Process and Content of Ukraine's Agricultural Land Use Monitoring Maksym Martynyuk1, Denys Nizalov2, Denis Bashlyk3 1Ministry of Agrarian Policy and Food, Ukraine; 2University of Kent, United Kingdom; 3Stategeocadastre, Ukraine

Ukraine: Change in Land Ownership Structure Launch of the land reform (Resolution of the Parliament on 18.12.1990 № 563-XII) Registered in the Land Cadaster (by 2017) Total: 42.2 mln ha (69.9% of total area) Private – 72% State – 22.6% Outdated statistical methods Based on historical records Reported by local authorities Source: Center for Land Reform Policy in Ukraine No up to date reliable information on land use!

State Service of Ukraine for Geodesy, Cartography and Cadastre Ensure that central and local government authorities, individuals and legal persons comply with land legislation of Ukraine; Remote sensing of actual agricultural land use shall be implemented in order to: Provide for implementation of the State policy for land use and land protection; Prevent violations of Ukrainian Law on land use and land protection, revealing such violations and taking actions for their elimination; Ensure that land owners and land users comply with national standards in the area of land use, protection of land fertility, preventing land contamination, providing for environmental protection.

State Service of Ukraine for Geodesy, Cartography and Cadastre Expected Results of the pilot: А) Analysis of the international and Ukrainian experience of remote sensing of agricultural land B) Comparative administrative records on land use from the State Land Cadastre with results of remote sensing of actual agricultural land use for pilot territories. C) Development of technical requirements for data on actual agricultural land use D) Development of proposals for rolling-out the remote sensing of agricultural land use for the rest of territory of Ukraine

Tasks for mapping within pilot project “Capacity Development for Evidence-based Land and Agricultural Policy-Making in Ukraine” Recognition of boundaries: cultivated land; agricultural crops; orchards, vineyard, berries; fallow land; grassland; water objects; forest (evergreen, deciduous, mixed); developed land; roads; irrigated land. Pilot territories

Satellite data Sentinel-2A: Sentinel-1A: Landsat-8: Swath Width – 100 km Revisit time: 10 days Cost - free Sentinel-1A: Nominal Scene Size - 250x250 km2 Revisit time - 12 days Landsat-8: Scene Size - 185x180 km2 Revisit time - 16 days Cost – free

Machine learning approach for crop classification 4. Geospatial analysis (data fusion from the classification maps and vector information) 3. Map filtration (voting and weighted voting approaches with division parcels into the fields) 2. Universal deep learning approach for time series classification at the regional level 1. No-data pixels restoration (clouds and shadows) using self-organized Kohonen maps

Distribution of ground data (training and test samples) Soy Winter wheat Sugar bits Corn Sunflower Bilotserkivskiy district Snigurivskiy district

Crop classification maps Bila Tserkva district

Comparison RS and Cadastral data: Boundary Errors

Comparison of RS and administrative data on crops: class misreporting 11

Comparison of RS and administrative data on crops: area misreporting 10 hа 12

Comparison of RS and administrative data on crops: class misreporting Winter wheat reported as sunflower Reported as hay land 13

Comparison of RS and administrative data on crops: shape misreporting

Use of non-registered land

Comparison of RS with Statistical Data (Winter wheat and maize) Bila Tserkva district Bila Tserkva district Class Official statistics (ha) Classification results (ha) Error, % Winter wheat 13730 23721 72.78 Maize 10512 25789 145.34 Snihurivka district CHECK the definition of errors Class Official statistics (ha) Classification results (ha) Error, % Winter wheat 31390 30517 -2.78 Maize 381 2307 505.55

Comparison of RS and Cadastral data Class of largest discrepancy Land cover Producer Accuracy % Class of largest discrepancy Agricultural land 92.10 Artificial (7.3 %) Artificial 96.56 Agricultural land (1.85%) Forests 49.23 Agricultural land (14.75%), Artificial (33.61%), Hay land (1.99%) Hay land and natural vegitation 21.35 Artificial (41.10%), Agricultural land (32.58%), Forests (2.62%), Water (2.28%) Swamps* 0.07 Artificial (72.40%), Hay land (10.63%), Water (9,76%), Agricultural (3.69%), Forests (3.45%) Water 78.74 Artificial(15.36%), Hay land (4.68%) Total accuracy: 81.06% Gaps: 9 % Overlaps: 0.46% Agricultural Land: RS results - 4972.41 hа Registered in Land Cadaster - 3839.27 hа Cadaster includes: 77.2 % of cultivated land Оцінювання здійснювалося шляхом побудови матриці помилок (confusion matrix) * Виділені як перекриття водних об'єктів та лук

Next steps Development of technical and administrative procedures to respond to discrepancies Scaling up Facilitate land registration Development of normative base and software

Thank you!