问题：

如何从R中的多个Aqua Modis netCDF文件中提取变量？

韩阳飙

2023-03-14

问题：

我在R中有一个代码，可以从单个Aqua Modis网络CDF文件中提取每月海面温度（SST）值（见下文）。但是，我在一个文件夹中有一批 59 个 Aqua Modis netCDF 文件。

目的：

我的目标是从所有59个netCDF文件的每个netCDF中提取变量的经度、纬度和SST，使用函数stack:：raster（）将它们转换为光栅文件，然后处理这些文件。

我的数据框有 650 行，它们是海豚 ID。我想提取 2016-2021 年期间每个海豚 ID 的平均 SST。一旦我提取了每个海豚ID的平均值SST，我想将这些值写入一个名为“ Average_SST”的列的.csv文件中。

不幸的是，由于所有权问题，我无法共享我的数据。

我是一个完全的新手在空间分析，我一直试图解决这个难题近4天通过观看YouTube，阅读教程和堆栈溢出。我现在感到非常困惑，我相信我将不得不循环通过所有的文件来实现我的目标。

如果有人能帮忙，在此提前致谢。

r代码:

从文件夹中打开所有59个Aqua Modis netCDF文件

##Open packages needed for our analysis
library(ncdf4)
library(terra)
library('RNetCDF')
library(raster)
library(sp)

filenames = list.files('~/Documents/Ocean_ColorSST_2016_2021',pattern='*.nc',full.names=TRUE)

##Open the 70 Aqua Modis netCDF files from their folder
SST <- nc_open(filenames[59])

##Print the results for SST
print(SST)

结果：

     3 variables (excluding dimension variables):
        short sst[lon,lat]   (Chunking: [87,44])  (Compression: shuffle,level 4)
            long_name: Sea Surface Temperature
            scale_factor: 0.00499999988824129
            add_offset: 0
            units: degree_C
            standard_name: sea_surface_temperature
            _FillValue: -32767
            valid_min: -1000
            valid_max: 10000
            display_scale: linear
            display_min: -2
            display_max: 45
        unsigned byte qual_sst[lon,lat]   (Chunking: [87,44])  (Compression: shuffle,level 4)
            long_name: Quality Levels, Sea Surface Temperature
            _FillValue: 255
            valid_min: 0
            valid_max: 5
        unsigned byte palette[eightbitcolor,rgb]   (Contiguous storage)  

     4 dimensions:
        lat  Size:4320 
            long_name: Latitude
            units: degrees_north
            standard_name: latitude
            _FillValue: -999
            valid_min: -90
            valid_max: 90
        lon  Size:8640 
            long_name: Longitude
            units: degrees_east
            standard_name: longitude
            _FillValue: -999
            valid_min: -180
            valid_max: 180
        rgb  Size:3 (no dimvar)
        eightbitcolor  Size:256 (no dimvar)
[1] ">>>> WARNING <<<  attribute data_bins is an 8-byte value, but R"
[1] "does not support this data type. I am returning a double precision"
[1] "floating point, but you must be aware that this could lose precision!"

