05_Clouds_and_ICESat-2_Data_Filtering: remove large images

Author: dshean

05_Clouds_and_ICESat-2_Data_Filtering/notebooks/Clouds_and_data_quality.ipynb

@@ -194,7 +194,7 @@
    "source": [
     "## 1.  Introduction: Signals and signal finding.\n",
     "\n",
-    "<img src=\"images/Four_photon_paths.jpg\"  width=600 height=600>\n",
+    "<img src=\"images/Four_photon_paths_sm.jpg\"  width=600 height=600>\n",
     "\n",
     "The photons that we see in ATLAS data can come to the receiver in a few different ways.  \n",
     "--(A, B): The majority of photons come from the sun.   These may reflect off clouds or off the land surface, and they arrive with a uniform random distribution. ATLAS does a good job of filtering these out, but some make it through into the data.  \n",
@@ -560,7 +560,7 @@
    "source": [
     "### 3.1 Taking our picture of cloud effects to the ice sheet\n",
     "We're next going to look at data from Byrd Glacier, in Antarctica.  This is one of the big outlet glaciers dumping ice from the East Antarctic plateau into the Ross Ice Shelf.  Here's a shaded-relief map from the REMA.\n",
-    "<img src=\"images/byrd_rema.png\">\n",
+    "<img src=\"images/byrd_rema_sm.jpg\">\n",
     "The glacier flows west to east (the REMA image is south-end-up, so east is on the left).  The inland catchment of the glacier should have a smooth ice surface, but the glacier trunk and the area where it joins the ice shelf are heavily crevassed.\n",
     "\n",
     "The dataset on AWS contains a large number of granules that I found with a spatial search using an NSIDC data query.  We can use matplotlib's scatter() function to make a map of all the elevations from all of these files."
@@ -783,7 +783,7 @@
    "source": [
     "There is one more way of flagging bad data that we can try, that can help clean up the remaining bad segments.  Recall that the the ATL06 data model fits both the height and the surface slope of segments: \n",
     "\n",
-    "<img src=\"images/dh_segment.png\"  width=500 height=450>\n",
+    "<img src=\"images/dh_segment_sm.jpg\"  width=500 height=450>\n",
     "\n",
     "Let's look at the segments including their slopes:"
    ]
@@ -919,7 +919,7 @@
     "\n",
     "A more insidious problem that clouds can cause comes about when an optically thin cloud lets photons through, but some of the photons scatter off ice grains in the forward (downward) direction and hit the surface before returning to the telescope.\n",
     "\n",
-    "<img src=\"images/Forward_scattering.png\"  width=600 height=600>\n",
+    "<img src=\"images/Forward_scattering_sm.jpg\"  width=600 height=600>\n",
     "\n",
     "The path for a photon that reaches the surface without hitting the cloud is shown in blue, the path of a scattered photon is shown in red.  Since photons are delayed by a small but random amount whose distribution depends on the height and thickness of the cloud, the expected probability distibution of the scattered photon heights is skewed low (shown in schematic at left), and the mean (or median) photon height has a negative bias. \n",
     "\n",

05_Clouds_and_ICESat-2_Data_Filtering/notebooks/Clouds_and_data_quality_rendered.ipynb

@@ -274,7 +274,7 @@
    "source": [
     "## 1.  Introduction: Signals and signal finding.\n",
     "\n",
-    "<img src=\"images/Four_photon_paths.jpg\"  width=600 height=600>\n",
+    "<img src=\"images/Four_photon_paths_sm.jpg\"  width=600 height=600>\n",
     "\n",
     "The photons that we see in ATLAS data can come to the receiver in a few different ways.  \n",
     "--(A, B): The majority of photons come from the sun.   These may reflect off clouds or off the land surface, and they arrive with a uniform random distribution. ATLAS does a good job of filtering these out, but some make it through into the data.  \n",
@@ -700,7 +700,7 @@
    "source": [
     "### 3.1 Taking our picture of cloud effects to the ice sheet\n",
     "We're next going to look at data from Byrd Glacier, in Antarctica.  This is one of the big outlet glaciers dumping ice from the East Antarctic plateau into the Ross Ice Shelf.  Here's a shaded-relief map from the REMA.\n",
-    "<img src=\"images/byrd_rema.png\">\n",
+    "<img src=\"images/byrd_rema_sm.jpg\">\n",
     "\n",
     "The glacier flows west to east (the REMA image is south-end-up, so east is on the left).  The inland catchment of the glacier should have a smooth ice surface, but the glacier trunk and the area where it joins the ice shelf are heavily crevassed.\n",
     "\n",
@@ -1213,7 +1213,7 @@
    "source": [
     "There is one more way of flagging bad data that we can try, that can help clean up the remaining bad segments.  Recall that the the ATL06 data model fits both the height and the surface slope of segments: \n",
     "\n",
-    "<img src=\"images/dh_segment.png\"  width=500 height=450>\n",
+    "<img src=\"images/dh_segment_sm.jpg\"  width=500 height=450>\n",
     "\n",
     "Let's look at the segments including their slopes:"
    ]
@@ -1420,7 +1420,7 @@
     "\n",
     "A more insidious problem that clouds can cause comes about when an optically thin cloud lets photons through, but some of the photons scatter off ice grains in the forward (downward) direction and hit the surface before returning to the telescope.\n",
     "\n",
-    "<img src=\"images/Forward_scattering.png\"  width=600 height=600>\n",
+    "<img src=\"images/Forward_scattering_sm.jpg\"  width=600 height=600>\n",
     "\n",
     "The path for a photon that reaches the surface without hitting the cloud is shown in blue, the path of a scattered photon is shown in red.  Since photons are delayed by a small but random amount whose distribution depends on the height and thickness of the cloud, the expected probability distibution of the scattered photon heights is skewed low (shown in schematic at left), and the mean (or median) photon height has a negative bias. \n",
     "\n",