Integrating Remote Sensing, GIS and Prediction Models to Monitor the Deforestation and Erosion in Peten Reserve, Guatemala

International audienceThis contribution provides a strategy for studying and modelling the deforestation and soil deterioration in the natural forest reserve of Peten, Guatemala, using a poor spatial database. A Multispectral Image Processing of Spot and TM Landsat data permits to understand the behaviour of the past land cover dynamics; a multi-temporal analysis of Normalized Difference Vegetation and Hydric Stress index, most informative RGB (according to statistical criteria) and Principal Components, points out the importance and the direction of environmental impacts. We gain from the Remote Sensing images new environmental criteria (distance from roads, oil pipe-line, DEM, etc.) which influence the spatial allocation of predicted land cover probabilities. We are comparing the results of different prospective approaches (Markov Chains, Multi Criteria Evaluation and Cellular Automata; Neural Networks) analysing the residues for improving the final model of future deforestation risk

Prospective modelling of environmental dynamics. A methodological comparison applied to mountain land cover changes

During the last 10 years, scientists performed significant advances in modelling environmental dynamics. A wide range of new methodological approaches in geomatics - such as neural networks, multi-agent systems or fuzzy logics - was developed. Despite these progresses, the modelling softwares available have to be considered as experimental tools rather than as improved procedures able to work for environmental management or decision support. Particularly, the authors consider that a large number of publications suffer from lakes in the validation of the model results. This contribution describes three different modelling approaches applied to prospective land cover prediction. The first one, a combined geomatic method, uses Markov chains for temporal transition prediction while their spatial assignment is supervised manually by the construction of suitability maps. Compared to this directed method, the two others may be considered as semi automatic because both the polychotomous regression and the multilayer perceptron only need to be optimized during a training step - the algorithms detect themselves the spatial-temporal changes in land cover. The authors describe the three methodological approaches and their practical applications to two mountain studied areas: one in French Pyrenees, the second including a large part of Sierra Nevada, Spain. The article focuses on the comparison of results. The main result is that prediction scores are on the more high that land cover is persistent. They also underline that the geomatic model is complementary to the statistical ones which perform higher overall prediction rate but produce worse simulations when land cover changes are numerous

Various Approaches for Predicting Land Cover in Mountain Areas

Using former maps, geographers intend to study the evolution of the land cover in order to have a prospective approach on the future landscape; predictions of the future land cover, by the use of older maps and environmental variables, are usually done through the GIS (Geographic Information System). We propose here to confront this classical geographical approach with statistical approaches: a linear parametric model (polychotomous regression modeling) and a nonparametric one (multilayer perceptron). These methodologies have been tested on two real areas on which the land cover is known at various dates; this allows us to emphasize the benefit of these two statistical approaches compared to GIS and to discuss the way GIS could be improved by the use of statistical models.Comment: 14 pages; Classifications: Information Theory; Probability Theory & Applications; Statistical Computing; Statistical Theory & Method

Modelling Tropical Deforestation: A Comparison of Approaches

International audienceTropical deforestation, as an important factor in global change, is a topic that recently has received considerable attention. GIS-based spatially explicit models that intend to predict the location of land use/cover change (LUCC) can help scientists and policy makers to understand, anticipate and possibly prevent the adverse effects of land-use change. There are many approaches and softwares to model LUCC such as CLUE-S, DINAMICA GEOMOD and IDRISI. This study intends to compare these four modelling approaches. First, a review of methods and tools employed by each software to carry out the simulation was done. Then, the four packages were applied to a "virtual" case which involves a map of deforestation, which comprises two types of deforestation (forest to shifting agriculture and forest to pasture lands), along with several explanatory variables (drivers). Deforestation was modelled using the four approaches and the output maps were compared

Dealing with locally-driven degradation: A quick start option under REDD+

The paper reviews a number of challenges associated with reducing degradation and its related emissions through national approaches to REDD+ under UNFCCC policy. It proposes that in many countries, it may in the short run be easier to deal with the kinds of degradation that result from locally driven community over-exploitation of forest for livelihoods, than from selective logging or fire control. Such degradation is low-level, but chronic, and is experienced over very large forest areas. Community forest management programmes tend to result not only in reduced degradation, but also in forest enhancement; moreover they are often popular, and do not require major political shifts. In principle these approaches therefore offer a quick start option for REDD+. Developing reference emissions levels for low-level locally driven degradation is difficult however given that stock losses and gains are too small to be identified and measured using remote sensing, and that in most countries there is little or no forest inventory data available. We therefore propose that forest management initiatives at the local level, such as those promoted by community forest management programmes, should monitor, and be credited for, only the net increase in carbon stock over the implementation period, as assessed by ground level surveys at the start and end of the period. This would also resolve the problem of nesting (ensuring that all credits are accounted for against the national reference emission level), since communities and others at the local level would be rewarded only for increased sequestration, while the national reference emission level would deal only with reductions in emissions from deforestation and degradation

