You want to ensure that you create accurate training samples. If you are not sure about the exact location of a tree, it is OK to skip it.You can zoom and pan around the map to make digitizing easier but be sure to digitize as many of the trees within the extent of the bookmark as you can.Here are a few details to help you as you identify the trees: When you're finished with this first bookmark's extent, you'll have approximately 180 samples recorded in the Training Samples Manager pane. Browse to the Databases folder and double-click the Results geodatabase. On the ribbon, on the Map tab, in the Layer group, click Add Data.
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If you would like extra guidance to help you understand how to draw these circles, or if you would like to skip digitizing the trees, a training sample dataset is available in the folder you downloaded.
You'll find and download the imagery for this study from OpenAerialMap, an open-source repository of high-resolution, multispectral imagery. Additionally, to calculate tree health, you'll need an image with spectral bands that will enable you to generate a vegetation health index. The model will only be able to identify the palm trees if the pixel size is small enough to distinguish palm canopies. Download the imageryĪccurate and high-resolution imagery is essential when extracting features. For the model to recognize what it's tasked with finding, you need to define images of palm trees so that it can identify similar pixels and tree sizes. Once you have the imagery, you'll create training samples and convert them to a format that can be used by a deep learning model. The first step is to find imagery that shows Kolovai, Tonga, and has a fine enough spatial and spectral resolution to identify trees.
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To simplify the process, you'll use a deep learning model in ArcGIS Pro to identify trees, then calculate their health based on a measure of vegetation greenness. Inventorying and assessing the health of each palm tree on the Kolovai, Tonga, plantation would take a lot of time and a large workforce.
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