基于Sentinel-2的青铜峡灌区水稻和玉米种植分布早期识别

doi:10.12118/j.issn.1000-6060.2023.541

Abstract

Abstract:

Timely and accurate understanding of crop distribution within irrigation areas is essential for the efficient allocation of irrigation water resources and precise field management. This study focuses on the Qingtongxia irrigation area in Ningxia, China, employing multitemporal Sentinel-2 satellite data to analyze early characteristics of rice and maize. Key “flooding” and “vegetation” signals are extracted, and a time-series dataset comprising the modified normalized difference water index (MNDWI) and normalized vegetation index (NDVI) is constructed. By analyzing sample thresholds for these key features, a decision tree model for the early planting distribution of rice and maize is established, facilitating the extraction of the spatial distribution for rice and maize planting in the Qingtongxia irrigation area in 2022. The results reveal the following: (1) During the latter half of the maize and rice seedling stages, from May 15 to 31, flooding and vegetation signals are crucial for differentiating between the two crops. (2) Based on the early crop phenological characteristics, the mapping accuracy of rice and corn images obtained from May 16 to May 31 was higher than 90%, with user accuracy exceeding 91% and overall accuracy exceeding 90%. The Kappa coefficient was higher than 0.88, significantly higher than the classification accuracy of the random forest classification method during the same period. (3) The proposed method demonstrates strong applicability in the early extraction of rice and maize planting distribution, requiring fewer ground samples for extension across both spatial and temporal scales. Therefore, this method provides significant support for early investigations of rice and maize planting distribution in the Qingtongxia irrigation area.

Key words: Qingtongxia irrigation area, Sentinel-2, normalized vegetation index, normalized difference water index, decision tree, rice, maize

ZHU Lei, WANG Ke, DING Yimin, SUN Zhenyuan, SUN Boyan. Early identification of rice and corn planting distribution in Qingtongxia irrigation area based on Sentinel-2[J].Arid Land Geography, 2024, 47(5): 850-860.

Figures/Tables 12

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References 29

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月份	2	3			4			5			6			7			8			9
旬	下	上	中	下	上	中	下	上	中	下	上	中	下	上	中	下	上	中	下	上	中	下
水稻								播种		出苗	分蘖		拔节			抽穗			乳熟	成熟
玉米						播种				出苗	拔节			抽雄		开花		灌浆		成熟
小麦	播种		出苗		三叶	分蘖		拔节		抽穗	开花		灌浆	成熟
葡萄				展藤	萌芽	出叶				开花	坐果			膨大			转色			成熟
枸杞				萌芽	展叶			开花		幼果			成熟

生育期	获取时间（年-月-日）	传感器与数据级别	数量/景	云覆盖率/%
播种前	2022-01-04	S2A-MSIL2A	6	<8
播种前	2022-03-15	S2A-MSIL2A	6	<5
播种期	2022-04-06	S2B-MSIL2A	5	<5
	2022-04-24	S2A-MSIL2A	5	<8
	2022-05-01	S2A-MSIL2A	6	<8
	2022-05-09	S2B-MSIL2A	6	<5
出苗期	2022-05-16	S2B-MSIL2A	5	<8
	2022-05-24	S2A-MSIL2A	6	<8
	2022-05-31	S2A-MSIL2A	6	<5
拔节期	2022-06-05	S2B-MSIL2A	6	<5
	2022-06-13	S2A-MSIL2A	6	<5
	2022-06-15	S2B-MSIL2A	6	<5
	2022-06-30	S2A-MSIL2A	6	<5

生育期	日期	玉米		水稻		总体精度/%	Kappa系数
生育期	日期	制图精度/%	用户精度/%	制图精度/%	用户精度/%	总体精度/%	Kappa系数
播种期	5月1日—16日	95.62	94.33	93.02	92.66	97.0413	0.920
出苗期	5月1日—24日	95.25	93.31	94.87	93.34	95.4182	0.908
	5月1日—31日	93.49	92.87	93.54	91.56	91.5336	0.882
拔节期	5月1日—6月05日	90.96	91.41	92.06	93.14	90.6971	0.851
拔节期	5月1日—6月13日	89.36	90.61	90.84	91.33	89.5663	0.801
	5月1日—6月30日	63.53	92.86	95.87	75.69	81.0671	0.609

生育期	日期	玉米		水稻		总体精度/%	Kappa系数
生育期	日期	制图精度/%	用户精度/%	制图精度/%	用户精度/%	总体精度/%	Kappa系数
播种期	5月16日	89.34	87.56	90.01	89.35	90.01	0.89
出苗期	5月24日	89.98	90.20	89.97	90.02	90.06	0.87
	5月31日	87.34	88.75	86.37	89.23	89.09	0.84
拔节期	6月05日	90.02	90.51	90.07	91.24	90.76	0.90
	6月13日	88.09	90.03	89.67	90.01	89.12	0.85
	6月30日	91.03	90.5	86.08	87.09	86.57	0.86

方法	最大值	最大值日期（年-月-日）	Kappa系数≥0.9 的首个日期（年-月-日）
基于早期物候特征方法	0.92	2022-05-16	2022-05-16
随机森林方法	0.90	2022-06-05	2022-06-05

Early identification of rice and corn planting distribution in Qingtongxia irrigation area based on Sentinel-2

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