R語言處理GIMMS NDVI3g數據

GIMMS NDVI3g 數據

植被指數是對植被冠層綠葉中葉綠素吸收的光合有效輻射的輻射度量，因此是該地區生理功能表面綠度水平的良好替代度量。在1980年代初的一系列文章中，康普頓·塔克（Compton J. Tucker）展示了如何利用NOAA的超高分辨率高分辨率輻射計（AVHRR）數據生成的歸一化植被指數（NDVI）來繪制土地覆蓋圖並監測植被變化和荒漠化在大陸和全球范圍內。在Web of Science上的簡單搜索顯示標題或摘要中包含NDVI的5000多篇文章。康普頓·塔克（Compton J.Tucker）在過去30年中，在全球庫存監控和建模系統（GIMMS）項目的框架內繼續生成NDVI時間序列，並通過不同的AVHRR傳感器精心組裝，並考慮了各種有害影響，例如校准GIMMS NDVI數據集的最新版本橫跨1981年7月至2011年12月，被稱為NDVI3g（來自AVHRR傳感器的第三代GIMMS NDVI）。

注意：此數據集已有更新。最新版本3g.v1跨度為1981年7月至2015年12月。原始版本3g.v0保留在原位置，並且仍可以訪問。
下載地址：數據可以直接在這里下載 https://ecocast.arc.nasa.gov/data/pub/gimms/

R語言下載處理GIMMS NDVI3g數據

這里介紹一個R語言包gimms，下面介紹一些常用的處理方法。

.nc4格式轉.tif格式

library('raster')
library("gimms","rgdal")

input<- 'G:/ndvi_GIMMS3g/data'
out<- 'G:/ndvi_GIMMS3g/data_tif'

for (value in 1981:2015) {

  fn1 <- paste0(input,"/ndvi3g_geo_v1_",value,"_","0712",".nc4")

  print(paste0("正在讀取...%s_%s",value,"0712"))

  ndvi3g <- rasterizeGimms(x = fn1)

  for (variable in 1:12) {

    name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0712","-",variable,".tif")

    print(paste0("正在處理...%s",name))

    writeRaster(x = ndvi3g[[variable]],filename = name, overwrite=TRUE)

  }

}

for (value in 1982:2015) {
  
  fn1 <- paste0(input,"/ndvi3g_geo_v1_",value,"_","0106",".nc4")
  
  print(paste0("正在讀取...%s_%s",value,"0106"))

  ndvi3g <- rasterizeGimms(x = fn1)
  
  for (variable in 1:12) {
    
    name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0106","-",variable,".tif")
    
    print(paste0("正在處理...%s",name))
    
    writeRaster(x = ndvi3g[[variable]],filename = name, overwrite=TRUE)
    
  }
  
}

最大月合成

library('sp')
library('raster')
library('gimms')
library('rgdal')

input<- 'G:/ndvi_GIMMS3g/data'
out<- 'G:/ndvi_GIMMS3g/data_mvc'

for (value in 1981:2015) {

  fn1 <- paste0(input,"/ndvi3g_geo_v1_",value,"_","0712",".nc4")

  print(paste0("正在讀取...%s_%s",value,"0712"))

  ndvi3g <- rasterizeGimms(x = fn1)

  mvc <- monthlyComposite(ndvi3g,indices = monthlyIndices(fn1))

  for (variable in 1:6) {

    mon<- 6+variable

    if(mon<10){

      name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0712","_0",mon,".tif")

    }else{

      name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0712","_",mon,".tif")

    }

    print(paste0("正在處理...%s",name))

    writeRaster(x = mvc[[variable]],filename = name, overwrite=TRUE)

  }

}

for (value in 1982:2015) {
  
  fn1 <- paste0(input,"/ndvi3g_geo_v1_",value,"_","0106",".nc4")
  
  print(paste0("正在讀取...%s_%s",value,"0106"))
  
  ndvi3g <- rasterizeGimms(x = fn1)
  
  mvc <- monthlyComposite(ndvi3g,indices = monthlyIndices(fn1))
  
  for (variable in 1:6) {
    
    mon<- variable
    
    if(mon<10){
      
      name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0712","_0",mon,".tif")
      
    }else{
      
      name <- paste0(out,"/ndvi3g_geo_v1_",value,"_","0712","_",mon,".tif")
      
    }
    
    print(paste0("正在處理...%s",name))
    
    writeRaster(x = mvc[[variable]],filename = name, overwrite=TRUE)
    
  }
  
}