Subject
Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry
Reference54 articles.
1. Akar, Ö., Güngör, O.J.I.J.o.R.S., 2015. Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey. 36, 442–464.
2. Blaschke, T.J.I.j.o.p., sensing, r., 2010. Object based image analysis for remote sensing. 65, 2–16.
3. Tea Cultivation Suitability Evaluation and Driving Force Analysis Based on AHP and Geodetector Results: A Case Study of Yingde in Guangdong;Chen;China.,2022
4. Claverie, M., Masek, J.G., Ju, J., Dungan, J.L.J.N.A., Space Administration : Washington, D., USA, 2017. Harmonized landsat-8 sentinel-2 (HLS) product user’s guide.
5. Di, Y., Dong, J., Zhu, F., Fu, P.J.C., Agriculture, E.i., 2022. A robust but straightforward phenology-based ginger mapping algorithm by using unique phenology features, and time-series Sentinel-2 images. 198, 107066.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献