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
2022-04-13 10:55:41	ga_s2am_ard_3-2-1_53JKG_2022-04-13_final.stac-item
2022-04-13 10:55:56	ga_s2am_ard_3-2-1_53JKF_2022-04-13_final.stac-item
2022-04-14 10:19:41	ga_s2am_ard_3-2-1_54LZQ_2022-04-14_final.stac-item
2022-04-14 10:19:55	ga_s2am_ard_3-2-1_54LZP_2022-04-14_final.stac-item
2022-04-14 10:20:09	ga_s2am_ard_3-2-1_54LZN_2022-04-14_final.stac-item
2022-04-14 10:20:24	ga_s2am_ard_3-2-1_54LZM_2022-04-14_final.stac-item
2022-04-14 10:20:38	ga_s2am_ard_3-2-1_54LZL_2022-04-14_final.stac-item
2022-04-14 10:21:47	ga_s2am_ard_3-2-1_54KWG_2022-04-14_final.stac-item
2022-04-14 10:21:50	ga_s2am_ard_3-2-1_54KVG_2022-04-14_final.stac-item
2022-04-14 10:22:01	ga_s2am_ard_3-2-1_54KWF_2022-04-14_final.stac-item
2022-04-14 10:22:04	ga_s2am_ard_3-2-1_54KVF_2022-04-14_final.stac-item
2022-04-14 10:22:16	ga_s2am_ard_3-2-1_54KWE_2022-04-14_final.stac-item
2022-04-14 10:22:19	ga_s2am_ard_3-2-1_54KVE_2022-04-14_final.stac-item
2022-04-14 10:22:26	ga_s2am_ard_3-2-1_54KUE_2022-04-14_final.stac-item
2022-04-14 10:22:30	ga_s2am_ard_3-2-1_54KWD_2022-04-14_final.stac-item
2022-04-14 10:22:34	ga_s2am_ard_3-2-1_54KVD_2022-04-14_final.stac-item
2022-04-14 10:22:37	ga_s2am_ard_3-2-1_54KUD_2022-04-14_final.stac-item
2022-04-14 10:22:41	ga_s2am_ard_3-2-1_54KXC_2022-04-14_final.stac-item
2022-04-14 10:22:45	ga_s2am_ard_3-2-1_54KWC_2022-04-14_final.stac-item
2022-04-14 10:22:48	ga_s2am_ard_3-2-1_54KVC_2022-04-14_final.stac-item
2022-04-14 10:22:51	ga_s2am_ard_3-2-1_54KUC_2022-04-14_final.stac-item
2022-04-14 10:22:56	ga_s2am_ard_3-2-1_54KXB_2022-04-14_final.stac-item
2022-04-14 10:22:59	ga_s2am_ard_3-2-1_54KWB_2022-04-14_final.stac-item
2022-04-14 10:23:03	ga_s2am_ard_3-2-1_54KVB_2022-04-14_final.stac-item
2022-04-14 10:23:06	ga_s2am_ard_3-2-1_54KUB_2022-04-14_final.stac-item
2022-04-14 10:23:09	ga_s2am_ard_3-2-1_54KXA_2022-04-14_final.stac-item
2022-04-14 10:23:14	ga_s2am_ard_3-2-1_54KWA_2022-04-14_final.stac-item
2022-04-14 10:23:17	ga_s2am_ard_3-2-1_54KVA_2022-04-14_final.stac-item
2022-04-14 10:23:20	ga_s2am_ard_3-2-1_54KUA_2022-04-14_final.stac-item
2022-04-14 10:23:28	ga_s2am_ard_3-2-1_54KWV_2022-04-14_final.stac-item
2022-04-14 10:23:32	ga_s2am_ard_3-2-1_54KVV_2022-04-14_final.stac-item
2022-04-14 10:23:35	ga_s2am_ard_3-2-1_54KUV_2022-04-14_final.stac-item
2022-04-14 10:23:40	ga_s2am_ard_3-2-1_54KTV_2022-04-14_final.stac-item
