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 10:12:24	ga_s2am_ard_3-2-1_54KZD_2022-04-01_final.stac-item
2022-04-02 11:24:43	ga_s2am_ard_3-2-1_51JXM_2022-04-02_final.stac-item
2022-04-03 10:51:06	ga_s2am_ard_3-2-1_53LPE_2022-04-03_final.stac-item
2022-04-04 10:21:28	ga_s2am_ard_3-2-1_54LXH_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 10:21:45	ga_s2am_ard_3-2-1_54KWG_2022-04-04_final.stac-item
2022-04-04 10:22:18	ga_s2am_ard_3-2-1_54KVE_2022-04-04_final.stac-item
2022-04-04 12:03:46	ga_s2am_ard_3-2-1_50KKB_2022-04-04_final.stac-item
2022-04-07 10:31:33	ga_s2am_ard_3-2-1_54KWG_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
2022-04-08 11:44:46	ga_s2am_ard_3-2-1_50JRS_2022-04-08_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 10:12:23	ga_s2am_ard_3-2-1_54KZD_2022-04-11_final.stac-item
2022-04-11 10:12:27	ga_s2am_ard_3-2-1_54KYD_2022-04-11_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 10:22:19	ga_s2am_ard_3-2-1_54KVE_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
2022-04-15 11:34:43	ga_s2am_ard_3-2-1_51JWM_2022-04-15_final.stac-item
2022-04-15 11:35:48	ga_s2am_ard_3-2-1_51JUH_2022-04-15_final.stac-item
2022-04-17 10:31:36	ga_s2am_ard_3-2-1_54KWG_2022-04-17_final.stac-item
2022-04-17 12:13:58	ga_s2am_ard_3-2-1_49KHR_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
2022-04-18 11:45:50	ga_s2am_ard_3-2-1_50JQN_2022-04-18_final.stac-item
2022-04-20 10:41:13	ga_s2am_ard_3-2-1_53LPE_2022-04-20_final.stac-item
2022-04-21 10:12:26	ga_s2am_ard_3-2-1_54KZD_2022-04-21_final.stac-item
2022-04-22 11:25:00	ga_s2am_ard_3-2-1_51JXL_2022-04-22_final.stac-item
2022-04-23 10:51:09	ga_s2am_ard_3-2-1_53LPE_2022-04-23_final.stac-item
2022-04-27 10:31:37	ga_s2am_ard_3-2-1_54KWG_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
2022-05-01 11:52:59	ga_s2am_ard_3-2-1_51KTU_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 11:21:40	ga_s2am_ard_3-2-1_52LCJ_2022-05-02_final.stac-item
2022-05-02 11:21:44	ga_s2am_ard_3-2-1_52LBJ_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 11:23:05	ga_s2am_ard_3-2-1_51KXU_2022-05-02_final.stac-item
2022-05-05 09:56:58	ga_s2am_ard_3-2-1_54HYF_2022-05-05_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 11:31:34	ga_s2am_ard_3-2-1_52LBJ_2022-05-05_final.stac-item
2022-05-05 11:31:43	ga_s2am_ard_3-2-1_51LYD_2022-05-05_final.stac-item
2022-05-05 11:32:16	ga_s2am_ard_3-2-1_51KXB_2022-05-05_final.stac-item
2022-05-06 11:00:59	ga_s2am_ard_3-2-1_53LLF_2022-05-06_final.stac-item
2022-05-06 11:01:17	ga_s2am_ard_3-2-1_53LKE_2022-05-06_final.stac-item
2022-05-06 11:01:36	ga_s2am_ard_3-2-1_52LGJ_2022-05-06_final.stac-item
2022-05-08 10:07:05	ga_s2am_ard_3-2-1_54HVF_2022-05-08_final.stac-item
2022-05-08 11:42:46	ga_s2am_ard_3-2-1_51KVV_2022-05-08_final.stac-item
2022-05-08 11:46:13	ga_s2am_ard_3-2-1_50JNM_2022-05-08_final.stac-item
2022-05-08 11:46:23	ga_s2am_ard_3-2-1_50JPL_2022-05-08_final.stac-item
2022-05-08 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2022-05-08_final.stac-item
2022-05-08 11:47:06	ga_s2am_ard_3-2-1_50HPH_2022-05-08_final.stac-item
2022-05-09 11:12:07	ga_s2am_ard_3-2-1_52KEG_2022-05-09_final.stac-item
2022-05-11 10:17:00	ga_s2am_ard_3-2-1_54HVF_2022-05-11_final.stac-item
2022-05-11 11:52:58	ga_s2am_ard_3-2-1_51KTU_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 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2022-05-11_final.stac-item
