Victor Phan
156 lines
4.1 KiB
Plaintext
156 lines
4.1 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "30681e56",
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"metadata": {},
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"source": [
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"# 🧪 Test Planetary Computer Connection\n",
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"\n",
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"Notebook này test kết nối và load dữ liệu từ Microsoft Planetary Computer"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e32c8eca",
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.insert(0, '/media/x79/2A7D-FAA0/remote-sensing')\n",
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"\n",
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"from load_data_no_odc import load_sentinel2_stac, load_sentinel1_stac\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"print(\"✅ Module imported successfully\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "501dd8ef",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Small test area (1 month, small bbox)\n",
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"bbox = (105.8, 9.5, 106.0, 9.7) # Small area in Mekong Delta\n",
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"date_range = (\"2023-01-01\", \"2023-01-31\") # 1 month only\n",
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"\n",
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"print(f\"Test parameters:\")\n",
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"print(f\" Bbox: {bbox}\")\n",
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"print(f\" Date: {date_range}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "187e2c1a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test Sentinel-2\n",
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"print(\"\\n\" + \"=\" * 70)\n",
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"print(\"Testing Sentinel-2 L2A\")\n",
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"print(\"=\" * 70)\n",
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"\n",
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"data_s2 = load_sentinel2_stac(\n",
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" bbox=bbox,\n",
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" date_range=date_range,\n",
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" bands=['red', 'green', 'blue', 'nir08', 'SCL'],\n",
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" resolution=60 # Lower resolution for faster test\n",
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")\n",
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"\n",
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"if data_s2 is not None:\n",
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" print(f\"\\n✅ SUCCESS! Sentinel-2 loaded\")\n",
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" print(f\" Dims: {dict(data_s2.dims)}\")\n",
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" print(f\" Vars: {list(data_s2.data_vars)}\")\n",
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"else:\n",
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" print(\"\\n❌ Failed to load Sentinel-2\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e688f3b9",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test Sentinel-1\n",
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"print(\"\\n\" + \"=\" * 70)\n",
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"print(\"Testing Sentinel-1 RTC\")\n",
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"print(\"=\" * 70)\n",
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"\n",
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"data_s1 = load_sentinel1_stac(\n",
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" bbox=bbox,\n",
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" date_range=date_range,\n",
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" bands=['vv', 'vh'],\n",
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" resolution=60 # Lower resolution for faster test\n",
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")\n",
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"\n",
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"if data_s1 is not None:\n",
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" print(f\"\\n✅ SUCCESS! Sentinel-1 loaded\")\n",
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" print(f\" Dims: {dict(data_s1.dims)}\")\n",
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" print(f\" Vars: {list(data_s1.data_vars)}\")\n",
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"else:\n",
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" print(\"\\n❌ Failed to load Sentinel-1\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "211796a7",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Visualize if data loaded successfully\n",
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"if data_s2 is not None:\n",
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" print(\"\\n📊 Visualizing Sentinel-2 RGB composite...\")\n",
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" \n",
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" # Select first timestep\n",
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" rgb = data_s2[['red', 'green', 'blue']].isel(time=0)\n",
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" \n",
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" # Plot\n",
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" fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n",
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" \n",
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" rgb['red'].plot(ax=axes[0], cmap='Reds')\n",
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" axes[0].set_title('Red band')\n",
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" \n",
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" rgb['green'].plot(ax=axes[1], cmap='Greens')\n",
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" axes[1].set_title('Green band')\n",
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" \n",
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" rgb['blue'].plot(ax=axes[2], cmap='Blues')\n",
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" axes[2].set_title('Blue band')\n",
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" \n",
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" plt.tight_layout()\n",
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" plt.show()\n",
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" \n",
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" print(\"✅ Visualization complete!\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d4e29a09",
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"metadata": {},
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"source": [
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"## ✅ Results\n",
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"\n",
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"Nếu cả 2 tests đều pass:\n",
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"- ✅ Kết nối Planetary Computer OK\n",
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"- ✅ Load Sentinel-2 OK\n",
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"- ✅ Load Sentinel-1 OK\n",
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"- ✅ Sẵn sàng sử dụng cho training!\n",
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"\n",
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"Next step: Sử dụng `01.train_DecisionTree_PlanetaryComputer.ipynb` để train model"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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