MATLAB中GIMMS NDVI3gv1转Geotiff

抱歉，一直没有升级代码，您需要自己处理一下，我把一期数据的元数据贴出来（回复中不支持格式），该文件第22行：short ndvi(time=12, lat=2160, lon=4320); :scale = "x 10000"; :missing_value = -5000.0; // double :valid_range = -0.3, 1.0; // double :units = "1"; 说明ndvi值为乘以10000后的数值，实际数值范围为-0.3~1，需要区分处理，转换后的水域是-32768,。另外参考percentile中的flag来判断数据来源是否是原始值0或是插值结果1或者季节数据2。 File "ndvi3g_geo_v1_1981_0712.nc4" File type: Hierarchical Data Format, version 5 netcdf file:/G:/DATA/GIMMS3gv1/ndvi3g_geo_v1_1981_0712.nc4 { dimensions: time = 12; lon = 4320; lat = 2160; variables: double time(time=12); :_ChunkSizes = 12U; // uint double lon(lon=4320); :_ChunkSizes = 4320U; // uint short satellites(time=12); :_ChunkSizes = 12U; // uint double lat(lat=2160); :_ChunkSizes = 2160U; // uint short ndvi(time=12, lat=2160, lon=4320); :scale = "x 10000"; :missing_value = -5000.0; // double :valid_range = -0.3, 1.0; // double :units = "1"; :_ChunkSizes = 2U, 540U, 1080U; // uint short percentile(time=12, lat=2160, lon=4320); :scale = "x 10"; :flags = "flag 0: from data flag 1: spline interpolation flag 2: possible snow/cloud cover"; :valid_range = "flag*2000 + [0 1000]"; :units = "%"; :_ChunkSizes = 2U, 540U, 1080U; // uint // global attributes: :FileName = "ndvi3g_geo_v1_1981_0712.nc4"; :Institution = "NASA/GSFC GIMMS"; :Data = "NDVI3g version 1"; :Reference = "1. Pinzon, J.E.; Tucker, C.J. A Non-Stationary 1981-2012 AVHRR NDVI3g Time Series. Remote Sens. 2014, 6, 6929-6960. 2. Pinzon, J.E.; Tucker, C.J. A Non-Stationary 1981-2015 AVHRR NDVI3g.v1 Time Series: an update. Remote Sens. 2016, in preparation "; :CommentsVersion1 = "version1 includes two major fixes (a and b), and three minor (c-g): (a) Reprocessed Level 2 entire SeaWIFS mission for the land products to reduce artifacts in the data, particularly changes in calibration after 2006 that generates drops in ndvi lower values. OB.DAAC / Ocean Biology Processing group NASA/GSFC 616 (april 2016) (b) Recovered ndvi negative values of snow-covered regions in winter Northern latitudes. In Version0, we masked them with zero values, creating artifacts in phenology parameters. (c) Arranged data in ncd format, compiled it in two nc4 files a year. Each nc4 file includes 6 months of ndvi data (jan-jun and jul-dec), with a total of 12 (15-day) composites each semester. (d) Rescaled ndvi values and splitted the flag values from them. (e) Added a new variable, percentile, to represent the distribution of ndvi values in the time series. Range 10*[0, 100] (f) Flag values are (simpler): flag 0: ndvi without apparent issues (good value) flag 1: ndvi retrieved from spline interpolation flag 2: ndvi retrieved from seasonal profile (possible snow/cloud) (g) Flag values are embeded on the percentile variable: 2000*flag + percentile. Thus, the actual percentile three ranges [0 1000], [2000 3000] and [4000 5000] could provide direct information of how interpolation is affecting the time series. "; :Temporalrange = "1981-07-01 -> 2015-12-31"; :Year = 1981.0; // double :RangeSemester = "Jul 1 - Dec 31 (7:0.5:12.5)"; :SpatialResolution = "1/12 x 1/12 degrees"; :TemporalResolution = "1/24 a year"; :_fill_val = -32768.0; // double :NorthernmostLatitude = "90"; :SouthernmostLatitude = "-90"; :WesternmostLongitude = "-180"; :EasternmostLongitude = "180"; }

下载的任何MATLAB代码中出现类似提示，先在网上搜索，可能是MATLAB版本差异，官方帮助见下方链接 https://ww2.mathworks.cn/help/map/ref/georefcells.html