2022-05-12 09:47:48	ga_s2am_ard_3-2-1_54HYC_2022-05-12_final.stac-item
2022-05-12 11:21:39	ga_s2am_ard_3-2-1_52LCJ_2022-05-12_final.stac-item
2022-05-12 11:21:42	ga_s2am_ard_3-2-1_52LBJ_2022-05-12_final.stac-item
2022-05-12 11:21:57	ga_s2am_ard_3-2-1_52LBH_2022-05-12_final.stac-item
2022-05-12 11:22:41	ga_s2am_ard_3-2-1_51KZV_2022-05-12_final.stac-item
2022-05-15 09:56:50	ga_s2am_ard_3-2-1_54HXG_2022-05-15_final.stac-item
2022-05-15 09:56:58	ga_s2am_ard_3-2-1_54HYF_2022-05-15_final.stac-item
2022-05-15 09:57:22	ga_s2am_ard_3-2-1_54HXD_2022-05-15_final.stac-item
2022-05-15 09:57:30	ga_s2am_ard_3-2-1_54HXD_2022-05-15_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 11:31:33	ga_s2am_ard_3-2-1_52LBJ_2022-05-15_final.stac-item
2022-05-15 11:31:43	ga_s2am_ard_3-2-1_51LYD_2022-05-15_final.stac-item
2022-05-15 11:32:01	ga_s2am_ard_3-2-1_51LXC_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 11:32:30	ga_s2am_ard_3-2-1_51KXA_2022-05-15_final.stac-item
2022-05-16 11:01:19	ga_s2am_ard_3-2-1_52LHK_2022-05-16_final.stac-item
2022-05-18 10:07:27	ga_s2am_ard_3-2-1_54HXD_2022-05-18_final.stac-item
2022-05-18 11:43:09	ga_s2am_ard_3-2-1_51KTU_2022-05-18_final.stac-item
2022-05-18 11:47:08	ga_s2am_ard_3-2-1_50HPH_2022-05-18_final.stac-item
2022-05-21 11:53:05	ga_s2am_ard_3-2-1_50KRD_2022-05-21_final.stac-item
2022-05-21 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2022-05-21_final.stac-item
2022-05-21 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-05-21_final.stac-item
2022-05-21 11:57:16	ga_s2am_ard_3-2-1_50HLH_2022-05-21_final.stac-item
2022-05-22 11:21:42	ga_s2am_ard_3-2-1_52LCJ_2022-05-22_final.stac-item
2022-05-22 11:23:07	ga_s2am_ard_3-2-1_51KXU_2022-05-22_final.stac-item
2022-05-25 09:56:53	ga_s2am_ard_3-2-1_54HXG_2022-05-25_final.stac-item
2022-05-25 09:57:00	ga_s2am_ard_3-2-1_54HYF_2022-05-25_final.stac-item
2022-05-25 09:57:25	ga_s2am_ard_3-2-1_54HXD_2022-05-25_final.stac-item
2022-05-25 09:57:33	ga_s2am_ard_3-2-1_54HXD_2022-05-25_final.stac-item
2022-05-25 11:31:31	ga_s2am_ard_3-2-1_51LYE_2022-05-25_final.stac-item
2022-05-25 11:31:36	ga_s2am_ard_3-2-1_52LBJ_2022-05-25_final.stac-item
2022-05-25 11:32:04	ga_s2am_ard_3-2-1_51LXC_2022-05-25_final.stac-item
2022-05-25 11:32:06	ga_s2am_ard_3-2-1_51KZB_2022-05-25_final.stac-item
2022-05-25 11:32:18	ga_s2am_ard_3-2-1_51KXB_2022-05-25_final.stac-item
2022-05-25 11:32:27	ga_s2am_ard_3-2-1_51KVB_2022-05-25_final.stac-item
2022-05-25 11:32:47	ga_s2am_ard_3-2-1_51KXV_2022-05-25_final.stac-item
2022-05-25 11:32:51	ga_s2am_ard_3-2-1_51KWV_2022-05-25_final.stac-item
2022-05-26 11:01:02	ga_s2am_ard_3-2-1_53LLF_2022-05-26_final.stac-item
2022-05-26 11:01:21	ga_s2am_ard_3-2-1_52LHK_2022-05-26_final.stac-item
2022-05-28 10:06:57	ga_s2am_ard_3-2-1_54HYF_2022-05-28_final.stac-item
2022-05-28 10:07:05	ga_s2am_ard_3-2-1_54HWF_2022-05-28_final.stac-item
2022-05-28 10:07:29	ga_s2am_ard_3-2-1_54HXD_2022-05-28_final.stac-item
2022-05-28 11:42:21	ga_s2am_ard_3-2-1_51KVB_2022-05-28_final.stac-item
2022-05-29 11:12:14	ga_s2am_ard_3-2-1_52KDG_2022-05-29_final.stac-item
2022-05-31 11:53:02	ga_s2am_ard_3-2-1_51KTU_2022-05-31_final.stac-item
2022-05-31 11:56:19	ga_s2am_ard_3-2-1_50JLM_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