Fig 1.
(a) The location of Qinling Mountains in China. The basemap was downloaded from http://bzdt.ch.mnr.gov.cn/index.html, and its figure number is GS(2019)1675. (b) Taibai Mountain, Landsat 8 image with a resolution of 15m, false color image (near-infrared (NIR), Red, Green), February 2017). The image is for illustrative purposes only.
Fig 2.
MAB distribution information of north and south slopes of the Taibai Mountain.
The MAB distribution information was referenced to Fang & Gao [48] and Li [49].
Table 1.
Remote sensing satellite image data information.
Fig 3.
Flowchart showing the major steps involved in the vegetation mapping process.
Table 2.
Parameters for image segmentation.
Fig 4.
Terrain constraint factors with MAB distribution information on Taibai Mountain.
The 1:10000 DSM data used to build the terrain constraint factor were generated from ZY-3 images.
Fig 5.
The process of generating vegetation belt layers with terrain constraint factors.
The image was Landsat 8 image with a resolution of 15m, false color image (NIR, Red, Green), February 2017. The image is for illustrative purposes only.
Fig 6.
The process of automatic samples selection of a specific class.
(a) Objects generated after the image multi-scale segmentation. (b) The Pinus armandii belt was superimposed on the segmentation results (c) Clustering of objects that fall within the belt (d) Initial samples (the most suitable category) selected from all the categories generated after clustering. (e) Verification and correction of initial samples.
Fig 7.
The top three categories for the number of objects in the clustering results of Pinus armandii belt.
The image was Landsat 8 image with a resolution of 15m, false color image (NIR, Red, Green), February 2017. The image is for illustrative purposes only. The categories showed in Column (a), (b) and (c) were the top three categories for the number of objects in the clustering result, and the categories in Column (a) were most suitable categories in the clustering results of Pinus armandii belt.
Fig 8.
The correction process of Pinus armandii samples by iterative clustering.
The image was Landsat 8 image with a resolution of 15 m, false color image (NIR, Red, Green), February 2017. (a) The first clustering result; (b) the second clustering result; (c) the last clustering result. The samples in the blue circles were the error samples. The image is for illustrative purposes only.
Table 3.
Comparison of the sample accuracies of the six clustering algorithm.
Fig 9.
Sample accuracies in different perspectives of Taibai Mountain.
(a) the comparison of sample accuracy before and after correction of the entire Taibai Mountain; (b) the sample accuracy on the north\south slope of Taibai Mountain; (c) the sample accuracy in the west \middle\east region of Taibai Mountain.
Fig 10.
Classification results of the corrected samples using RF classifier.
(a) Vegetation classification results, (b) distribution of error points (white stars).
Table 4.
Confusion matrix of the classification results of the RF classifier.
Table 5.
Confusion matrix of the classification results of the KNN classifier.