Search ga_s2am_ard_3 across 2022

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
2022-05-11 11:54:12	ga_s2am_ard_3-2-1_50KNV_2022-05-11_final.stac-item
2022-05-11 11:54:15	ga_s2am_ard_3-2-1_50KMV_2022-05-11_final.stac-item
2022-05-11 11:54:17	ga_s2am_ard_3-2-1_50KQU_2022-05-11_final.stac-item
2022-05-11 11:54:22	ga_s2am_ard_3-2-1_50KPU_2022-05-11_final.stac-item
2022-05-11 11:54:26	ga_s2am_ard_3-2-1_50KNU_2022-05-11_final.stac-item
2022-05-11 11:54:27	ga_s2am_ard_3-2-1_50JQT_2022-05-11_final.stac-item
2022-05-11 11:54:30	ga_s2am_ard_3-2-1_50KMU_2022-05-11_final.stac-item
2022-05-11 11:54:37	ga_s2am_ard_3-2-1_50JPT_2022-05-11_final.stac-item
2022-05-11 11:54:37	ga_s2am_ard_3-2-1_50KLU_2022-05-11_final.stac-item
2022-05-11 11:54:41	ga_s2am_ard_3-2-1_50JNT_2022-05-11_final.stac-item
2022-05-11 11:54:44	ga_s2am_ard_3-2-1_50JMT_2022-05-11_final.stac-item
2022-05-11 11:54:48	ga_s2am_ard_3-2-1_50JLT_2022-05-11_final.stac-item
2022-05-11 11:54:51	ga_s2am_ard_3-2-1_50JPS_2022-05-11_final.stac-item
2022-05-11 11:54:55	ga_s2am_ard_3-2-1_50JNS_2022-05-11_final.stac-item
2022-05-11 11:54:58	ga_s2am_ard_3-2-1_50JMS_2022-05-11_final.stac-item
2022-05-11 11:55:01	ga_s2am_ard_3-2-1_50JLS_2022-05-11_final.stac-item
2022-05-11 11:55:06	ga_s2am_ard_3-2-1_50JPR_2022-05-11_final.stac-item
2022-05-11 11:55:10	ga_s2am_ard_3-2-1_50JNR_2022-05-11_final.stac-item
2022-05-11 11:55:13	ga_s2am_ard_3-2-1_50JMR_2022-05-11_final.stac-item
2022-05-11 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-05-11_final.stac-item
2022-05-11 11:55:19	ga_s2am_ard_3-2-1_50JPQ_2022-05-11_final.stac-item
2022-05-11 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2022-05-11_final.stac-item
2022-05-11 11:55:28	ga_s2am_ard_3-2-1_50JMQ_2022-05-11_final.stac-item
2022-05-11 11:55:30	ga_s2am_ard_3-2-1_50JPP_2022-05-11_final.stac-item
2022-05-11 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-05-11_final.stac-item
2022-05-11 11:55:38	ga_s2am_ard_3-2-1_50JNP_2022-05-11_final.stac-item
2022-05-11 11:55:42	ga_s2am_ard_3-2-1_50JMP_2022-05-11_final.stac-item
2022-05-11 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-05-11_final.stac-item
2022-05-11 11:55:50	ga_s2am_ard_3-2-1_50JKP_2022-05-11_final.stac-item
2022-05-11 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-05-11_final.stac-item
2022-05-11 11:55:57	ga_s2am_ard_3-2-1_50JMN_2022-05-11_final.stac-item
2022-05-11 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-05-11_final.stac-item
2022-05-11 11:56:03	ga_s2am_ard_3-2-1_50JKN_2022-05-11_final.stac-item
2022-05-11 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-05-11_final.stac-item
2022-05-11 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-05-11_final.stac-item
2022-05-11 11:56:15	ga_s2am_ard_3-2-1_50JLM_2022-05-11_final.stac-item
2022-05-11 11:56:17	ga_s2am_ard_3-2-1_50JKM_2022-05-11_final.stac-item
2022-05-11 11:56:22	ga_s2am_ard_3-2-1_50JNL_2022-05-11_final.stac-item
2022-05-11 11:56:26	ga_s2am_ard_3-2-1_50JML_2022-05-11_final.stac-item
2022-05-11 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-05-11_final.stac-item
2022-05-11 11:56:34	ga_s2am_ard_3-2-1_50HNK_2022-05-11_final.stac-item
2022-05-11 11:56:40	ga_s2am_ard_3-2-1_50HMK_2022-05-11_final.stac-item
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final.stac-item
2022-05-11 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2022-05-11_final.stac-item
2022-05-11 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-05-11_final.stac-item
2022-05-11 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-05-11_final.stac-item
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final.stac-item
2022-12-20 12:02:58	ga_s2am_ard_3-2-1_50KLE_2022-12-20_nrt.stac-item
2022-12-20 12:03:00	ga_s2am_ard_3-2-1_50KKE_2022-12-20_nrt.stac-item
