Optimizing remote sensing-based methodology for drained land monitoring: a case study of the Leningrad Region

Abstract

This article addresses the need to improve the methodology for monitoring hydro-reclamation systems. The study aims to justify the use of digital technologies to enhance the monitoring of agricultural land in response to a changing climate. The research was conducted between 2022 and 2024. The subject of the research is a tract of agricultural land – specifically, field 10-0 within the Menkovo Branch, located in the Gatchina District of the Leningrad Region. This land is characterized by excessive moisture and a high groundwater level, necessitating optimization of its hydro-reclamation system. To analyze groundwater levels in the study area, wells were drilled in key locations. Based on reconnaissance photo and video documentation, and statistical groundwater level data, the most representative field for research was selected. Visual analysis and NDVI index analysis corresponding to winter wheat growth stages, combined with groundwater level dynamics, revealed a correlation between elevated groundwater levels and suppressed vegetation. The working hypothesis that monitoring without specifying precise dates is ineffective was supported. Analyzing the efficiency of NDVI data, the study identified optimal monitoring times. Factoring in losses observed in the monitoring data analysis (ranging from 5% to 9%), this targeted monitoring approach is projected to increase yields from 52.7 c/ha to 59.1 c/ha. The estimated total cost of implementing this stage-specific monitoring program throughout the growing season is 128,000 rubles annually