The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County
This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology d...
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Kharazmi University
2024-12-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-4038-en.pdf |
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| author | ALI hashemi Hojjatollah Yazdanpanah Mehdi Momeni |
| author_facet | ALI hashemi Hojjatollah Yazdanpanah Mehdi Momeni |
| author_sort | ALI hashemi |
| collection | DOAJ |
| description | This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error. |
| format | Article |
| id | doaj-art-b8b96824674a4484bc83d64491487886 |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2024-12-01 |
| publisher | Kharazmi University |
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| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-b8b96824674a4484bc83d644914878862025-01-31T17:32:13ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382024-12-012475254272The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab CountyALI hashemi0Hojjatollah Yazdanpanah1Mehdi Momeni2 PhD Candidate of Climatology, Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran. Associate Professor of Climatology, Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran Associate Professor of Remote Sensing, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, Iran. This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.http://jgs.khu.ac.ir/article-1-4038-en.pdftemperaturehumidityprecipitationbayesian regressionneural networkarmax |
| spellingShingle | ALI hashemi Hojjatollah Yazdanpanah Mehdi Momeni The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County تحقیقات کاربردی علوم جغرافیایی temperature humidity precipitation bayesian regression neural network armax |
| title | The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County |
| title_full | The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County |
| title_fullStr | The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County |
| title_full_unstemmed | The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County |
| title_short | The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County |
| title_sort | effect of climatic variables on vegetation indices case study orange orchards in hassan abad darab county |
| topic | temperature humidity precipitation bayesian regression neural network armax |
| url | http://jgs.khu.ac.ir/article-1-4038-en.pdf |
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