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GCS_GDA_1994
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GDA_1994_Australia_Albers
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OBJECTID
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OID
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Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
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P_CLASS
Double
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RCI
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Length of feature in internal units.
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Positive real numbers that are automatically generated.
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Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
{3B0D503E-8964-4790-B660-02C1F081014E}
x
dataset
Department of Environment and Science
Science Leader, Remote Sensing Centre
+61731705688
41 Boggo Road
Dutton Park
QLD
4000
dan.tindall@des.qld.gov.au
20230704
ArcGIS Metadata
1.0
Queensland Spatial Catalogue
Download Service
Department of Resources
Open the Queensland Spatial Catalogue (QSpatial). Select the large SEARCH button and all available records are displayed. Select one of the four filter options provided and then the further options within the filter. The resultant search is then displayed. Select your record and complete the order.
http://qldspatial.information.qld.gov.au/catalogue/
downloadableData
10.0
ESRI ArcGIS Server Geoportal Extension Content Type
Department of Environment and Science
Remote Sensing Centre
From the Queensland Spatial Catalogue as
400
http://qldspatial.information.qld.gov.au/catalogue/custom/search.page?q=%22Active crop groups 1987 to 2023%22
Active crop groups 1988 ongoing
DP_ACTIVE_CROP_1987_2023.zip
2023-04-12
Department of Environment and Science
Science Leader, Remote Sensing Centre
Department of Environment and Science
Science Leader, Remote Sensing Centre
Department of Resources
QSpatial Support
(07) 3330 4101
Opendata@resources.qld.gov.au
This dataset shows the broad groups of crops grown in Queensland's Strategic Cropping Land, for a particular growing-season. The predicted group is stored in the attribute table (field 'CLASS'), along with the probability of the prediction (field 'P_CLASS', the larger this value, the more certain is 'CLASS').
The statistical classifier predicts these classes of crops in summer: "Cotton", "Sugarcane", and "OtherCrop" (predominantly sorghum, but also includes, e.g., maize, mung bean, peanut).
In winter, the statistical classifier predicts only a "Crop" class (i.e. whether a crop was grown or not).
Note that the extent of the mapping changes by season: in winter the maps are restricted to what we define as the 'western' cropping zone only; in summer, predictions extend further, into the potential sugarcane-growing areas of the 'coastal' zone (which includes northern NSW). Any other crops grown in the coastal zone, apart from sugarcane, are not considered.
Credits: © State of Queensland (Department of Environment and Science), 2023
Department of Environment and Science
Science Leader, Remote Sensing Centre
+61731705688
41 Boggo Road
Dutton Park
QLD
4000
AU
dan.tindall@des.qld.gov.au
Spatial Data Format
1
AGRICULTURE
AGRICULTURE-Crops
LAND-Cover
LAND-Use
ANZLIC Search Words
Sciences
Queensland Open Data Categories
Active
crop
active crop
Common name
Theme keywords input by metadata
publisher
AGRICULTURE
AGRICULTURE-Crops
LAND-Cover
LAND-Use
Sciences
Active
crop
active crop
Creative Commons Attribution 4.0 International
© State of Queensland (Department of Environment and Science) 2023
This material is licensed under a Creative Commons - Attribution 4.0 International licence.
The Department of Environment and Science requests attribution in the following manner:
© State of Queensland (Department of Environment and Science) 2023.
Resource Access Level
Spatial Information Resource
138
155
-29.5
-9
2023-04-12
2023-04-12
true
144.611589
153.582915
-29.767071
-15.520075
Public
Metadata Access Level
All the data described here has been generated from the analysis of satellite imagery at a spatial resolution of approximately 30 m. A grid of Landsat TM, ETM+ and OLI data were supplemented by Sentinel-2 (after 2016) and MODIS (after 2000) imagery when large temporal data gaps occurred.
Breiman, L. (2001). Random Forests. Machine Learning, 45, 5-32. http://dx.doi.org/10.1023/A:1010933404324 Bunting, P., Clewley, D. Lucas, R.M. and Gillingham, S. (2014). The Remote Sensing and GIS Software Library (RSGISLib). Computers and Geosciences, 62, 216-226. http://dx.doi.org/10.1016/j.cageo.2013.08.007. Danaher, T. and Collett, L (2006). Development, Optimisation and Multi-temporal Application of a Simple Landsat Based Water Index. Proceedings of the 13th Australasian Remote Sensing and Photogrammetry Conference, Canberra, Australia, November 2006. Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013). An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens., 5(1), 83-109. http://dx.doi.org/10.3390/rs5010083. Flood, N. (2014). Continuity of Reflectance Data between Landsat-7 ETM+ and Landsat-8 OLI, for Both Top-of-Atmosphere and Surface Reflectance: A Study in the Australian Landscape. Remote Sensing, 6, 7952-7970. http://dx.doi.org/10.3390/rs6097952. Schmidt, M., Pringle, M., Devadas, R., Denham, J., and Tindall, D. (2016). A Framework for Large-Area Mapping of Past and Present Cropping Activity Using Seasonal Landsat Images and Time Series Metrics. Remote Sensing, 8, 312; http://dx.doi.org/doi:10.3390/rs8040312.
EPSG Geodetic Parameter
Dataset
2007-07-16
Version 6.13
EPSG
6.12(9.3.0.0)