2022-04-14 10:23:43	ga_s2am_ard_3-2-1_53KRQ_2022-04-14_final.stac-item
2022-04-14 10:23:43	ga_s2am_ard_3-2-1_54KWU_2022-04-14_final.stac-item
2022-04-14 10:23:46	ga_s2am_ard_3-2-1_54KVU_2022-04-14_final.stac-item
2022-04-14 10:23:49	ga_s2am_ard_3-2-1_54KUU_2022-04-14_final.stac-item
2022-04-14 10:23:53	ga_s2am_ard_3-2-1_54KTU_2022-04-14_final.stac-item
2022-04-14 10:23:53	ga_s2am_ard_3-2-1_53KRP_2022-04-14_final.stac-item
2022-04-14 10:23:57	ga_s2am_ard_3-2-1_54JWT_2022-04-14_final.stac-item
2022-04-14 10:24:01	ga_s2am_ard_3-2-1_54JVT_2022-04-14_final.stac-item
2022-04-14 10:24:04	ga_s2am_ard_3-2-1_54JUT_2022-04-14_final.stac-item
2022-04-14 10:24:07	ga_s2am_ard_3-2-1_53JRN_2022-04-14_final.stac-item
2022-04-14 10:24:07	ga_s2am_ard_3-2-1_54JTT_2022-04-14_final.stac-item
2022-04-14 10:24:11	ga_s2am_ard_3-2-1_54JWS_2022-04-14_final.stac-item
2022-04-14 10:24:15	ga_s2am_ard_3-2-1_54JVS_2022-04-14_final.stac-item
2022-04-14 10:24:19	ga_s2am_ard_3-2-1_54JUS_2022-04-14_final.stac-item
2022-04-14 10:24:21	ga_s2am_ard_3-2-1_53JRM_2022-04-14_final.stac-item
2022-04-14 10:24:22	ga_s2am_ard_3-2-1_54JTS_2022-04-14_final.stac-item
2022-04-14 10:24:24	ga_s2am_ard_3-2-1_54JWR_2022-04-14_final.stac-item
2022-04-14 10:24:30	ga_s2am_ard_3-2-1_54JVR_2022-04-14_final.stac-item
2022-04-14 10:24:33	ga_s2am_ard_3-2-1_54JUR_2022-04-14_final.stac-item
2022-04-14 10:24:36	ga_s2am_ard_3-2-1_54JTR_2022-04-14_final.stac-item
2022-04-14 10:24:43	ga_s2am_ard_3-2-1_53JQL_2022-04-14_final.stac-item
2022-04-14 10:24:44	ga_s2am_ard_3-2-1_54JVQ_2022-04-14_final.stac-item
2022-04-14 10:24:48	ga_s2am_ard_3-2-1_54JUQ_2022-04-14_final.stac-item
2022-04-14 10:24:51	ga_s2am_ard_3-2-1_54JTQ_2022-04-14_final.stac-item
2022-04-14 10:24:54	ga_s2am_ard_3-2-1_53JQK_2022-04-14_final.stac-item
2022-04-14 10:24:59	ga_s2am_ard_3-2-1_54JVP_2022-04-14_final.stac-item
2022-04-14 10:25:02	ga_s2am_ard_3-2-1_54JUP_2022-04-14_final.stac-item
2022-04-14 10:25:05	ga_s2am_ard_3-2-1_54JTP_2022-04-14_final.stac-item
2022-04-14 10:25:08	ga_s2am_ard_3-2-1_53JQJ_2022-04-14_final.stac-item
2022-04-14 10:25:13	ga_s2am_ard_3-2-1_54JVN_2022-04-14_final.stac-item
2022-04-14 10:25:17	ga_s2am_ard_3-2-1_54JUN_2022-04-14_final.stac-item
2022-04-14 10:25:20	ga_s2am_ard_3-2-1_54JTN_2022-04-14_final.stac-item
2022-04-14 10:25:23	ga_s2am_ard_3-2-1_53JQH_2022-04-14_final.stac-item
2022-04-14 10:25:27	ga_s2am_ard_3-2-1_54JVM_2022-04-14_final.stac-item
