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Article

Walnut Acreage Extraction and Growth Monitoring Based on the NDVI Time Series and Google Earth Engine

1
Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Tarim University, Alar 843300, China
2
College of Horticulture and Forestry, Tarim University, Alar 843300, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(9), 5666; https://doi.org/10.3390/app13095666
Submission received: 5 April 2023 / Revised: 27 April 2023 / Accepted: 3 May 2023 / Published: 4 May 2023

Abstract

Walnut (Juglans regia) planting is the main economic pillar industry in southern Xinjiang. Based on the Google Earth Engine (GEE) cloud platform, the NDVI maximum synthesis method was used to estimate changes in the walnut cultivation area in Ganquan Town, South Xinjiang, from 2017 to 2021. The simultaneous difference between NDVI and meteorological conditions was also used to monitor the growth and correlation analysis of walnuts from April to September 2021. To improve the classification accuracy of the extracted walnut plantation area, Sentinel-2 image data were selected, and features were trained using the random forest algorithm, and by combining topographic features, texture features, NDVI, and EVI. The results show that, compared with Statistical Yearbook data, the average error of the extracted walnut planted area is less than 10%, the overall classification accuracy is 92.828%, the average kappa coefficient is 90.344%, and the average walnut classification accuracy is 94.4%. The accuracy of the data was significantly improved by adding vegetation indices EVI and NDVI compared with the single vegetation index. An analysis of the results from monitoring comparative growth shows that the growth of walnuts in Ganquan was better during the hardcore and oil transformation stages compared with 2020, and in the fruit development stage, the growth was the same as in 2020, and overall, the growth of walnuts in 2021 was better than in previous years.
Keywords: walnut planting area extraction; Xinjiang region; Google Earth Engine; random forest; normalized difference vegetation index (NDVI); Sentinel-2 walnut planting area extraction; Xinjiang region; Google Earth Engine; random forest; normalized difference vegetation index (NDVI); Sentinel-2

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MDPI and ACS Style

Shi, Z.; Zhang, R.; Bai, T.; Li, X. Walnut Acreage Extraction and Growth Monitoring Based on the NDVI Time Series and Google Earth Engine. Appl. Sci. 2023, 13, 5666. https://doi.org/10.3390/app13095666

AMA Style

Shi Z, Zhang R, Bai T, Li X. Walnut Acreage Extraction and Growth Monitoring Based on the NDVI Time Series and Google Earth Engine. Applied Sciences. 2023; 13(9):5666. https://doi.org/10.3390/app13095666

Chicago/Turabian Style

Shi, Ziyan, Rui Zhang, Tiecheng Bai, and Xu Li. 2023. "Walnut Acreage Extraction and Growth Monitoring Based on the NDVI Time Series and Google Earth Engine" Applied Sciences 13, no. 9: 5666. https://doi.org/10.3390/app13095666

APA Style

Shi, Z., Zhang, R., Bai, T., & Li, X. (2023). Walnut Acreage Extraction and Growth Monitoring Based on the NDVI Time Series and Google Earth Engine. Applied Sciences, 13(9), 5666. https://doi.org/10.3390/app13095666

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