Progressive Web Application for Forest Inventory Management and Tree Volume Assessment

Abstract

Forest inventory data collection is fundamental to sustainable forest management, timber traceability, and regulatory compliance. Traditional inventory methods often involve manual data recording followed by post-fieldwork computational analysis and transcription into digital systems, creating temporal delays, transcription errors, and potential data integrity issues. This paper presents a novel Progressive Web Application (PWA) designed to streamline forest inventory data collection, tree volume calculation, and data management in real-time field conditions. The application implements two complementary volume calculation methodologies: the form factor method and the conic formula method, alongside automated quality classification and minimum diameter validation systems. Developed using modern web technologies, the PWA features robust offline functionality, low resource demands (e.g., 1.2s initial load time, 2.4MB offline cache, minimal battery impact), and standardized CSV export. Field validation with data in tropical forest (n=310 trees) confirmed high agreement between methods (Pearson r=0.995, explaining 99% of variance; mean bias -0.08 m<sup>3</sup>, 95% limits of agreement -0.15 to -0.01 m<sup>3</sup>), with the conic method showing a 3.2% systematic underestimation suitable for calibration or complementary use. Compared to paper-based approaches, the digital app achieved a 52% reduction in time per tree (from 6.8 to 3.3 minutes), complete elimination of transcription errors, data loss, and calculation errors, and immediate data availability with direct export compatibility. User acceptance was very high (mean ratings 4.7-5.0/5), with qualitative feedback emphasizing efficiency, reliability, and data quality. The open-architecture design facilitates adaptation to diverse forest types and management systems, while the PWA framework ensures accessibility without installation barriers. This tool represents a significant advancement in digital forestry, enhancing efficiency, accuracy, and reliability in tropical forest inventory and management.