    61 global attributes:
        product_name: AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc
        instrument: MODIS
        title: MODISA Level-3 Standard Mapped Image
        project: Ocean Biology Processing Group (NASA/GSFC/OBPG)
        platform: Aqua
        temporal_range: month
        processing_version: R2019.0
        date_created: 2021-12-03T08:21:22.000Z
        history: l3mapgen par=AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc.param 
        l2_flag_names: LAND,HISOLZEN
        time_coverage_start: 2021-09-01T00:45:00.000Z
        time_coverage_end: 2021-10-01T02:55:00.000Z
        start_orbit_number: 102808
        end_orbit_number: 103246
        map_projection: Equidistant Cylindrical
        latitude_units: degrees_north
        longitude_units: degrees_east
        northernmost_latitude: 90
        southernmost_latitude: -90
        westernmost_longitude: -180
        easternmost_longitude: 180
        geospatial_lat_max: 90
        geospatial_lat_min: -90
        geospatial_lon_max: 180
        geospatial_lon_min: -180
        latitude_step: 0.0416666679084301
        longitude_step: 0.0416666679084301
        sw_point_latitude: -89.9791641235352
        sw_point_longitude: -179.97917175293
        spatialResolution: 4.64 km
        geospatial_lon_resolution: 0.0416666679084301
        geospatial_lat_resolution: 0.0416666679084301
        geospatial_lat_units: degrees_north
        geospatial_lon_units: degrees_east
        number_of_lines: 4320
        number_of_columns: 8640
        measure: Mean
        suggested_image_scaling_minimum: -2
        suggested_image_scaling_maximum: 45
        suggested_image_scaling_type: LINEAR
        suggested_image_scaling_applied: No
        _lastModified: 2021-12-03T08:21:22.000Z
        Conventions: CF-1.6 ACDD-1.3
        institution: NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group
        standard_name_vocabulary: CF Standard Name Table v36
        naming_authority: gov.nasa.gsfc.sci.oceandata
        id: AQUA_MODIS.20210901_20210930.L3b.MO.SST.nc/L3/AQUA_MODIS.20210901_20210930.L3b.MO.SST.nc
        license: https://science.nasa.gov/earth-science/earth-science-data/data-information-policy/
        creator_name: NASA/GSFC/OBPG
        publisher_name: NASA/GSFC/OBPG
        creator_email: data@oceancolor.gsfc.nasa.gov
        publisher_email: data@oceancolor.gsfc.nasa.gov
        creator_url: https://oceandata.sci.gsfc.nasa.gov
        publisher_url: https://oceandata.sci.gsfc.nasa.gov
        processing_level: L3 Mapped
        cdm_data_type: grid
        keywords: Earth Science > Oceans > Ocean Optics > Sea Surface Temperature
        keywords_vocabulary: NASA Global Change Master Directory (GCMD) Science Keywords
        data_bins: 20227868
        data_minimum: -1.80000007152557
        data_maximum: 40.0000038146973
> SST_brick <- brick(list[59], "sst")
Error in h(simpleError(msg, call)) : 
  error in evaluating the argument 'x' in selecting a method for function 'brick': object of type 'builtin' is not subsettable
> ##Print the results for SST
> print(SST)
File /Users/kirstymedcalf/Documents/DMAD/Publication/DMAD_Maps_Analysis_Publication/Montenegro_Final_Analysis_Folders/Ocean_ColorSST_2016_2021/AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc (NC_FORMAT_NETCDF4):

     3 variables (excluding dimension variables):
        short sst[lon,lat]   (Chunking: [87,44])  (Compression: shuffle,level 4)
            long_name: Sea Surface Temperature
            scale_factor: 0.00499999988824129
            add_offset: 0
            units: degree_C
            standard_name: sea_surface_temperature
            _FillValue: -32767
            valid_min: -1000
            valid_max: 10000
            display_scale: linear
            display_min: -2
            display_max: 45
        unsigned byte qual_sst[lon,lat]   (Chunking: [87,44])  (Compression: shuffle,level 4)
            long_name: Quality Levels, Sea Surface Temperature
            _FillValue: 255
            valid_min: 0
            valid_max: 5
        unsigned byte palette[eightbitcolor,rgb]   (Contiguous storage)  

     4 dimensions:
        lat  Size:4320 
            long_name: Latitude
            units: degrees_north
            standard_name: latitude
            _FillValue: -999
            valid_min: -90
            valid_max: 90
        lon  Size:8640 
            long_name: Longitude
            units: degrees_east
            standard_name: longitude
            _FillValue: -999
            valid_min: -180
            valid_max: 180
        rgb  Size:3 (no dimvar)
        eightbitcolor  Size:256 (no dimvar)
[1] ">>>> WARNING <<<  attribute data_bins is an 8-byte value, but R"
[1] "does not support this data type. I am returning a double precision"
[1] "floating point, but you must be aware that this could lose precision!"

