|
22 | 22 | }, |
23 | 23 | { |
24 | 24 | "cell_type": "code", |
25 | | - "execution_count": 24, |
| 25 | + "execution_count": null, |
26 | 26 | "metadata": {}, |
27 | 27 | "outputs": [], |
28 | 28 | "source": [ |
|
56 | 56 | }, |
57 | 57 | { |
58 | 58 | "cell_type": "code", |
59 | | - "execution_count": 32, |
| 59 | + "execution_count": null, |
60 | 60 | "metadata": {}, |
61 | | - "outputs": [ |
62 | | - { |
63 | | - "name": "stdout", |
64 | | - "output_type": "stream", |
65 | | - "text": [ |
66 | | - "✅ Configuration loaded\n" |
67 | | - ] |
68 | | - } |
69 | | - ], |
| 61 | + "outputs": [], |
70 | 62 | "source": [ |
71 | 63 | "# STAC API Configuration\n", |
72 | 64 | "STAC_API_URL = \"https://stac.core.eopf.eodc.eu/\"\n", |
73 | 65 | "\n", |
74 | 66 | "# Webhook Configuration\n", |
75 | | - "WEBHOOK_URL = \"http://localhost:12001/samples\"\n", |
| 67 | + "WEBHOOK_URL = \"http://localhost:12000/samples\"\n", |
76 | 68 | "\n", |
77 | 69 | "print(\"✅ Configuration loaded\")" |
78 | 70 | ] |
|
86 | 78 | }, |
87 | 79 | { |
88 | 80 | "cell_type": "code", |
89 | | - "execution_count": 26, |
| 81 | + "execution_count": null, |
90 | 82 | "metadata": {}, |
91 | | - "outputs": [ |
92 | | - { |
93 | | - "name": "stdout", |
94 | | - "output_type": "stream", |
95 | | - "text": [ |
96 | | - "Area of Interest: [12.4, 41.8, 12.6, 42.0]\n", |
97 | | - "Time Range: 2025-07-01T00:00:00Z to 2025-07-31T23:59:59Z\n" |
98 | | - ] |
99 | | - } |
100 | | - ], |
| 83 | + "outputs": [], |
101 | 84 | "source": [ |
102 | 85 | "# Area of Interest (AOI) - Bounding box: [min_lon, min_lat, max_lon, max_lat]\n", |
103 | 86 | "# Example: Rome area\n", |
104 | | - "aoi_bbox = [12.4, 41.8, 12.6, 42.0]\n", |
| 87 | + "# aoi_bbox = [12.4, 41.8, 12.6, 42.0]\n", |
105 | 88 | "# Example 2: Majorca area (2.1697998046875004%2C39.21097520599528%2C3.8177490234375004)\n", |
106 | 89 | "# aoi_bbox = [2.16, 39.21, 3.82, 39.78]\n", |
107 | 90 | "# Example 3: France Full\n", |
108 | 91 | "# aoi_bbox = [-5.14, 41.33, 9.56, 51.09]\n", |
| 92 | + "# Example 4: Lagoon From Venice to Trieste\n", |
| 93 | + "aoi_bbox = [12.0, 44.4, 14.0, 45.0]\n", |
109 | 94 | "\n", |
110 | 95 | "# Time range\n", |
111 | | - "start_date = \"2025-07-01T00:00:00Z\"\n", |
112 | | - "end_date = \"2025-07-31T23:59:59Z\"\n", |
| 96 | + "start_date = \"2025-01-01T00:00:00Z\"\n", |
| 97 | + "end_date = \"2025-12-31T23:59:59Z\"\n", |
113 | 98 | "\n", |
114 | 99 | "print(f\"Area of Interest: {aoi_bbox}\")\n", |
115 | 100 | "print(f\"Time Range: {start_date} to {end_date}\")" |
|
124 | 109 | }, |
125 | 110 | { |
126 | 111 | "cell_type": "code", |
127 | | - "execution_count": 27, |
| 112 | + "execution_count": null, |
128 | 113 | "metadata": {}, |
129 | | - "outputs": [ |
130 | | - { |
131 | | - "name": "stdout", |
132 | | - "output_type": "stream", |
133 | | - "text": [ |
134 | | - "\n", |
135 | | - "📚 Available Collections (12 total):\n", |
136 | | - "\n", |
137 | | - " - sentinel-2-l2a\n", |
138 | | - " The Sentinel-2 Level-2A Collection 1 product provides orthorectified Surface Reflectance (Bottom-Of-...\n", |
139 | | - "\n", |
140 | | - " - sentinel-3-slstr-l1-rbt\n", |
