The dynamic of consolidation of urban areas in Latin America has allowed that almost 80% of the population concentrates in cities; this has produced changes in land covers and modified regional climate, propitiating the appearance of urban heat islands. The Metropolitan Area of Toluca, State of Mexico, Mexico, holds the fifth national place in population size and experiences this process, because of this, the objective is to analyze and compare the spatiotemporal characteristics of the atmospheric urban heat island obtained from data gathered from 12 urban and rural weather stations with the surface urban heat island obtained from the digital processing of four Landsat 8 images. Results show the year-round presence of night-time atmospheric urban heat islands, which reach a peak in autumn (up to 6 °C). Daytime atmospheric urban heat islands occur in summer and autumn with a maximum intensity of 4 °C. For their part, surface urban heat islands occur in spring, summer and autumn and reach maximums of 19 °C in intensity. A strong correlation was found between wetness and surface temperature (coefficient of determination, 0.8) in spring and winter. Soil wetness directly impacts the formation of weak urban heat islands in dry season, and intense ones in wet season, while the green areas and the winds affect the spatial distribution of the same.

Seed bank and established vegetation in the last remnants of the Mexican Central Plateau wetlands: the Lerma marshes

Dams must provide human development with economic viability, social equitability, and be environmentally sustainable However, environmental and social impacts are often negative and seldom considered in the design of these projects. We made a multitemporal analysis classifying 26 satellite images of several Mexican hydroelectric power stations between 1972 and 2016 to evaluate the effect of dams on the change in land use. Eleven socio-economic indicators were also compared before and after the construction of the dam to document effects on local communities. We use the Land Change Modeler to quantify the net changes in land use and land cover. We found a mean decrease in tropical forest (1,404.19 km2) and temperate forest (1,191.26 km2) and an increase in agriculture (2,241.26 km2) and urban use (92.9 km2). The results also show that although some indicators improved, the environmental deterioration around these projects shows that they are not sustainable. Graphical Abstract

Mexico’s vast archaeological research tradition has increased with the use of remote sensing technologies; however, this recent approach is still costly in emerging market economies. In addition, the scales of prospection, landscape, and violence affect the type of research that heritage-culture ministries and universities can conduct. In Central Mexico, researchers have studied the pre-Hispanic Settlement Pattern during the Mesoamerican Postclassic (900-1521 AD) within the scope of the Aztec Empire and its conquests. There are settlements indications before and during the rule of the central empire, but the evidence is difficult to identify, particularly in the southwest of the capital, in the transition between the Lerma and Balsas River basins and their political-geographical complexities. This research focuses on a Geographic Information System (GIS)-based processing of multiple source data, the potential prospection of archaeological sites based on spatial data integration from Sentinel-2 optical sensors, Unmanned Aerial Vehicle (UAV), Digital Terrain Model (DTM), Normalized Difference Vegetation Index (NDVI) and field validation. What is revealed is the relationship between terrain morphologies and anthropic modifications. A binary map expresses possible archaeological remnants as a percentage; NDVI pixels and the morphometry values were associated with anthropic features (meso-reliefs with a tendency to regular geometries: slope, orientation, and roughness index); they were then interpreted as probable archaeological evidence. Within archaeological fieldwork, with limited resources (time, funding and staff), this approach proposes a robust method that can be replicated in other mountainous landscapes that are densely covered by vegetation.