透水性のある表面を特定するためにMultiband imageryを使用しようとしています

Question

こんにちは、このチュートリアル https://learn.arcgis.com/en/projects/calculate-impervious-surfaces-from-spectral-imagery/ を使って、私たちの都市での植樹の可能性がある透水性のある表面を見つけています。Classify the imageryのステップ3でRunをクリックすると、処理は数時間、約20時間ほど続きますが、これはエリアの大きさを考えれば予想されることです。「ERROR 003436: No training samples found for these classes: Roof(Black Grey), ImperviousShadow, ArtificialTurf, Crop. Failed to execute (TrainSupportVectorMachineClassifier). Failed at 2022年2月24日 13:25:05 (経過時間: 48分34秒)」のようなエラーが出ますが、サンプルには作物地を示して保存しました。<\/P> 2回目の実行では「ERROR 003436: No training samples found for these classes: Roof(Black Grey), ImperviousShadow, ArtificialTurf, Crop. Failed to execute (TrainSupportVectorMachineClassifier). Failed at 2022年2月25日 18:01:58 (経過時間: 47分33秒)」というエラーが出て、再び影を示しました。 <\/P> 最終的に実行して結果を得たとき、それらは非常に不正確で、例えば開放水域を作物地として識別していました。指示に従ったので問題が何か分かりません。大量の画像シリーズを処理しようとしているからでしょうか？<\/P> <\/P>

IvanPotic · Answer

I had the same problem with the "ERROR 003436".

I want to confirm that @Taren_Esri first suggestion solved my problem.

I clipped the satellite imagery twice. First clip was wider area of Interest and second clip was the "area of interest", significantly smaller part. I was trying to classify smaller clipped part ignoring the fact that I noticed that when zooming to layer I have some invisible buffer (no data or some other problem that arose during clipping). Reverting the classification process to the wide clipped footage saved the day and the new classification process went smoothly. I used previously collected training samples from correctly formatted shape file.

Taren_Esri · Answer

For the sake of future reference, I recently worked on a case that resolved this same issue. If you encounter this error message, check two things. The first is that you are running your analysis on the same and original raster you trained your classes on. This means it can't have been clipped, masked, etc.  The second is ensuring your input training sample feature class is actually split and individual features that are appropriately labeled for their class. This means no multipart features. You can run Multipart to Singlepart to split them up if needed. Hope this helps someone!

dvandommelen · Answer

I've received this same error. Anyone know an answer?