Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2023-01-16 10:12:25	ga_s2am_ard_3-2-1_54KXD_2023-01-16_final.stac-item
2023-01-16 10:12:32	ga_s2am_ard_3-2-1_54KZC_2023-01-16_final.stac-item
2023-01-16 10:12:36	ga_s2am_ard_3-2-1_54KYC_2023-01-16_final.stac-item
2023-01-16 10:12:39	ga_s2am_ard_3-2-1_54KXC_2023-01-16_final.stac-item
2023-01-16 10:12:47	ga_s2am_ard_3-2-1_54KZB_2023-01-16_final.stac-item
2023-01-16 10:12:51	ga_s2am_ard_3-2-1_54KYB_2023-01-16_final.stac-item
2023-01-16 10:12:54	ga_s2am_ard_3-2-1_54KXB_2023-01-16_final.stac-item
2023-01-16 10:13:00	ga_s2am_ard_3-2-1_54KWB_2023-01-16_final.stac-item
2023-01-16 10:13:01	ga_s2am_ard_3-2-1_55KBR_2023-01-16_final.stac-item
2023-01-16 10:13:01	ga_s2am_ard_3-2-1_54KZA_2023-01-16_final.stac-item
2023-01-16 10:13:05	ga_s2am_ard_3-2-1_54KYA_2023-01-16_final.stac-item
2023-01-16 10:13:08	ga_s2am_ard_3-2-1_54KXA_2023-01-16_final.stac-item
2023-01-16 10:13:12	ga_s2am_ard_3-2-1_54KWA_2023-01-16_final.stac-item
2023-01-16 10:13:15	ga_s2am_ard_3-2-1_55KBQ_2023-01-16_final.stac-item
2023-01-16 10:13:16	ga_s2am_ard_3-2-1_54KZV_2023-01-16_final.stac-item
2023-01-16 10:13:19	ga_s2am_ard_3-2-1_54KYV_2023-01-16_final.stac-item
2023-01-16 10:13:23	ga_s2am_ard_3-2-1_54KXV_2023-01-16_final.stac-item
2023-01-16 10:13:26	ga_s2am_ard_3-2-1_54KWV_2023-01-16_final.stac-item
2023-01-16 10:13:29	ga_s2am_ard_3-2-1_55KBP_2023-01-16_final.stac-item
2023-01-16 10:13:30	ga_s2am_ard_3-2-1_54KZU_2023-01-16_final.stac-item
2023-01-16 10:13:34	ga_s2am_ard_3-2-1_54KYU_2023-01-16_final.stac-item
2023-01-16 10:13:37	ga_s2am_ard_3-2-1_54KXU_2023-01-16_final.stac-item
2023-01-16 10:13:41	ga_s2am_ard_3-2-1_55JBN_2023-01-16_final.stac-item
2023-01-16 10:13:41	ga_s2am_ard_3-2-1_54KWU_2023-01-16_final.stac-item
2023-01-16 10:13:42	ga_s2am_ard_3-2-1_54JZT_2023-01-16_final.stac-item
2023-01-16 10:13:48	ga_s2am_ard_3-2-1_54JYT_2023-01-16_final.stac-item
2023-01-16 10:13:52	ga_s2am_ard_3-2-1_54JXT_2023-01-16_final.stac-item
2023-01-16 10:13:56	ga_s2am_ard_3-2-1_54JWT_2023-01-16_final.stac-item
2023-01-16 10:14:02	ga_s2am_ard_3-2-1_54JVT_2023-01-16_final.stac-item
2023-01-16 10:14:02	ga_s2am_ard_3-2-1_54JYS_2023-01-16_final.stac-item
2023-01-16 10:14:06	ga_s2am_ard_3-2-1_54JXS_2023-01-16_final.stac-item
2023-01-16 10:14:08	ga_s2am_ard_3-2-1_54JWS_2023-01-16_final.stac-item
2023-01-16 10:14:10	ga_s2am_ard_3-2-1_54JVS_2023-01-16_final.stac-item