141 | | - " The Sentinel-3 SLSTR Level-1B RBT product provides radiances and brightness temperatures for each pi...\n", |
142 | | - "\n", |
143 | | - " - sentinel-3-olci-l2-lrr\n", |
144 | | - " The Sentinel-3 OLCI L2 LRR product provides land and atmospheric geophysical parameters computed for...\n", |
145 | | - "\n", |
146 | | - " - sentinel-2-l1c\n", |
147 | | - " The Sentinel-2 Level-1C product is composed of 110x110 km2 tiles (ortho-images in UTM/WGS84 projecti...\n", |
148 | | - "\n", |
149 | | - " - sentinel-3-olci-l2-lfr\n", |
150 | | - " The Sentinel-3 OLCI L2 LFR product provides land and atmospheric geophysical parameters computed for...\n", |
151 | | - "\n", |
152 | | - " - sentinel-3-olci-l1-efr\n", |
153 | | - " The Sentinel-3 OLCI L1 EFR product provides TOA radiances at full resolution for each pixel in the i...\n", |
154 | | - "\n", |
155 | | - " - sentinel-1-l1-grd\n", |
156 | | - " The Sentinel-1 Level-1 Ground Range Detected (GRD) products consist of focused SAR data that has bee...\n", |
157 | | - "\n", |
158 | | - " - sentinel-3-slstr-l2-frp\n", |
159 | | - " The Sentinel-3 SLSTR Level-2 FRP product provides global (over land and water) fire radiative power.\n", |
160 | | - "\n", |
161 | | - " - sentinel-3-olci-l1-err\n", |
162 | | - " The Sentinel-3 OLCI L1 ERR product provides TOA radiances at reduced resolution for each pixel in th...\n", |
163 | | - "\n", |
164 | | - " - sentinel-1-l1-slc\n", |
165 | | - " The Sentinel-1 Level-1 Single Look Complex (SLC) products consist of focused SAR data, geo-reference...\n", |
166 | | - "\n", |
167 | | - " - sentinel-3-slstr-l2-lst\n", |
168 | | - " The Sentinel-3 SLSTR Level-2 LST product provides land surface temperature.\n", |
169 | | - "\n", |
170 | | - " - sentinel-1-l2-ocn\n", |
171 | | - " The Sentinel-1 Level-2 Ocean (OCN) products for wind, wave and currents applications may contain the...\n", |
172 | | - "\n" |
173 | | - ] |
174 | | - } |
175 | | - ], |
| 114 | + "outputs": [], |
176 | 115 | "source": [ |
177 | 116 | "# Connect to STAC API\n", |
178 | 117 | "catalog = Client.open(STAC_API_URL)\n", |
|
203 | 142 | "cell_type": "code", |
204 | 143 | "execution_count": null, |
205 | 144 | "metadata": {}, |
206 | | - "outputs": [ |
207 | | - { |
208 | | - "name": "stdout", |
209 | | - "output_type": "stream", |
210 | | - "text": [ |
211 | | - "🔍 Searching collection: sentinel-2-l2a\n", |
212 | | - "🎯 Target collection for processing: sentinel-2-l2a\n" |
213 | | - ] |
214 | | - } |
215 | | - ], |
| 145 | + "outputs": [], |
216 | 146 | "source": [ |
217 | 147 | "# Choose the source collection to search\n", |
218 | 148 | "source_collection = \"sentinel-2-l2a\" # Change this to your desired collection\n", |
219 | 149 | "\n", |
220 | 150 | "# Choose the target collection for processing\n", |
221 | | - "target_collection = \"sentinel-2-l2a-staging\" # Change this to your target collection\n", |
| 151 | + "target_collection = \"sentinel-2-l2a\" # Change this to your target collection\n", |
222 | 152 | "\n", |
223 | 153 | "print(f\"🔍 Searching collection: {source_collection}\")\n", |
224 | 154 | "print(f\"🎯 Target collection for processing: {target_collection}\")" |
