Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/73815
Title: ปัจจัยที่มีผลต่อการแพร่ระบาดของเพลี้ยกระโดดในนาข้าวในสภาวะต่างสภาพภูมิอากาศด้วยข้อมูลดาวเทียมหลายช่วงเวลา ในตำบลแม่คือ อำเภอดอยสะเก็ด จังหวัดเชียงใหม่
Other Titles: Factors influencing the planthopper’s outbreak in paddy field on different climate conditions with multi-temporal satellite data in Mae Khue Sub-District, Doi Saket District, Chiang Mai Province
Authors: ชนัดดา ปีหลวง
Authors: อริศรา เจริญปัญญาเนตร
ชนัดดา ปีหลวง
Keywords: การแพร่ระบาดของเพลี้ยกระโดด;สภาวะต่างสภาพภูมิอากาศ;ตัวแบบทำนายพื้นที่ระบาด;ดาวเทียม Landsat 8;พื้นที่นาข้าว
Issue Date: Jul-2022
Publisher: เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่
Abstract: In the study of Factors Influencing the planthopper’s outbreak in paddy field on different climate conditions with multi-temporal satellite data in Mae Khue Sub-District, Doi Saket District, Chiang Mai Province, the study has three objectives to achieve which 1) to classify the paddy field that is infected by brown-backed planthopper (BPH) and white-backed planthopper (WPH) on different climate conditions, 2) to analyze the root cause of the outbreak of BPH and WPH on different climate conditions, and 3) to implement the model to predict the outbreak area of BPH and WPH. The climate conditions that are investigated are including normal condition in 2014, El Niño condition in 2015, and La Niña condition in 2016, respectively. The paddy field is classified by visual interpretation and the infested paddy field is identified by computing a land surface temperature using Thermal Infrared Sensor (TIRS) Band 10 from Landsat 8-TIR and determining the potential temperature range using statistic approaches including mean and standard deviation. On the influencing factors, 6 factors are experimented including 1) Land Surface Temperature (LST) 2) plant’s humidity 3) soil moisture 4) an amount of Carbon Dioxide 5) Salinity Index (SI) and 6) Leaf Area Index (LIA), respectively. The three models are implemented based on three primary climates conditions using multiple linear regression analysis which the dependent variable (y) is the normal and infected areas, and the independent variables are 6 previously mentioned influencing factors. As a result, the study was shown that the potential temperature ranges of BPH and WPH outbreak area between 22.966 – 24.337 °C under the normal condition in 2014, 23.805 – 24.774 °C under the El Niño condition in 2015, and 24.528 – 25.602 °C under the La Niña condition in 2016, respectively. Also, the model accuracies of the prediction are 70.635%, 76.866%, and 69.072%, respectively. The model’s functions are resolved by the equation y = -17.736 + 0.4308 LST+ 7.091NDMI + 53.53SI - 1.209LAI (R-Squared = 0.872) in the normal model, y = -7.158 + 0.0640LST + 1.560CO2 + 17.77SI + 1.6241LAI (R-Squared = 0.777) in the El Niño model, and y = -26.41 + 1.0259 LST + 3.36 NDMI + 26.9CO2 (R-Squared = 0.612) in the La Niña model, respectively. Also, the normal model is indicated that LSI, plant’s humidity, SI, and LAI are the influencing factors of outbreaking and the El Niño model is indicated that LSI, the CO2 amount, SI, and LAI are the influencing factors, and the La Niña model is indicated that only LSI, soil moisture, and the CO2 amount are the influencing factors, respectively.
URI: http://cmuir.cmu.ac.th/jspui/handle/6653943832/73815
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