Search ga_s2am_ard_3 whole collection

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

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

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

ID of a dataset type:

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

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

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

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

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

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

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

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

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

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

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

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

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

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

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

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

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

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

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First 100 results (query limit)

Time (local)	Label
2023-10-16 10:19:49	ga_s2am_ard_3-2-1_55LBJ_2023-10-16_final.stac-item
2023-10-16 10:19:54	ga_s2am_ard_3-2-1_54LYP_2023-10-16_final.stac-item
2023-10-16 10:20:04	ga_s2am_ard_3-2-1_55LBH_2023-10-16_nrt.stac-item
2023-10-16 10:20:05	ga_s2am_ard_3-2-1_54LZN_2023-10-16_final.stac-item
2023-10-16 10:20:09	ga_s2am_ard_3-2-1_54LYN_2023-10-16_final.stac-item
2023-10-16 10:20:12	ga_s2am_ard_3-2-1_54LXN_2023-10-16_final.stac-item
2023-10-16 10:20:17	ga_s2am_ard_3-2-1_54LWN_2023-10-16_final.stac-item
2023-10-16 10:20:27	ga_s2am_ard_3-2-1_54LXM_2023-10-16_final.stac-item
2023-10-16 10:20:59	ga_s2am_ard_3-2-1_54LWK_2023-10-16_final.stac-item
2023-10-16 10:21:14	ga_s2am_ard_3-2-1_54LWJ_2023-10-16_final.stac-item
2023-10-16 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2023-10-16_final.stac-item
2023-10-16 10:21:21	ga_s2am_ard_3-2-1_54LYH_2023-10-16_final.stac-item
2023-10-16 10:21:54	ga_s2am_ard_3-2-1_54KXF_2023-10-16_final.stac-item
2023-10-16 10:22:13	ga_s2am_ard_3-2-1_54KYD_2023-10-16_final.stac-item
2023-10-16 10:22:23	ga_s2am_ard_3-2-1_54KXD_2023-10-16_final.stac-item
2023-10-16 10:22:34	ga_s2am_ard_3-2-1_54KUD_2023-10-16_final.stac-item
2023-10-16 10:22:37	ga_s2am_ard_3-2-1_54KXC_2023-10-16_final.stac-item
2023-10-16 10:22:47	ga_s2am_ard_3-2-1_54KUC_2023-10-16_final.stac-item
2023-10-16 10:22:52	ga_s2am_ard_3-2-1_54KXB_2023-10-16_final.stac-item
2023-10-16 10:23:02	ga_s2am_ard_3-2-1_54KUB_2023-10-16_final.stac-item
2023-10-16 10:23:10	ga_s2am_ard_3-2-1_54KWA_2023-10-16_final.stac-item
2023-10-16 10:23:13	ga_s2am_ard_3-2-1_54KVA_2023-10-16_final.stac-item
