Predicting Insect Pest Outbreaks Using Climate Models and Remote Sensing
Gaurav Chaturvedi *
Department of Agricultural Meteorology, Acharya Narendra Deva University of Agriculture & Technology, Kumarganj, Ayodhya, Uttar Pradesh, India.
Gudipati Naveen
Department of Entomology, Assam Agricultural University, Jorhat, PIN - 785013, Assam, India.
Ulfat Jan
Advanced Research Station for Saffron & Seed Spices, SKUAST-Kashmir, Pampore, Jammu and Kashmir, India.
Adarsh V S
Department of Agricultural Statistics, College of Agriculture, Vellayani, Kerala Agricultural University, Thrissur, Kerala, India.
Ambika Prasad Mishra
Department of Soil Science and Agricultural Chemistry, Sri Sri University, Faculty of Agriculture, Cuttack, Odisha, India.
Suchismita Mishra
Department of Floriculture and Landscaping, Institute of Agricultural Sciences, Siksha O Anusandhan Deemed to be University, Bhubaneswar, 751030, Odisha, India.
Chetna Khokhar
Department of Chemistry, CCS Haryana Agricultural University, Hisar, Haryana, India.
Thiruvengadam K
Department of Agricultural Entomology, RVS Agricultural College Thanjavur, Tamil Nadu, India.
*Author to whom correspondence should be addressed.
Abstract
Insect pest outbreaks threaten agricultural productivity and global food security. Predicting their outbreaks is crucial for implementing effective pest management strategies. Traditional pest control measures often rely on reactive interventions, leading to significant economic losses. However, climate models and remote sensing technologies have emerged as powerful tools for predicting pest outbreaks before they occur. Climate models analyze atmospheric conditions to forecast pest behaviour, while remote sensing provides real-time data on environmental factors influencing pest populations. This paper discusses the integration of these technologies, highlighting key methodologies, case studies, challenges, and future directions in pest outbreak prediction. The findings underscore the importance of interdisciplinary approaches in developing early warning systems and sustainable pest management strategies.
Keywords: Insect pests, climate models, remote sensing, pest outbreak prediction, agricultural sustainability, early warning systems