2022-12-20 12:03:07	ga_s2am_ard_3-2-1_50KMD_2022-12-20_nrt.stac-item
2022-12-20 12:03:10	ga_s2am_ard_3-2-1_50KLD_2022-12-20_nrt.stac-item
2022-12-20 12:03:13	ga_s2am_ard_3-2-1_50KKD_2022-12-20_nrt.stac-item
2022-12-20 12:03:22	ga_s2am_ard_3-2-1_50KMC_2022-12-20_final.stac-item
2022-12-20 12:03:25	ga_s2am_ard_3-2-1_50KLC_2022-12-20_final.stac-item
2022-12-28 11:23:09	ga_s2am_ard_3-2-1_51KYT_2022-12-28_final.stac-item
2022-12-28 11:23:12	ga_s2am_ard_3-2-1_51KXT_2022-12-28_final.stac-item
2022-12-28 11:23:15	ga_s2am_ard_3-2-1_52KCB_2022-12-28_final.stac-item
2022-12-28 11:23:19	ga_s2am_ard_3-2-1_52KBB_2022-12-28_final.stac-item
2022-12-28 11:23:20	ga_s2am_ard_3-2-1_51KZS_2022-12-28_final.stac-item
2022-12-28 11:23:23	ga_s2am_ard_3-2-1_51KYS_2022-12-28_final.stac-item
2022-12-28 11:23:26	ga_s2am_ard_3-2-1_52KCA_2022-12-28_final.stac-item
2022-12-28 11:23:27	ga_s2am_ard_3-2-1_51KXS_2022-12-28_final.stac-item
2022-12-28 11:23:33	ga_s2am_ard_3-2-1_52KBA_2022-12-28_final.stac-item
2022-12-28 11:23:34	ga_s2am_ard_3-2-1_51KZR_2022-12-28_final.stac-item
2022-12-28 11:23:38	ga_s2am_ard_3-2-1_51KYR_2022-12-28_final.stac-item
2022-12-28 11:23:41	ga_s2am_ard_3-2-1_51KXR_2022-12-28_final.stac-item
2022-12-28 11:23:48	ga_s2am_ard_3-2-1_52KBV_2022-12-28_final.stac-item
2022-12-28 11:23:48	ga_s2am_ard_3-2-1_51KZQ_2022-12-28_final.stac-item
2022-12-28 11:23:52	ga_s2am_ard_3-2-1_51KYQ_2022-12-28_final.stac-item
2022-12-28 11:23:56	ga_s2am_ard_3-2-1_51KXQ_2022-12-28_final.stac-item
2022-12-28 11:24:00	ga_s2am_ard_3-2-1_51KWQ_2022-12-28_final.stac-item
2022-12-28 11:24:03	ga_s2am_ard_3-2-1_51KZP_2022-12-28_final.stac-item
2022-12-28 11:24:03	ga_s2am_ard_3-2-1_52KBU_2022-12-28_final.stac-item
2022-12-28 11:24:07	ga_s2am_ard_3-2-1_51KYP_2022-12-28_final.stac-item
2022-12-28 11:24:10	ga_s2am_ard_3-2-1_51KXP_2022-12-28_final.stac-item
2022-12-28 11:24:13	ga_s2am_ard_3-2-1_51KWP_2022-12-28_final.stac-item
2022-12-28 11:24:17	ga_s2am_ard_3-2-1_51JZN_2022-12-28_final.stac-item
2022-12-28 11:24:17	ga_s2am_ard_3-2-1_52JBT_2022-12-28_final.stac-item
2022-12-28 11:24:21	ga_s2am_ard_3-2-1_51JYN_2022-12-28_final.stac-item
2022-12-28 11:24:25	ga_s2am_ard_3-2-1_51JXN_2022-12-28_final.stac-item
2022-12-28 11:24:28	ga_s2am_ard_3-2-1_51JWN_2022-12-28_final.stac-item
2022-12-28 11:24:31	ga_s2am_ard_3-2-1_51JZM_2022-12-28_final.stac-item
2022-12-28 11:24:31	ga_s2am_ard_3-2-1_52JBS_2022-12-28_final.stac-item
2022-12-28 11:24:35	ga_s2am_ard_3-2-1_51JYM_2022-12-28_final.stac-item
2022-12-28 11:24:39	ga_s2am_ard_3-2-1_51JXM_2022-12-28_final.stac-item
2022-12-28 11:24:42	ga_s2am_ard_3-2-1_52JBR_2022-12-28_final.stac-item
2022-12-28 11:24:42	ga_s2am_ard_3-2-1_51JWM_2022-12-28_final.stac-item
2022-12-28 11:24:46	ga_s2am_ard_3-2-1_51JYL_2022-12-28_final.stac-item
2022-12-28 11:24:47	ga_s2am_ard_3-2-1_52JBR_2022-12-28_final.stac-item
2022-12-28 11:24:48	ga_s2am_ard_3-2-1_51JXL_2022-12-28_final.stac-item
2022-12-28 11:24:48	ga_s2am_ard_3-2-1_51JXM_2022-12-28_final.stac-item
2022-12-28 11:24:49	ga_s2am_ard_3-2-1_51JWL_2022-12-28_final.stac-item
2022-12-28 11:24:49	ga_s2am_ard_3-2-1_51JWM_2022-12-28_final.stac-item
2022-12-28 11:24:53	ga_s2am_ard_3-2-1_51JYL_2022-12-28_final.stac-item
2022-12-28 11:24:55	ga_s2am_ard_3-2-1_51JXL_2022-12-28_final.stac-item
2022-12-28 11:24:57	ga_s2am_ard_3-2-1_51JWL_2022-12-28_final.stac-item
2022-12-28 11:25:02	ga_s2am_ard_3-2-1_51JVL_2022-12-28_final.stac-item
2022-12-28 11:25:04	ga_s2am_ard_3-2-1_51JYK_2022-12-28_final.stac-item
2022-12-28 11:25:08	ga_s2am_ard_3-2-1_51JXK_2022-12-28_final.stac-item
2022-12-28 11:25:12	ga_s2am_ard_3-2-1_51JWK_2022-12-28_final.stac-item

Return to ga_s2am_ard_3 across 2022 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

2022

All months