2023-10-16 10:23:36	ga_s2am_ard_3-2-1_54KTV_2023-10-16_final.stac-item
2023-10-16 10:23:42	ga_s2am_ard_3-2-1_54KVU_2023-10-16_final.stac-item
2023-10-16 10:23:45	ga_s2am_ard_3-2-1_54KUU_2023-10-16_final.stac-item
2023-10-16 10:24:18	ga_s2am_ard_3-2-1_54JTS_2023-10-16_final.stac-item
2023-10-16 10:24:20	ga_s2am_ard_3-2-1_54JWR_2023-10-16_final.stac-item
2023-10-16 10:24:26	ga_s2am_ard_3-2-1_54JVR_2023-10-16_final.stac-item
2023-10-16 10:24:29	ga_s2am_ard_3-2-1_54JUR_2023-10-16_final.stac-item
2023-10-16 10:24:30	ga_s2am_ard_3-2-1_54JWQ_2023-10-16_final.stac-item
2023-10-16 10:24:39	ga_s2am_ard_3-2-1_53JQL_2023-10-16_final.stac-item
2023-10-16 10:24:40	ga_s2am_ard_3-2-1_54JVQ_2023-10-16_final.stac-item
2023-10-16 10:24:44	ga_s2am_ard_3-2-1_54JUQ_2023-10-16_final.stac-item
2023-10-16 10:24:47	ga_s2am_ard_3-2-1_54JTQ_2023-10-16_final.stac-item
2023-10-16 10:24:55	ga_s2am_ard_3-2-1_54JVP_2023-10-16_final.stac-item
2023-10-16 10:25:04	ga_s2am_ard_3-2-1_53JQJ_2023-10-16_final.stac-item
2023-10-16 10:25:10	ga_s2am_ard_3-2-1_54JVN_2023-10-16_final.stac-item
2023-10-16 10:25:13	ga_s2am_ard_3-2-1_54JUN_2023-10-16_final.stac-item
2023-10-16 10:25:16	ga_s2am_ard_3-2-1_54JTN_2023-10-16_final.stac-item
2023-10-16 10:25:19	ga_s2am_ard_3-2-1_53JQH_2023-10-16_final.stac-item
2023-10-16 10:25:23	ga_s2am_ard_3-2-1_54JVM_2023-10-16_final.stac-item
2023-10-16 10:25:27	ga_s2am_ard_3-2-1_54JUM_2023-10-16_final.stac-item
2023-10-16 10:25:31	ga_s2am_ard_3-2-1_54JTM_2023-10-16_final.stac-item
2023-10-16 10:25:33	ga_s2am_ard_3-2-1_53JQG_2023-10-16_final.stac-item
2023-10-16 10:25:39	ga_s2am_ard_3-2-1_53JPG_2023-10-16_final.stac-item
2023-10-16 10:25:56	ga_s2am_ard_3-2-1_54HUK_2023-10-16_final.stac-item
2023-10-16 10:26:02	ga_s2am_ard_3-2-1_53HQE_2023-10-16_final.stac-item
2023-10-16 10:26:06	ga_s2am_ard_3-2-1_53HPE_2023-10-16_final.stac-item
2023-10-16 10:26:22	ga_s2am_ard_3-2-1_54HUH_2023-10-16_final.stac-item
2023-10-16 10:26:23	ga_s2am_ard_3-2-1_54HTH_2023-10-16_final.stac-item
2023-10-16 10:26:24	ga_s2am_ard_3-2-1_53HQC_2023-10-16_final.stac-item
2023-10-16 10:26:25	ga_s2am_ard_3-2-1_53HPC_2023-10-16_final.stac-item
2023-10-16 10:26:30	ga_s2am_ard_3-2-1_54HTH_2023-10-16_final.stac-item
2023-10-16 10:26:31	ga_s2am_ard_3-2-1_53HQC_2023-10-16_final.stac-item
2023-10-16 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-10-16_final.stac-item
2023-10-16 10:27:10	ga_s2am_ard_3-2-1_54HTE_2023-10-16_final.stac-item
2023-10-16 10:27:11	ga_s2am_ard_3-2-1_53HQV_2023-10-16_final.stac-item
2023-10-16 10:27:13	ga_s2am_ard_3-2-1_53HPV_2023-10-16_final.stac-item
2023-10-16 10:27:15	ga_s2am_ard_3-2-1_53HNV_2023-10-16_nrt.stac-item
2023-10-16 12:00:36	ga_s2am_ard_3-2-1_50LPP_2023-10-16_nrt.stac-item
2023-10-16 12:00:39	ga_s2am_ard_3-2-1_50LNP_2023-10-16_nrt.stac-item
2023-10-16 12:00:43	ga_s2am_ard_3-2-1_50LMP_2023-10-16_nrt.stac-item
2023-10-16 12:00:46	ga_s2am_ard_3-2-1_50LQN_2023-10-16_nrt.stac-item
