Abstract: With the low-altitude economy emerging as a national strategic industry,this paper explores how a low-altitude remote sensing system,driven by surveying,mapping and geographic information,can support the entire lifecycle of high-standard farmland,including construction,management,and utilization.An integrated “air-sky-ground-network” monitoring architecture was established by integrating multi-source geospatial data from BeiDou navigation,5G communication,high-resolution satellites,UAV remote sensing,and ground-based sensors.By incorporating AI-based image interpretation and spatio-temporal analysis models,a geomatics-driven digital management framework for high-standard farmland was developed.In a pilot application conducted in Huanxian county,Gansu province,the proposed framework achieved over 92% accuracy in automatic identification of farmland engineering facilities and 88.4% accuracy in crop growth status classification.In addition,during an emergency response to an irrigation system failure,anomalies in multi-source geospatial data enabled fault localization and early warning to be completed within three hours.The results demonstrate that the integration of low-altitude remote sensing with geomatics provides an effective solution for the digital and intelligent management of high-standard farmland.The proposed framework offers a replicable and scalable paradigm for the large-scale application of the low-altitude economy in agriculture.

Key words: low-altitude remote sensing, high-standard farmland, surveying,mapping and geographic information, multi-source data fusion, digital management