or dying of leaves, stems, or the entire plant. To contain the dieback of boxwood spreadness, the early detection and disease distribution maps are required. Dieback of boxwood causes a range of changes in color, shape and leaf size to photosynthesis, transpiration. Through remote sensing techniques e.g. satellite image processing data, the variation of thermal and visual characteristics of the plant could be used to measure and illustrate the symptoms of the disease. In this study, five common vegetation indices, e.g. DVI, NDVI, SAVI, SR, and PHI, were extracted and calculated from Landsat 8 satellite image data from six regions in Gilan province, located in the northern part of Iran out of 150 maps over the 2014 - 2018 time period. It was turned out that among aforementioned indices, based upon the results of the models, SR and NDVI indices were more useful for disease spreadness, respectively. Our disease progression model fitting criteria showed that it this technique could be probably used to assess the extent of the affected areas and also the disease progress in investigated regions in the future.
Satellite Image Processing, Vegetation Indices, Landsat 8, Iran, Forest, Dieback
