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
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KWU_2016-04-06_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51KVT_2016-06-05_final
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HQH_2016-10-03_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_51KVB_2016-10-16_final.stac-item
2016-10-17 11:11:30	ga_s2am_ard_3-2-1_51HWC_2016-10-17_final
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HLH_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50KRD_2016-10-26_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KWS_2016-11-12_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51KVT_2017-01-01_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_51KTT_2017-02-03_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_50KRC_2017-03-25_final.stac-item
2017-05-11 11:35:01	ga_s2am_ard_3-2-1_50JQL_2017-05-11_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_51KUP_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_51KVS_2017-06-13_final.stac-item
2017-07-06 11:56:07	ga_s2am_ard_3-2-1_50JNM_2017-07-06_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JGM_2017-12-26_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51JUL_2018-02-25_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_51KUT_2018-03-10_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_51KVA_2018-03-20_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51KWU_2018-05-06_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51KWQ_2018-05-16_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HNH_2018-06-18_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51KUV_2018-06-28_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51KXQ_2018-09-10_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KRC_2018-10-29_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KVB_2018-11-05_final.stac-item
2018-12-15 11:42:19	ga_s2am_ard_3-2-1_51KVA_2018-12-15_final.stac-item
2018-12-15 11:43:21	ga_s2am_ard_3-2-1_51KUS_2018-12-15_final.stac-item
2018-12-22 11:33:33	ga_s2am_ard_3-2-1_51KWR_2018-12-22_final.stac-item
2019-01-25 11:14:52	ga_s2am_ard_3-2-1_51JYL_2019-01-25_final.stac-item
2019-05-14 11:43:00	ga_s2am_ard_3-2-1_51KVU_2019-05-14_final.stac-item
2019-06-07 11:24:04	ga_s2am_ard_3-2-1_51KXQ_2019-06-07_final.stac-item
2019-06-17 11:23:46	ga_s2am_ard_3-2-1_51KXR_2019-06-17_final.stac-item
2019-07-07 11:27:12	ga_s2am_ard_3-2-1_51HTC_2019-07-07_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-19 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-19_final.stac-item
2019-09-01 11:43:18	ga_s2am_ard_3-2-1_51KTT_2019-09-01_final.stac-item
2019-09-18 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2019-09-18_final.stac-item
2020-01-09 11:44:17	ga_s2am_ard_3-2-1_50KPU_2020-01-09_final.stac-item
2020-02-25 11:33:18	ga_s2am_ard_3-2-1_51KXS_2020-02-25_final.stac-item
2020-03-25 12:04:57	ga_s2am_ard_3-2-1_49JGM_2020-03-25_final.stac-item
2020-05-04 12:05:41	ga_s2am_ard_3-2-1_50JLP_2020-05-04_final.stac-item
2020-05-18 11:43:23	ga_s2am_ard_3-2-1_51KTT_2020-05-18_final.stac-item
2020-06-07 11:42:52	ga_s2am_ard_3-2-1_51KUV_2020-06-07_final.stac-item
2020-06-24 11:34:16	ga_s2am_ard_3-2-1_51KWP_2020-06-24_final.stac-item
2020-07-04 11:33:10	ga_s2am_ard_3-2-1_51KVU_2020-07-04_final.stac-item
2020-08-30 11:24:20	ga_s2am_ard_3-2-1_51KWP_2020-08-30_final.stac-item
2020-09-28 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-09-28_final
2021-03-04 11:46:23	ga_s2am_ard_3-2-1_50JNL_2021-03-04_final.stac-item
