Random Forest Winter Wheat Extraction Algorithm Based on Spatial Features of Neighborhood Samples

Nayi Wang, Xiangsuo Fan, Jinlong Fan and Chuan Yan
Additional contact information
Nayi Wang: School of Electrical, Electronic and Computer Science, Guangxi University of Science and Technology, Liuzhou 545006, China
Xiangsuo Fan: School of Electrical, Electronic and Computer Science, Guangxi University of Science and Technology, Liuzhou 545006, China
Jinlong Fan: National Satellite Meteorological Center of China Meteorological Administratio, Beijing 100089, China
Chuan Yan: School of Electrical, Electronic and Computer Science, Guangxi University of Science and Technology, Liuzhou 545006, China

Mathematics, 2022, vol. 10, issue 13, 1-20

Abstract: In order to effectively obtain the winter wheat growing area in a large part of the Guanzhong plain, this paper proposes a random forest Guanzhong plain winter wheat extraction algorithm based on spatial features of neighborhood samples using the 250 m resolution spectral imager (MERSI) of the FY-3 satellite as the data source. In this paper, first, the training and validation samples were obtained by constructing a neighborhood sample space sampling model, then the study area was classified using an integrated learning random forest Classifier, and finally the classification data obtained from different time phases were fused using voting game theory to obtain the final classification result map. The land use change and winter wheat distribution change from 2011 to 2014 were also analyzed. The experimental results showed that the overall accuracy of winter wheat obtained after random forest fusion processing was the highest compared with the traditional algorithm, reaching 98.63%. At the same time, LANDSAT 8 images were used to obtain the distribution of winter wheat, and the distribution areas obtained from MERSI data and LANDSAT 8 images were generally consistent in terms of spatial distribution as shown by the distribution areas at the county scale.

Keywords: FY-3; winter wheat; random forest; neighborhood sample; fusion processing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/13/2206/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/13/2206/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:13:p:2206-:d:846939

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().