The 1992 reform of the European Common Agricultural Policy (CAP) introduced the Land Parcel Identification System (LPIS), a geodatabase of land parcels used to monitor and regulate agricultural subsidies. Traditionally, the LPIS has relied on high-resolution aerial orthophotos; however, recent advancements in very-high-resolution (VHR) satellite imagery present new opportunities to enhance its effectiveness. This study explores the feasibility of utilizing PlanetScope, a commercial VHR optical satellite constellation, to map agricultural parcels within the LPIS. A test was conducted in Umbria, Italy, integrating existing datasets with a series of PlanetScope images from 2023. A segmentation workflow was designed, employing the Normalized difference Vegetation Index (NDVI) alongside the Edge segmentation method with varying sensitivity thresholds. An accuracy evaluation based on geometric metrics, comparing detected parcels with cadastral references, revealed that a 30% scale threshold yielded the most reliable results, achieving an accuracy rate of 83.3%. The results indicate that the short revisit time of PlanetScope compensates for its lower spatial resolution compared to traditional orthophotos, allowing accurate delineation of parcels. However, challenges remain in automating parcel matching and integrating alternative methods for accuracy assessment. Further research should focus on refining segmentation parameters and optimizing PlanetScope’s temporal and spectral resolution to strengthen LPIS performance, ultimately fostering more sustainable and data-driven agricultural management.

Segmentation of Multitemporal PlanetScope Data to Improve the Land Parcel Identification System (LPIS) / Obialero, Marco; Boccardo, Piero. - In: REMOTE SENSING. - ISSN 2072-4292. - 17:12(2025). [10.3390/rs17121962]

Segmentation of Multitemporal PlanetScope Data to Improve the Land Parcel Identification System (LPIS)

Obialero, Marco;Boccardo, Piero
2025

Abstract

The 1992 reform of the European Common Agricultural Policy (CAP) introduced the Land Parcel Identification System (LPIS), a geodatabase of land parcels used to monitor and regulate agricultural subsidies. Traditionally, the LPIS has relied on high-resolution aerial orthophotos; however, recent advancements in very-high-resolution (VHR) satellite imagery present new opportunities to enhance its effectiveness. This study explores the feasibility of utilizing PlanetScope, a commercial VHR optical satellite constellation, to map agricultural parcels within the LPIS. A test was conducted in Umbria, Italy, integrating existing datasets with a series of PlanetScope images from 2023. A segmentation workflow was designed, employing the Normalized difference Vegetation Index (NDVI) alongside the Edge segmentation method with varying sensitivity thresholds. An accuracy evaluation based on geometric metrics, comparing detected parcels with cadastral references, revealed that a 30% scale threshold yielded the most reliable results, achieving an accuracy rate of 83.3%. The results indicate that the short revisit time of PlanetScope compensates for its lower spatial resolution compared to traditional orthophotos, allowing accurate delineation of parcels. However, challenges remain in automating parcel matching and integrating alternative methods for accuracy assessment. Further research should focus on refining segmentation parameters and optimizing PlanetScope’s temporal and spectral resolution to strengthen LPIS performance, ultimately fostering more sustainable and data-driven agricultural management.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3003689
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