OpenGIS_Vietnam_Work_with_geospatial_data.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNhBhAs1C0GXUeYNkn/pbje",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/soiqualang/colab/blob/master/OpenGIS_Vietnam_Work_with_geospatial_data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Tính khoảng cách giữa 2 điểm"
      ],
      "metadata": {
        "id": "Vz6Q3M1Vw4dK"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IERD3ZojjfzB",
        "outputId": "724a1902-67ab-48f8-ac40-eaae561d4e5b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.6295810540359369\n"
          ]
        }
      ],
      "source": [
        "# Tính khoảng cách giữa 2 điểm\n",
        "import geopandas as gpd\n",
        "from shapely.geometry import Point\n",
        "\n",
        "# Tạo 2 điểm\n",
        "point1 = Point(-122.224167, 37.176389)\n",
        "point2 = Point(-122.419416, 37.774929)\n",
        "\n",
        "# Tỉnh khoảng cách giữa 2 điểm\n",
        "distance = point1.distance(point2)\n",
        "\n",
        "# Show kết quả\n",
        "print(distance)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Tạo buffer từ 1 điểm"
      ],
      "metadata": {
        "id": "rDCZwf0zw9vd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import geopandas as gpd\n",
        "from shapely.geometry import Point, Polygon\n",
        "\n",
        "# Tạo điểm\n",
        "point = Point(10.775592424689332, 106.70302168729125)\n",
        "\n",
        "# Tạo vùng đệm xung quanh điểm với bán kính 1000 mét\n",
        "buffer = point.buffer(0.001)\n",
        "\n",
        "# Tạo GeoDataFrame từ điểm và vùng đệm\n",
        "geometry = [point, buffer]\n",
        "gdf = gpd.GeoDataFrame(geometry=geometry, columns=['geometry'])\n",
        "\n",
        "# Hiển thị điểm và vùng đệm trên bản đồ\n",
        "gdf.plot(color=['yellow', 'green'])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 480
        },
        "id": "tKt1vZ6IqUSC",
        "outputId": "17226ef8-380d-4df8-fbe6-09b05d2827bc"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 52
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Tìm các điểm nằm trong bán kính cho phép"
      ],
      "metadata": {
        "id": "zecwQ82PxENK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import geopandas as gpd\n",
        "from shapely.geometry import Point, Polygon\n",
        "\n",
        "# Tạo điểm\n",
        "point = Point(10.775592424689332, 106.70302168729125)\n",
        "\n",
        "# Tạo vùng đệm xung quanh điểm với bán kính 1000 mét\n",
        "\n",
        "buffer = point.buffer(0.001)\n",
        "\n",
        "# Tạo điểm từ tọa độ\n",
        "point1 = Point(10.775619761168818, 106.70282689719542)\n",
        "point2 = Point(10.776467190801428, 106.70175555166836)\n",
        "point3 = Point(10.777751998919879, 106.70292429224334)\n",
        "\n",
        "# Kiểm tra xem các điểm có nằm trong vùng đệm không\n",
        "is_inside1 = buffer.contains(point1)\n",
        "is_inside2 = buffer.contains(point2)\n",
        "is_inside3 = buffer.contains(point3)\n",
        "\n",
        "# Hiển thị vị trí các điểm so với vùng đệm\n",
        "print(f\"Point 1 is inside the buffer: {is_inside1}\")\n",
        "print(f\"Point 2 is inside the buffer: {is_inside2}\")\n",
        "print(f\"Point 3 is inside the buffer: {is_inside3}\")\n",
        "\n",
        "# Vẽ các điểm và vùng đệm trên bản đồ\n",
        "geometry = [point, point1, point2, point3, buffer]\n",
        "gdf = gpd.GeoDataFrame(geometry=geometry, columns=['geometry'])\n",
        "\n",
        "gdf.plot(color=['yellow', 'red', 'red', 'red', 'green'])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        },
        "id": "SyGwOac0sNyx",
        "outputId": "4722fe1d-cfb6-41d5-deae-bbdb8d6d5988"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Point 1 is inside the buffer: True\n",
            "Point 2 is inside the buffer: False\n",
            "Point 3 is inside the buffer: False\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "tbFzLtM1tTU7"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}