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Showing 2 results for Dvi Index

Mohamad Reza Mobasheri:, Samira Ranjbar,
Volume 17, Issue 44 (6-2017)
Abstract

The goal of this study is to identify farms which are affected by wheat rust disease. For this, the sensor data of Landsat 7 satellites in growing season of 2013 and 2014 along with some laboratorial data containing reflectance spectrum of leaf and leaf health degree in different levels of disease are used. The reflectance values of leaf are collected by an ASD spectroradiometer in the range of red and near infrared spectrum. The spectral are simulated for Landsat sensor bands using their spectral response functions. Then with the index of DVI and data obtained for leaf health, the Wheat Health Index was introduced. The correlation coefficient obtained is 0.82 and the relevant RMSE is 0.089 which is really good result for diagnosing highly advanced disease. The results show that, this index has a good performance in wheat high growing season when the greenness is high. It can diagnose regions that are healthy from those whom are blighted. Because the WHI index is a spectral index and is sensitive to leaf color, if the acquired images are close to the harvesting time, its performance will be weakened. The selected region in this survey is located in Fars, province, Saadatshahr city.


Adel Nabi Zadeh Balkhanloo, Zahra Hejazizadeh, Parviz Zeaiean Firoozabadi,
Volume 18, Issue 50 (6-2018)
Abstract

Continuous decline in Lake Urmia water levels In recent years, the decline of rainfall and river flows and constant droughts has become the main concern of the people and the people. To study climate change and increase of temperature in the catchment area of ​​Lake Urmia, two factors for measuring the temperature and properties of satellite images were used which indicate the importance of land surface temperature changes (LST) and normalized vegetation differences (NDVI). This study was carried out using the satellite data of the periodic watershed (2008-2008) to investigate the spatial relationship between NDVI-Ts and NDVI-ΔT to investigate the actual agricultural drought occurrence. The goal is to extract the VTCI (vegetation temperature index) index, which is capable of identifying drought stress at regional scale. The results showed that the slope is negative for the warm edge, where it is positive for the cold edge. The gradient gradient shows that the maximum temperature is reduced when the NDVI value increases for any interval. The slope on the cold edge indicates that the minimum temperature rises when the NDVI value rises. Overall, at the warm and cold edges, it has been observed that the drought trend over 2009-2008 is higher than in 2010. In the days of Julius Day 257, the slope of the cold edge from 2008 to 2010 is decreasing. But at the hot edge, intercept pixels for 2008 is more than 323 degrees Kelvin, where in 2009-2010 it is less than 323 degrees Kelvin. In general, the correlation coefficient (R2) is different in the TS-NDVI spacing between (0.90-0.99). The present study showed that with the integration of satellite satellite data with meteorological data, the VTCI threshold for drought stress varies from year to year depending on the data conditions.


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