2023-10-16 12:00:50	ga_s2am_ard_3-2-1_50LPN_2023-10-16_nrt.stac-item
2023-10-16 12:00:53	ga_s2am_ard_3-2-1_50LNN_2023-10-16_nrt.stac-item
2023-10-16 12:00:56	ga_s2am_ard_3-2-1_50LMN_2023-10-16_nrt.stac-item
2023-10-16 12:01:05	ga_s2am_ard_3-2-1_50LPM_2023-10-16_nrt.stac-item
2023-10-16 12:01:31	ga_s2am_ard_3-2-1_50LPK_2023-10-16_nrt.stac-item
2023-10-16 12:01:33	ga_s2am_ard_3-2-1_50LNK_2023-10-16_nrt.stac-item
2023-10-16 12:01:35	ga_s2am_ard_3-2-1_50LMK_2023-10-16_nrt.stac-item
2023-10-16 12:03:14	ga_s2am_ard_3-2-1_50KKD_2023-10-16_nrt.stac-item
2023-10-16 12:03:25	ga_s2am_ard_3-2-1_50KLC_2023-10-16_final.stac-item
2023-10-16 12:03:28	ga_s2am_ard_3-2-1_50KKC_2023-10-16_final.stac-item
2023-10-16 12:03:40	ga_s2am_ard_3-2-1_50KLB_2023-10-16_final.stac-item
2023-10-16 12:03:51	ga_s2am_ard_3-2-1_50KMA_2023-10-16_final.stac-item
2023-10-16 12:04:12	ga_s2am_ard_3-2-1_50KKV_2023-10-16_final.stac-item
2023-10-16 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-10-16_final.stac-item
2023-10-16 12:04:20	ga_s2am_ard_3-2-1_50KMU_2023-10-16_final.stac-item
2023-10-16 12:04:24	ga_s2am_ard_3-2-1_50KLU_2023-10-16_final.stac-item
2023-10-16 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-10-16_final.stac-item
2023-10-16 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-10-16_final.stac-item
2023-10-16 12:04:56	ga_s2am_ard_3-2-1_50JKS_2023-10-16_final.stac-item
2023-10-16 12:04:58	ga_s2am_ard_3-2-1_50JMR_2023-10-16_final.stac-item
2023-10-16 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-10-16_final.stac-item
2023-10-16 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-10-16_final.stac-item
2023-10-16 12:05:11	ga_s2am_ard_3-2-1_50JKR_2023-10-16_final.stac-item
2023-10-16 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-10-16_final.stac-item
2023-10-16 12:05:18	ga_s2am_ard_3-2-1_49JFL_2023-10-16_final.stac-item
2023-10-16 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2023-10-16_final.stac-item
2023-10-16 12:05:25	ga_s2am_ard_3-2-1_50JKQ_2023-10-16_final.stac-item
2023-10-16 12:05:36	ga_s2am_ard_3-2-1_50JLP_2023-10-16_final.stac-item
2023-10-16 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-10-16_final.stac-item
2023-10-16 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-10-16_final.stac-item
2023-10-16 12:05:46	ga_s2am_ard_3-2-1_49JFJ_2023-10-16_nrt.stac-item
2023-10-16 12:05:54	ga_s2am_ard_3-2-1_50JKN_2023-10-16_final.stac-item
2023-10-16 12:05:57	ga_s2am_ard_3-2-1_49JGH_2023-10-16_final.stac-item
2023-10-16 12:06:03	ga_s2am_ard_3-2-1_50JLM_2023-10-16_final.stac-item
2023-10-16 12:06:09	ga_s2am_ard_3-2-1_50JKM_2023-10-16_final.stac-item
2023-10-16 12:06:12	ga_s2am_ard_3-2-1_49JGG_2023-10-16_nrt.stac-item
2023-10-16 12:06:13	ga_s2am_ard_3-2-1_50JLL_2023-10-16_final.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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

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