[Response of vegetation to terrestrial water storage in Southwest China]. / 西南地区植被对陆地水储量的响应.

To explore the responses of vegetation growth to change in terrestrial water storage in Southwest China, we analyzed the change trend and relationship between vegetation and terrestrial water storage anomaly (TWSA) in Southwest China from January 2003 to December 2021 by using TWSA data of Gravity Recovery and Climate Experi-ment (GRACE) satellite and normalized differential vegetation index (NDVI) data. The results showed that NDVI in Southwest China during the study period showed an overall upward trend. Meanwhile, TWSA showed a significant downward trend in central and southern Tibet, and a significant upward trend in northwest Tibet and southeast region of Southwest China. Results of Pearson correlation analysis showed that there were significant spatial differences in responses of NDVI to TWSA changes in Southwest China. NDVI had a significant negative response to TWSA changes in most regions of Tibet, but a significant positive response to TWSA changes in most regions of southeast region of Southwest China. Such differences were driven by climate change and topography.

Karst study of Jinfo Mountain based on image analysis.

The KDR (karst development rate) of rocks and their PCR(porosity of carbonate rocks) are common research topics in Jinfo Mountain. The use of traditional carbonate research methods (TCRMs) for karst studies has been shown to be costly and time-consuming. Therefore, this study attempted to find a new, reliable, low-cost, and time-saving method for karst research. The Jinfo Mountain area is a typical carbonate rock area that is suitable for karst research. In this study, many images of rock samples from the Jinfo Mountain were obtained using rock-polarizing microscopes, which provided a good basis for the karst study of Jinfo Mountain. Furthermore, in this study, image analysis technology was used to find the karst development rate of rocks and their porosity. To ensure the accuracy of these research results, we compared the research results obtained using the image analysis techniques with those obtained using TCRM. The comparison showed that the image analysis technology is a feasible research techniques for studying karst in the Jinfo Mountain area. Furthermore, it has good reference significance for other karst study outside the Jinfo Mountain area.

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

In this paper, climate change in the Jinping area is investigated. The climate change trend in the Jinping area is studied by plotting the porosity value of the carbonate rocks as a curve. By comparing the curve established using the climate change data from published articles, it is found that the B value curve obtained using the saddle line is the closest to the curve established using the climate change data from published articles. This shows that the carbonate porosity in the Jinping area obtained using an image analysis technique can be used for climate change research.

Evaluation of ecological quality in southeast Chongqing based on modified remote sensing ecological index.

Rocky desertification is a serious ecological and environmental problem in Southwest China. Quickly and scientifically reveal the distribution and changes of ecological environment quality in rocky desertification areas, which is of great significance to rocky desertification restoration, ecological environment governance and sustainable development. Based on the remote sensing ecological index (RSEI), in addition to greenness, humidity, dryness, and heat, combined with the degree of rocky desertification, this study used the principal component analysis (PCA) method to construct a modified remote sensing ecological index (MRSEI). Then, the temporal and spatial variation characteristics and imaging factors of the ecological environment quality in the typical rocky desertification region of southeastern Chongqing from 2001 to 2021 were explored. The results revealed that the greenness and humidity indicators had a positive effect on the ecological quality, while the indicators of dryness, heat and rocky desertification had the opposite impact. From 2001 to 2021, the ecological environment quality in southeastern Chongqing showed a trend of gradual improvement, and the improvement area accounted for about 70% of the total area. The elevation, slope, monthly average precipitation, and land use pattern were the main factors influencing the quality of the ecological environment in the region.

Porosity of the porous carbonate rocks in the Jingfengqiao-Baidiao area based on finite automata.

This study is based on the processing of computed microtomography images of rock samples. In this study, a finite automation is constructed using the grey value, red-green-blue (RGB) value and Euler number of polarized images of carbonate rocks from the Jingfengqiao-Baidiao area. The finite automaton is used to perform black and white binary processing of the polarized images of the carbonate rocks. The porosity of the carbonate rock is calculated based on the black and white binarization processing results of the polarized images of the carbonate rocks. The obtained porosity is compared with the carbonate porosity obtained by use of the traditional carbonate research method. When the two porosities are close, the image processing threshold of the finite automata is considered to be credible. Based on the finite automata established using the image processing threshold, the black and white binary images of the polarized images of the carbonate rocks are used to establish a rock pore image using ImageJ2X. The polarized images of the carbonate rocks are classified according to their RGB values using the finite automata for the porosity classification, and the obtained images are used as textures to paste onto a cube to construct a three-dimensional data model of the carbonate rocks. This study also uses 16S rDNA analysis to verify the formation mechanism of the carbonate pores in the Jingfengqiao-Baidiao area. The results of the 16S rDNA analysis show that the pores in the carbonate rocks in the Jingfengqiao-Baidiao area are closely related to microorganisms, represented by denitrifying bacteria.