Research on climate change based on carbonate porosity analysis in Jinping, China

obtained via thresholding using the gray value and RGB values. To distinguish it from the background color of the manuscript (white), the binary image is displayed in blue-black instead of white-black. The polarized light microscope images of all of the carbonate rocks were used to obtain the porosity using the method shown in Fig 6, and Table 2 was obtained. Fig 6 and Table 2 present the results of the porosity study of carbonate rock polarizing microscopic images using finite automata. Based on these results, the finite automata algo- rithm is a good algorithm for porosity research involving carbonate image analysis. When studying the porosity of carbonate rock images, the finite automaton does not necessarily require the use of saddle line mapping to obtain the porosity of the carbonate rock. If different gray values or RGB values are used as the threshold of the finite automata, the porosity of car- bonate rocks can also be obtained. 3.3 Use of image analysis results to generate climate change curves Curves for loess and stalagmites can reflect climate change because loess and stalagmites are closely related to climate. The porosity of carbonate rocks is also closely related to climate change. The porosity curves of carbonate rocks should be similar to the curves for loess and stalagmites, which can reflect local climate changes. Therefore, in this study, it was assumed that the porosity curve created using the carbonate rock polarized images could be used as the

Table 2. Porosity obtained from polarized light microscope images of carbonate rocks from the Jinping area using the RGB values and gray value. A B C D E F G H I J 1-1 P 1(q+m) 27 0.022 101 0.077 135 2.643 101 0.387 1-2 P 1(q+m) 27 0.097 101 0.257 135 2.066 27 1.009 1-3 P 1(q+m) 27 0.717 101 1.121 135 3.151 27 1.385 2-1 P 2β 27 1.271 101 2.599 27 1.76 101 2.471 2-2 P 2β 27 1.792 101 2.284 27 1.997 101 2.573 2-3 P 2β 27 0.707 101 2.59 27 1.341 101 3.017 3-1 P 2x 27 1.244 101 2.672 27 2.483 27 6.154 3-2 P 2x 27 3.948 27 1.802 27 7.135 27 14.198 4-1 T 1q 27 3.99 27 1.602 27 5.886 27 6.312 4-2 T 1q 27 0.097 101 0.225 27 0.159 101 0.359 5-1 T 2b 27 0.03 101 0.406 27 0.043 101 0.52 5-2 T 2b 122 0.716 135 0.224 135 2.125 27 0.669 5-3 T 2b 27 0.083 101 1.902 27 0.59 27 2.47 6-1 T 2y 175 5.908 27 8.047 27 8.429 27 13.92 6-2 T 2y 27 3.402 27 1.268 27 2.06 27 19.38 7-1 T 2z 175 1.878 27 6.69 27 7.697 27 22.93 7-2 T 2z 27 5.162 27 2.275 27 2.637 27 19.15 7-3 T 2z 27 5.039 27 2.897 27 3.235 27 19.37 8-1 T 3 27 3.31 27 1.502 27 5.639 27 12.72 8-2 T 3 27 4.217 27 2.43 27 6.141 27 11.008 8-3 T 3 27 3.318 27 1.912 27 6.055 27 15.556 9-1 J 1 27 1.858 27 0.95 27 3.765 27 13.722 9-2 J 1 27 2.04 27 0.523 27 5.043 27 15.803 9-3 J 1 27 6.62 27 4.01 27 4.802 27 22.476

A: serial number; B: Strata; C: Gray value threshold; D: Porosity obtained using gray value threshold (%); E: R threshold; F: Porosity obtained using R threshold (%); G: G threshold; H: Porosity obtained using G threshold (%); I: B threshold; J: Porosity obtained using B threshold (%). https://doi.org/10.1371/journal.pone.0281630.t002 PLOS ONE Research on climate change based on carbonate porosity analysis in Jinping PLOS ONE | https://doi.org/10.1371/journal.pone.0281630 March 30, 2023 12 / 21