P2P-ST: A Pixel-to-Parcel Scale-Transform Method for Cropland Monitoring

This study proposes a pixel-to-parcel scale-transform framework, termed P2P-ST, based on pixel unmixing to enable the unified generation, representation, and management of multi-source remote sensing data at the parcel scale. This repository contains the processed datasets and supporting code associated with the study “P2P-ST: A Pixel-to-Parcel Scale-Transform Method for Cropland Monitoring”. The study develops a pixel-to-parcel scale-transform framework that converts remote sensing signals from the pixel scale to the agricultural parcel scale, thereby reducing pixel-level heterogeneity, mixed-pixel effects, and salt-and-pepper noise in cropland monitoring applications. The dataset includes parcel-level remote sensing time-series data derived from Sentinel-2 and MODIS imagery, evaluation results for multi-source data consistency, crop classification assessment outputs, valid-observation statistics during crop-sensitive growth stages, and data used to reproduce the main figures and tables in the manuscript. The accompanying code provides the main processing and analysis procedures for implementing and evaluating the P2P-ST framework. The original satellite imagery was obtained from publicly available Sentinel-2 and MODIS products through Google Earth Engine and related NASA/ESA data portals. Because of the large volume of raw satellite imagery, the repository provides processed and analysis-ready data products rather than the full original image archive. These materials are intended to support transparency, reproducibility, and reuse of the results reported in the manuscript.本研究提出了一种基于像元分解（pixel unmixing）的像素-地块尺度转换框架，命名为P2P-ST，以实现地块尺度下多源遥感数据的统一生成、表征与管理。 本代码仓库包含与《P2P-ST：一种面向农田监测的像素-地块尺度转换方法》研究相关的处理后数据集与配套代码。该研究构建了像素-地块尺度转换框架，可将遥感信号从像元尺度转换至农业地块尺度，从而削弱农田监测应用中的像元级异质性、混合像元效应与椒盐噪声。 本数据集涵盖基于Sentinel-2与MODIS影像获取的地块级遥感时间序列数据、多源数据一致性评估结果、作物分类评估输出结果、作物关键生育期有效观测统计数据，以及用于复现论文手稿中主要图表的相关数据。配套代码提供了实现与评估P2P-ST框架所需的核心处理与分析流程。 原始卫星影像通过谷歌地球引擎（Google Earth Engine）及相关美国国家航空航天局（NASA）、欧洲空间局（ESA）数据门户，从公开可用的Sentinel-2与MODIS产品中获取。鉴于原始卫星影像数据量庞大，本仓库仅提供处理完成且可直接用于分析的数据产品，而非完整的原始影像档案。本数据集旨在支撑论文中所报道结果的透明性、可复现性与复用性。