This is the vegetation index (NDVI) for Maduo County in July, August and September of 2016. It is obtained through calculation based on the multispectral data of GF-1. The spatial resolution is 16 m. The GF-1 data are processed by mosaicking, projection coordinating, data subsetting and other methods. The maximum synthesis is then conducted every month in July, August, and September.
LI Fei, Fei Li, Zhijun Zhang
The NDVI data set is the sixth version of the MODIS Normalized Difference Vegetation Index product (2001-2016) jointly released by NASA EOSDIS LP DAAC and the US Geological Survey (USGS EROS). The product has a temporal resolution of 16 days and a spatial resolution of 0.05 degrees. This version is a Climate Modeling Grid (CMG) data product generated from the original NDVI product (MYD13A2) with a resolution of 1 kilometer. Please indicate the source of these data as follows in acknowledgments: The MOD13C NDVI product was retrieved online courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, The [PRODUCT] was (were) retrieved from the online [TOOL], courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
NASA
This dataset contains three basic remote sensing data of digital topography (DEM), TM remote sensing image and NDVI vegetation index of badan jilin desert. 1. DEM, digital terrain data, from the SRTM1 data set released by NASA in the United States, was cropped in the desert area.The resolution is 30 m.The data is stored in the DEM folder, and the dm.ovr file can be opened by ArcGIS. 2. TM image data.The composite data of Landsat TM/ETM + 543 band released by NASA were cropped in the desert lake group distribution area.The resolution is 30 m.From 1990 to 2010, one scene was selected in summer and one scene in autumn every five years to analyze the long-term changes of the lake.In 2002, there was a scene for each quarter to analyze the changes of the lake during the year.The data is stored in TM folder, TIFF format, can be opened by ArcGIS or ENVI software.The file naming rule is yyyymm.tif, where yyyy refers to the year and mm to the month. For example, 199009 refers to the time corresponding to the impact data of September 1990. 3. NDVI, vegetation index.The modis-ndvi product MOD13Q1, released by NASA, was cropped in desert areas.The NDVI data of every ten days of the growing season (June, July, August and September) from 2000 to 2012 are included. The spatial resolution is 250 m and the temporal resolution is 16 days.Stored in NDVI folder, TIFF format, can be opened by ArcGIS or ENVI software.Mosaic_tmp_yyyyddd.hdfout.250m_16_days_ndvi_roi.tif, Where yyyy represents the year and DDD represents the day of DDD of the year.
JIN Xiaomei, HU Xiaonong
The NDVI data of GIMMS (glaobal modelling and mapping studies) is the latest global vegetation index change data released by NASA c-j-tucker et al in November 2003. This data set includes the changes in the vegetation index of the long time series of the qaidam basin from 1981 to 2006. The format is the standard ENVI format, and the projection is ALBERS. The temporal resolution is 15 days and the spatial resolution is 8km.GIMMS NDVI data recorded the vegetation changes in 22a region in the format of satellite data. 1. File format: The gimms-ndvi data set contains all the.rar compressed files with a 15-day interval from July 1981 to 2006, including one XML document, one.hdr header file, one.img file, and one.jpg image file after unzipped. 2. File name: The naming rule for compressed files in NOAA/ avhrr-ndvi data set is: YYMMM15a(b). N ** -vig_data_envi.After unzipping, there are four files with the same file name and attributes: XML document, header file (suffix:.hdf), remote sensing image file (suffix:.img) and JPEG image file. Remote sensing image files with suffixes.img and.hdf, which are used by users to analyze vegetation index, can be opened in ENVI and ERDAS software.
National Aeronautics and Space Administration
The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient number). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN= (NDVI+0.1)/0.004. The data set is the Shule River long-time series vegetation index data set, which is mainly aimed at normalized difference vegetation index (NDVI). It includes spectral reflectance of four bands synthesized every 10 days and maximum NDVI for 10 days from 1998 to 2008. The spatial resolution is 1km and the temporal resolution is ten days.
Greet Janssens
The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient number). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN= (NDVI+0.1)/0.004. The dataset is a long-time series vegetation index dataset of Qinghai Lake Basin, which is mainly aimed at normalized difference vegetation index (NDVI). It includes spectral reflectance of four bands synthesized every 10 days from 1998 to 2008 and maximum NDVI for 10 days, with a spatial resolution of 1km and a temporal resolution of 10 days.
