SRTM n'est pas assez fiable comme source pour les altitudes ? Si j'en crois leur rapport<br><a href="http://www2.jpl.nasa.gov/srtm/SRTM_paper.pdf">http://www2.jpl.nasa.gov/srtm/SRTM_paper.pdf</a><br><br>ca a l'air de bonne précision quand meme :<br>
<img src="data:image/png;base64,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" alt=""><br>
"Table 1 summarizes the 90% errors estimated using the available ground truth [Rodriguez et al., 2005;2006]. The absolute vertical accuracy is better than 9 m, indicating that SRTM improved on its design goal of 16 m absolute by almost a factor of 2. Fig. 14 shows the spatial patterns of the vertical error. <br>
Note that the greatest errors are associated with steep terrain (Himalaya, Andes) and very smooth sandy surfaces with low SNR (Sahara Desert).<br><br><div class="gmail_quote">Le 28 septembre 2012 10:05, Eric Sibert <span dir="ltr"><<a href="mailto:courrier@eric.sibert.fr" target="_blank">courrier@eric.sibert.fr</a>></span> a écrit :<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div class="im"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Juste pour rappeler que la BD Alti au pas de 250m est déjà libérée...et que ça<br>
ne répond pas au besoin. Gilles, je m'associe à ta demande, en parlant bien de<br>
la version au pas de 50m :-)<br>
</blockquote>
<br></div>
A défaut d'orthophoto, la BD_Alti à 50 m et les photos brutes, ça devrait le faire :-p<span class="HOEnZb"><font color="#888888"><br>
<br>
Eric</font></span><div class="HOEnZb"><div class="h5"><br>
<br>
<br>
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