Where do animals move within a municipality?

Case study: the municipality of Lacroix-Falgarde (Haute-Garonne).

Natural areas do not function in isolation: they form a network within which species must be able to move. However, urbanization, transportation infrastructure, and changing agricultural practices contribute to the fragmentation of natural habitats. This fragmentation can limit species movement and reduce exchanges of individuals between populations.

But how can we identify the areas that facilitate—or, conversely, hinder—these movements?

For a forest species, the shortest path between two forested areas is not necessarily the most favorable one. Landscape characteristics influence how easily it can move: certain structures, such as hedgerows or woodlands, can facilitate movement, while others can act as obstacles of varying significance.

Based on the ecological characteristics and movement capabilities of species such as the European hedgehog (Erinaceus europaeus), the Morimus asper, or the stag beetle (Lucanus cervus), it is possible to model the least-cost paths across the landscape. For this study, we use MitiConnect, a QGIS plugin based on the Graphab tool. It allows us to represent the resistance of various landscape elements to species movement and to identify the theoretically most favorable paths.

Can we improve this connectivity through land-use planning?

That is the question we explore in this case study. We simulate a scenario in which new hedgerows would be planted along the edges of agricultural plots. The goal is to assess the extent to which these measures could alter the least-cost paths and improve connectivity between forested areas.

What is the purpose of this approach?

Modeling ecological connectivity makes it possible, in particular, to:

• identify strategic areas that should be preserved;
• identify areas where landscaping could improve ecological connectivity;
• compare different scenarios for landscape evolution or restoration.

These results serve as a decision-making tool for land-use planning. They describe potential connectivity, not actual travel patterns observed in the field.

According to microclimatic modeling, planting vegetation at a high school could reduce the ground surface temperature by an average of 6 °C during heat waves.

The summer of 2026 was the hottest on record in France since 1900. On June 23, in the midst of a heat wave, the Haute-Garonne department was under a red alert. We modeled conditions for that day at the Saint-Exupéry High School in Blagnac.

In the site's current condition (map on the left), the ground heats up significantly: at 4:00 p.m. (local time), it reaches an average of 57 °C, and exceeds 70 °C in some areas. These areas contribute to making the courtyards and walkways unbearable for students and staff.

In the proposed solution (map on the right), approximately 1.8 ha of bare soil is replaced with grass, and 20 mature trees are planted in the hottest areas, which have been identified in advance.

The PALM-4U model takes into account solar radiation and shadows cast by buildings and trees, wind, and heat exchange between the ground, buildings, vegetation, and the air, along with the day's weather.

Key findings of this study:

In vegetated areas, the ground surface temperature would drop by an average of 19 °C, falling from 64 °C to 45 °C, and would decrease by more than 30 °C in some places. Across the entire site, the average decrease would be 6 °C.

What studies like this one make possible:

• identifying the areas that heat up the most;
• determining where and what to plant;
• comparing several landscape design scenarios to find the one that best balances the site's intended use (courtyards, pathways, sports fields) with the greatest reduction in heat, before planting the first tree.

The benefits are measured in terms of comfort and quality of life: more pleasant outdoor spaces for users, and well-informed decisions for local governments.

Why not start preparing today for the heat waves of tomorrow? Let's talk about your projects!

Description:

In the video, we can observe the various stages of this study: first, the tracking of the piece of ham (the bait); next, the tracking of the ants; and finally, the representation of the whole, including the buffer zone used to collect information.

Methodology:

We engineered an end-to-end video tracking and spatial data analytics pipeline in R to quantify cooperative transport mechanisms within ant colonies.

By integrating multi-object video tracking (AnTracks) for individual trajectories with dynamic target geometry tracking (Kinovea) for the bait, raw high-density video feeds of Paratrechina longicornis were converted into precise spatial coordinates.

We applied custom geometric polygon filtering—accounting for centroid-to-mandible offsets with a 1.5 mm confidence margin—and a 1,000-resample non-parametric bootstrap algorithm to eliminate tracking noise and isolate true interaction events.

Key results of this study:

The analysis revealed key quantitative insights into the adaptability of ants: while static food targets yielded predictable interaction durations with a mean bite time of 5.26 s (σ = 0.32 s), dynamic transport on mobile targets more than doubled interaction time to 10.58 s (σ = 3.89 s), quantifying continuous individual reorganization and heterogeneous behavior during collective transport.

69 °C at ground level in Toulouse: What do satellite images reveal about urban heat islands?

On July 7, 2026, in the midst of the second summer heat wave, the TIRS-2 thermal sensor on the Landsat 9 satellite was used to map the surface temperature of Toulouse.

The result: an average surface temperature of 48.3 °C, with maximum values reaching 69 °C!

These observations come against the backdrop of exceptional weather conditions. According to Météo-France, the summer of 2026 was the hottest on record in France since 1900. It was also marked by very low rainfall, with a 40% precipitation deficit nationwide, making this summer the second driest since 1959.

Where were surface temperatures the highest?

The highest temperatures were observed primarily in heavily developed areas: industrial and commercial zones, major transportation infrastructure, sports facilities, and paved surfaces.

Temperatures exceeding 50 °C were also observed in several residential areas in the south and west of Toulouse, particularly around Bellefontaine, Mirail, Reynerie, and Croix-de-Pierre.

Conversely, the lowest temperatures are concentrated primarily along the Garonne River and in certain green areas of the city, where the presence of water and vegetation helps limit surface heating.

Why map these temperatures?

Satellite thermal imagery makes it possible to highlight thermal contrasts on a city-wide scale and identify areas where urban surfaces accumulate the most heat.

This approach, however, has significant limitations: Landsat measures surface temperature, not air temperature at human height. Furthermore, its native thermal resolution of 100 m does not allow for precise differentiation between various surface types within a single pixel, which may include roofs, roads, and vegetation.

Despite these limitations, remote sensing is a valuable tool for urban environmental assessment. When combined with data on vegetation, soil sealing, and urban morphology, it helps identify priority areas and guide strategies for greening, de-sealing, and adapting cities to extreme heat.