如何从经纬度距离矩阵中提取行列偏移的指定距离值？

问题描述 #

我拥有一组包含纬度（latitude）和经度（longitude）的坐标数据，已计算出每个观测点到第一个起始点的距离，得到了可转换为data frame的距离矩阵。现在需要从该矩阵中提取一组特定的距离值，提取规则为：第1行第V1列、第2行第V1列、第3行第V2列、第4行第V3列、第5行第V4列……以此类推，最终得到8个观测值，第一个值为起始点的0，后续为对应偏移位置的距离。

解决方案 #

可以通过生成对应行和列的索引来精准提取目标值，以下是R语言实现代码：

# 假设距离矩阵存储为 dist_matrix
row_indices <- 1:8  # 目标行索引（共8行）
# 生成目标列索引：前2行取第1列，第3行及以后列索引 = 行索引 - 1
col_indices <- ifelse(row_indices <= 2, 1, row_indices - 1)

# 提取对应位置的值
extracted_values <- dist_matrix[row_indices, col_indices]
# 为提取结果命名（可选）
names(extracted_values) <- paste0("观测值_", 1:8)

# 查看结果
extracted_values

根据提供的距离矩阵，执行上述代码后得到的提取结果为：

• 观测值_1: 0.0000
• 观测值_2: 1.21866
• 观测值_3: 87.07661
• 观测值_4: 159.368
• 观测值_5: 205.100
• 观测值_6: 322.563
• 观测值_7: 308.865
• 观测值_8: 175.726

原始数据 #

structure(list(latitude = c(38.4839693048603, 38.4839676888751, 
38.484000841, 38.4840256406904, 38.4842629760156, 38.4849478163079
), longitude = c(-123.055495022123, -123.055491287216, -123.055793254511, 
-123.056350426841, -123.05700151085, -123.057715977783)), row.names = c(NA, 
6L), class = "data.frame")

英尺单位距离矩阵 #

structure(list(V1 = structure(c(0, 1.21865987279359, 85.9395893412895, 
245.140367411948, 443.345616384121, 727.792251173584), units = structure(list(
    numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V2 = structure(c(1.21865987279359, 0, 87.076605103043, 246.25311887669, 
    444.523156907811, 729.010874767996), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V3 = structure(c(85.9395893412895, 87.076605103043, 0, 159.368289208323, 
    358.047418709711, 648.709228910322), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V4 = structure(c(245.140367411948, 246.25311887669, 159.368289208323, 
    0, 205.10072777621, 515.020408170641), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V5 = structure(c(443.345616384121, 444.523156907811, 358.047418709711, 
    205.10072777621, 0, 322.563054256646), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V6 = structure(c(727.792251173584, 729.010874767996, 648.709228910322, 
    515.020408170641, 322.563054256646, 0), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V7 = structure(c(1018.50792414677, 1019.71647638936, 943.971774385934, 
    819.591063850584, 631.321251450188, 308.865461805431), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units"), 
    V8 = structure(c(1191.19804190322, 1192.4014434649, 1117.85419293343, 
    995.173866175853, 806.723702197458, 484.163222522177), units = structure(list(
        numerator = "ft", denominator = character(0)), class = "symbolic_units"), class = "units")), row.names = c(NA, 
6L), class = "data.frame")

距离矩阵表格 #

内容的提问来源于stack exchange，提问作者Brittany Poling