Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat

Landsat-9 is the latest satellite of the Landsat program and provides useful agricultural remote sensing data. The earlier the crop distribution data is obtained, the greater the value of the data. However, whether Landsat-9 image is suitable for the early-season mapping of winter garlic and winter...

Full description

Saved in:
Bibliographic Details
Main Authors: Haifeng Tian, Mengdan Yang, Fangli Wu, Yaochen Qin, Xiwang Zhang, Jiayi Liu, Weiyang Yan
Format: Article
Language:English
Published: Taylor & Francis Group 2024-11-01
Series:Geo-spatial Information Science
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/10095020.2024.2311868
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846127669830221824
author Haifeng Tian
Mengdan Yang
Fangli Wu
Yaochen Qin
Xiwang Zhang
Jiayi Liu
Weiyang Yan
author_facet Haifeng Tian
Mengdan Yang
Fangli Wu
Yaochen Qin
Xiwang Zhang
Jiayi Liu
Weiyang Yan
author_sort Haifeng Tian
collection DOAJ
description Landsat-9 is the latest satellite of the Landsat program and provides useful agricultural remote sensing data. The earlier the crop distribution data is obtained, the greater the value of the data. However, whether Landsat-9 image is suitable for the early-season mapping of winter garlic and winter wheat is a problem worthy of attention. Therefore, this study evaluates the potential to use two Landsat-9 images, acquired on 13 December 2021 and 30 January 2022, for the early-season identification of winter garlic and winter wheat in China. According to J-M (Jeffries-Matusita) distances, we evaluated the separability of winter garlic, winter wheat, and other ground objects based on the two Landsat-9 images. Then, winter garlic and winter wheat were extracted by using unsupervised classification method, i.e. the IsoData and K-means clustering algorithms, and supervised classification method, i.e. the Random Forest (RF), and Support Vector Machine (SVM) algorithms. The separability between garlic and wheat in January is stronger than that in December. The classification overall accuracy based on the Landsat-9 image on 30 January 2022 is 92.03% with a kappa coefficient of 0.87 using the SVM algorithm. This period is about 4 months earlier than the crop harvest period. Landsat-9 images have good potentiality for early-season mapping of winter garlic and winter wheat.
format Article
id doaj-art-6d84ce08bc644801ae456a74a4ff3324
institution Kabale University
issn 1009-5020
1993-5153
language English
publishDate 2024-11-01
publisher Taylor & Francis Group
record_format Article
series Geo-spatial Information Science
spelling doaj-art-6d84ce08bc644801ae456a74a4ff33242024-12-11T11:57:33ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532024-11-012762199221010.1080/10095020.2024.2311868Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheatHaifeng Tian0Mengdan Yang1Fangli Wu2Yaochen Qin3Xiwang Zhang4Jiayi Liu5Weiyang Yan6Henan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaHenan International Joint Laboratory of Geospatial Technology, College of Geography and Environmental Science, Henan University, Kaifeng, ChinaLandsat-9 is the latest satellite of the Landsat program and provides useful agricultural remote sensing data. The earlier the crop distribution data is obtained, the greater the value of the data. However, whether Landsat-9 image is suitable for the early-season mapping of winter garlic and winter wheat is a problem worthy of attention. Therefore, this study evaluates the potential to use two Landsat-9 images, acquired on 13 December 2021 and 30 January 2022, for the early-season identification of winter garlic and winter wheat in China. According to J-M (Jeffries-Matusita) distances, we evaluated the separability of winter garlic, winter wheat, and other ground objects based on the two Landsat-9 images. Then, winter garlic and winter wheat were extracted by using unsupervised classification method, i.e. the IsoData and K-means clustering algorithms, and supervised classification method, i.e. the Random Forest (RF), and Support Vector Machine (SVM) algorithms. The separability between garlic and wheat in January is stronger than that in December. The classification overall accuracy based on the Landsat-9 image on 30 January 2022 is 92.03% with a kappa coefficient of 0.87 using the SVM algorithm. This period is about 4 months earlier than the crop harvest period. Landsat-9 images have good potentiality for early-season mapping of winter garlic and winter wheat.https://www.tandfonline.com/doi/10.1080/10095020.2024.2311868Landsat-9winter garlicwinter wheatearly-season mappingremote sensing
spellingShingle Haifeng Tian
Mengdan Yang
Fangli Wu
Yaochen Qin
Xiwang Zhang
Jiayi Liu
Weiyang Yan
Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
Geo-spatial Information Science
Landsat-9
winter garlic
winter wheat
early-season mapping
remote sensing
title Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
title_full Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
title_fullStr Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
title_full_unstemmed Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
title_short Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat
title_sort potentiality of landsat 9 for early season mapping of winter garlic and winter wheat
topic Landsat-9
winter garlic
winter wheat
early-season mapping
remote sensing
url https://www.tandfonline.com/doi/10.1080/10095020.2024.2311868
work_keys_str_mv AT haifengtian potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT mengdanyang potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT fangliwu potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT yaochenqin potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT xiwangzhang potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT jiayiliu potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat
AT weiyangyan potentialityoflandsat9forearlyseasonmappingofwintergarlicandwinterwheat