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

First 100 results (query limit)

Time (local)	Label
2021-11-16 10:19:55	ga_ls9c_ard_3-2-1_100072_2021-11-16_final.stac-item
2021-12-12 10:10:39	ga_ls9c_ard_3-2-1_099070_2021-12-12_final.stac-item
2021-12-12 11:52:44	ga_ls9c_ard_3-2-1_115078_2021-12-12_final.stac-item
2021-12-14 11:38:45	ga_ls9c_ard_3-2-1_113074_2021-12-14_final.stac-item
2021-12-19 10:18:47	ga_ls9c_ard_3-2-1_100075_2021-12-19_final.stac-item
2021-12-20 09:26:21	ga_ls9c_ard_3-2-1_091083_2021-12-19_final.stac-item
2021-12-28 10:14:36	ga_ls9c_ard_3-2-1_099080_2021-12-28_final.stac-item
2021-12-31 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-31_final.stac-item
2022-01-01 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-01-01_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-29 11:53:29	ga_ls9c_ard_3-2-1_115080_2022-01-29_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-03-03 09:20:42	ga_ls9c_ard_3-2-1_090085_2022-03-02_final.stac-item
2022-03-04 09:57:59	ga_ls9c_ard_3-2-1_097070_2022-03-04_final.stac-item
2022-03-08 11:14:57	ga_ls9c_ard_3-2-1_109077_2022-03-08_final.stac-item
2022-03-26 09:28:01	ga_ls9c_ard_3-2-1_091088_2022-03-25_final.stac-item
2022-03-30 10:34:12	ga_ls9c_ard_3-2-1_103068_2022-03-30_final.stac-item
2022-04-02 09:33:00	ga_ls9c_ard_3-2-1_092085_2022-04-02_final.stac-item
2022-04-13 10:51:40	ga_ls9c_ard_3-2-1_105081_2022-04-13_final.stac-item
2022-05-20 11:09:51	ga_ls9c_ard_3-2-1_108081_2022-05-20_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-05-24 09:06:39	ga_ls9c_ard_3-2-1_088082_2022-05-23_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-09 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-07-08_final.stac-item
2022-07-19 09:51:40	ga_ls9c_ard_3-2-1_096070_2022-07-19_final.stac-item
2022-08-10 09:21:39	ga_ls9c_ard_3-2-1_090087_2022-08-09_final.stac-item
2022-08-10 09:22:51	ga_ls9c_ard_3-2-1_090090_2022-08-09_final.stac-item
2022-08-14 10:30:15	ga_ls9c_ard_3-2-1_102073_2022-08-14_final.stac-item
2022-09-01 11:58:01	ga_ls9c_ard_3-2-1_116076_2022-09-01_final.stac-item
2022-09-02 11:05:11	ga_ls9c_ard_3-2-1_107083_2022-09-02_final.stac-item
2022-09-07 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-09-07_final.stac-item
2022-09-13 09:07:24	ga_ls9c_ard_3-2-1_088082_2022-09-12_final.stac-item
2022-09-16 09:39:56	ga_ls9c_ard_3-2-1_093086_2022-09-16_final.stac-item
2022-09-21 09:53:43	ga_ls9c_ard_3-2-1_096074_2022-09-21_final.stac-item
2022-09-29 09:07:30	ga_ls9c_ard_3-2-1_088082_2022-09-28_final.stac-item
2022-10-04 09:27:13	ga_ls9c_ard_3-2-1_091085_2022-10-03_final.stac-item
2022-10-16 11:25:44	ga_ls9c_ard_3-2-1_111072_2022-10-16_final.stac-item
2022-10-18 09:36:53	ga_ls9c_ard_3-2-1_093078_2022-10-18_final.stac-item
2022-10-19 10:22:33	ga_ls9c_ard_3-2-1_100084_2022-10-19_final.stac-item
2022-10-20 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-10-19_final.stac-item
2022-10-29 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-10-28_final.stac-item
2022-10-29 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-10-29_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-05 11:02:34	ga_ls9c_ard_3-2-1_107076_2022-11-05_final.stac-item
