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

porous carbonate rocks provide a good research basis for climate change in the local carbonate rock area. Climate change research requires a time axis, and the stratum is a good basis for construct- ing the time axis. In the carbonate rock area, if the collected carbonate rock samples include all of the carbonate rock strata, this is sufficient to establish the time axis for climate change research. If the research funds permit, it is suggested that more carbonate rock samples be col- lected from the same stratum, and the average porosity of these carbonate rock samples be taken as the basis for the climate change curve. This can improve the accuracy of the climate change curve. 2.2 Porosity analysis using a polarized light image of a carbonate rock and a finite automaton When a polarized image of a carbonate rock is used to analyze the pores in the carbonate rock, the main method is to divide the number of pixels in the image that are pores by the total num- ber of pixels. Thus, the premise of obtaining the porosity of the carbonate rock using the image analysis method is to correctly identify the carbonate pore pixels. In this study, in order to correctly identify the pore pixels in the polarized image of the carbonate rock, a finite automaton was used as the algorithm model for the carbonate rock image analysis. The gray value has been commonly used to conduct carbonate climate change research in previous stud- ies, and the gray value formula is relatively easy to introduce in finite automata. Owing to the

characteristics of finite automata, the modification to the mapping must be conducted using a finite number. The porosity change curve based on the gray value shown in Figure 7 is not consistent with the climate change trend shown in Fig 8(a). The gray scale curve based on polarized images of carbonate rock samples created in this study was mainly obtained using the gray scale formula. Since a given polarized image of a carbonate rock is different from the other images, the standard gray-scale formula may not be suitable for use with polarized images of carbonate rocks. For this reason, finite automata were used in this study [26]. 2.3 Fitting of climate change curves Curve fitting is a common operation in computer graphics. The curve established from the pore value of the carbonate rock will not have too many nodes due to the small number of car- bonate rock samples. However, the number of curve nodes obtained using research methods such as stalagmites and lake sediments is very large. Thus, the number of nodes in the climate change curve established using the carbonate porosity should not be too small. It is not feasible to add curve nodes by appending carbonate samples. Curve fitting is a more feasible method. There are many curve fitting algorithms, and choosing an appropriate algorithm is a very important issue. The following points must be considered when selecting a curve fitting algo- rithm. The algorithm cannot change the general trend of the climate change curve, and the

algorithm should provide sufficient fitting values. In this study, the cardioids curvy function was chosen to fit the climate change curve. x ¼ a � ð2 � cosðtÞ cosð2 � tÞÞ y ¼ a � ð2 � sinðtÞ sinð2 � tÞÞ t 2 ½0; 360� 8 > > > < > > > : ð1Þ According to the above curve fitting formula, the curve in Fig 8(b) was fit to that in Fig 3 (b). 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 6 / 21