Search ga_ls9c_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:

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):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

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:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

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 Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

98 results

Time (local)	Label
2021-11-18 11:43:25	ga_ls9c_ard_3-2-1_113081_2021-11-18_final.stac-item
2021-12-17 10:28:20	ga_ls9c_ard_3-2-1_102068_2021-12-17_final.stac-item
2021-12-20 09:25:09	ga_ls9c_ard_3-2-1_091080_2021-12-19_final.stac-item
2022-01-01 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-01-01_final.stac-item
2022-01-06 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-06_final.stac-item
2022-01-13 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-01-13_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-01-31 11:42:19	ga_ls9c_ard_3-2-1_113083_2022-01-31_final.stac-item
2022-02-06 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-02-05_final.stac-item
2022-04-09 09:35:33	ga_ls9c_ard_3-2-1_093076_2022-04-09_final.stac-item
2022-05-07 11:38:08	ga_ls9c_ard_3-2-1_113074_2022-05-07_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-13 11:01:47	ga_ls9c_ard_3-2-1_107076_2022-05-13_final.stac-item
2022-06-10 11:26:26	ga_ls9c_ard_3-2-1_111076_2022-06-10_final.stac-item
2022-06-13 10:16:30	ga_ls9c_ard_3-2-1_100071_2022-06-13_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_final.stac-item
2022-06-27 10:29:09	ga_ls9c_ard_3-2-1_102071_2022-06-27_final.stac-item
2022-07-28 11:28:06	ga_ls9c_ard_3-2-1_111079_2022-07-28_final.stac-item
2022-08-04 09:57:28	ga_ls9c_ard_3-2-1_096084_2022-08-04_final.stac-item
2022-08-04 11:35:10	ga_ls9c_ard_3-2-1_112081_2022-08-04_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-09-16 09:39:56	ga_ls9c_ard_3-2-1_093086_2022-09-16_final.stac-item
2022-09-16 09:40:44	ga_ls9c_ard_3-2-1_093088_2022-09-16_final.stac-item
2022-09-20 09:11:39	ga_ls9c_ard_3-2-1_089077_2022-09-19_final.stac-item
2022-09-26 11:51:34	ga_ls9c_ard_3-2-1_115075_2022-09-26_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final.stac-item
2022-10-11 09:32:39	ga_ls9c_ard_3-2-1_092083_2022-10-11_final.stac-item
2022-10-17 10:29:19	ga_ls9c_ard_3-2-1_102070_2022-10-17_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-28 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-11-27_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-11-28 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-11-28_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-03 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-12-03_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_final.stac-item
2022-12-25 09:12:31	ga_ls9c_ard_3-2-1_089079_2022-12-24_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-01-26 10:49:47	ga_ls9c_ard_3-2-1_105075_2023-01-26_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-09 09:26:59	ga_ls9c_ard_3-2-1_091084_2023-02-08_final.stac-item
2023-02-27 09:15:11	ga_ls9c_ard_3-2-1_089086_2023-02-26_final.stac-item
2023-03-05 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-03-05_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-27 11:15:44	ga_ls9c_ard_3-2-1_109079_2023-03-27_final.stac-item
2023-03-30 10:04:53	ga_ls9c_ard_3-2-1_098072_2023-03-30_final.stac-item
2023-03-30 10:07:17	ga_ls9c_ard_3-2-1_098078_2023-03-30_final.stac-item
2023-04-03 11:20:16	ga_ls9c_ard_3-2-1_110075_2023-04-03_final.stac-item
2023-04-05 09:29:01	ga_ls9c_ard_3-2-1_092075_2023-04-04_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-04-10 09:52:18	ga_ls9c_ard_3-2-1_095087_2023-04-10_final.stac-item
2023-04-20 10:22:56	ga_ls9c_ard_3-2-1_101071_2023-04-20_final.stac-item
2023-04-30 09:27:24	ga_ls9c_ard_3-2-1_091087_2023-04-29_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-06-10 09:20:29	ga_ls9c_ard_3-2-1_090086_2023-06-09_final.stac-item
2023-06-18 10:02:16	ga_ls9c_ard_3-2-1_098067_2023-06-18_final.stac-item
2023-06-18 10:08:39	ga_ls9c_ard_3-2-1_098083_2023-06-18_final.stac-item
2023-06-22 11:19:38	ga_ls9c_ard_3-2-1_110075_2023-06-22_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-07-17 09:34:51	ga_ls9c_ard_3-2-1_093075_2023-07-17_final.stac-item
2023-07-20 10:02:33	ga_ls9c_ard_3-2-1_098067_2023-07-20_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-07-29 11:42:05	ga_ls9c_ard_3-2-1_113084_2023-07-29_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-14 09:21:34	ga_ls9c_ard_3-2-1_090087_2023-09-13_final.stac-item
2023-09-15 11:38:31	ga_ls9c_ard_3-2-1_113074_2023-09-15_final.stac-item
2023-09-17 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-09-17_final.stac-item
2023-09-26 09:41:02	ga_ls9c_ard_3-2-1_094074_2023-09-26_final.stac-item
2023-10-03 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-10-03_final.stac-item
2023-10-08 10:04:16	ga_ls9c_ard_3-2-1_098070_2023-10-08_final.stac-item
2023-10-09 09:16:15	ga_ls9c_ard_3-2-1_089089_2023-10-08_final.stac-item
2023-10-23 09:22:43	ga_ls9c_ard_3-2-1_091074_2023-10-22_final.stac-item
2023-10-24 10:03:11	ga_ls9c_ard_3-2-1_098067_2023-10-24_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-22 11:17:59	ga_ls9c_ard_3-2-1_109084_2023-11-22_final.stac-item
2023-11-25 10:07:14	ga_ls9c_ard_3-2-1_098077_2023-11-25_final.stac-item
2023-11-29 09:41:20	ga_ls9c_ard_3-2-1_094074_2023-11-29_final.stac-item
2023-12-12 10:50:05	ga_ls9c_ard_3-2-1_105076_2023-12-12_final.stac-item
2024-01-11 11:01:38	ga_ls9c_ard_3-2-1_107074_2024-01-11_final.stac-item
2024-01-12 10:07:13	ga_ls9c_ard_3-2-1_098077_2024-01-12_final.stac-item
2024-01-16 09:44:30	ga_ls9c_ard_3-2-1_094082_2024-01-16_final.stac-item
2024-01-26 10:18:20	ga_ls9c_ard_3-2-1_100074_2024-01-26_final.stac-item
2024-01-27 11:02:24	ga_ls9c_ard_3-2-1_107076_2024-01-27_final.stac-item
2024-02-10 11:14:50	ga_ls9c_ard_3-2-1_109076_2024-02-10_final.stac-item
2024-02-19 11:11:42	ga_ls9c_ard_3-2-1_108084_2024-02-19_final.stac-item
2024-02-20 11:52:33	ga_ls9c_ard_3-2-1_115078_2024-02-20_final.stac-item
2024-02-29 11:46:46	ga_ls9c_ard_3-2-1_114079_2024-02-29_final.stac-item
2024-03-21 10:24:25	ga_ls9c_ard_3-2-1_101074_2024-03-21_final.stac-item
2024-04-21 11:18:50	ga_ls9c_ard_3-2-1_110072_2024-04-21_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years