2022-11-07 09:15:21	ga_ls9c_ard_3-2-1_089086_2022-11-06_final.stac-item
2022-11-10 11:21:10	ga_ls9c_ard_3-2-1_110076_2022-11-10_final.stac-item
2022-11-13 11:51:40	ga_ls9c_ard_3-2-1_115075_2022-11-13_final.stac-item
2022-11-17 11:25:46	ga_ls9c_ard_3-2-1_111072_2022-11-17_final.stac-item
2022-11-18 10:29:20	ga_ls9c_ard_3-2-1_102070_2022-11-18_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-16 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-12-15_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2023-01-08 09:24:08	ga_ls9c_ard_3-2-1_091077_2023-01-07_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-09 10:07:23	ga_ls9c_ard_3-2-1_098077_2023-01-09_final.stac-item
2023-01-13 11:24:18	ga_ls9c_ard_3-2-1_110084_2023-01-13_final.stac-item
2023-01-16 10:12:41	ga_ls9c_ard_3-2-1_099075_2023-01-16_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-02-06 10:28:58	ga_ls9c_ard_3-2-1_102069_2023-02-06_final.stac-item
2023-02-07 09:36:57	ga_ls9c_ard_3-2-1_093078_2023-02-07_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-11 10:52:18	ga_ls9c_ard_3-2-1_105081_2023-02-11_final.stac-item
2023-02-18 10:56:23	ga_ls9c_ard_3-2-1_106076_2023-02-18_final.stac-item
2023-02-19 11:38:50	ga_ls9c_ard_3-2-1_113074_2023-02-19_final.stac-item
2023-02-20 09:07:06	ga_ls9c_ard_3-2-1_088081_2023-02-19_final.stac-item
2023-03-05 11:53:25	ga_ls9c_ard_3-2-1_115080_2023-03-05_final.stac-item
2023-03-16 09:57:31	ga_ls9c_ard_3-2-1_096084_2023-03-16_final.stac-item
2023-03-22 10:53:41	ga_ls9c_ard_3-2-1_106070_2023-03-22_final.stac-item
2023-04-08 11:41:58	ga_ls9c_ard_3-2-1_113083_2023-04-08_final.stac-item
2023-04-14 09:27:07	ga_ls9c_ard_3-2-1_091086_2023-04-13_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-26 10:03:02	ga_ls9c_ard_3-2-1_097084_2023-05-26_final.stac-item
2023-06-09 10:10:32	ga_ls9c_ard_3-2-1_099072_2023-06-09_final.stac-item
2023-06-10 10:56:58	ga_ls9c_ard_3-2-1_106080_2023-06-10_final.stac-item
2023-06-13 11:24:38	ga_ls9c_ard_3-2-1_111072_2023-06-13_final.stac-item
2023-06-14 10:27:48	ga_ls9c_ard_3-2-1_102069_2023-06-14_final.stac-item
2023-06-15 09:34:10	ga_ls9c_ard_3-2-1_093074_2023-06-15_final.stac-item
2023-06-25 10:10:26	ga_ls9c_ard_3-2-1_099072_2023-06-25_final.stac-item
2023-07-10 11:06:43	ga_ls9c_ard_3-2-1_108073_2023-07-10_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-09-10 09:41:04	ga_ls9c_ard_3-2-1_094074_2023-09-10_final.stac-item
2023-09-14 10:53:40	ga_ls9c_ard_3-2-1_106070_2023-09-14_final.stac-item
2023-09-18 10:33:44	ga_ls9c_ard_3-2-1_102082_2023-09-18_final.stac-item
2023-09-21 09:27:20	ga_ls9c_ard_3-2-1_091086_2023-09-20_final.stac-item
2023-09-24 09:52:14	ga_ls9c_ard_3-2-1_096071_2023-09-24_final.stac-item
2023-09-26 11:19:07	ga_ls9c_ard_3-2-1_110072_2023-09-26_final.stac-item
2023-09-28 11:11:08	ga_ls9c_ard_3-2-1_108083_2023-09-28_final.stac-item
2023-10-05 09:39:20	ga_ls9c_ard_3-2-1_093085_2023-10-05_final.stac-item
2023-10-09 09:16:15	ga_ls9c_ard_3-2-1_089089_2023-10-08_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years