2022-04-14 10:25:31	ga_s2am_ard_3-2-1_54JUM_2022-04-14_final.stac-item
2022-04-14 10:25:35	ga_s2am_ard_3-2-1_54JTM_2022-04-14_final.stac-item
2022-04-14 10:25:37	ga_s2am_ard_3-2-1_53JQG_2022-04-14_final.stac-item
2022-04-14 10:25:38	ga_s2am_ard_3-2-1_54JVL_2022-04-14_final.stac-item
2022-04-14 10:25:43	ga_s2am_ard_3-2-1_53JPG_2022-04-14_final.stac-item
2022-04-14 10:25:46	ga_s2am_ard_3-2-1_54JUL_2022-04-14_final.stac-item
2022-04-14 10:25:49	ga_s2am_ard_3-2-1_54JTL_2022-04-14_final.stac-item
2022-04-14 10:25:52	ga_s2am_ard_3-2-1_53JQF_2022-04-14_final.stac-item
2022-04-14 10:25:55	ga_s2am_ard_3-2-1_53JPF_2022-04-14_final.stac-item
2022-04-14 10:26:00	ga_s2am_ard_3-2-1_54HUK_2022-04-14_final.stac-item
2022-04-14 10:26:04	ga_s2am_ard_3-2-1_54HTK_2022-04-14_final.stac-item
2022-04-14 10:26:06	ga_s2am_ard_3-2-1_53HQE_2022-04-14_final.stac-item
2022-04-14 10:26:10	ga_s2am_ard_3-2-1_53HPE_2022-04-14_final.stac-item
2022-04-14 10:26:15	ga_s2am_ard_3-2-1_54HUJ_2022-04-14_final.stac-item
2022-04-14 10:26:18	ga_s2am_ard_3-2-1_54HTJ_2022-04-14_final.stac-item
2022-04-14 10:26:21	ga_s2am_ard_3-2-1_53HQD_2022-04-14_final.stac-item
2022-04-14 10:26:24	ga_s2am_ard_3-2-1_53HPD_2022-04-14_final.stac-item
2022-04-14 10:26:30	ga_s2am_ard_3-2-1_54HUH_2022-04-14_final.stac-item
2022-04-14 10:26:33	ga_s2am_ard_3-2-1_54HTH_2022-04-14_final.stac-item
2022-04-14 10:26:35	ga_s2am_ard_3-2-1_53HQC_2022-04-14_final.stac-item
2022-04-14 10:26:39	ga_s2am_ard_3-2-1_53HPC_2022-04-14_final.stac-item
2022-04-14 10:26:43	ga_s2am_ard_3-2-1_54HUG_2022-04-14_final.stac-item
2022-04-14 10:26:43	ga_s2am_ard_3-2-1_53HNC_2022-04-14_final.stac-item
2022-04-14 10:26:47	ga_s2am_ard_3-2-1_54HTG_2022-04-14_final.stac-item
2022-04-14 10:26:49	ga_s2am_ard_3-2-1_53HQB_2022-04-14_final.stac-item
2022-04-14 10:26:53	ga_s2am_ard_3-2-1_53HPB_2022-04-14_final.stac-item
2022-04-14 10:26:53	ga_s2am_ard_3-2-1_54HUF_2022-04-14_final.stac-item
2022-04-14 10:26:57	ga_s2am_ard_3-2-1_53HNB_2022-04-14_final.stac-item
2022-04-14 10:27:02	ga_s2am_ard_3-2-1_54HTF_2022-04-14_final.stac-item
2022-04-14 10:27:04	ga_s2am_ard_3-2-1_53HQA_2022-04-14_final.stac-item
2022-04-14 10:27:08	ga_s2am_ard_3-2-1_53HPA_2022-04-14_final.stac-item
2022-04-14 10:27:15	ga_s2am_ard_3-2-1_54HTE_2022-04-14_final
2022-04-14 10:27:16	ga_s2am_ard_3-2-1_53HQV_2022-04-14_final

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

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