Exploring subtle land use and land cover changes: a framework for future landscape studies

UMR AMAP, équipe 3International audienceLand cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling

PKA and Epac cooperate to augment bradykinin-induced interleukin-8 release from human airway smooth muscle cells

Background: Airway smooth muscle contributes to the pathogenesis of pulmonary diseases by secreting inflammatory mediators such as interleukin-8 (IL-8). IL-8 production is in part regulated via activation of G(q)-and G(s)-coupled receptors. Here we study the role of the cyclic AMP (cAMP) effectors protein kinase A (PKA) and exchange proteins directly activated by cAMP (Epac1 and Epac2) in the bradykinin-induced IL-8 release from a human airway smooth muscle cell line and the underlying molecular mechanisms of this response.Methods: IL-8 release was assessed via ELISA under basal condition and after stimulation with bradykinin alone or in combination with fenoterol, the Epac activators 8-pCPT-2'-O-Me-cAMP and Sp-8-pCPT-2'-O-Me-cAMPS, the PKA activator 6-Bnz-cAMP and the cGMP analog 8-pCPT-2'-O-Me-cGMP. Where indicated, cells were pre-incubated with the pharmacological inhibitors Clostridium difficile toxin B-1470 (GTPases), U0126 (extracellular signal-regulated kinases ERK1/2) and Rp-8-CPT-cAMPS (PKA). The specificity of the cyclic nucleotide analogs was confirmed by measuring phosphorylation of the PKA substrate vasodilator-stimulated phosphoprotein. GTP-loading of Rap1 and Rap2 was evaluated via pull-down technique. Expression of Rap1, Rap2, Epac1 and Epac2 was assessed via western blot. Downregulation of Epac protein expression was achieved by siRNA. Unpaired or paired two-tailed Student's t test was used.Results: The beta(2)-agonist fenoterol augmented release of IL-8 by bradykinin. The PKA activator 6-Bnz-cAMP and the Epac activator 8-pCPT-2'-O-Me-cAMP significantly increased bradykinin-induced IL-8 release. The hydrolysis-resistant Epac activator Sp-8-pCPT-2'-O-Me-cAMPS mimicked the effects of 8-pCPT-2'-O-Me-cAMP, whereas the negative control 8-pCPT-2'-O-Me-cGMP did not. Fenoterol, forskolin and 6-Bnz-cAMP induced VASP phosphorylation, which was diminished by the PKA inhibitor Rp-8-CPT-cAMPS. 6-Bnz-cAMP and 8-pCPT-2'-O-Me-cAMP induced GTP-loading of Rap1, but not of Rap2. Treatment of the cells with toxin B-1470 and U0126 significantly reduced bradykinin-induced IL-8 release alone or in combination with the activators of PKA and Epac. Interestingly, inhibition of PKA by Rp-8-CPT-cAMPS and silencing of Epac1 and Epac2 expression by specific siRNAs largely decreased activation of Rap1 and the augmentation of bradykinin-induced IL-8 release by both PKA and Epac.Conclusion: Collectively, our data suggest that PKA, Epac1 and Epac2 act in concert to modulate inflammatory properties of airway smooth muscle via signaling to the Ras-like GTPase Rap1 and to ERK1/2.</p

Interest in intermediate soft-classified maps in land change model validation: suitability versus transition potential

International audienceThis study compares two types of intermediate soft-classified maps. The first type uses land use/cover suitability maps based on a multi-criteria evaluation (MCE). The second type focuses on the transition potential between land use/cover categories based on a multi-layer perceptron (MLP). The concepts and methodological approaches are illustrated in a comparable manner using a Corine data set from the Murcia region (2300 km 2 , Spain) in combination with maps of drivers that were created with two stochastic, discretely operating, commonly used tools (MCE in CA_MARKOV and MLP in Land Change Modeler). The importance of the different approaches and techniques for the obtained results is illustrated by comparing the specific characteristics of both approaches by validating the suitability versus transition potential maps to each other using a Spearman correlation matrix and, between the Corine maps, using classical ROC (receiver operating characteristic) statistics. Then, we propose a new use of ROC statistics to compare these intermediate soft-classified maps with their respective hard-classified maps of the models for each category. The validation of these results can be beneficial in choosing a suitable model and provide a better understanding of the implications of the different modeling steps and the advantages and limitations of the modeling tools

Mise en place d'une méthodologie pour une classification automatique de l'occupation des sols à partir de photos aériennes panchromatiques dans la vallée du Vicdessos

National audienc