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
2022-04-01 10:11:29	ga_s2am_ard_3-2-1_54LYH_2022-04-01_final.stac-item
2022-04-01 10:12:09	ga_s2am_ard_3-2-1_54KZE_2022-04-01_final.stac-item
2022-04-03 10:51:24	ga_s2am_ard_3-2-1_53LND_2022-04-03_final.stac-item
2022-04-04 10:21:24	ga_s2am_ard_3-2-1_54LYH_2022-04-04_final.stac-item
2022-04-04 10:21:34	ga_s2am_ard_3-2-1_54LVH_2022-04-04_final.stac-item
2022-04-04 10:21:39	ga_s2am_ard_3-2-1_54KYG_2022-04-04_final.stac-item
2022-04-04 10:21:48	ga_s2am_ard_3-2-1_54KVG_2022-04-04_final.stac-item
2022-04-06 09:25:31	ga_s2am_ard_3-2-1_56JLL_2022-04-05_final.stac-item
2022-04-06 09:25:55	ga_s2am_ard_3-2-1_56HMJ_2022-04-05_final.stac-item
2022-04-07 10:31:43	ga_s2am_ard_3-2-1_54KVG_2022-04-07_final.stac-item
2022-04-07 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-04-07_final.stac-item
2022-04-09 09:35:11	ga_s2am_ard_3-2-1_56JLM_2022-04-09_final.stac-item
2022-04-10 10:40:41	ga_s2am_ard_3-2-1_53LPG_2022-04-10_final.stac-item
2022-04-11 10:10:52	ga_s2am_ard_3-2-1_55LCE_2022-04-11_final.stac-item
2022-04-11 10:11:14	ga_s2am_ard_3-2-1_54LYJ_2022-04-11_final.stac-item
2022-04-11 10:11:24	ga_s2am_ard_3-2-1_55LBC_2022-04-11_final.stac-item
2022-04-11 10:11:44	ga_s2am_ard_3-2-1_54KYG_2022-04-11_final.stac-item
2022-04-11 10:12:04	ga_s2am_ard_3-2-1_54KXF_2022-04-11_final.stac-item
2022-04-11 10:12:09	ga_s2am_ard_3-2-1_54KZE_2022-04-11_final.stac-item
2022-04-13 10:50:37	ga_s2am_ard_3-2-1_53LPG_2022-04-13_final.stac-item
2022-04-14 10:21:40	ga_s2am_ard_3-2-1_54KYG_2022-04-14_final.stac-item
2022-04-14 10:21:43	ga_s2am_ard_3-2-1_54KXG_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 10:21:58	ga_s2am_ard_3-2-1_54KXF_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 10:22:16	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 10:22:30	ga_s2am_ard_3-2-1_54KWD_2022-04-14_final.stac-item
2022-04-15 11:35:07	ga_s2am_ard_3-2-1_51JTL_2022-04-15_final.stac-item
2022-04-17 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-04-17_final.stac-item
2022-04-17 12:14:22	ga_s2am_ard_3-2-1_50KKU_2022-04-17_final.stac-item
2022-04-18 11:44:49	ga_s2am_ard_3-2-1_51JTM_2022-04-18_final.stac-item
2022-04-19 09:35:14	ga_s2am_ard_3-2-1_56JLM_2022-04-19_final.stac-item
2022-04-19 09:35:31	ga_s2am_ard_3-2-1_56JKL_2022-04-19_final.stac-item
2022-04-21 10:10:55	ga_s2am_ard_3-2-1_55LCE_2022-04-21_final.stac-item
2022-04-21 10:11:27	ga_s2am_ard_3-2-1_55LBC_2022-04-21_final.stac-item
2022-04-21 10:12:02	ga_s2am_ard_3-2-1_54KXF_2022-04-21_final.stac-item
2022-04-24 10:21:38	ga_s2am_ard_3-2-1_54LVH_2022-04-24_final.stac-item
2022-04-24 10:21:52	ga_s2am_ard_3-2-1_54KVG_2022-04-24_final.stac-item
2022-04-27 10:31:47	ga_s2am_ard_3-2-1_54KVG_2022-04-27_final.stac-item
2022-04-27 12:14:13	ga_s2am_ard_3-2-1_50KKV_2022-04-27_final.stac-item
2022-04-28 11:45:05	ga_s2am_ard_3-2-1_51JTL_2022-04-28_final.stac-item
2022-04-29 09:35:15	ga_s2am_ard_3-2-1_56JLM_2022-04-29_final.stac-item
2022-05-01 10:17:31	ga_s2am_ard_3-2-1_54HVD_2022-05-01_final.stac-item
2022-05-02 09:47:49	ga_s2am_ard_3-2-1_54HYC_2022-05-02_final.stac-item
2022-05-02 09:48:27	ga_s2am_ard_3-2-1_55GEP_2022-05-02_final.stac-item
2022-05-02 09:48:35	ga_s2am_ard_3-2-1_55GDP_2022-05-02_final.stac-item
2022-05-02 09:48:50	ga_s2am_ard_3-2-1_55GDN_2022-05-02_final.stac-item
2022-05-02 11:21:37	ga_s2am_ard_3-2-1_52LDJ_2022-05-02_final.stac-item
2022-05-02 11:21:59	ga_s2am_ard_3-2-1_51LZC_2022-05-02_final.stac-item
2022-05-02 11:22:14	ga_s2am_ard_3-2-1_51KZB_2022-05-02_final.stac-item