2023-01-16 10:14:11	ga_s2am_ard_3-2-1_54JYS_2023-01-16_final.stac-item
2023-01-16 10:14:11	ga_s2am_ard_3-2-1_54JYR_2023-01-16_final.stac-item
2023-01-16 10:14:13	ga_s2am_ard_3-2-1_54JXR_2023-01-16_final.stac-item
2023-01-16 10:14:13	ga_s2am_ard_3-2-1_54JXS_2023-01-16_final.stac-item
2023-01-16 10:14:14	ga_s2am_ard_3-2-1_54JWS_2023-01-16_final.stac-item
2023-01-16 10:14:16	ga_s2am_ard_3-2-1_54JVS_2023-01-16_final.stac-item
2023-01-16 10:14:18	ga_s2am_ard_3-2-1_54JYR_2023-01-16_final.stac-item
2023-01-16 10:14:21	ga_s2am_ard_3-2-1_54JXR_2023-01-16_final.stac-item
2023-01-16 10:14:24	ga_s2am_ard_3-2-1_54JWR_2023-01-16_final.stac-item
2023-01-16 10:14:27	ga_s2am_ard_3-2-1_54JVR_2023-01-16_final.stac-item
2023-01-16 10:14:31	ga_s2am_ard_3-2-1_54JYQ_2023-01-16_final.stac-item
2023-01-16 10:14:35	ga_s2am_ard_3-2-1_54JXQ_2023-01-16_final.stac-item
2023-01-16 10:14:39	ga_s2am_ard_3-2-1_54JWQ_2023-01-16_final.stac-item
2023-01-16 10:14:42	ga_s2am_ard_3-2-1_54JVQ_2023-01-16_final.stac-item
2023-01-16 10:14:44	ga_s2am_ard_3-2-1_54JYP_2023-01-16_final.stac-item
2023-01-16 10:14:50	ga_s2am_ard_3-2-1_54JXP_2023-01-16_final.stac-item
2023-01-16 10:14:53	ga_s2am_ard_3-2-1_54JWP_2023-01-16_final.stac-item
2023-01-16 10:14:54	ga_s2am_ard_3-2-1_54JYN_2023-01-16_final.stac-item
2023-01-16 10:14:57	ga_s2am_ard_3-2-1_54JVP_2023-01-16_final.stac-item
2023-01-16 10:15:04	ga_s2am_ard_3-2-1_54JXN_2023-01-16_final.stac-item
2023-01-16 10:15:04	ga_s2am_ard_3-2-1_54JUP_2023-01-16_final.stac-item
2023-01-16 10:15:08	ga_s2am_ard_3-2-1_54JWN_2023-01-16_final.stac-item
2023-01-16 10:15:11	ga_s2am_ard_3-2-1_54JVN_2023-01-16_final.stac-item
2023-01-16 10:15:15	ga_s2am_ard_3-2-1_54JUN_2023-01-16_final.stac-item
2023-01-16 10:15:19	ga_s2am_ard_3-2-1_54JXM_2023-01-16_final.stac-item
2023-01-16 10:15:22	ga_s2am_ard_3-2-1_54JWM_2023-01-16_final.stac-item
2023-01-16 10:15:26	ga_s2am_ard_3-2-1_54JVM_2023-01-16_final.stac-item
2023-01-16 10:15:29	ga_s2am_ard_3-2-1_54JUM_2023-01-16_final.stac-item
2023-01-16 10:15:33	ga_s2am_ard_3-2-1_54JXL_2023-01-16_final.stac-item
2023-01-16 10:15:37	ga_s2am_ard_3-2-1_54JWL_2023-01-16_final.stac-item
2023-01-16 10:15:41	ga_s2am_ard_3-2-1_54JVL_2023-01-16_final.stac-item
2023-01-16 10:15:44	ga_s2am_ard_3-2-1_54JUL_2023-01-16_final.stac-item
2023-01-16 10:15:46	ga_s2am_ard_3-2-1_54HXK_2023-01-16_final.stac-item
