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This machine learning dataset predicts the extent of the waterbodies identified within Northland Region. |
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This machine learning dataset predicts the extent of the waterbodies identified within Northland Region. |
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Biospatial Limited Photoblique Limited Auckland Council Northland Regional Council |
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5000 |
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[] |
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<DIV STYLE="text-align:Left;"><DIV><DIV><UL><LI><P><SPAN STYLE="font-size:10pt">Wetlands were mapped using a combination of LiDAR (2018) and RGBI (2014-2016) imagery captured by Northland and Auckland Councils. Waterbodies were validated using a combination of Photoblique and GIS desktop techniques. </SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">Slope, Spectral signatures, Topographic wetness index and vegetation structure were were inputs into the machine learning model. </SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">Information is current to the datasets available. </SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">The spatial extents can be used as a guide for where a waterbody exists</SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">Data was derived using a combination of machine learning model training and manual output validation. </SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">Elevation data has been attached for data overlay in Photoblique. </SPAN></P></LI><LI><P><SPAN>Data is presented using a polygon approach for ease of display.</SPAN></P></LI></UL><P><SPAN>Data Limitations: </SPAN></P><UL><LI><P><SPAN>Data may be subject to some false positive and/or false negative results. </SPAN></P></LI><LI><P><SPAN>The spatial extents can be used as a guide for where waterbodies exist </SPAN></P></LI><LI><P><SPAN>Scale is created to a 1m resolution </SPAN></P></LI><LI><P><SPAN>Data is a representation of the capture date of the imagery and LiDAR </SPAN></P></LI></UL></DIV></DIV></DIV> |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Northland Regional Council and Biospatial Limited maintain ownership of the dataset. </SPAN></P></DIV></DIV></DIV> |
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| title:
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Biospatial_PondPolygones_Nrth20240401TEMP |
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| tags:
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["Waterbodies","Northland","Wetlands","Machine learning"] |
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en-US |
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150000000 |
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