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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JKQ_2015-10-08_final.stac-item
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JKT_2015-10-08_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHS_2016-01-16_final
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JPR_2016-03-03_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JLN_2016-04-15_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HPG_2016-06-05_final
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HMK_2016-06-11_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-07-14_final
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_49KHQ_2016-08-13_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_50JPL_2016-08-14_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JNP_2016-09-19_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGN_2016-10-12_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-10-22_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50JMM_2017-03-05_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLP_2017-03-18_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLP_2017-04-07_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49KHP_2017-04-20_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_50JLR_2017-05-20_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JMM_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JNQ_2017-06-13_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49KHQ_2017-06-19_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JKS_2017-07-09_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_49JHN_2017-07-19_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JLQ_2017-07-29_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HLH_2017-08-25_final.stac-item
2017-09-14 11:51:53	ga_s2am_ard_3-2-1_50JNM_2017-09-14_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JGN_2018-01-05_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HMK_2018-01-19_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HMH_2018-02-01_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNJ_2018-02-18_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JLR_2018-03-03_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNJ_2018-03-20_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JHN_2018-04-05_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-04-08_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JNQ_2018-05-02_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HMH_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50JPM_2018-05-09_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HMK_2018-06-28_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HLH_2018-07-11_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HQH_2018-08-17_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLT_2018-09-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLS_2018-10-12_final.stac-item
2018-11-28 11:56:28	ga_s2am_ard_3-2-1_50HMK_2018-11-28_final.stac-item
2018-12-02 11:36:40	ga_s2am_ard_3-2-1_50HQJ_2018-12-02_final.stac-item
2018-12-21 12:05:14	ga_s2am_ard_3-2-1_50JLQ_2018-12-21_final.stac-item
2018-12-31 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2018-12-31_final.stac-item
2019-02-19 12:06:00	ga_s2am_ard_3-2-1_50JLM_2019-02-19_final.stac-item
2019-02-23 11:45:50	ga_s2am_ard_3-2-1_50JNN_2019-02-23_final.stac-item
2019-02-23 11:46:01	ga_s2am_ard_3-2-1_50JPM_2019-02-23_final.stac-item
2019-03-05 11:45:45	ga_s2am_ard_3-2-1_50JPN_2019-03-05_final.stac-item
2019-05-24 11:45:28	ga_s2am_ard_3-2-1_50JNQ_2019-05-24_final.stac-item
2019-05-24 11:46:08	ga_s2am_ard_3-2-1_50JPM_2019-05-24_final.stac-item
2019-06-03 11:46:11	ga_s2am_ard_3-2-1_50JNM_2019-06-03_final.stac-item
2019-06-06 11:55:45	ga_s2am_ard_3-2-1_50JNP_2019-06-06_final.stac-item
2019-07-29 12:04:44	ga_s2am_ard_3-2-1_50JLT_2019-07-29_final.stac-item
2019-08-25 11:55:04	ga_s2am_ard_3-2-1_50JPR_2019-08-25_final.stac-item
2019-12-23 11:56:31	ga_s2am_ard_3-2-1_50HMK_2019-12-23_final.stac-item
2020-02-14 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2020-02-14_final.stac-item
2020-03-12 11:56:00	ga_s2am_ard_3-2-1_50JNM_2020-03-12_final.stac-item
2020-05-11 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-05-11_final.stac-item
2020-07-24 11:36:39	ga_s2am_ard_3-2-1_50HQK_2020-07-24_final.stac-item
2020-07-30 11:56:10	ga_s2am_ard_3-2-1_50JNM_2020-07-30_final.stac-item
2020-07-30 11:56:42	ga_s2am_ard_3-2-1_50HMK_2020-07-30_final.stac-item
2020-08-09 11:54:54	ga_s2am_ard_3-2-1_50JPS_2020-08-09_final.stac-item
2020-08-26 11:46:35	ga_s2am_ard_3-2-1_50HQK_2020-08-26_final.stac-item
2020-10-15 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2020-10-15_final.stac-item
2020-10-21 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2020-10-21_final.stac-item
2020-11-07 11:56:09	ga_s2am_ard_3-2-1_50JNM_2020-11-07_final.stac-item
2020-11-24 11:46:14	ga_s2am_ard_3-2-1_50JMM_2020-11-24_final.stac-item
2021-01-06 11:56:05	ga_s2am_ard_3-2-1_50JNM_2021-01-06_final.stac-item
2021-01-09 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2021-01-09_final.stac-item
2021-03-27 11:54:56	ga_s2am_ard_3-2-1_50JLS_2021-03-27_final.stac-item
2021-04-19 12:05:03	ga_s2am_ard_3-2-1_50JKR_2021-04-19_final.stac-item
2021-06-05 11:57:07	ga_s2am_ard_3-2-1_50HMH_2021-06-05_final.stac-item
2021-09-07 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-09-07_final.stac-item
2021-09-10 11:47:21	ga_s2am_ard_3-2-1_50HNG_2021-09-10_final
2021-09-26 12:04:39	ga_s2am_ard_3-2-1_50JMT_2021-09-26_final.stac-item
2022-03-02 11:55:42	ga_s2am_ard_3-2-1_50JMP_2022-03-02_final.stac-item
2022-04-18 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-04-18_final.stac-item
2022-06-07 11:46:21	ga_s2am_ard_3-2-1_50JMM_2022-06-07_final.stac-item
2022-07-13 12:05:21	ga_s2am_ard_3-2-1_50JLR_2022-07-13_final.stac-item
2022-07-30 11:55:48	ga_s2am_ard_3-2-1_50JMP_2022-07-30_final.stac-item
2022-10-21 12:04:44	ga_s2am_ard_3-2-1_50JKT_2022-10-21_final.stac-item
2022-11-07 11:54:48	ga_s2am_ard_3-2-1_50JLT_2022-11-07_final.stac-item
2022-11-27 11:56:36	ga_s2am_ard_3-2-1_50HMK_2022-11-27_final.stac-item
2022-12-17 11:55:02	ga_s2am_ard_3-2-1_50JPR_2022-12-17_final.stac-item
2023-01-23 11:45:50	ga_s2am_ard_3-2-1_50JNN_2023-01-23_final.stac-item
2023-01-26 11:54:37	ga_s2am_ard_3-2-1_50JMT_2023-01-26_final.stac-item
2023-01-29 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2023-01-29_final.stac-item
2023-03-10 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-03-10_final
2023-05-09 12:04:57	ga_s2am_ard_3-2-1_50JKS_2023-05-09_final
2023-05-23 11:47:24	ga_s2am_ard_3-2-1_50HNG_2023-05-23_final
2023-07-02 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-07-02_final
2023-07-15 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-15_final
2023-08-24 11:56:10	ga_s2am_ard_3-2-1_50JNM_2023-08-24_final
2024-02-20 11:54:56	ga_s2am_ard_3-2-1_50JLS_2024-02-20_final
2024-03-01 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2024-03-01_final
2024-03-11 11:55:06	ga_s2am_ard_3-2-1_50JNR_2024-03-11_final
2024-04-07 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2024-04-07_final
2024-04-10 11:56:31	ga_s2am_ard_3-2-1_50HNK_2024-04-10_final

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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