@Article{phyton.2022.020117,
AUTHOR = {Dongping Zha, Haisheng Cai, Xueling Zhang, Qinggang He, Liting Chen, Chunqing Qiu, Shufang Xia},
TITLE = {Extracting Lotus Fields Using the Spectral Characteristics of GF-1 Satellite Data},
JOURNAL = {Phyton-International Journal of Experimental Botany},
VOLUME = {91},
YEAR = {2022},
NUMBER = {10},
PAGES = {2297--2311},
URL = {http://www.techscience.com/phyton/v91n10/48002},
ISSN = {1851-5657},
ABSTRACT = {The lotus (<i>Nelumbo nucifera</i> Gaertn.) is an aquatic plant that grows in shallow water and has long been cultivated
in South China. It can improve the incomes of farmers and plays an important role in alleviating poverty in rural
China. However, a modern method is required to accurately estimate the area of lotus fields. Lotus has spectral
characteristics similar to those of rice, grassland, and shrubs. The features surrounding areas where it is grown are
complex, small, and fragmented. Few studies have examined the remote sensing extraction of lotus fields, and
automatic extraction and mapping are still challenging methods. Here, we compared the spectral characteristics
of lotus fields and other ground objects and devised a remote sensing method for the rapid extraction of lotus
fields. Using this method, the extraction accuracy of lotus was 96.3%. The Kappa coefficient was 0.926, which
is higher than those of the unsupervised K-means classification, Mahalanobis distance, and support vector
machine supervised classification, and demonstrates the potential of this method for extracting and mapping lotus
fields by remote sensing.},
DOI = {10.32604/phyton.2022.020117}
}