225 | 155 | ] |
226 | 156 | }, |
227 | 157 | { |
228 | 158 | "cell_type": "code", |
229 | | - "execution_count": 29, |
| 159 | + "execution_count": null, |
230 | 160 | "metadata": {}, |
231 | | - "outputs": [ |
232 | | - { |
233 | | - "name": "stdout", |
234 | | - "output_type": "stream", |
235 | | - "text": [ |
236 | | - "\n", |
237 | | - "✅ Found 10 items (after filtering).\n", |
238 | | - "\n" |
239 | | - ] |
240 | | - } |
241 | | - ], |
| 161 | + "outputs": [], |
242 | 162 | "source": [ |
243 | 163 | "# Search for items\n", |
244 | 164 | "search = catalog.search(\n", |
245 | 165 | " collections=[source_collection],\n", |
246 | 166 | " bbox=aoi_bbox,\n", |
247 | 167 | " datetime=f\"{start_date}/{end_date}\", # Adjust as needed\n", |
248 | | - " limit=100, # Adjust limit as needed\n", |
| 168 | + " limit=200, # Adjust limit as needed\n", |
249 | 169 | ")\n", |
250 | 170 | "\n", |
251 | 171 | "# Collect items paginated results and clean them (workaround for issue #26)\n", |
|
286 | 206 | }, |
287 | 207 | { |
288 | 208 | "cell_type": "code", |
289 | | - "execution_count": 33, |
| 209 | + "execution_count": null, |
290 | 210 | "metadata": {}, |
291 | 211 | "outputs": [], |
292 | 212 | "source": [ |
|
327 | 247 | }, |
328 | 248 | { |
329 | 249 | "cell_type": "code", |
330 | | - "execution_count": 35, |
| 250 | + "execution_count": null, |
331 | 251 | "metadata": {}, |
332 | | - "outputs": [ |
333 | | - { |
334 | | - "name": "stdout", |
335 | | - "output_type": "stream", |
336 | | - "text": [ |
337 | | - "\n", |
338 | | - "📤 Submitting 10 items to pipeline...\n", |
339 | | - "\n", |
340 | | - "✅ Submitted: S2C_MSIL2A_20250728T100051_N0511_R122_T33TTG_20250728T153115\n", |
341 | | - "✅ Submitted: S2C_MSIL2A_20250728T100051_N0511_R122_T32TQM_20250728T153115\n", |
342 | | - "✅ Submitted: S2B_MSIL2A_20250713T100029_N0511_R122_T33TUG_20250713T123724\n", |
343 | | - "✅ Submitted: S2B_MSIL2A_20250713T100029_N0511_R122_T33TTG_20250713T123724\n", |
344 | | - "✅ Submitted: S2B_MSIL2A_20250713T100029_N0511_R122_T32TQM_20250713T123724\n", |
345 | | - "✅ Submitted: S2C_MSIL2A_20250708T100051_N0511_R122_T33TTG_20250708T155705\n", |
346 | | - "✅ Submitted: S2C_MSIL2A_20250708T100051_N0511_R122_T32TQM_20250708T155705\n", |
347 | | - "✅ Submitted: S2B_MSIL2A_20250703T100029_N0511_R122_T33TUG_20250703T122001\n", |
348 | | - "✅ Submitted: S2B_MSIL2A_20250703T100029_N0511_R122_T33TTG_20250703T122001\n", |
349 | | - "✅ Submitted: S2B_MSIL2A_20250703T100029_N0511_R122_T32TQM_20250703T122001\n", |
350 | | - "\n", |
351 | | - "📊 Summary:\n", |
352 | | - " - Successfully submitted: 10\n", |
353 | | - " - Failed: 0\n", |
354 | | - " - Total: 10\n" |
355 | | - ] |
356 | | - } |
357 | | - ], |
| 252 | + "outputs": [], |
358 | 253 | "source": [ |
359 | 254 | "# Submit all found items to the pipeline\n", |
360 | 255 | "if items:\n", |
|
439 | 334 | "name": "python", |
440 | 335 | "nbconvert_exporter": "python", |
441 | 336 | "pygments_lexer": "ipython3", |
442 | | - "version": "3.13.1" |
| 337 | + "version": "3.11.0" |
443 | 338 | } |
444 | 339 | }, |
445 | 340 | "nbformat": 4, |
|
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