NECCPB-1: The first cropland parcel boundary dataset from meter-level imagery of Northeast China

<p>The Northeast China Plain is one of the world's three largest black soil regions, characterized by high organic matter content, rich nutrients, and strong water retention capabilities. Suitable climate conditions and abundant rainfall promote the growth of crops such as corn, soybeans, and rice, making it one of the main grain production bases in China, accounting for about one-fifth of the country's grain output. The grain production in the Northeast China black soil region is crucial for food security in China and globally. This area's farmland parcels are the basic units of agricultural production and the cornerstone of precision agriculture management, providing detailed information on cultivated land location, boundaries, shape, and area. Utilizing this parcel-scale information, governments and farm managers can devise more precise planting strategies and optimize management methods, thereby enhancing the quality and productivity of crops, ensuring a continuous food supply, and promoting sustainable agricultural development.</p> <p>The first cropland parcel boundary dataset from meter-level imagery of Northeast China (NECCPB-1) was developed based on deep learning models and a custom-designed automatic parcel merging strategy. A total of 10.22 TB of very-high-resolution (VHR) imagery was downloaded and uploaded, covering the entire region of Northeast China and an area of 1,240,000 km&sup2;. After further removal of non-cropland regions based on phenological differences, 32,395,946 parcels were obtained.</p> <p>&nbsp;Rigorous validation using manually drawn reference parcels demonstrated that this dataset had high accuracy in parcel delineation (Extraction Precision, EP: 0.85) and high consistency with the reference parcels (|Completeness Deviation|, |CompD|: 0.02; Intersection over Union, IoU: 0.90). Further comparison with official Third Survey reports confirmed the high reliability of the NECCPB-1 dataset, which exhibited an average relative difference of -3.6% and an absolute relative difference of 9.8%.</p> <p>A series of cross-validations with seven widely used cropland datasets (ESA_GLC10, ESRI_GLC10, FROM_GLC10, CLD10, GLAD250, GFSAD30, and SinoLC-1).&nbsp;The recall, precision, and F1 scores of the NECCPB-1 were calculated as 0.91, 0.93, and 0.92, respectively, using publicly validated sample points of land cover. Moreover, NECCPB-1 performed best regarding cropland completeness, achieving an intersection ratio (IR) of 0.94, as calculated using the reference parcels.</p> <p>Due to the extensive size of the dataset and potential policy considerations, access to the data will be granted based on specific inquiries. Please contact us at zhengjia@iga.ac.cn or guotianhao@iga.ac.cn&nbsp; for further details. Please indicate your purpose and other details. Thank you!</p>