Selecionando pixels em um raster com base na distância como uma função da altura deles a partir de pixels em um segundo raster

Question

<\/HEAD>Estamos trabalhando em um projeto que analisa pontos potenciais de travessia para Squirrel Gliders entre manchas de árvores em ambos os lados de uma rodovia. Mapeamos a vegetação sobre fotos aéreas e a fórmula para distâncias potenciais de voo que usaremos é "x"=1,8 x altura da árvore. Eu tenho um modelo digital de elevação das alturas das árvores que posso usar. O que eu gostaria de fazer é ter um raster (Raster A) de um lado da estrada que tenha valores 0 (sem potencial de pouso) e 1 (1 sendo locais aceitáveis para pouso), o segundo raster (Raster B) do outro lado da rodovia terá valores 0 (sem vegetação para decolagem) e onde houver vegetação aceitável para decolagem, o valor de cada pixel será a altura do dossel da árvore daquele pixel.<\/P> O resultado que eu gostaria de tentar alcançar é criar um novo raster de saída (Raster C) mostrando apenas onde: pixels do Raster B são identificados que estão dentro de uma distância de 1,8 vezes seu valor (altura) a partir de qualquer pixel com valor 1 no Raster A.<\/P> Sou novo neste fórum e não espero que alguém faça todo o trabalho por mim, mas só quero tentar não desperdiçar o tempo e dinheiro do meu departamento se eu estiver indo pelo caminho errado ao abordar este problema. Tenho certeza de que existem outras formas de abordar isso também.. Não tenho experiência com python ou model builder, mas se alguém puder me assegurar que o que quero fazer pode ser feito e me direcionar sobre como começar e qual tipo de ferramenta\/script usar para trabalhar nisso, ficarei muito grato.<\/P><\/BODY><\/HTML>

GabrielUpchurch1 · Answer

I considered your vector-based idea as well and that is what I would have suggested had you responded that you did not have access to Spatial Analyst.  It will definitely meet your needs and is less complicated (and therefore faster as well).  My preference is towards raster analysis and modeling when it is a possible because it offers considerably more spatial analysis possibilities and allows for more creativity and flexibility than vector data.  Something to consider, I try to avoid converting between raster and vector data unless absolutely necessary due to the potential to introduce inaccuracies into your data.  If you might do further spatial analysis beyond just obtaining suitable takeoff sites then I would give some advance consideration to the possible need for any data conversions that would be necessary.  With attention to detail, the right settings and some QA/QC, you can definitely convert between raster and vector data successfully.  I just want to throw that out there because I often see users converting back and forth all willy-nilly with little thought for the processes they are undertaking.

Best of luck to you!

LisaRedmond1 · Answer

Thanks Gabriel,

That sounds like a great suggestion and yes I was thinking however I did it would have to be one way and then flip the scenario. Overnight I thought about it and also came up with a sneaky alternative – by converting my potential takeoff gridcells to points with a table value of their height. Then doing a find nearest polygon distance (suitable landing layer)and the table would be populated with that distance. Then just use calculator to populate another field with the 1.8 x height and then just have a fourth field showing which points have a flight formula value greater than  their distance to nearest landing polygon. Again a one way analysis.  Fantastic to know I have a couple of options to play with and now to just edit and fine tune my data before running it all.

Thanks again for taking the time to help me. It is very much appreciated.

Lisa Redmond

GabrielUpchurch1 · Answer

Hi Lisa,

Here is an (untested) idea.  It is a one-way analysis so if you want to consider travel in both directions, you will need to reverse and repeat for the other side of the road.

1. Create a single raster dataset that covers your entire area of interest (AOI = both sides of road).  This dataset should only contain values of 1 for acceptable landing locations.  All other cells in the AOI should be NoData.  Let’s call this dataset Landing.

2. Run Landing through the Euclidean Distance tool in the Spatial Analyst ‘Distance’ toolset:  Euclidean Distance—Help | ArcGIS for Desktop .  This tool will calculate distances from all NoData cells to the nearest landing location.  The output dataset, let’s call it Distance, will contain cell values of 0 for all landing locations and actual distance values for all the original NoData cells.

3. Create a single raster dataset that covers your entire AOI that contains height values for all takeoff locations and 0 values for all other cells.  Let’s call this dataset Takeoff.

4. Now multiply the Distance dataset by the Takeoff dataset.  You can use the Times tool (Spatial Analyst ‘Math’ toolset) or Raster Calculator (Spatial Analyst ‘Map Algebra’ toolset).  This dataset will give you the actual distance to height relationship between the takeoff and landing locations.  Let’s call it Actual_D2H.

5. Create a single raster dataset that covers your entire AOI that contains the comparison distance to height relationship (1.8 x tree height).  You can do this by multiplying the Takeoff dataset by 1.8.  Once again you can use the Times tool or Raster Calculator to create this dataset.  Let’s call it Comparison_D2H.

6. Finally, you can use a Conditional statement in Raster Calculator to change all values in Actual_D2H to 0 (or NoData) that have a value greater than the acceptable distance value in Comparison_D2H.  This will leave you with only cell values that contain distances less than 1.8 times the takeoff locations height.  Conditional Statements help:  Conditional evaluation with Con—Help | ArcGIS for Desktop

This is just a rough idea and there are many details that would need to be worked out but I think it may help get you where you need to go.  Let me know if you have any questions or need further explanation on any of the steps.