1 km 16 days EVI
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 1 km 16 days EVI name : 1 km 16 days EVI units : EVI
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
1 km 16 days NDVI
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 1 km 16 days NDVI name : 1 km 16 days NDVI units : NDVI
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
1 km 16 days VI Quality
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 1 km 16 days VI Quality name : 1 km 16 days VI Quality units : bit field
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
ET_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MODIS Gridded 500m 8-day Composite Evapotranspiration (ET) name : ET_500m units : kg/m^2/8day
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
ET_QC_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : ET_QC_500m name : ET_QC_500m units : none
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
FparExtra_QC
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra+Aqua pass-through QC for FPAR and LAI (8-day composite) name : FparExtra_QC units : class-flag
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
FparLai_QC
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra+Aqua QC for FPAR and LAI (8-day composite) name : FparLai_QC units : class-flag
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
FparStdDev_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra Gridded 500M Standard Deviation FPAR (8-day composite) name : FparStdDev_500m units : Percent
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
Fpar_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra Gridded 500M FPAR (8-day composite) name : Fpar_500m units : Percent
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
LE_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MODIS Gridded 500m 8-day Composite latent heat flux (LE) name : LE_500m units : J/m^2/day
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
LST_Day_1km
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Daily daytime 1km grid Land-surface Temperature name : LST_Day_1km units : K
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
LST_Night_1km
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Daily nighttime 1km grid Land-surface Temperature name : LST_Night_1km units : K
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
LaiStdDev_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra Gridded 500M Standard Deviation Leaf Area Index (8-day composite) name : LaiStdDev_500m units : m^2/m^2
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
Lai_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MOD15A2H MODIS/Terra Gridded 500M Leaf Area Index LAI (8-day composite) name : Lai_500m units : m^2/m^2
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
PET_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MODIS Gridded 500m 8-day Composite potential Evapotranspiration (ET) name : PET_500m units : kg/m^2/8day
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
PLE_500m
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : MODIS Gridded 500m 8-day Composite potential latent heat flux (LE) name : PLE_500m units : J/m^2/day
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
QC_Day
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Quality control for daytime LST and emissivity name : QC_Day
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
QC_Night
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Quality control for nighttime LST and emissivity name : QC_Night
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
aspect_max
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
aspect_mean
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
aspect_min
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
aspect_std
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
burned_areas
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
clc_2006
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
RepresentationType : THEMATIC STATISTICS_COVARIANCES : 134.7975361912512 STATISTICS_MAXIMUM : 48 STATISTICS_MEAN : 25.790668746788 STATISTICS_MINIMUM : 1 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 11.610234114403 name : clc_2006
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
clc_2012
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
RepresentationType : THEMATIC STATISTICS_COVARIANCES : 135.8886173847565 STATISTICS_MAXIMUM : 48 STATISTICS_MEAN : 25.733156200754 STATISTICS_MINIMUM : 1 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 11.65712732129 name : clc_2012
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
clc_2018
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
RepresentationType : THEMATIC STATISTICS_COVARIANCES : 136.429646247598 STATISTICS_MAXIMUM : 48 STATISTICS_MEAN : 25.753373398066 STATISTICS_MINIMUM : 1 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 11.680310194836 name : clc_2018
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
dem_max
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
BandName : Band_1 RepresentationType : ATHEMATIC STATISTICS_COVARIANCES : 170299.0228961734 STATISTICS_MAXIMUM : 2905.8544921875 STATISTICS_MEAN : 430.74131537734 STATISTICS_MINIMUM : -36.388916015625 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 412.67302176926 long_name : Band_1 name : dem_max
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
dem_mean
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
BandName : Band_1 RepresentationType : ATHEMATIC STATISTICS_COVARIANCES : 170299.0228961734 STATISTICS_MAXIMUM : 2905.8544921875 STATISTICS_MEAN : 430.74131537734 STATISTICS_MINIMUM : -36.388916015625 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 412.67302176926 long_name : Band_1 name : dem_mean
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
dem_min
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
BandName : Band_1 RepresentationType : ATHEMATIC STATISTICS_COVARIANCES : 170299.0228961734 STATISTICS_MAXIMUM : 2905.8544921875 STATISTICS_MEAN : 430.74131537734 STATISTICS_MINIMUM : -36.388916015625 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 412.67302176926 long_name : Band_1 name : dem_min
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
dem_std
