Pest attack determination in paddy areas using multispectral remote sensing images

Infestation of rice plant-hopper is one of the most notable risks in rice yield in tropical areas especially in Asia. Early recognition of pest infestation by means of remote sensing will support precision farming practices. Farmers cannot determine the location of spread and apply pesticide at the...

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Main Author:	Ghobadifar, Faranak
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Rice - Pests Remote sensing Image analysis
Online Access:	http://psasir.upm.edu.my/id/eprint/65606/1/FK%202015%20153IR.pdf
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spelling	my-upm-ir.656062018-10-02T07:07:47Z Pest attack determination in paddy areas using multispectral remote sensing images 2015-02 Ghobadifar, Faranak Infestation of rice plant-hopper is one of the most notable risks in rice yield in tropical areas especially in Asia. Early recognition of pest infestation by means of remote sensing will support precision farming practices. Farmers cannot determine the location of spread and apply pesticide at the right place within their farms. Under particular conducive environment such as high temperature and humidity, pest population will increase. The damage caused by the pest to crop is well known. The major aspects of satellite remote sensing are timely estimates of agriculture crop yield and prediction of pests and disease infestation. On-farm pest management and crop protection strongly depend on diagnosis of crop stress in the fields. The main purpose of this research was to determinate pest attack in paddy field using remote sensing by assessing weather data and their effect on the pests infestation. To address this issue, detection of sheath blight in rice farming was examined by using SPOT-5 images for discriminating healthy parts from unhealthy ones. Specific image indices such as Normalized Difference Vegetation Index (NDVI), Standard difference indices (SDI) and Ratio Vegetation Index (RVI) were used, for analyses using ENVI 4.8, SPSS and ArcGIS software. Also, this research presents the extraction of weather data such as temperature and relative humidity (RH) derived from Landsat images by investigating and comparing with the pest infestation during special time. The data set satisfied several quality criteria and was used for extracting temperature (T), Normalize Difference Vegetation Index (NDVI), Relative Humidity (RH) and Extraterrestrial radiation (Ra) from Landsat images. Results showed that all the indices to recognize infected plants from uninfected ones are significant at α = 0.01. It showed that the indices can be good indicators for pest discrimination in the paddy areas. Examination of the association between the disease indices indicated that band 3 (near infrared) and band 4 (mid infrared) in SPOT-5 images have a relatively high correlation. Image investigations revealed that pest were existing at the higher limits of tolerable temperatures when at nymph’s stage. By this means, models for each date were created, consequently, based on the model and analysis it can be concluded that pest can be alive at the higher limits of acceptable temperatures and RH. Therefore, it states that between tillering to flowering stage of paddy which encounter with March while the plants are between 70 and 90 days of the growth stage, high temperature up to 32°C and also RH up to 85% cause increases in distribution and survival of pest. Transferring from one growth stage to the other for pest was caused by temperature. Based on the models temperature and RH are two significant factors which can affect pest infestation in the field. On the other hand, indices like NDVI, SDI and RVI stated differences between infected parts from healthy plants. Consequently, it can be concluded that it is better to use any method for preventing from pest attack at early March. Rice - Pests Remote sensing Image analysis 2015-02 Thesis http://psasir.upm.edu.my/id/eprint/65606/ http://psasir.upm.edu.my/id/eprint/65606/1/FK%202015%20153IR.pdf text en public doctoral Universiti Putra Malaysia Rice - Pests Remote sensing Image analysis
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Rice - Pests Remote sensing Image analysis
spellingShingle	Rice - Pests Remote sensing Image analysis Ghobadifar, Faranak Pest attack determination in paddy areas using multispectral remote sensing images
description	Infestation of rice plant-hopper is one of the most notable risks in rice yield in tropical areas especially in Asia. Early recognition of pest infestation by means of remote sensing will support precision farming practices. Farmers cannot determine the location of spread and apply pesticide at the right place within their farms. Under particular conducive environment such as high temperature and humidity, pest population will increase. The damage caused by the pest to crop is well known. The major aspects of satellite remote sensing are timely estimates of agriculture crop yield and prediction of pests and disease infestation. On-farm pest management and crop protection strongly depend on diagnosis of crop stress in the fields. The main purpose of this research was to determinate pest attack in paddy field using remote sensing by assessing weather data and their effect on the pests infestation. To address this issue, detection of sheath blight in rice farming was examined by using SPOT-5 images for discriminating healthy parts from unhealthy ones. Specific image indices such as Normalized Difference Vegetation Index (NDVI), Standard difference indices (SDI) and Ratio Vegetation Index (RVI) were used, for analyses using ENVI 4.8, SPSS and ArcGIS software. Also, this research presents the extraction of weather data such as temperature and relative humidity (RH) derived from Landsat images by investigating and comparing with the pest infestation during special time. The data set satisfied several quality criteria and was used for extracting temperature (T), Normalize Difference Vegetation Index (NDVI), Relative Humidity (RH) and Extraterrestrial radiation (Ra) from Landsat images. Results showed that all the indices to recognize infected plants from uninfected ones are significant at α = 0.01. It showed that the indices can be good indicators for pest discrimination in the paddy areas. Examination of the association between the disease indices indicated that band 3 (near infrared) and band 4 (mid infrared) in SPOT-5 images have a relatively high correlation. Image investigations revealed that pest were existing at the higher limits of tolerable temperatures when at nymph’s stage. By this means, models for each date were created, consequently, based on the model and analysis it can be concluded that pest can be alive at the higher limits of acceptable temperatures and RH. Therefore, it states that between tillering to flowering stage of paddy which encounter with March while the plants are between 70 and 90 days of the growth stage, high temperature up to 32°C and also RH up to 85% cause increases in distribution and survival of pest. Transferring from one growth stage to the other for pest was caused by temperature. Based on the models temperature and RH are two significant factors which can affect pest infestation in the field. On the other hand, indices like NDVI, SDI and RVI stated differences between infected parts from healthy plants. Consequently, it can be concluded that it is better to use any method for preventing from pest attack at early March.
format	Thesis
qualification_level	Doctorate
author	Ghobadifar, Faranak
author_facet	Ghobadifar, Faranak
author_sort	Ghobadifar, Faranak
title	Pest attack determination in paddy areas using multispectral remote sensing images
title_short	Pest attack determination in paddy areas using multispectral remote sensing images
title_full	Pest attack determination in paddy areas using multispectral remote sensing images
title_fullStr	Pest attack determination in paddy areas using multispectral remote sensing images
title_full_unstemmed	Pest attack determination in paddy areas using multispectral remote sensing images
title_sort	pest attack determination in paddy areas using multispectral remote sensing images
granting_institution	Universiti Putra Malaysia
publishDate	2015
url	http://psasir.upm.edu.my/id/eprint/65606/1/FK%202015%20153IR.pdf
_version_	1747812348896215040

Pest attack determination in paddy areas using multispectral remote sensing images

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