Flemish Institute for Technological Research (VITO)
GIMMS (glaobal inventory modelling and mapping studies) NDVI data is the latest global vegetation index change data released by NASA C-J-Tucker and others in November 2003. This dataset is a long-term GIMMS vegetation index dataset of the Qinghai Lake Basin, which includes changes in the vegetation index from 1981 to 2006. The time resolution is 15 days and the spatial resolution is 8 km. GIMMS NDVI data recorded the changes of vegetation in 22a area in the format of satellite data.
National Aeronautics and Space Administration
The data used in this research was provided by the Pathfinder database of the EROS (Earth Resource Observation System) data center. The vegetation index NDVI was prepared by using the NOAA-AVHRR data source after radiation correction and geometric rough correction. Every day, each track image is processed with geometric fine correction, removal of bad lines, and removal of clouds, etc., and then NDVI calculation and synthesis. The daily NDVI calculation formula is: 1000 × (b2-b1) / (b2 + b1), where b1 and b2 are the first and second channels of AVHRR. Parameter table of Pathfinder AVHRR Parameter / Variable Definition Unit Range NDVI Normalized Vegetation Index None (-1,1) CLAVR identification Cloudiness index from CLAVR algorithm None (0,30) QC identification Data quality identification None (0,16) Scanning angle Sensor angle Radian (-1.05, 1.05) Solar zenith angle Solar zenith angle per pixel Radian (0, 1.04) Relative zenith angle Relative zenith angle of the sensor Radian (-1.05, 1.05) Ch1 reflectance Reflectance of the first channel (0.58-0.68um) Percent (0,100) Ch2 reflectance Reflectivity of the second channel (0.72--1.10um) Percentage (0, 100) Ch3 brightness temperature Bright temperature value of the third channel (3.55-3.95um) Kelvin temperature scale (160, 340) Ch4 brightness temperature Brightness value of the fourth channel (10.3-11.3um) Kelvin temperature scale (160, 340) Ch5 brightness temperature Bright temperature value of the fifth channel (11.5-12.5um) Kelvin temperature scale (160, 340) The data set includes data on NDVI in China's sub-regions from 1981 to June-September 2001, and data on tens of months in each of the years 1982, 1986, 1991, and 1996 (a total of 343 in 84 months, of which 1981 in June 1981). Data are missing in January and July 1st, and September 3rd 1994) Dataset attributes and format: This data set is stored in a year folder, which contains .HDR header files, .IMG files, and .JPG image files under the same file name. The data in the IMG is stored as integers. The naming rules are as follows: avhrrpf. *. Intfgl.yymmdd_geo where * represents ch1 or ch2 or ch4 or ch5 or ndvi, please refer to Table 1 for its specific meaning and range; yy represents the last two digits of the year; mm represents the month; dd represents the specific date. Data projection: Size is 963, 688 Coordinate System is: GEOGCS ["WGS 84", DATUM ["WGS_1984", SPHEROID ["WGS 84", 6378137,298.257223563, AUTHORITY ["EPSG", "7030"]], TOWGS84 [0,0,0,0,0,0,0], AUTHORITY ["EPSG", "6326"]], PRIMEM ["Greenwich", 0, AUTHORITY ["EPSG", "8901"]], UNIT ["degree", 0.0174532925199433, AUTHORITY ["EPSG", "9108"]], AUTHORITY ["EPSG", "4326"]] Origin = (70.035426000000001, 54.945585999999999) Pixel Size = (0.072727000000000, -0.072727000000000) Corner Coordinates: Upper Left (70.0354260, 54.9455860) (70d 2'7.53 "E, 54d56'44.11" N) Lower Left (70.0354260, 4.9094100) (70d 2'7.53 "E, 4d54'33.88" N) Upper Right (140.0715270, 54.9455860) (140d 4'17.50 "E, 54d56'44.11" N) Lower Right (140.0715270, 4.9094100) (140d 4'17.50 "E, 4d54'33.88" N) Center (105.0534765, 29.9274980) (105d 3'12.52 "E, 29d55'38.99" N) Band 1 Block = 963x1 Type = UInt16, ColorInterp = Undefined Computed Min / Max = 1.000,55480.000
Tucker, C.J., J.E.Pinzon, M.E.Brown