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
BandName : Band_1 RepresentationType : ATHEMATIC STATISTICS_COVARIANCES : 170299.0228961734 STATISTICS_MAXIMUM : 2905.8544921875 STATISTICS_MEAN : 430.74131537734 STATISTICS_MINIMUM : -36.388916015625 STATISTICS_SKIPFACTORX : 1 STATISTICS_SKIPFACTORY : 1 STATISTICS_STDDEV : 412.67302176926 long_name : Band_1 name : dem_std
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
era5_max_t2m
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 2 metre temperature name : era5_max_t2m units : K
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_max_tp
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Total precipitation name : era5_max_tp units : m
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_max_u10
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 10 metre U wind component name : era5_max_u10 units : m s**-1
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_max_v10
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 10 metre V wind component name : era5_max_v10 units : m s**-1
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_min_t2m
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 2 metre temperature name : era5_min_t2m units : K
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_min_tp
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : Total precipitation name : era5_min_tp units : m
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_min_u10
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 10 metre U wind component name : era5_min_u10 units : m s**-1
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
era5_min_v10
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
long_name : 10 metre V wind component name : era5_min_v10 units : m s**-1
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
fwi
(time, y, x)
float32
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
name : fwi title : Fire Weather Index units : -
Array Chunk
Bytes 6.32 GiB 2.75 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float32 numpy.ndarray
700
562
4314
ignition_points
(time, y, x)
float64
dask.array<chunksize=(288, 50, 50), meta=np.ndarray>
Array Chunk
Bytes 12.64 GiB 5.49 MiB
Shape (4314, 562, 700) (288, 50, 50)
Count 2521 Tasks 2520 Chunks
Type float64 numpy.ndarray
700
562
4314
number_of_fires
(time)
int64
dask.array<chunksize=(288,), meta=np.ndarray>
Array Chunk
Bytes 33.70 kiB 2.25 kiB
Shape (4314,) (288,)
Count 16 Tasks 15 Chunks
Type int64 numpy.ndarray
4314
1
population_density_2009
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30021.15234375 STATISTICS_MEAN : 82.238914394041 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 671.48598504916 name : population_density_2009
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2010
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30363.30859375 STATISTICS_MEAN : 82.147479667057 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 671.88602769617 name : population_density_2010
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2011
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30233.619140625 STATISTICS_MEAN : 82.027437460922 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 670.9042302745 name : population_density_2011
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2012
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30224.205078125 STATISTICS_MEAN : 82.107784707183 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 690.0772575156 name : population_density_2012
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2013
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 29517.470703125 STATISTICS_MEAN : 81.931516848424 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 687.19612524192 name : population_density_2013
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2014
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30178.935546875 STATISTICS_MEAN : 81.840487639716 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 686.75219541252 name : population_density_2014
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2015
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 29919.798828125 STATISTICS_MEAN : 81.714012872504 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 684.62444513266 name : population_density_2015
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2016
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30245.38671875 STATISTICS_MEAN : 81.694480644465 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 687.63942943867 name : population_density_2016
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2017
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30296.751953125 STATISTICS_MEAN : 81.73828589391 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 687.54544893798 name : population_density_2017
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2018
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 30178.298828125 STATISTICS_MEAN : 81.510859548732 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 685.82322299114 name : population_density_2018
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2019
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 29704.583984375 STATISTICS_MEAN : 81.406228331852 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 682.22370306917 name : population_density_2019
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
population_density_2020
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
STATISTICS_MAXIMUM : 29829.5859375 STATISTICS_MEAN : 81.333684900144 STATISTICS_MINIMUM : 0 STATISTICS_STDDEV : 681.53318412642 name : population_density_2020
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
roads_density_2020
(y, x)
float64
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 3.00 MiB 19.53 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float64 numpy.ndarray
700
562
slope_max
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
slope_mean
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
slope_min
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562
slope_std
(y, x)
float32
dask.array<chunksize=(50, 50), meta=np.ndarray>
Array Chunk
Bytes 1.50 MiB 9.77 kiB
Shape (562, 700) (50, 50)
Count 169 Tasks 168 Chunks
Type float32 numpy.ndarray
700
562