Detection and Projection of Forest Changes by Using the Markov Chain Model and Cellular Automata

The spatio-temporal analysis of land use changes could provide basic information for managing the protection, conservation and production of forestlands, which promotes a sustainable resource use of temperate ecosystems. In this study we modeled and analyzed the spatial and temporal dynamics of land use of a temperate forests in the region of Pueblo Nuevo, Durango, Mexico. Data from the Landsat images Multispectral Scanner (MSS) 1973, Thematic Mapper (TM) 1990, and Operational Land Imager (OLI) 2014 were used. Supervised classification methods were then applied to generate the land use for these years. To validate the land use classifications on the images, the Kappa coefficient was used. The resulting Kappa coefficients were 91%, 92% and 90% for 1973, 1990 and 2014, respectively. The analysis of the change dynamics was assessed with Markov Chains and Cellular Automata (CA), which are based on probabilistic modeling techniques. The Markov Chains and CA show constant changes in land use. The class most affected by these changes is the pine forest. Changes in the extent of temperate forest of the study area were further projected until 2028, indicating that the area of pine forest could be continuously reduced. The results of this study could provide quantitative information, which represents a base for assessing the sustainability in the management of these temperate forest ecosystems and for taking actions to mitigate their degradation

Past and Future Spatial Growth Dynamics of Chihuahua City, Mexico: Pressures for Land Use

In this study, the transitions of land use that occurred in the urban and peripheral areas of Chihuahua City, Mexico, were determined for the period 1989–2014. Landsat TM and OLI scenes, as well as the method of Markov Chains (MC) were used. Grasslands and Shrublands were the land uses that experienced the highest pressures for land use. Grasslands occupied 23.5% of the area in 1989, decreasing to 16.01% in 2014. Likewise, Shrublands were reduced from 54.53% to 48.06%. The areas occupied by Croplands, Oak forest, Water bodies and Riparian vegetation stayed in general constant. In contrast, the urban area increased from 13.6% to 28.6% of the total area studied. In addition, projections of land use for 2019 and 2024 were generated through the method of MC and Cellular Automata (CA). According to the projections, validated with an agreement of 0.90, the Human settlements would continue to expand, occupying 38.57% by 2019 and almost half of the studied territory (47.33%) by 2024. The ecosystems with the highest pressure for land use change will continue to be the Grasslands and Shrublands. By 2024, the former would lose 15.8% while the latter would lose 16.7% of the area. These methods are valuable for urban planning and the results could support growth plans for Chihuahua City, Mexico, with a sustainable approach

Modeling the Potential Distribution of Picea chihuahuana Martínez, an Endangered Species at the Sierra Madre Occidental, Mexico

Species distribution models (SDMs) help identify areas for the development of populations or communities to prevent extinctions, especially in the face of the global environmental change. This study modeled the potential distribution of the tree Picea chihuahuana Martínez, a species in danger of extinction, using the maximum entropy modeling method (MaxEnt) at three scales: local, state and national. We used a total of 38 presence data from the Sierra Madre Occidental. At the local scale, we compared MaxEnt with the reclassification and overlay method integrated in a geographic information system. MaxEnt generated maps with a high predictive capability (AUC > 0.97). The distribution of P. chihuahuana is defined by vegetation type and minimum temperature at national and state scales. At the local scale, both models calculated similar areas for the potential distribution of the species; the variables that better defined the species distribution were vegetation type, aspect and distance to water flows. Populations of P. chihuahuana have always been small, but our results show potential habitat greater than the area of the actual distribution. These results provide an insight into the availability of areas suitable for the species’ regeneration, possibly through assisted colonization

Estimation of Vegetation Cover Using Digital Photography in a Regional Survey of Central Mexico

The methods for measuring vegetation cover in Mexican forest surveys are subjective and imprecise. The objectives of this research were to compare the sampling designs used to measure the vegetation cover and estimate the over and understory cover in different land uses, using digital photography. The study was carried out in 754 circular sampling sites in central Mexico. Four spatial sampling designs were evaluated in three spatial distribution patterns of the trees. The sampling designs with photographic captures in diagonal form had lower values of mean absolute error (MAE < 0.12) and less variation in random and grouped patterns. The Carbon and Biomass Sampling Plot (CBSP) design was chosen due to its smaller error in the different spatial tree patterns. The image processing was performed using threshold segmentation techniques and was automated through an application developed in the Python language. The two proposed methods to estimate vegetation cover through digital photographs were robust and replicable in all sampling plots with different land uses and different illumination conditions. The automation of the process avoided human estimation errors and ensured the reproducibility of the results. This method is working for regional surveys and could be used in national surveys due to its functionality

Lifetime Effective Dose Assessment Based on Background Outdoor Gamma Exposure in Chihuahua City, Mexico

Determining ionizing radiation in a geographic area serves to assess its effects on a population’s health. The aim of this study was to evaluate the spatial distribution of the background environmental outdoor gamma dose rates in Chihuahua City. This study also estimated the annual effective dose and the lifetime cancer risks of the population of this city. To determine the outdoor gamma dose rate in air, the annual effective dose and the lifetime cancer risk, 48 sampling points were randomly selected in Chihuahua City. Outdoor gamma dose rate measurements were carried out by using a Geiger-Müller counter. Outdoor gamma dose rates ranged from 113 to 310 nGy·h−1. At the same sites, 48 soil samples were taken to obtain the activity concentrations of 226Ra, 232Th and 40K and to calculate their terrestrial gamma dose rates. Radioisotope activity concentrations were determined by gamma spectrometry. Calculated gamma dose rates ranged from 56 to 193 nGy·h−1. Results indicated that the lifetime effective dose of the inhabitants of Chihuahua City is on average 19.8 mSv, resulting in a lifetime cancer risk of 0.001. In addition, the mean of the activity concentrations in soil were 52, 73 and 1097 Bq·kg−1, for 226Ra, 232Th and 40K, respectively. From the analysis, the spatial distribution of 232Th, 226Ra and 40K is to the north, to the north-center and to the south of city, respectively. In conclusion, the natural background gamma dose received by the inhabitants of Chihuahua City is high and mainly due to the geological characteristics of the zone. From the radiological point of view, this kind of study allows us to identify the importance of manmade environments, which are often highly variable and difficult to characterize