洪涝有源淹没算法及淹没结果分析

洪涝模拟仿真的实现方法主要有两种：一种是基于水动力学的洪水演进模型；还有一种是基于DEM的洪水淹没分析。详细分析例如以下：

我是GIS从业者，从我们的专业角度出发，选择基于DEM的洪水淹没分析来做洪涝的模拟仿真。而基于DEM的洪水淹没分析方法主要分为有源淹没和无源淹没。

本篇博客採用有源淹没算法实现洪涝的模拟，算法为八领域种子扩散算法。

採用C#版本号GDAL编写了FloodSimulation类，以下给出所有源码：

  class FloodSimulation
    {
        #region 类成员变量

        //点结构体
        public struct Point
        {
            public int X;          //行号
            public int Y;          //列号
            public int Elevation;  //像素值(高程值)
            public bool IsFlooded; //淹没标记

        };
        private bool[,] IsFlood;                //淹没区域标记二维数组，用于标记淹没栅格
        private List<Point> m_FloodBufferList;  //淹没缓冲区堆栈
      
        public Dataset m_DEMDataSet;            //DEM数据集
        public Dataset m_FloodSimulatedDataSet; //洪涝淹没范围数据集
        public int m_XSize;                     //数据X方向栅格个数
        public int m_YSize;                     //数据Y方向栅格个数
        public OSGeo.GDAL.Driver driver;        //影像格式驱动
        public int[] m_FloodBuffer;            //填充缓冲区（洪涝淹没范围）
        public int[] m_DEMdataBuffer;          //DEM数据（存储高程值） 

        public double m_AreaFlooded;            //水面面积
        public double m_WaterVolume;            //淹没水体体积
        /* 这里的GeoTransform(影像坐标变换參数)的定义是：通过像素所在的行列值得到其左上角点空间坐标的运算參数
            比如:某图像上(P,L)点左上角的实际空间坐标为：
            Xp = GeoTransform[0] + P * GeoTransform[1] + L * GeoTransform[2];
            Yp = GeoTransform[3] + P * GeoTransform[4] + L * GeoTransform[5];                                                                     */
        public double[] m_adfGeoTransform;   

        #endregion
        
        //构造函数
        public FloodSimulation()
        {
            m_adfGeoTransform = new double[6];
            m_FloodBufferList = new List<Point>();
            
        }

        /// <summary>
        /// 载入淹没区DEM,并创建淹没范围影像
        /// </summary>
        /// <param name="m_DEMFilePath">DEM文件路径</param>
        /// <returns></returns>
        public void loadDataSet(string m_DEMFilePath)
        {
            //读取DEM数据
            m_DEMDataSet = Gdal.Open(m_DEMFilePath, Access.GA_ReadOnly);
            m_XSize = m_DEMDataSet.RasterXSize;
            m_YSize = m_DEMDataSet.RasterYSize;
            
            //获取影像坐标转换參数
            m_DEMDataSet.GetGeoTransform(m_adfGeoTransform); 
            //读取DEM数据到内存中
            Band m_DEMBand = m_DEMDataSet.GetRasterBand(1); //获取第一个波段
            m_DEMdataBuffer = new int [m_XSize * m_YSize];
            m_DEMBand.ReadRaster(0, 0, m_XSize, m_YSize, m_DEMdataBuffer, m_XSize, m_YSize, 0, 0);

            //淹没范围填充缓冲区
            m_FloodBuffer = new int[m_XSize * m_YSize];
            IsFlood=new bool[m_XSize,m_YSize];

            //初始化二维淹没区bool数组
            for (int i = 0; i < m_XSize; i++)
            {
                for (int j = 0; j < m_YSize; j++)
                {
                    IsFlood[i, j] = false;
                }
            }

            //创建洪涝淹没范围影像
            string m_FloodImagePath = System.IO.Path.GetDirectoryName(System.Windows.Forms.Application.ExecutablePath) + "\FloodSimulation\FloodedRegion.tif";
            if (System.IO.File.Exists(m_FloodImagePath))
            {
                System.IO.File.Delete(m_FloodImagePath);
            }

            //在GDAL中创建影像,先须要明白待创建影像的格式,并获取到该影像格式的驱动
            driver = Gdal.GetDriverByName("GTiff");
            //调用Creat函数创建影像
            // m_FloodSimulatedDataSet = driver.CreateCopy(m_FloodImagePath, m_DEMDataSet, 1, null, null, null);
            m_FloodSimulatedDataSet = driver.Create(m_FloodImagePath, m_XSize, m_YSize, 1, DataType.GDT_Float32, null);
            //设置影像属性
            m_FloodSimulatedDataSet.SetGeoTransform(m_adfGeoTransform); //影像转换參数
            m_FloodSimulatedDataSet.SetProjection(m_DEMDataSet.GetProjectionRef()); //投影
            //m_FloodSimulatedDataSet.WriteRaster(0, 0, m_XSize, m_YSize, m_FloodBuffer, m_XSize, m_YSize, 1, null, 0, 0, 0);
            
            //输出影像
            m_FloodSimulatedDataSet.GetRasterBand(1).WriteRaster(0, 0, m_XSize, m_YSize, m_FloodBuffer, m_XSize, m_YSize, 0, 0);
            m_FloodSimulatedDataSet.GetRasterBand(1).FlushCache();
            m_FloodSimulatedDataSet.FlushCache();

