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

80 results

Time (local)	Label
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-17 11:25:08	ga_ls9c_ard_3-2-1_111071_2022-01-17_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-11 09:45:39	ga_ls9c_ard_3-2-1_094085_2022-02-11_final.stac-item
2022-03-12 10:48:14	ga_ls9c_ard_3-2-1_105072_2022-03-12_final.stac-item
2022-03-22 09:50:46	ga_ls9c_ard_3-2-1_095083_2022-03-22_final.stac-item
2022-03-27 11:46:34	ga_ls9c_ard_3-2-1_114079_2022-03-27_final.stac-item
2022-04-14 11:34:55	ga_ls9c_ard_3-2-1_112081_2022-04-14_final.stac-item
2022-04-23 09:50:57	ga_ls9c_ard_3-2-1_095084_2022-04-23_final.stac-item
2022-04-28 10:05:30	ga_ls9c_ard_3-2-1_098074_2022-04-28_final.stac-item
2022-05-21 11:51:31	ga_ls9c_ard_3-2-1_115077_2022-05-21_final.stac-item
2022-06-15 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-06-15_final.stac-item
2022-06-26 09:47:29	ga_ls9c_ard_3-2-1_095075_2022-06-26_final.stac-item
2022-06-28 09:36:43	ga_ls9c_ard_3-2-1_093079_2022-06-28_final.stac-item
2022-07-19 09:51:40	ga_ls9c_ard_3-2-1_096070_2022-07-19_final.stac-item
2022-07-23 11:11:29	ga_ls9c_ard_3-2-1_108084_2022-07-23_final.stac-item
2022-08-10 10:54:09	ga_ls9c_ard_3-2-1_106071_2022-08-10_final.stac-item
2022-08-29 09:51:02	ga_ls9c_ard_3-2-1_095083_2022-08-29_final.stac-item
2022-09-02 11:02:24	ga_ls9c_ard_3-2-1_107076_2022-09-02_final.stac-item
2022-09-05 09:58:00	ga_ls9c_ard_3-2-1_096085_2022-09-05_final.stac-item
2022-09-20 09:14:02	ga_ls9c_ard_3-2-1_089083_2022-09-19_final.stac-item
2022-09-21 11:34:36	ga_ls9c_ard_3-2-1_112079_2022-09-21_final.stac-item
2022-10-07 11:35:48	ga_ls9c_ard_3-2-1_112082_2022-10-07_final.stac-item
2022-10-14 10:02:23	ga_ls9c_ard_3-2-1_097080_2022-10-14_final.stac-item
2022-10-21 11:46:17	ga_ls9c_ard_3-2-1_114077_2022-10-21_final.stac-item
2022-10-31 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-31_final.stac-item
2022-11-04 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-11-04_final.stac-item
2022-11-15 09:59:38	ga_ls9c_ard_3-2-1_097073_2022-11-15_final.stac-item
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-12 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-12-12_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2023-04-10 09:50:42	ga_ls9c_ard_3-2-1_095083_2023-04-10_final.stac-item
2023-04-19 11:20:09	ga_ls9c_ard_3-2-1_110075_2023-04-19_final.stac-item
2023-05-14 09:37:39	ga_ls9c_ard_3-2-1_093082_2023-05-14_final.stac-item
2023-05-14 11:16:56	ga_ls9c_ard_3-2-1_109083_2023-05-14_final.stac-item
2023-05-23 09:32:33	ga_ls9c_ard_3-2-1_092085_2023-05-23_final.stac-item
2023-06-07 10:24:07	ga_ls9c_ard_3-2-1_101075_2023-06-07_final.stac-item
2023-06-08 09:28:29	ga_ls9c_ard_3-2-1_092075_2023-06-07_final.stac-item
2023-06-16 10:19:49	ga_ls9c_ard_3-2-1_100080_2023-06-16_final.stac-item
2023-06-25 11:50:55	ga_ls9c_ard_3-2-1_115076_2023-06-25_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-06 09:51:43	ga_ls9c_ard_3-2-1_096071_2023-07-06_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-08-05 10:06:41	ga_ls9c_ard_3-2-1_098077_2023-08-05_final.stac-item
2023-08-09 11:18:52	ga_ls9c_ard_3-2-1_110072_2023-08-09_final.stac-item
2023-08-14 09:57:44	ga_ls9c_ard_3-2-1_097070_2023-08-14_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-08-21 10:09:57	ga_ls9c_ard_3-2-1_098085_2023-08-21_final.stac-item
2023-08-25 11:23:46	ga_ls9c_ard_3-2-1_110084_2023-08-25_final.stac-item
2023-09-07 09:12:32	ga_ls9c_ard_3-2-1_089080_2023-09-06_final.stac-item
2023-09-17 09:51:40	ga_ls9c_ard_3-2-1_095085_2023-09-17_final.stac-item
2023-09-17 11:23:46	ga_ls9c_ard_3-2-1_111068_2023-09-17_final.stac-item
2023-09-22 10:05:00	ga_ls9c_ard_3-2-1_098072_2023-09-22_final.stac-item
2023-10-01 11:37:42	ga_ls9c_ard_3-2-1_113072_2023-10-01_final.stac-item
2023-10-09 09:13:51	ga_ls9c_ard_3-2-1_089083_2023-10-08_final.stac-item
2023-10-24 10:03:11	ga_ls9c_ard_3-2-1_098067_2023-10-24_final.stac-item
2023-10-29 10:25:40	ga_ls9c_ard_3-2-1_101077_2023-10-29_final.stac-item
2023-11-02 10:02:29	ga_ls9c_ard_3-2-1_097081_2023-11-02_final.stac-item
2023-11-11 11:34:50	ga_ls9c_ard_3-2-1_112080_2023-11-11_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-24 11:04:27	ga_ls9c_ard_3-2-1_107081_2023-11-24_final.stac-item
2023-11-27 09:55:17	ga_ls9c_ard_3-2-1_096078_2023-11-27_final.stac-item
2023-11-30 10:23:48	ga_ls9c_ard_3-2-1_101072_2023-11-30_final.stac-item
2023-12-02 11:52:18	ga_ls9c_ard_3-2-1_115077_2023-12-02_final.stac-item
2023-12-24 09:35:59	ga_ls9c_ard_3-2-1_093076_2023-12-24_final.stac-item
2024-01-01 10:26:58	ga_ls9c_ard_3-2-1_101080_2024-01-01_final.stac-item
2024-01-05 09:57:48	ga_ls9c_ard_3-2-1_097069_2024-01-05_final.stac-item
2024-01-09 11:12:47	ga_ls9c_ard_3-2-1_109071_2024-01-09_final.stac-item
2024-01-10 10:20:46	ga_ls9c_ard_3-2-1_100080_2024-01-10_final.stac-item
2024-01-21 11:41:05	ga_ls9c_ard_3-2-1_113080_2024-01-21_final.stac-item
2024-02-10 09:40:20	ga_ls9c_ard_3-2-1_093087_2024-02-10_final.stac-item
2024-02-22 10:00:27	ga_ls9c_ard_3-2-1_097076_2024-02-22_final.stac-item
2024-04-20 10:37:36	ga_ls9c_ard_3-2-1_103077_2024-04-20_final.stac-item
2024-04-26 10:01:35	ga_ls9c_ard_3-2-1_097080_2024-04-26_final.stac-item
2024-05-02 09:28:04	ga_ls9c_ard_3-2-1_091089_2024-05-01_nrt.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