2022-05-02 11:22:17	ga_s2am_ard_3-2-1_51KYB_2022-05-02_final.stac-item
2022-05-02 11:22:56	ga_s2am_ard_3-2-1_52KBD_2022-05-02_final.stac-item
2022-05-05 09:57:41	ga_s2am_ard_3-2-1_54HYC_2022-05-05_final.stac-item
2022-05-05 09:57:50	ga_s2am_ard_3-2-1_54HWC_2022-05-05_final.stac-item
2022-05-05 11:32:34	ga_s2am_ard_3-2-1_51KWA_2022-05-05_final.stac-item
2022-05-06 09:28:35	ga_s2am_ard_3-2-1_55GFP_2022-05-05_final.stac-item
2022-05-06 11:01:02	ga_s2am_ard_3-2-1_53LKF_2022-05-06_final.stac-item
2022-05-06 11:01:13	ga_s2am_ard_3-2-1_53LLE_2022-05-06_final.stac-item
2022-05-08 10:07:30	ga_s2am_ard_3-2-1_54HWD_2022-05-08_final.stac-item
2022-05-08 10:07:45	ga_s2am_ard_3-2-1_54HWC_2022-05-08_final.stac-item
2022-05-08 11:42:25	ga_s2am_ard_3-2-1_51KVA_2022-05-08_final.stac-item
2022-05-09 09:38:35	ga_s2am_ard_3-2-1_55GEP_2022-05-09_final.stac-item
2022-05-09 09:38:39	ga_s2am_ard_3-2-1_55GDP_2022-05-09_final.stac-item
2022-05-09 09:38:53	ga_s2am_ard_3-2-1_55GDN_2022-05-09_final.stac-item
2022-05-09 11:10:33	ga_s2am_ard_3-2-1_52LGN_2022-05-09_final.stac-item
2022-05-09 11:12:15	ga_s2am_ard_3-2-1_52KCG_2022-05-09_final.stac-item
2022-05-12 09:47:57	ga_s2am_ard_3-2-1_55HBS_2022-05-12_final.stac-item
2022-05-12 09:48:25	ga_s2am_ard_3-2-1_55GEP_2022-05-12_final.stac-item
2022-05-12 09:48:49	ga_s2am_ard_3-2-1_55GDN_2022-05-12_final.stac-item
2022-05-12 11:22:22	ga_s2am_ard_3-2-1_52KCF_2022-05-12_final.stac-item
2022-05-15 09:57:41	ga_s2am_ard_3-2-1_54HYC_2022-05-15_final.stac-item
2022-05-15 09:57:50	ga_s2am_ard_3-2-1_54HWC_2022-05-15_final.stac-item
2022-05-15 11:31:39	ga_s2am_ard_3-2-1_51LZD_2022-05-15_final.stac-item
2022-05-15 11:32:04	ga_s2am_ard_3-2-1_51KZB_2022-05-15_final.stac-item
2022-05-15 11:32:12	ga_s2am_ard_3-2-1_51KYB_2022-05-15_final.stac-item
2022-05-18 10:06:44	ga_s2am_ard_3-2-1_54HYG_2022-05-18_final.stac-item
2022-05-18 10:06:59	ga_s2am_ard_3-2-1_54HXF_2022-05-18_final.stac-item
2022-05-18 11:42:33	ga_s2am_ard_3-2-1_51KVA_2022-05-18_final.stac-item
2022-05-19 09:38:32	ga_s2am_ard_3-2-1_55GFP_2022-05-19_final.stac-item
2022-05-21 11:53:05	ga_s2am_ard_3-2-1_50KRD_2022-05-21_final.stac-item
2022-05-22 09:48:26	ga_s2am_ard_3-2-1_55GCQ_2022-05-22_final.stac-item
2022-05-22 11:21:47	ga_s2am_ard_3-2-1_51LZD_2022-05-22_final.stac-item
2022-05-22 11:22:19	ga_s2am_ard_3-2-1_51KYB_2022-05-22_final.stac-item
2022-05-23 10:51:32	ga_s2am_ard_3-2-1_53LMD_2022-05-23_final.stac-item
2022-05-25 09:57:52	ga_s2am_ard_3-2-1_54HWC_2022-05-25_final.stac-item
2022-05-25 09:57:57	ga_s2am_ard_3-2-1_55HBS_2022-05-25_final.stac-item
2022-05-25 11:31:42	ga_s2am_ard_3-2-1_51LZD_2022-05-25_final.stac-item
2022-05-26 09:28:45	ga_s2am_ard_3-2-1_55GEP_2022-05-25_final.stac-item
2022-05-26 11:00:47	ga_s2am_ard_3-2-1_52LGN_2022-05-26_final.stac-item
2022-05-28 10:07:23	ga_s2am_ard_3-2-1_54HVE_2022-05-28_final.stac-item
2022-05-28 10:07:48	ga_s2am_ard_3-2-1_54HWC_2022-05-28_final.stac-item
2022-05-28 11:46:41	ga_s2am_ard_3-2-1_50HPK_2022-05-28_final.stac-item
2022-05-29 09:38:38	ga_s2am_ard_3-2-1_55GEP_2022-05-29_final.stac-item
2022-05-29 09:38:56	ga_s2am_ard_3-2-1_55GDN_2022-05-29_final.stac-item
2022-05-29 11:11:44	ga_s2am_ard_3-2-1_52LDJ_2022-05-29_final.stac-item
2022-05-29 11:12:14	ga_s2am_ard_3-2-1_52KDG_2022-05-29_final.stac-item
2022-05-29 11:12:31	ga_s2am_ard_3-2-1_52KCF_2022-05-29_final.stac-item
2022-05-31 10:17:19	ga_s2am_ard_3-2-1_54HVE_2022-05-31_final.stac-item
2022-05-31 10:17:33	ga_s2am_ard_3-2-1_54HVD_2022-05-31_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years