洪澇有源淹沒演算法及淹沒結果分析
洪澇模擬模擬的實現方法主要有兩種：一種是基於水動力學的洪水演進模型；另一種是基於DEM的洪水淹沒分析。具體分析如下：
我是GIS從業者，從我們的專業角度出發，選擇基於DEM的洪水淹沒分析來做洪澇的模擬模擬。而基於DEM的洪水淹沒分析方法主要分為有源淹沒和無源淹沒。
本篇部落格採用有源淹沒演算法實現洪澇的模擬，演算法為八領域種子擴散演算法。採用C#版本GDAL編寫了FloodSimulation類，下面給出全部原始碼：
class FloodSimulation
{
#region 類成員變數
//點結構體
public struct Point
{
public int X; //行號
public int Y; //列號
public int Elevation; //畫素值(高程值)
public bool IsFlooded; //淹沒標記
};
private bool[,] IsFlood; //淹沒區域標記二維陣列，用於標記淹沒柵格
private List<Point> m_FloodBufferList; //淹沒緩衝區堆疊
public Dataset m_DEMDataSet; //DEM資料集
public Dataset m_FloodSimulatedDataSet; //洪澇淹沒範圍資料集
public int m_XSize; //資料X方向柵格個數
public int m_YSize; //資料Y方向柵格個數
public OSGeo.GDAL.Driver driver; //影像格式驅動
public int[] m_FloodBuffer; //填充緩衝區（洪澇淹沒範圍）
public int[] m_DEMdataBuffer; //DEM資料（儲存高程值）
public double m_AreaFlooded; //水面面積
public double m_WaterVolume; //淹沒水體體積
/* 這裡的GeoTransform(影像座標變換引數)的定義是：通過畫素所在的行列值得到其左上角點空間座標的運算引數
例如:某影象上(P,L)點左上角的實際空間座標為：
Xp = GeoTransform[0] + P * GeoTransform[1] + L * GeoTransform[2];
Yp = GeoTransform[3] + P * GeoTransform[4] + L * GeoTransform[5]; */
public double[] m_adfGeoTransform;
#endregion
//建構函式
public FloodSimulation()
{
m_adfGeoTransform = new double[6];
m_FloodBufferList = new List<Point>();
}
/// <summary>
/// 載入淹沒區DEM,並建立淹沒範圍影像
/// </summary>
/// <param name="m_DEMFilePath">DEM檔案路徑</param>
/// <returns></returns>
public void loadDataSet(string m_DEMFilePath)
{
//讀取DEM資料
m_DEMDataSet = Gdal.Open(m_DEMFilePath, Access.GA_ReadOnly);
m_XSize = m_DEMDataSet.RasterXSize;
m_YSize = m_DEMDataSet.RasterYSize;
//獲取影像座標轉換引數
m_DEMDataSet.GetGeoTransform(m_adfGeoTransform);
//讀取DEM資料到記憶體中
Band m_DEMBand = m_DEMDataSet.GetRasterBand(1); //獲取第一個波段
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);
//淹沒範圍填充緩衝區
m_FloodBuffer = new int[m_XSize * m_YSize];
IsFlood=new bool[m_XSize,m_YSize];
//初始化二維淹沒區bool陣列
for (int i = 0; i < m_XSize; i++)
{
for (int j = 0; j < m_YSize; j++)
{
IsFlood[i, j] = false;
}
}
//建立洪澇淹沒範圍影像
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中建立影像,先需要明確待建立影像的格式,並獲取到該影像格式的驅動
driver = Gdal.GetDriverByName("GTiff");
//呼叫Creat函式建立影像
// 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);
//設定影像屬性
m_FloodSimulatedDataSet.SetGeoTransform(m_adfGeoTransform); //影像轉換引數
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);
//輸出影像
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>
/// 種子擴散演算法淹沒分析
/// </summary>
/// <param name="m_Lat">種子點緯度</param>
/// <param name="m_Log">種子點經度</param>
/// <param name="m_FloodLevel">淹沒水位</param>
public void FloodFill8Direct(double m_Lat,double m_Log,double m_FloodLevel)
{
//首先根據種子點經緯度獲取其所在行列號
Point pFloodSourcePoint = new Point();
int x, y;
geoToImageSpace(m_adfGeoTransform, m_Log, m_Lat, out x, out y);
pFloodSourcePoint.X = x;
pFloodSourcePoint.Y = y;
//獲取種子點高程值
pFloodSourcePoint.Elevation = GetElevation(pFloodSourcePoint);
m_FloodBufferList.Add(pFloodSourcePoint);
//判斷堆疊中時候還有未被淹沒點，如有繼續搜尋，沒有則淹沒分析結束。
while (m_FloodBufferList.Count!=0)
{
Point pFloodSourcePoint_temp = m_FloodBufferList[0];
int rowX = pFloodSourcePoint_temp.X;
int colmY = pFloodSourcePoint_temp.Y;
//標記可淹沒,並從淹沒堆疊中移出
IsFlood[rowX, colmY] = true;
m_FloodBuffer[getIndex(pFloodSourcePoint_temp)] = 1;
m_FloodBufferList.RemoveAt(0);
//向中心柵格單元的8個臨近方向搜尋連通域
for (int i = rowX - 1; i < rowX + 2; i++)
{
for (int j = colmY - 1; j < colmY + 2; j++)
{
//判斷是否到達柵格邊界
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);
//搜尋可以淹沒且未被標記的柵格單元
if ((temp_point.Elevation<m_FloodLevel||temp_point.Elevation <= pFloodSourcePoint_temp.Elevation) && IsFlood[temp_point.X, temp_point.Y] == false)
{
//將符合條件的柵格單元加入堆疊，標記為淹沒，避免重複運算
m_FloodBufferList.Add(temp_point);
IsFlood[temp_point.X, temp_point.Y] = true;
m_FloodBuffer[getIndex(temp_point)] = 1;
}
}
}
}
}
//統計淹沒網格數
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>
/// 輸出洪澇淹沒範圍圖
/// </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>
/// 獲取第x行第y列柵格索引
/// </summary>
/// <param name="point">柵格點</param>
/// <returns>該點在DEM記憶體陣列中的索引</returns>
private int getIndex(Point point)
{
return point.Y* m_XSize + point.X;
}
/// <summary>
/// 獲取高程值
/// </summary>
/// <param name="m_point">柵格點</param>
/// <returns>高程值</returns>
private int GetElevation(Point m_point)
{
return m_DEMdataBuffer[getIndex(m_point)];
}
/// <summary>
/// 從畫素空間轉換到地理空間
/// </summary>
/// <param name="adfGeoTransform">影像座標變換引數</param>
/// <param name="pixel">畫素所在行</param>
/// <param name="line">畫素所在列</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>
/// 從地理空間轉換到畫素空間
/// </summary>
/// <param name="adfGeoTransform">影像座標變化引數</param>
/// <param name="x">X(經度)</param>
/// <param name="y">Y（緯度）</param>
/// <param name="pixel">畫素所在行</param>
/// <param name="line">畫素所在列</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]);
}
}
模擬結果在ArcGlobe中的顯示效果圖：
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作者：召喚師峽谷
來源：CSDN
原文：https://blog.csdn.net/giser_whu/article/details/41288761
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