Menu des cours. Calendrier des cours · Cours de Télédétection · Cours de SIG · Cours de GPS. Course. No course has been selected. Please selected a course . Lillesand T.M. and Kiefer R.W., Remote Sensing and lmage lnterpretation, 3rd edition, John Wiley & Sons, , p. Monget J.-M., Cours de teledetection. Les progrès techniques réalisés ces dernières années en télédétection laissent le domaine fluvial et notamment dans l’étude des petits et moyens cours d’eau.
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Recent progress in remote sensing is promising significant advances in fluvial sciences particularly in the study of small and medium rivers. Indeed, sensor resolutions are improving markedly thus allowing for narrower channels to be imaged and acquisition frequencies for airborne methods have also improved thus allowing for multi-annual surveys.
Furthermore, satellite data can now be complemented by catchment scale high resolution airborne orthorectified imagery often collected by national agencies such as the IGN.
Data acquisition can now be planned on a multi-annual basis and acquired from a range of platforms such as standard survey aircraft, helicopters, ultralight aircraft or unmanned aerial vehicles UAVs.
The aim of this paper is to illustrate progress in this field with a series of examples. Using both satellite data SPOT, Landsat and QuickBird and UAV data, the paper will examine a range of temporal and spatial scales from river reaches exceeding ten kilometres to smaller reaches where human impacts have been diagnosed. NDVI longitudinal variation profile coefficient of variation calculated on ash and poplar data coverage on an image B. Deux exemples illustrent ces propos.
Le principe retenu repose sur le calcul de la semi-variance. Celle-ci permet le calcul de la semi-variance 2D. Etat de la bande active en Active channel in Bel Hadj Ali A. Water Resources ResearchArticle No.
Earth Surface Processes and Landforms 31, Earth Surface Processes and Landforms Gravel Bed Rivers 6. Remote Sensing of Environment Tools in Fluvial Geomorphology. Earth Surface Processes and Landforms 22, A quick look at a large river.
CU-SIGETA | Centre universitaire SIG et Teledetection au Burkina Faso
Photogrammetric Record 16, Earth Surface Courw and Landforms 32, Applied Optics Geomorphology 55, Remote Sensing of the Environment 43, International Journal of Remote Sensing 19, Freshwater Biology 29, Photogrammetric Engineering end remote sensing 67, Hydrological Processes GIS and remote sensing analyses. Paper presented at the Braided Rivers Conference, Br.
Group, London, April, poster unpublished.
Hydrological Sciences Journal Remote sensing is increasingly used teledetectioj order to characterise river corridors. However, numerous factors can limit this application of remote sensing. The spatial resolution of the sensors must be adapted to the detection of river and flood plain features e. Furthermore, the temporal acquisition rate of data must be capable of teledetectiion rapid change, sometimes on the order of a few hours post-flood.
As a result of these limitations, satellite remote sensing has only been applied to large rivers and their catchments Muller et al. In recent years, new satellite data has begun to offer data on metric e.
This new high-resolution data is available and better suited to the characterisation of intra-fluvial landscapes.
Abridged English version
Despite this progress, few studies have applied satellite remote sensing to a detailed characterisation of fluvial forms owing to still insufficient spatial resolution. Satellite remote sensing data can only be successful if certain threshold conditions are met. These threshold conditions insure that the remotes sensing data if of sufficient spatial and temporal resolution to adequately characterise the river and the surrounding floodplain.
We present three examples. First, we discuss the lower Ain valley. Landsat 7 TM data is used to examine the impact of a series of hydropower dams on the growth rates of riparian vegetation. Given the resolution of Landsat data it is not possible to detect individual forest units. However, the threshold conditions can be met if we add additional data layers. This demonstrates an important downstream trend where incised, upstream, sectors are clearly distinct from the downstream, un-incised, sectors.
Therefore, this data clearly localises the impact of the dam on vegetation health. Our objective is to use SPOT 5 imagery in order to identify origin and retention points for the entire catchment. Supervised classification was used to segment the SPOT 5 image in three classes: This result illustrates the downstream structures for each dominant class and allows us to identify two principal domains: This structural difference provides a partial explanation to the spatial distribution of woody debris.
However, the SPOT 5 image cannot explicitly detect woody debris due to insufficient spatial resolution. In order to offset this limitation, field surveys were conducted in order to localise woody debris. These field surveys confirm the presence of favourable conditions to the presence of woody debris fig. Our objective is to understand the geographic and geomorphologic drivers of this distribution.
In order to assess antecedent structures, dendrochronological surveys were required. This ground work was planned using QuickBird satellite data which has sufficiently high resolution to identify mature individual tree crowns. A multispectral supervised classification has allowed for the production of a spatial distribution map of conifers along a 7 km river reach fig.
When satellite data is unsuitable, airborne images can be used fig.
In general, small-scale river surfaces are characterised with airborne data. Dr type of data has a markedly higher resolution, down to centimetric scales, and it is much easier to coordinate the acquisition of airborne data with field data. Here we illustrate two key applications of high-resolution airborne data: The main objective is to study sedimentation and eutrophication processes responsible for the infilling of oxbow lakes.
Using well-established methods Carbonneau et al. Second, we show an example of grain-size mapping. Once again we use high-resolution imagery obtained from the Pixy UAS. This imagery ed well-defined, homogeneous grain-size patches present on the exposed gravel bars fig. Following established methods Carbonneau et al. Validation of this model is shown in fig. Multitemporal data acquisitions have their own specific limitations which have resulted in very few studies.
In the case of river environments, only UAS have the low deployment cost and required flexibility. For example, teledetectjon discuss a study cour morphological teledetecrion following a sediment management program aiming to redress the reach scale sediment deficit resulting from the construction of dams.
Over m 3 were mechanically injected into the river. The example follows the progress of this sediment through a 5 km reach. This reach contains two injection sites: The bathymetry was measured with high-resolution imagery acquired from a Pixy UAS before and 1 year after the injection fig.
This has allowed for a sediment budget of the reach to be established tab. These maps have also allowed us to measure that the distance travelled by the sediment is between m to m thus demonstrating the use of imagery for the evaluation of river management works. Characterisation of alluvial plains by remote sensing: HunterBertrand Moulin et Mathieu Gagnage. La dynamique temporelle des corridors fluviaux. Agrandir Original png, k. Agrandir Original png, 65k. Agrandir Original png, 86k.
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Agrandir Original png, 17k. Bibliographie Bel Hadj Ali A. Annexe Abridged English version Remote sensing is increasingly used in order to characterise river corridors. Table des illustrations Titre Fig.