High-resolution distribution map of apple orchards in China based on multisource data

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Authors: Wenqiang Xie, Y. J. Song, Xuefeng Cui, Xiaodong Yan, Shuaifeng Song
Cited by: 2
References: 44

Abstract

China is the world's leading apple producer and vital to global fruit supply and food security. Apple production depends on yield and planting area, both strongly influenced by climate. Regional climate variations cause differing cultivation suitability, exacerbating production disparities. Although climate models can project impacts on apples, the lack of high-resolution distribution data limits reliable large-scale assessment. Mapping apple orchards is more challenging than field crops due to complex growing conditions. To tackle this challenge, we developed the first 30-m national-scale apple orchard distribution map of China (AOMC) for 2019-2021, covering 96% of China's total apple orchard area. This dataset is generated based on an apple-phenology-driven algorithm framework, which integrates apple phenology and multi-source geographical information with the time-weighted dynamic time warping algorithm. Validations revealed that the dataset accurately represented orchard locations (Overall accuracy: 87%) and correlated strongly with municipal-level statistics (R²: 0.892-0.925). The AOMC supports the monitoring of spatiotemporal changes in China's apple production patterns, serves as critical input for crop models, and advances the sustainable development and climate resilience of apple industry.

Fields of Study & Subjects

Remote Sensing in Agriculture Plant Physiology and Cultivation Studies Smart Agriculture and AI

Publication details

Journal / source
Scientific Data
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
8 April 2026
Language
EN