Mapping Paddy Rice Distribution and Cropping Intensity in China from 2014 to 2019 with Landsat Images, Effective Flood Signals, and Google Earth Engine

Paddy rice cropping systems play a vital role in food security, water use, gas emission estimates, and grain yield prediction. Due to alterations the labor structure high cost of paddy planting, (single or double rice) have drastically changed China recent years; many double-cropping fields been converted single-cropping other crops, especially southern China. Few maps detect single intensity for (CIPR) with 30 m resolution. The Landsat-based effective flooding signal-based phenology (EFSP) method, which distinguishes CIPR frequency signal (EFe), was proposed tested cloud/ice/shadow excluded by bit arithmetic, generating good observation map, several non-paddy masks were established improve classification accuracy. Threshold values calculated through mapped data agricultural census data. Image processing (more than 684,000 scenes) algorithm implementation accomplished cloud computing approach Google Earth Engine (GEE) platform. resultant from 2014 2019 evaluated statistical yearbooks high-resolution images, producer (user) accuracy kappa coefficients ranging 0.92 0.96 (0.76–0.87) 0.67–0.80, respectively. Additionally, determination higher 0.88 2019. Maps derived EFSP illustrate that are mainly concentrated Cfa (warm, fully humid, hot summer, 49% vs. 56%) climate zone show slightly decreasing trend. trend is more pronounced due shortages rural household labor. However, expanded Dwa (cold, dry winter, 11%) Dwb warm 9%) zones. regional coincides planting area but shows significant decrease south China, Hunan Province, results demonstrate can effectively support mapping combinations Landsat 7 8 provide enough observations monitor agriculture.