I am Lalit, a Geospatial and Precision Agriculture Specialist with more than 4 years of experience, where I explore geospatial modeling, machine learning, and big data analytics for agricultural applications. Recognized as an expert in GIS and Remote Sensing, I am passionate about designing scalable, open-source geospatial tools that empower agricultural decision-making.
My research interests include remote sensing, geo-analytics, and machine learning applications, emphasizing integrated approaches to agricultural monitoring. My overall goal is to make complex geospatial analyses more accessible, optimized, and scalable to academics and practitioners alike. Through collaborative projects and international publications, I aim to advance our understanding of precision agriculture and promote sustainable farming practices. You can reach me via LinkedIn, or Email.
Interests
Education
Projects
AI-Driven System for Post-Disaster Agricultural Damage Assessment
Serving as the GIS AI/ML Spatial Engineering Lead for developing an AI-driven system to assess agricultural damage after disasters by integrating satellite imagery, UAV datasets, and advanced spatial analysis workflows. Leading spatial data processing, AI/ML model development, and operational integration for rapid, data-driven decision-making for disaster response and agricultural resilience in Nepal.
Precision Nutrient Management in Paddy using Multispectral Drone Imagery
Implementing precision agriculture techniques for paddy cultivation using multispectral drone imagery to optimize nutrient application. The project focuses on developing site-specific nutrient management strategies based on vegetation indices and soil variability analysis at Khumaltar, Lalitpur.
Detecting Citrus Greening using High Resolution UAV Imagery and Deep Learning
Developing an automated detection system for citrus greening disease (Huanglongbing) using high-resolution UAV imagery and deep learning algorithms. The project aims to enable early detection and management of this devastating citrus disease through advanced computer vision techniques.
Skills & Technologies
GIS & Remote Sensing
Programming & Data Analysis
Machine Learning & AI
UAV & Photogrammetry
Database & Cloud
Visualization & Web
Invited Talks & Training
Spatial Data Analysis and Visualization Using GIS
5 days program at CNRM Pakhribas funded by UGC Nepal
GIS professionals and researchers
AI in Cattle Insurance
Winter School on Annual Nepal AI School by NAMII
AI researchers and practitioners
GIS and Remote Sensing for Precision Agriculture with QGIS
School of Agriculture, Tikapur Campus funded by UGC Nepal
Agriculture students and professionals
Open Source Contributions
SmartCSV Exporter
A QGIS plugin for intelligent CSV export functionality with advanced data formatting options, field mapping, and batch processing capabilities. Streamlines the process of exporting spatial data to CSV format with customizable export templates and data validation features.
GeoSat (Upcoming)
An advanced QGIS plugin for soil mapping and geostatistical analysis of soil data. Features automated soil property interpolation, kriging analysis, variogram modeling, and comprehensive soil health assessment tools. Designed to support precision agriculture and soil management decisions.
Publications
Use of Satellite Data for Claim Validation in Agriculture Insurance in Nepal
BC, L. & Poudel, S.
GeoWorld Vol III, 2 • 2025
Safety behavior of Nepalese Strawberry Farmers as Reflected by the Protection Motivation Theory
Bhandari, G., BC, L., Sapkota, U. et. al
International Journal of Environmental Research • 2025
Effect of Different Fertilizers on Yield and Vitamin C content of Cauliflower (Brassica oleracea var botrytis) - A review
Belbase, P., and BC, L.
Asian Journal of Agricultural and Horticultural Research • 2020