Un SIG pour analyser les stratégies de mise en valeur du milieu par des éleveurs de moutons

Une base de données géographique «Milieu naturel - pratiques d’élevage» a été mise en place sur un secteur de l’arrière-pays méditerranéen, le Lodévois (Hérault)

A spatial stochastic algorithm to reconstruct artificial drainage networks from incomplete network delineations

Contact: [email protected], [email protected], [email protected] spatial stochastic algorithm that aims to reconstruct an entire artificial drainage network of a cultivated landscape from disconnected reaches of the network is proposed here. This algorithm uses random network initialisation and a simulated annealing algorithm, both of which are based on random pruning or branching processes, to converge the multi-objective properties of the networks; the reconstructed networks are directed tree graphs, conform to a given cumulative length and maximise the proportion of reconnected reaches. This algorithm runs within a directed plot boundaries lattice, with the direction governed by elevation. The proposed algorithm was applied to a 2.6-km2 catchment of a Languedocian vineyard in the south of France. The 24-km-long reconstructed networks maximised the reconnection of the reaches obtained either from a hydrographic database or remote sensing data processing. The distribution of the reconstructed networks compared to the actual networks was determined using specific topographical and topological metrics on the networks. The results show that adding data on disconnected reaches to constrain reconstruction, while increasing the accuracy of the reconstructed network topology, also adds biases to the geometry and topography of the reconstructed network. This network reconstruction method allows the mapping of uncertainties in the representation while integrating most of the available knowledge about the networks, including local data and global characteristics. It also permits the assessment of the benefits of the remote sensing partial detection process in drainage network mapping

Simulating the effects of spatial configurations of agricultural ditch drainage networks on surface runoff from agricultural catchments

The study of runoff is a crucial issue because it is closely related to flooding, water quality and erosion. In cultivated catchments, agricultural ditch drainage networks are known to influence runoff. As anthropogenic elements, agricultural ditch drainage networks can therefore be altered to better manage surface runoff in cultivated catchments. However, the relationship between the spatial configuration, i.e., the density and the topology, of agricultural ditch drainage networks and surface runoff in cultivated catchments is not understood. We studied this relationship by using a random network simulator that was coupled to a distributed hydrological model. The simulations explored a large variety of spatial configurations corresponding to a thousand stochastic agricultural ditch drainage networks on a 6.4 km2 Mediterranean cultivated catchment. Next, several distributed hydrological functions were used to compute water flow-paths and runoff for each simulation. The results showed that (i) denser networks increased the drained volume and the peak discharge and decreased hillslopes runoff, (ii) greater network density did not affect the surface runoff any further above a given network density, (iii) the correlation between network density and runoff was weaker for small subcatchments (< 2 km2) where the variability in the drained area that resulted from changes in agricultural ditch drainage networks increased the variability of runoff and (iv) the actual agricultural ditch drainage network appeared to be well optimized for managing runoff as compared with the simulated networks. Finally, our results highlighted the role of agricultural ditch drainage networks in intercepting and decreasing overland flow on hillslopes and increasing runoff in drainage networks

Chapitre 2 - Enjeux autour des terres agricoles et des données pédologiques : point de vue opérationnel d’un service de l’État en région

Foncier et développement En France, la planification de l’espace urbain relève du niveau local (communes et intercommunalités) dans le respect du cadre réglementaire qui impose la prise en considération d’enjeux nationaux tels que la préservation des populations (risques naturels en particulier) ou la protection de l’environnement. Il n’existe pas aujourd’hui de prescriptions nationales imposant la préservation d..

Reconnaissance du patrimoine agronomique des sols : une démarche novatrice en Languedoc-Roussillon.

En Languedoc-Roussillon, depuis les années 1960, l’afflux de population se traduit par une urbanisation rapide et mal maîtrisée de la plaine littorale, notamment sur les terres les plus productives. La perte de ces terres est au cœur des préoccupations des institutions et des acteurs agricoles qui s’interrogent sur les conditions à réunir pour conserver ce patrimoine productif à long terme. Cet article présente la démarche novatrice conduite avec les instances agricoles régionales et départementales pour contribuer à la reconnaissance et à la préservation du patrimoine agronomique des sols. La démarche s’appuie sur la construction d’un indice de qualité des sols spatialisé et sur la mise en place d’une méthode de traitement d’images satellitaires pour suivre la progression des espaces artificialisés dans le temps. L’application de ces méthodologies, à l’échelle des quatre départements littoraux du Languedoc-Roussillon, permet d’estimer la quantité et la qualité des terres perdues par artificialisation de 1997 à 2009. Les résultats de cette étude révèlent les besoins en connaissance qui permettraient d’identifier et de mesurer les enjeux liés à la protection des espaces agricoles en zone périurbaine. La production de données spatiales nouvelles a permis de répondre en partie aux besoins des acteurs, en revanche d’importants efforts restent à faire pour accompagner la diffusion et assurer l’opérationnalité des données produites.Population growth in the Languedoc coastal region has been very high for several decades. This phenomenon has spawned rapid and uncontrolled urban sprawl at the expense of agricultural lands. While these lands have often high agronomical potential, they are most often permanently lost. This paper presents an innovative approach with the agricultural institutions of Languedoc-Roussillon and is intended to contribute to the acknowledgement and preservation of our agronomical land heritage. The proposed approach is based on the construction of a spatialized soil quality index and on the application of a satellites images treatment process in order to follow the evolution of artificialized spaces in time. The application of those methodologies, scalled to the four coastal Departements of Languedoc-Roussilon, allow to estimate the quantity and the quality of lost lands by artificialization, from 1997 to 2009. The results of this study reveals the importance of needs remaining to be given to produce a fine knowledge that would allow to identify and to measure the goals linked to the protection of agricultural lands in periurban area. The production of new spatial data has allowed a partial response to the needs of stakeholders, however significant efforts are needed to ensure operational capability of the produced data