        }

        /// <summary>
        /// 种子扩散算法淹没分析
        /// </summary>
        /// <param name="m_Lat">种子点纬度</param>
        /// <param name="m_Log">种子点经度</param>
        /// <param name="m_FloodLevel">淹没水位</param>
        public void FloodFill8Direct(double m_Lat,double m_Log,double m_FloodLevel)
        {
            //首先依据种子点经纬度获取其所在行列号
            Point pFloodSourcePoint = new Point();
            int x, y;
            geoToImageSpace(m_adfGeoTransform, m_Log, m_Lat, out x, out y);
            pFloodSourcePoint.X = x;
            pFloodSourcePoint.Y = y;
            
            //获取种子点高程值
            pFloodSourcePoint.Elevation = GetElevation(pFloodSourcePoint);
            m_FloodBufferList.Add(pFloodSourcePoint);

            //推断堆栈中时候还有未被淹没点，如有继续搜索。没有则淹没分析结束。

            while (m_FloodBufferList.Count!=0)
            {
                Point pFloodSourcePoint_temp = m_FloodBufferList[0];
                int rowX = pFloodSourcePoint_temp.X;
                int colmY = pFloodSourcePoint_temp.Y;
               
                //标记可淹没,并从淹没堆栈中移出
                IsFlood[rowX, colmY] = true;
                m_FloodBuffer[getIndex(pFloodSourcePoint_temp)] = 1;
                m_FloodBufferList.RemoveAt(0); 
                
                //向中心栅格单元的8个临近方向搜索连通域
                for (int i = rowX - 1; i < rowX + 2; i++)
                {
                    for (int j = colmY - 1; j < colmY + 2; j++)
                    {
                        //推断是否到达栅格边界
                        if (i<=m_XSize&&j<=m_YSize)
                        {
                            Point temp_point = new Point();
                            temp_point.X = i;
                            temp_point.Y = j;
                            temp_point.Elevation = GetElevation(temp_point);
                            //搜索能够淹没且未被标记的栅格单元
                            if ((temp_point.Elevation<m_FloodLevel||temp_point.Elevation <= pFloodSourcePoint_temp.Elevation) && IsFlood[temp_point.X, temp_point.Y] == false)
                            {
                                //将符合条件的栅格单元增加堆栈，标记为淹没，避免反复运算
                                m_FloodBufferList.Add(temp_point);
                                IsFlood[temp_point.X, temp_point.Y] = true;
                                m_FloodBuffer[getIndex(temp_point)] = 1;
                            }
                            
                        }
                       
                    }
                }
            }
            //统计淹没网格数
            int count = 0;
            for (int i = 0; i < m_XSize; i++)
            {
                for (int j = 0; j < m_YSize; j++)
                {
                    if (IsFlood[i,j]==true)
                    {
                        count++;
                    }
                }
            }
      
        }
        
        /// <summary>
        /// 输出洪涝淹没范围图
        /// </summary>
        public void OutPutFloodRegion()
        {
            m_FloodSimulatedDataSet.GetRasterBand(1).WriteRaster(0, 0, m_XSize, m_YSize, m_FloodBuffer, m_XSize, m_YSize, 0, 0);
            // m_FloodSimulatedDataSet.WriteRaster(0, 0, m_XSize, m_YSize, m_FloodBuffer, m_XSize, m_YSize, 1, null, 0, 0, 0);
            m_FloodSimulatedDataSet.GetRasterBand(1).FlushCache();
            m_FloodSimulatedDataSet.FlushCache();
        }

//         public void OutPutFloodedInfo()
//         {
//         }
        /// <summary>
        /// 获取第x行第y列栅格索引
        /// </summary>
        /// <param name="point">栅格点</param>
        /// <returns>该点在DEM内存数组中的索引</returns>
        private int getIndex(Point point)
        {
            return  point.Y* m_XSize + point.X;
        }

        /// <summary>
        /// 获取高程值
        /// </summary>
        /// <param name="m_point">栅格点</param>
        /// <returns>高程值</returns>
        private int GetElevation(Point m_point)
        {
            return m_DEMdataBuffer[getIndex(m_point)];

        }

        /// <summary>
        /// 从像素空间转换到地理空间
        /// </summary>
        /// <param name="adfGeoTransform">影像坐标变换參数</param>
        /// <param name="pixel">像素所在行</param>
        /// <param name="line">像素所在列</param>
        /// <param name="x">X</param>
        /// <param name="y">Y</param>
        public void imageToGeoSpace(double[] m_GeoTransform, int pixel, int line, out double X, out double Y)
        {
            X = m_GeoTransform[0] + pixel * m_GeoTransform[1] + line * m_GeoTransform[2];
            Y = m_GeoTransform[3] + pixel * m_GeoTransform[4] + line * m_GeoTransform[5];
        }

        /// <summary>
        /// 从地理空间转换到像素空间
        /// </summary>
        /// <param name="adfGeoTransform">影像坐标变化參数</param>
        /// <param name="x">X(经度)</param>
        /// <param name="y">Y（纬度）</param>
        /// <param name="pixel">像素所在行</param>
        /// <param name="line">像素所在列</param>
        public void geoToImageSpace(double[] m_GeoTransform, double x, double y, out int pixel, out int line)
        {
            line = (int)((y * m_GeoTransform[1] - x * m_GeoTransform[4] + m_GeoTransform[0] * m_GeoTransform[4] - m_GeoTransform[3] * m_GeoTransform[1]) / (m_GeoTransform[5] * m_GeoTransform[1] - m_GeoTransform[2] * m_GeoTransform[4]));
            pixel = (int)((x - m_GeoTransform[0] - line * m_GeoTransform[2]) / m_GeoTransform[1]);
        }


    }

模拟结果在ArcGlobe中的显示效果图：

欢迎大家留言交流。