diff --git a/export/gaps.edges.detection.html b/export/gaps.edges.detection.html
index 3e32f883fe77450859f6b0759a98ca63972e3c57..5c4a1b43442125a414e4c44be3bab8ab8fa92f82 100644
--- a/export/gaps.edges.detection.html
+++ b/export/gaps.edges.detection.html
@@ -11,7 +11,7 @@
 
 <meta name="author" content="Jean-Matthieu Monnet" />
 
-<meta name="date" content="2021-05-17" />
+<meta name="date" content="2021-07-06" />
 
 <title>R workflow for forest gaps and edges detection from ALS data</title>
 
@@ -189,7 +189,7 @@ pre code {
 
 <h1 class="title toc-ignore">R workflow for forest gaps and edges detection from ALS data</h1>
 <h4 class="author">Jean-Matthieu Monnet</h4>
-<h4 class="date">2021-05-17</h4>
+<h4 class="date">2021-07-06</h4>
 
 </div>
 
@@ -197,23 +197,22 @@ pre code {
 <hr />
 <p>This tutorial presents R code for forest gaps and edges detection from Airborne Laser Scanning (ALS) data. The workflow is based on functions from packages <code>lidaRtRee</code> and <code>lidR</code>.</p>
 <p>Licence: GNU GPLv3 / <a href="https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/R/gap.edges.detection.Rmd">Source page</a></p>
+<p>Many thanks to Pascal Obstétar for checking code and improvement suggestions.</p>
 <div id="study-area-and-als-data" class="section level2">
 <h2>Study area and ALS data</h2>
 <p>The study area is a 200m x 200m forest located in the Jura mountain (France). The following code shows how to extract the ALS data from a folder containing normalized LAS files, and compute the Canopy Height Model (CHM) at 1 m resolution.</p>
 <pre class="r"><code># build catalog from folder with normalized LAS/LAZ files
-cata &lt;- lidR::catalog(&quot;/las.folder/&quot;)
+cata &lt;- lidR::readALSLAScatalog(&quot;/las.folder/&quot;)
 # set coordinate system
-sp::proj4string(cata) &lt;- sp::CRS(SRS_string = &quot;EPSG:2154&quot;)
-# set sensor type
-lidR::sensor(cata) &lt;- &quot;ALS&quot;
+lidR::projection(cata) &lt;- 2154
 # define region of interest where points should be extracted
 centre &lt;- c(944750, 6638750)
 size &lt;- 250
 # extract data on square area centered on centre
-las &lt;- lidR::clip_rectangle(cata, centre[1] - size, centre[2] - size, centre[1] + 
+las &lt;- lidR::clip_rectangle(cata, centre[1] - size, centre[2] - size, centre[1] +
     size, centre[2] + size)
 # compute canopy height model from normalized point cloud
-chm &lt;- lidaRtRee::points2DSM(las, 1, centre[1] - size, centre[1] + size, centre[2] - 
+chm &lt;- lidaRtRee::points2DSM(las, 1, centre[1] - size, centre[1] + size, centre[2] -
     size, centre[2] + size)
 # save chm in Rdata file save(chm, file=&#39;chm.rda&#39;)</code></pre>
 <p>If the CHM has been previously calculated.</p>
@@ -251,15 +250,15 @@ par(mfrow = c(1, 2))
 # max value of surface (log)
 z.lim &lt;- log(max(raster::values(gaps1$gap.surface)))
 # plot gap surface
-raster::plot(log(gaps1$gap.surface), main = &quot;log(Gap surface) (1)&quot;, zlim = c(0, z.lim), 
+raster::plot(log(gaps1$gap.surface), main = &quot;log(Gap surface) (1)&quot;, zlim = c(0, z.lim),
     col = rainbow(255, end = 5/6))
-raster::plot(log(gaps2$gap.surface), main = &quot;log(Gap surface) (2)&quot;, zlim = c(0, z.lim), 
+raster::plot(log(gaps2$gap.surface), main = &quot;log(Gap surface) (2)&quot;, zlim = c(0, z.lim),
     col = rainbow(255, end = 5/6))</code></pre>
 <p><img src="data:image/png;base64,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" width="70%" style="display: block; margin: auto;" /></p>
 <p>Gaps can be vectorized for display over the original CHM.</p>
 <pre class="r"><code># convert to vector
 gaps1.v &lt;- raster::rasterToPolygons(gaps1$gap.id, dissolve = TRUE)</code></pre>
-<pre><code>## Loading required namespace: rgeos</code></pre>
+<pre><code>## Le chargement a nécessité le package : rgeos</code></pre>
 <pre class="r"><code># display gaps over original CHM
 raster::plot(chm, main = &quot;Gaps over CHM (1)&quot;)
 sp::plot(gaps1.v, add = T)</code></pre>
@@ -300,10 +299,10 @@ legend(&quot;topright&quot;, c(&quot;1&quot;, &quot;2&quot;), fill = c(&quot;red
 chm &lt;- lidaRtRee::chmchablais3
 chm[is.na(chm)] &lt;- 0
 # Perform gap detection with distance ratio criterion
-gaps1 &lt;- lidaRtRee::gapDetection(chm, ratio = 2, gap.max.height = 1, min.gap.surface = 50, 
+gaps1 &lt;- lidaRtRee::gapDetection(chm, ratio = 2, gap.max.height = 1, min.gap.surface = 50,
     nlFilter = &quot;None&quot;)
 # Perform gap detection with distance ratio criterion and gap reconstruction
-gaps1r &lt;- lidaRtRee::gapDetection(chm, ratio = 2, gap.max.height = 1, min.gap.surface = 50, 
+gaps1r &lt;- lidaRtRee::gapDetection(chm, ratio = 2, gap.max.height = 1, min.gap.surface = 50,
     gapReconstruct = TRUE, nlFilter = &quot;None&quot;)
 # display detected gaps
 par(mfrow = c(1, 3))
diff --git a/export/gaps.edges.detection.pdf b/export/gaps.edges.detection.pdf
index 20a3d9422634a9f1b28e8fbfff974d64d8872a93..7498ab06af19da4880ea5710cf4cc33f232ba94f 100644
Binary files a/export/gaps.edges.detection.pdf and b/export/gaps.edges.detection.pdf differ