Grapevine Yield Big-data for Soil and Climate Zoning. A case study in Languedoc-Roussillon, France

New winegrower and resource datasets appear to be a great opportunity to understand which are the environmental factors involved in grapevine yield spatially. Such analysis can help regional label managers and winegrowers for the conception of local adaptation strategies to climate change, reducing yield gaps. In the present study, we aggregated yield a big dataset obtained from Pays d’Oc winegrowers (n = 96677) between 2010 and 2018 at the municipality level (n = 606), located in the Languedoc-Roussillon region, in the South of France. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select significant indicators capable of estimating grapevine yield at the municipality level, these include: Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. We then determined spatial zones by creating clusters of municipalities with similar soil and climate characteristics. The seven zones presented two marked yield levels. Yet, all zones had municipalities with both high yield and high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than just by a single environmental factor. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental factors, plant material and farming practices

Digital mapping of GlobalSoilMap soil properties at a broad scale: a review

Soils are essential for supporting food production and providing ecosystem services but are under pressure due to population growth, higher food demand, and land use competition. Because of the effort to ensure the sustainable use of soil resources, demand for current, updatable soil information capable of supporting decisions across scales is increasing. Digital soil mapping (DSM) addresses the drawbacks of conventional soil mapping and has been increasingly used for delivering soil information in a time- and cost-efficient manner with higher spatial resolution, better map accuracy, and quantified uncertainty estimates. We reviewed 244 articles published between January 2003 and July 2021 and then summarised the progress in broad-scale (spatial extent >10,000 km2) DSM, focusing on the 12 mandatory soil properties for GlobalSoilMap. We observed that DSM publications continued to increase exponentially; however, the majority (74.6%) focused on applications rather than methodology development. China, France, Australia, and the United States were the most active countries, and Africa and South America lacked country-based DSM products. Approximately 78% of articles focused on mapping soil organic matter/carbon content and soil organic carbon stocks because of their significant role in food security and climate regulation. Half the articles focused on soil information in topsoil only (<30 cm), and studies on deep soil (100–200 cm) were less represented (21.7%). Relief, organisms, and climate were the three most frequently used environmental covariates in DSM. Nonlinear models (i.e. machine learning) have been increasingly used in DSM for their capacity to manage complex interactions between soil information and environmental covariates. Soil pH was the best predicted soil property (average R2 of 0.60, 0.63, and 0.56 at 0–30, 30–100, and 100–200 cm). Other relatively well-predicted soil properties were clay, silt, sand, soil organic carbon (SOC), soil organic matter (SOM), SOC stocks, and bulk density, and coarse fragments and soil depth were poorly predicted (R2 < 0.28). In addition, decreasing model performance with deeper depth intervals was found for most soil properties. Further research should pursue rescuing legacy data, sampling new data guided by well-designed sampling schemas, collecting representative environmental covariates, improving the performance and interpretability of advanced spatial predictive models, relating performance indicators such as accuracy and precision to cost-benefit and risk assessment analysis for improving decision support; moving from static DSM to dynamic DSM; and providing high-quality, fine-resolution digital soil maps to address global challenges related to soil resources

Les terres agricoles face à l’urbanisation

La perte de terres agricoles liées à l’urbanisation constitue l’une des facettes de la consommation des terres. Commencé dans les années 1970, ce phénomène — essentiellement dû à l’étalement urbain — prend des proportions jusque-là inégalées. Les conséquences de ces processus d’artificialisation sont multiples et portent à la fois sur la production et sur la sécurité alimentaire ainsi que sur la perte de biodiversité. Ces processus interrogent aussi les formes de solidarité territoriale entre les villes et les espaces péri-urbains et ruraux. Issu d’une collaboration scientifique lancée au début des années 2010 entre l’Université de technologie de Sydney (University of Technology Sydney, UTS) et l’Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture (Irstea), cet ouvrage aborde des points clés de la problématique de la consommation des terres en se focalisant sur les terres agricoles en France et en Australie. Plutôt que d’offrir une analyse comparative approfondie de la planification des terres agricoles périurbaines entre les deux pays, il propose une exploration des « boîtes à outils » de l’ingénierie territoriale développées et mobilisées pour faire face à l’enjeu de la perte de terres agricoles liée à l’urbanisation. Il offre également un « arrêt sur image » dans un panorama de champs de recherche en pleine évolution, autant du point de vue théorique que méthodologique