ndvi_climatology_ls: Monthly NDVI Climatologies produced by Digital Earth Africa.

All years

Monthly NDVI Climatologies produced by Digital Earth Africa.

ndvi_climatology_ls whole collection

Last processed
3,482 datasets
  • 32,089,301km2 (approx.)
  • 3482 unique regions
  • Entirely EPSG:6933

Sources

Metadata (eo3)

Common fields

cloud_cover • collection_category • crs_raw • data_coverage • eo_gsd • eo_sun_azimuth • eo_sun_elevation • format GeoTIFF instrument • label • platform • product_family statistics rmse • rmse_x • rmse_y • sat_orbit_state • sat_relative_orbit •

JSON / GeoJSON

Location 🔗 (samples)

s3://deafrica-services/ndvi_climatology_ls/1-0-0/

Measurements 🔗

nodata
float32 mean_jan / MEAN_JAN / mean_january NaN
float32 mean_feb / MEAN_FEB / mean_february NaN
float32 mean_mar / MEAN_MAR / mean_march NaN
float32 mean_apr / MEAN_APR / mean_april NaN
float32 mean_may / MEAN_MAY NaN
float32 mean_jun / MEAN_JUN / mean_june NaN
float32 mean_jul / MEAN_JUL / mean_july NaN
float32 mean_aug / MEAN_AUG / mean_august NaN
float32 mean_sep / MEAN_SEP / mean_september NaN
float32 mean_oct / MEAN_OCT / mean_october NaN
float32 mean_nov / MEAN_NOV / mean_november NaN
float32 mean_dec / MEAN_DEC / mean_december NaN
float32 stddev_jan / STDDEV_JAN / stddev_january NaN
float32 stddev_feb / STDDEV_FEB / stddev_feburary NaN
float32 stddev_mar / STDDEV_MAR / stddev_march NaN
float32 stddev_apr / STDDEV_APR / stddev_april NaN
float32 stddev_may / STDDEV_MAY NaN
float32 stddev_jun / STDDEV_JUN / stddev_june NaN
float32 stddev_jul / STDDEV_JUL / stddev_july NaN
float32 stddev_aug / STDDEV_AUG / stddev_august NaN
float32 stddev_sep / STDDEV_SEP / stddev_september NaN
float32 stddev_oct / STDDEV_OCT / stddev_october NaN
float32 stddev_nov / STDDEV_NOV / stddev_november NaN
float32 stddev_dec / STDDEV_DEC / stddev_december NaN
int16 count_jan / COUNT_JAN / count_january -999
int16 count_feb / COUNT_FEB / count_february -999
int16 count_mar / COUNT_MAR / count_march -999
int16 count_apr / COUNT_APR / count_april -999
int16 count_may / COUNT_MAY -999
int16 count_jun / COUNT_JUN / count_june -999
int16 count_jul / COUNT_JUL / count_july -999
int16 count_aug / COUNT_AUG / count_august -999
int16 count_sep / COUNT_SEP / count_september -999
int16 count_oct / COUNT_OCT / count_october -999
int16 count_nov / COUNT_NOV / count_november -999
int16 count_dec / COUNT_DEC / count_december -999

Total: 36

Storage Parameters 🔗

crs EPSG:6933 resolution x 30 y -30

Definition 🔗

RAW As Stac
name: ndvi_climatology_ls
license: CC-BY-4.0
metadata_type: eo3
description: Monthly NDVI Climatologies produced by Digital Earth Africa.
metadata:
product:
name: ndvi_climatology_ls
measurements:
[ [36 items...]
name: mean_jan
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_JAN
mean_january
]
,
name: mean_feb
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_FEB
mean_february
]
,
name: mean_mar
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_MAR
mean_march
]
,
name: mean_apr
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_APR
mean_april
]
,
name: mean_may
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_MAY
]
,
name: mean_jun
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_JUN
mean_june
]
,
name: mean_jul
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_JUL
mean_july
]
,
name: mean_aug
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_AUG
mean_august
]
,
name: mean_sep
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_SEP
mean_september
]
,
name: mean_oct
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_OCT
mean_october
]
,
name: mean_nov
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_NOV
mean_november
]
,
name: mean_dec
dtype: float32
units: 1
nodata: NaN
aliases: [
MEAN_DEC
mean_december
]
,
name: stddev_jan
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_JAN
stddev_january
]
,
name: stddev_feb
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_FEB
stddev_feburary
]
,
name: stddev_mar
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_MAR
stddev_march
]
,
name: stddev_apr
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_APR
stddev_april
]
,
name: stddev_may
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_MAY
]
,
name: stddev_jun
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_JUN
stddev_june
]
,
name: stddev_jul
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_JUL
stddev_july
]
,
name: stddev_aug
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_AUG
stddev_august
]
,
name: stddev_sep
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_SEP
stddev_september
]
,
name: stddev_oct
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_OCT
stddev_october
]
,
name: stddev_nov
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_NOV
stddev_november
]
,
name: stddev_dec
dtype: float32
units: 1
nodata: NaN
aliases: [
STDDEV_DEC
stddev_december
]
,
name: count_jan
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_JAN
count_january
]
,
name: count_feb
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_FEB
count_february
]
,
name: count_mar
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_MAR
count_march
]
,
name: count_apr
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_APR
count_april
]
,
name: count_may
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_MAY
]
,
name: count_jun
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_JUN
count_june
]
,
name: count_jul
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_JUL
count_july
]
,
name: count_aug
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_AUG
count_august
]
,
name: count_sep
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_SEP
count_september
]
,
name: count_oct
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_OCT
count_october
]
,
name: count_nov
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_NOV
count_november
]
,
name: count_dec
dtype: int16
units: 1
nodata: -999
aliases: [
COUNT_DEC
count_december
]
,
]
storage:
crs: EPSG:6933
resolution:
x: 30
y: -30