Remote sensing extraction of jujube planting area in Xinjiang based on RF classification optimization and SNIC clustering
Received date: 2023-07-23
Revised date: 2023-10-07
Online published: 2024-07-09
This study aims to efficiently extract the distribution information and planting area of jujube crops in Xinjiang, China, providing essential data support for predicting yield and price, consolidating poverty alleviation achievements, and aiding rural revitalization. Utilizing the Google Earth Engine cloud platform, this research accesses Sentinel-1 radar images, Sentinel-2 optical images, and SRTM terrain data covering Xinjiang. From these data, 44 features including spectral, textural, and terrain attributes are extracted, followed by a feature selection process. The optimized random forest classifier, after hyperparameter tuning, produces a spatial distribution map of Xinjiang’s jujube planting areas with a 10 m resolution for the year 2021. Superpixel clustering method further processes the major jujube planting areas to determine the exact planting extents. The findings are as follows: (1) Employing a simple non-iterative clustering algorithm for classification and post-processing, the identified jujube cultivated area in Xinjiang spans 4253 km², predominantly located in the southern regions of Aksu, Kashgar, Hotan Prefectures, and Bayingolin Mongol Autonomous Prefecture, as well as Turpan and Hami Cities in the east. (2) The accuracy of feature extraction is significantly enhanced through hyperparameter optimization of the random forest classifier, yielding an average overall classification accuracy of 0.86, a Kappa coefficient of 0.82, a producer accuracy for jujube extraction of 0.87, and a user accuracy of 0.80, as assessed via the confusion matrix. (3) Features from the Sentinel-1 polarization band are crucial for jujube information extraction, supplemented effectively by spectral and textural features. Leveraging multisource remote sensing data, this method facilitates rapid acquisition of distribution and area data for jujube planting in Xinjiang, markedly benefiting agricultural modernization, resource conservation, and regional economic development.
ZHAO Guobing , ZHENG Jianghua , WANG Lei , GAO Jian , LUO Lei , Nigela TUERXUN , HAN Wanqiang , GUAN Jingyun . Remote sensing extraction of jujube planting area in Xinjiang based on RF classification optimization and SNIC clustering[J]. Arid Land Geography, 2024 , 47(6) : 1004 -1014 . DOI: 10.12118/j.issn.1000-6060.2023.382
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