The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN=(NDVI+0.1)/0.004. The data set is a subset extraction from China, including spectral reflectance of four bands synthesized every 10 days and 10 days' maximum NDVI. It is data from 1998 to 2007 with a spatial resolution of 1km and a temporal resolution of 10 days. File format: Hfr and img files. The file naming rule is: CHN _ NDV _ YYYMMDD, where YYYYMMDD is the date of the day represented by the file and is also the main identifier different from other files. The remote sensing image files with suffix. IMG and. HDF used by users to analyze vegetation index can be opened in ENVI and ERDAS software. Coordinate system and projection Plate_Carree (Lon/Lat) PROJ_CENTER_LON 0.000000 PROJ_CENTER_LAT 0.000000 PIXEL_SIZE_UNITS DEGREES/PIXEL PIXEL_SIZE_X 0.0089285714 PIXEL_SIZE_Y 0.0089285714 SEMI_AXIS_MAJ 6378137.000000 SEMI_AXIS_MIN 6356752.314000 UL_LON (DEG) 73.000000 UL_LAT (DEG) 54.000000 LR_LON (DEG) 135.500000 LR_LAT (DEG) 5.000000 Corner coordinates are: Corner Coordinates: Upper Left ( 69.9955357, 55.0044643) Lower Left ( 69.9955357, 14.9955358) Upper Right ( 137.0044641, 55.0044643) Lower Right ( 137.0044641, 14.9955358) Where Upper Left is the upper left corner, Lower Left is the lower left corner, Upper Right is the upper right corner, and Lower Right is the lower right corner.
Greet Janssens, Food and Agriculture Organization of the United Nations（FAO）
GIMMS (glaobal inventory modelling and mapping studies) NDVI data is the latest global vegetation index change data released by NASA C-J-Tucker and others in November 2003. The dataset includes the global vegetation index changes from 1981 to 2006, the format is ENVI standard format, the projection is ALBERS, and its time resolution is 15 days and its spatial resolution is 8km. GIMMS NDVI data recorded the changes of vegetation in 22a area in the format of satellite data. 1. File format: The GIMMS-NDVI dataset contains all rar compressed files with a 15-day interval from July 1981 to 2006. After decompression, it includes an XML file, an .HDR header file, an .IMG file, and a .JPG image file. 2. File naming: The naming rules for compressed files in the NOAA / AVHRR-NDVI data set are: YYMMM15a (b) .n **-VIg_data_envi.rar, where YY-year, MMM-abbreviated English month letters, 15a-synthesized in the first half of the month, 15b-synthesized in the second half of the month, **-Satellite. After decompression, there are 4 files with the same file name, and the attributes are: XML document, header file (suffix: .HDF), remote sensing image file (suffix: .IMG), and JPEG image file. In this data set, the user uses the remote sensing image file with the suffix .IMG to analyze the vegetation index. Remote sensing image files with suffix of .IMG and .HDF used by users to analyze vegetation indices can be opened in ENVI and ERDAS software. 3. The data header file information is as follows: Coordinate System is: PROJECTION ["Albers_Conic_Equal_Area"], PARAMETER ["standard_parallel_1", 25], PARAMETER ["standard_parallel_2", 47], PARAMETER ["latitude_of_center", 0], PARAMETER ["longitude_of_center", 105], PARAMETER ["false_easting", 0], PARAMETER ["false_northing", 0], UNIT ["Meter", 1]] Pixel Size = (8000.000000000000000, -8000.000000000000000) Corner Coordinates: Upper Left (-3922260.739, 6100362.950) (51d20'23.06 "E, 46d21'21.43" N) Lower Left (-3922260.739, 1540362.950) (71d16'1.22 "E, 8d41'42.21" N) Upper Right (3277739.261, 6100362.950) (151d 8'57.22 "E, 49d 9'35.37" N) Lower Right (3277739.261, 1540362.950) (133d30'58.46 "E, 10d37'13.35" N) Center (-322260.739, 3820362.950) (101d22'21.08 "E, 35d42'18.02" N) Band 1 Block = 900x1 Type = Int16, ColorInterp = Undefined Computed Min / Max = -16066.000,11231.000 4. Conversion relationship between DN value and NDVI NDVI = DN / 1000, divided by 10000 after 2003 The NDVI value should be between [-1,1]. Data outside this interval represent other features, such as water bodies.
Tucker, C.J., J.E.Pinzon, M.E.Brown
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