洪涝有源淹没算法及淹没结果分析

怼烎@ 2022-08-10 11:55 128阅读 0赞

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；另一种是基于DEM的洪水淹没分析。具体分析如下：

![Center][]![Center 1][]

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。

![Center 2][]

本篇博客采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。采用C\#版本GDAL编写了FloodSimulation类，下面给出全部源代码：

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(影像坐标变换参数)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参数
                例如: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>
            /// 加载淹没区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;
                
                //获取影像坐标转换参数
                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,先需要明确待创建影像的格式,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); //影像转换参数
                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)
            {
                //首先根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);
    
                //判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++)
                        {
                            //判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);
                                //搜索可以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加入堆栈，标记为淹没，避免重复运算
                                    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">影像坐标变换参数</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">影像坐标变化参数</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：

![Center 3][]

欢迎大家留言交流。

[Center]: https://img-blog.csdn.net/20141119210749844?watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQvZ2lzZXJfd2h1/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/Center
[Center 1]: /images/20220810/5ed4b6e658fa4d38a6cd892ec66811ef.png
[Center 2]: /images/20220810/db7ea26bfda846f491c65dc58cab5074.png
[Center 3]: /images/20220810/e1c8e3155f5a4b388616caf207adfede.png