2023-01-16 10:15:51	ga_s2am_ard_3-2-1_54HWK_2023-01-16_final.stac-item
2023-01-16 10:15:55	ga_s2am_ard_3-2-1_54HVK_2023-01-16_final.stac-item
2023-01-16 10:15:57	ga_s2am_ard_3-2-1_54HXJ_2023-01-16_final.stac-item
2023-01-16 10:15:58	ga_s2am_ard_3-2-1_54HUK_2023-01-16_final.stac-item
2023-01-16 10:16:06	ga_s2am_ard_3-2-1_54HWJ_2023-01-16_final.stac-item
2023-01-16 10:16:10	ga_s2am_ard_3-2-1_54HVJ_2023-01-16_final.stac-item
2023-01-16 10:16:13	ga_s2am_ard_3-2-1_54HUJ_2023-01-16_final.stac-item
2023-01-16 10:16:17	ga_s2am_ard_3-2-1_54HTJ_2023-01-16_final.stac-item
2023-01-16 10:16:20	ga_s2am_ard_3-2-1_54HWH_2023-01-16_final.stac-item
2023-01-16 10:16:24	ga_s2am_ard_3-2-1_54HVH_2023-01-16_final.stac-item
2023-01-16 10:16:27	ga_s2am_ard_3-2-1_54HUH_2023-01-16_final.stac-item
2023-01-16 10:16:30	ga_s2am_ard_3-2-1_54HTH_2023-01-16_final.stac-item
2023-01-16 10:16:35	ga_s2am_ard_3-2-1_54HWG_2023-01-16_final.stac-item
2023-01-16 10:16:39	ga_s2am_ard_3-2-1_54HVG_2023-01-16_final.stac-item
2023-01-16 10:16:42	ga_s2am_ard_3-2-1_54HUG_2023-01-16_final.stac-item
2023-01-16 10:16:45	ga_s2am_ard_3-2-1_54HTG_2023-01-16_final.stac-item
2023-01-16 10:16:48	ga_s2am_ard_3-2-1_53HQB_2023-01-16_final.stac-item
2023-01-16 10:16:49	ga_s2am_ard_3-2-1_54HWF_2023-01-16_final.stac-item
2023-01-16 10:16:53	ga_s2am_ard_3-2-1_54HVF_2023-01-16_final.stac-item
2023-01-16 10:16:57	ga_s2am_ard_3-2-1_54HUF_2023-01-16_final.stac-item
2023-01-16 10:17:00	ga_s2am_ard_3-2-1_54HTF_2023-01-16_final.stac-item
2023-01-16 10:17:00	ga_s2am_ard_3-2-1_54HWE_2023-01-16_final.stac-item
2023-01-16 10:17:01	ga_s2am_ard_3-2-1_53HQA_2023-01-16_final.stac-item
2023-01-16 10:17:07	ga_s2am_ard_3-2-1_54HVE_2023-01-16_final.stac-item
2023-01-16 10:17:11	ga_s2am_ard_3-2-1_54HUE_2023-01-16_final
2023-01-16 10:17:22	ga_s2am_ard_3-2-1_54HVD_2023-01-16_final.stac-item
2023-01-16 10:17:26	ga_s2am_ard_3-2-1_54HUD_2023-01-16_final
2023-01-16 10:17:29	ga_s2am_ard_3-2-1_54HTD_2023-01-16_nrt.stac-item
2023-01-16 10:17:30	ga_s2am_ard_3-2-1_53HQU_2023-01-16_nrt.stac-item
2023-01-16 10:17:34	ga_s2am_ard_3-2-1_54HVC_2023-01-16_final
2023-01-16 10:17:36	ga_s2am_ard_3-2-1_54HUC_2023-01-16_nrt.stac-item
2023-01-16 10:17:37	ga_s2am_ard_3-2-1_53HPU_2023-01-16_nrt.stac-item
2023-01-16 10:17:37	ga_s2am_ard_3-2-1_54HTC_2023-01-16_nrt.stac-item
2023-01-16 10:17:38	ga_s2am_ard_3-2-1_53HQT_2023-01-16_nrt.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years