    61 global attributes:
        product_name: AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc
        instrument: MODIS
        title: MODISA Level-3 Standard Mapped Image
        project: Ocean Biology Processing Group (NASA/GSFC/OBPG)
        platform: Aqua
        temporal_range: month
        processing_version: R2019.0
        date_created: 2021-12-03T08:21:22.000Z
        history: l3mapgen par=AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc.param 
        l2_flag_names: LAND,HISOLZEN
        time_coverage_start: 2021-09-01T00:45:00.000Z
        time_coverage_end: 2021-10-01T02:55:00.000Z
        start_orbit_number: 102808
        end_orbit_number: 103246
        map_projection: Equidistant Cylindrical
        latitude_units: degrees_north
        longitude_units: degrees_east
        northernmost_latitude: 90
        southernmost_latitude: -90
        westernmost_longitude: -180
        easternmost_longitude: 180
        geospatial_lat_max: 90
        geospatial_lat_min: -90
        geospatial_lon_max: 180
        geospatial_lon_min: -180
        latitude_step: 0.0416666679084301
        longitude_step: 0.0416666679084301
        sw_point_latitude: -89.9791641235352
        sw_point_longitude: -179.97917175293
        spatialResolution: 4.64 km
        geospatial_lon_resolution: 0.0416666679084301
        geospatial_lat_resolution: 0.0416666679084301
        geospatial_lat_units: degrees_north
        geospatial_lon_units: degrees_east
        number_of_lines: 4320
        number_of_columns: 8640
        measure: Mean
        suggested_image_scaling_minimum: -2
        suggested_image_scaling_maximum: 45
        suggested_image_scaling_type: LINEAR
        suggested_image_scaling_applied: No
        _lastModified: 2021-12-03T08:21:22.000Z
        Conventions: CF-1.6 ACDD-1.3
        institution: NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group
        standard_name_vocabulary: CF Standard Name Table v36
        naming_authority: gov.nasa.gsfc.sci.oceandata
        id: AQUA_MODIS.20210901_20210930.L3b.MO.SST.nc/L3/AQUA_MODIS.20210901_20210930.L3b.MO.SST.nc
        license: https://science.nasa.gov/earth-science/earth-science-data/data-information-policy/
        creator_name: NASA/GSFC/OBPG
        publisher_name: NASA/GSFC/OBPG
        creator_email: data@oceancolor.gsfc.nasa.gov
        publisher_email: data@oceancolor.gsfc.nasa.gov
        creator_url: https://oceandata.sci.gsfc.nasa.gov
        publisher_url: https://oceandata.sci.gsfc.nasa.gov
        processing_level: L3 Mapped
        cdm_data_type: grid
        keywords: Earth Science > Oceans > Ocean Optics > Sea Surface Temperature
        keywords_vocabulary: NASA Global Change Master Directory (GCMD) Science Keywords
        data_bins: 20227868
        data_minimum: -1.80000007152557
        data_maximum: 40.0000038146973

##从每个Aqua Modis文件中提取SST、经度和纬度值，为感兴趣的变量创建59个列表。然而，我认为我只是提取了一个Aqua Modis文件的值[1]

SST_filenames <- ncvar_get(SST, "sst")
lon_filenames <- ncvar_get(SST, "lon")
lat_filenames <- ncvar_get(SST, "lat")

我以为我会尝试 brick（）函数但没有成功，因为我仍然认为我正在从单个 Aqua Modis 文件 [1] 中提取值。.

SST_brick <- brick(filenames[59], "sst")
lon_brick <- brick(filenames[59], "lon")
lat_brick <- brick(filenames[59], "lat")

SST_brick的结果

   lass      : RasterBrick 
    dimensions : 4320, 8640, 37324800, 1  (nrow, ncol, ncell, nlayers)
    resolution : 0.04166667, 0.04166667  (x, y)
    extent     : -180, 180, -90.00001, 90  (xmin, xmax, ymin, ymax)
    crs        : +proj=longlat +datum=WGS84 +no_defs 
    source     : AQUA_MODIS.20210901_20210930.L3m.MO.SST.sst.4km.nc 
    names      : layer 
    varname    : sst

如果我使用对象SST，我想我还是打开了单个Aqua Modis netCDF文件的值[1]

SST_filenames <- ncvar_get(SST, "sst")
lon_filenames <- ncvar_get(SST, "lon")
lat_filenames <- ncvar_get(SST, "lat")

颜光临

2023-03-14

您似乎误解了RasterStack或SpatRaster对象是什么。您打印了SST_brick，它清楚地显示它知道经度和纬度。您不需要其他任何东西。

与

library(terra)
filenames = list.files('~/Documents/Ocean_ColorSST_2016_2021',pattern='*.nc',full.names=TRUE)

假设＜code＞海豚＜/code＞是一个矩阵或数据。带有变量“经度”和“纬度”的框架，您可以对一个文件这样做：

SST <- rast(filenames[1], "sst")
e <- extract(SST, dolphins[, c("longitude", "latitude")])

但是你可以像这样一蹴而就

SSTs <- rast(filenames, "sst")
e <- extract(SSTs, dolphins[, c("longitude", "latitude")])

如何从R中的多个Aqua Modis netCDF文件中提取变量？

共有1个答案

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