2021-05-07 11:26:45	ga_s2am_ard_3-2-1_51HVD_2021-05-07_final.stac-item
2021-07-22 11:45:07	ga_s2am_ard_3-2-1_50JQR_2021-07-22_final.stac-item
2021-07-22 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2021-07-22_final.stac-item
2021-07-22 11:47:10	ga_s2am_ard_3-2-1_50HNH_2021-07-22_final.stac-item
2021-07-29 11:35:22	ga_s2am_ard_3-2-1_51JWJ_2021-07-29_final.stac-item
2021-07-29 11:37:14	ga_s2am_ard_3-2-1_50HQG_2021-07-29_final
2021-08-11 11:42:48	ga_s2am_ard_3-2-1_51KUV_2021-08-11_final.stac-item
2021-09-17 11:33:42	ga_s2am_ard_3-2-1_51KVR_2021-09-17_final.stac-item
2021-09-26 12:05:44	ga_s2am_ard_3-2-1_50JKP_2021-09-26_final.stac-item
2021-10-04 11:23:47	ga_s2am_ard_3-2-1_51KXR_2021-10-04_final.stac-item
2021-10-07 11:32:24	ga_s2am_ard_3-2-1_51KVB_2021-10-07_final.stac-item
2021-10-20 11:43:20	ga_s2am_ard_3-2-1_51KUT_2021-10-20_final.stac-item
2021-12-26 11:32:30	ga_s2am_ard_3-2-1_51KWA_2021-12-26_final.stac-item
2021-12-26 11:32:48	ga_s2am_ard_3-2-1_51KVV_2021-12-26_final.stac-item
2022-02-17 11:43:16	ga_s2am_ard_3-2-1_51KUT_2022-02-17_final.stac-item
2022-04-22 11:24:06	ga_s2am_ard_3-2-1_51KWQ_2022-04-22_final.stac-item
2022-05-14 12:03:48	ga_s2am_ard_3-2-1_50KKB_2022-05-14_final.stac-item
2022-05-18 11:43:09	ga_s2am_ard_3-2-1_51KTU_2022-05-18_final.stac-item
2022-05-31 11:56:01	ga_s2am_ard_3-2-1_50JMN_2022-05-31_final.stac-item
2022-06-17 11:43:14	ga_s2am_ard_3-2-1_51KTU_2022-06-17_final.stac-item
2022-06-23 12:06:07	ga_s2am_ard_3-2-1_50JKN_2022-06-23_final.stac-item
2022-08-26 11:42:55	ga_s2am_ard_3-2-1_51KVV_2022-08-26_final.stac-item
2022-08-26 11:42:58	ga_s2am_ard_3-2-1_51KUV_2022-08-26_final
2022-09-18 11:53:19	ga_s2am_ard_3-2-1_50KRC_2022-09-18_final.stac-item
2022-10-22 11:33:29	ga_s2am_ard_3-2-1_51KWS_2022-10-22_final.stac-item
2022-12-24 11:42:55	ga_s2am_ard_3-2-1_51KVU_2022-12-24_final.stac-item
2023-01-13 11:43:16	ga_s2am_ard_3-2-1_50KRC_2023-01-13_final.stac-item
2023-01-23 11:42:42	ga_s2am_ard_3-2-1_51KUV_2023-01-23_final.stac-item
2023-02-19 11:33:24	ga_s2am_ard_3-2-1_51KWS_2023-02-19_nrt.stac-item
2023-02-22 11:43:41	ga_s2am_ard_3-2-1_51KUR_2023-02-22_final
2023-03-28 11:26:46	ga_s2am_ard_3-2-1_51HUD_2023-03-28_final
2023-04-09 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-04-09_final
2023-05-06 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-05-06_final
2023-07-19 11:33:49	ga_s2am_ard_3-2-1_51KVR_2023-07-19_final
2023-08-18 11:37:09	ga_s2am_ard_3-2-1_50HQH_2023-08-18_final
2023-08-21 11:47:08	ga_s2am_ard_3-2-1_50HPH_2023-08-21_final
2023-09-07 11:34:16	ga_s2am_ard_3-2-1_51KWP_2023-09-07_final
2023-10-27 11:33:52	ga_s2am_ard_3-2-1_51KXQ_2023-10-27_final
2023-11-09 11:43:29	ga_s2am_ard_3-2-1_51KUS_2023-11-09_final
2023-11-15 12:03:22	ga_s2am_ard_3-2-1_50KMC_2023-11-15_final
2023-11-16 11:36:18	ga_s2am_ard_3-2-1_50JQL_2023-11-16_final
2023-12-19 11:42:42	ga_s2am_ard_3-2-1_51KUV_2023-12-19_final
2024-01-05 11:32:40	ga_s2am_ard_3-2-1_51KWV_2024-01-05_final
2024-01-05 11:32:43	ga_s2am_ard_3-2-1_51KVV_2024-01-05_final
2024-01-15 11:37:20	ga_s2am_ard_3-2-1_50HNG_2024-01-15_final
2024-02-04 11:34:06	ga_s2am_ard_3-2-1_51KWP_2024-02-04_final
2024-02-24 11:33:51	ga_s2am_ard_3-2-1_51KXQ_2024-02-24_final
2024-04-17 11:43:32	ga_s2am_ard_3-2-1_51KUS_2024-04-17_final
2024-04-24 11:33:59	ga_s2am_ard_3-2-1_51KWQ_2024-04-24_final
2024-05-04 11:33:04	ga_s2am_ard_3-2-1_51KVU_2024-05-04_final
2024-05-14 11:33:04	ga_s2am_ard_3-2-1_51KVU_2024-05-14_nrt

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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