Python遥感开发之批量拼接

前言：主要借助python实现遥感影像的批量拼接，遥感影像的批量拼接主要分为两种情况，一种是遥感图像无交错，另一种情况是遥感图像相互有交错。具体实现请参考以下代码，如有问题请及时反馈。

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1 遥感图像无交错的批量拼接

此方法是各个遥感文件是没有相互交错的拼接，如下图所示。个人可以使用Arcgis进行查看。

实现思路：通过每个遥感数据的经纬度进行拼接下一个遥感数据文件。

import os
from osgeo import gdal

def get_data_list(file_path, out = ""):
    list1 = []  # 文件的完整路径
    if os.path.isdir(file_path):
        fileList = os.listdir(file_path)
        if out != "":
            for f in fileList:
                out_data = out + "\\" + f
                out_data = out_data.replace(".HDF", "_ndvi.tif")
                list1.append(out_data)
        else:
            for f in fileList:
                pre_data = file_path + '\\' + f  # 文件的完整路径
                list1.append(pre_data)
        return list1

def get_same_list(image, infile_list):
    infile_list02 = []
    for data in infile_list:
        if image in data:
            # print("----", data)
            infile_list02.append(data)
    return infile_list02

def get_same_image_list(infile_list):
    image_list= []
    for file in infile_list:
        filename = file[-31:-23]
        if filename not in image_list:
            image_list.append(filename)
    return list(set(image_list))

def pinjie(infile_list,outfile):
    ds = gdal.Open(infile_list[0])
    cols = ds.RasterXSize
    rows = ds.RasterYSize
    ingeo = ds.GetGeoTransform()
    proj = ds.GetProjection()
    minx = ingeo[0]
    maxy = ingeo[3]
    maxx = ingeo[0] + ingeo[1] * cols
    miny = ingeo[3] + ingeo[5] * rows
    ds = None
    for file in infile_list[1:]:
        ds = gdal.Open(file)
        cols = ds.RasterXSize
        rows = ds.RasterYSize
        geo = ds.GetGeoTransform()
        minx_ = geo[0]
        maxy_ = geo[3]
        maxx_ = geo[0] + geo[1] * cols
        miny_ = geo[3] + geo[5] * rows
        minx = min(minx, minx_)
        maxy = max(maxy, maxy_)
        maxx = max(maxx, maxx_)
        miny = min(miny, miny_)
        geo = None
        ds = None
    newcols = int((maxx - minx) / abs(ingeo[1]))
    newrows = int((maxy - miny) / abs(ingeo[5]))
    driver = gdal.GetDriverByName("GTiff")
    outds = driver.Create(outfile, newcols, newrows, 1, gdal.GDT_Int16)
    outgeo = (minx, ingeo[1], 0, maxy, 0, ingeo[5])
    outds.SetGeoTransform(outgeo)
    outds.SetProjection(proj)
    outband = outds.GetRasterBand(1)
    for file in infile_list:
        ds = gdal.Open(file)
        data = ds.ReadAsArray()
        geo = ds.GetGeoTransform()
        x = int(abs((geo[0] - minx) / ingeo[1]))
        y = int(abs((geo[3] - maxy) / ingeo[5]))
        outband.WriteArray(data, x, y)
        ds = None
    outband.FlushCache()
    pass
if __name__ == '__main__':

    infile = r"C:\Users\Administrator\Desktop\01提取ndvi"
    outfile = r"C:\Users\Administrator\Desktop\02拼接"
    infile_list = get_data_list(infile)
    image_name_list = get_same_image_list(infile_list)
    print(image_name_list)
    for name in image_name_list:
        print(name)
        infile_list02 = get_same_list(name, infile_list)
        pinjie(infile_list02,outfile+"\\"+name+".tif")

2 遥感图像有交错的批量拼接

此方法是各个遥感文件是有相互交错的拼接，如下图所示，具体可以使用Arcgis进行查看。

实现思路：借助gdal中WarpOptions的方法实现，有点类似于镶嵌

import numpy as np
from osgeo import gdal, gdalconst
import os

def RasterMosaic(firstinputfilePath, inputfileList, outputfilePath):
    inputrasfile1 = gdal.Open(firstinputfilePath, gdal.GA_ReadOnly)  # 第一幅影像
    inputProj1 = inputrasfile1.GetProjection()
    options = gdal.WarpOptions(srcSRS=inputProj1, dstSRS=inputProj1, format='GTiff')
    gdal.Warp(outputfilePath, inputfileList, options=options)

def get_data_list(file_path, out=""):
    list1 = []  # 文件的完整路径
    if os.path.isdir(file_path):
        fileList = os.listdir(file_path)
        if out != "":
            for f in fileList:
                out_data = out + "\\" + f
                out_data = out_data.replace(".HDF", "_ndvi.tif")
                list1.append(out_data)
        else:
            for f in fileList:
                pre_data = file_path + '\\' + f  # 文件的完整路径
                list1.append(pre_data)
        return list1


def get_same_image_list(infile_list):
    image_list = []
    for file in infile_list:
        filename = file[-20:-12]
        if filename not in image_list:
            image_list.append(filename)
    return list(set(image_list))

def get_infile(image,infile_list):
    for data in infile_list:
        if image in data:
            return data

def get_same_list(image, infile_list):
    infile_list02 = []
    for data in infile_list:
        if image in data:
            infile_list02.append(data)
    return infile_list02

if __name__ == '__main__':
    inputfile_path = r"D:\风云数据\MERSI-II陆表反射比1KM段产品\b1\01原始"
    outfile = r"D:\风云数据\MERSI-II陆表反射比1KM段产品\b1\02拼接"
    infile_list = get_data_list(inputfile_path)
    image_list = get_same_image_list(infile_list)
    print(image_list)
    for image in image_list:
        firstinputfilePath = get_infile(image,infile_list)
        infile_list02 = get_same_list(image, infile_list)
        print(image)
        print(firstinputfilePath)
        print(infile_list02)
        RasterMosaic(firstinputfilePath, infile_list02, outfile+"\\"+image+"_b1.tif")
        print("-------")