Spatial tools for LiDAR based watershed management and forestry analysis integrated in gvSIG
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Franceschi, Silvia (HydroloGIS - Free University of Bolzano)
Antonello, Andrea (HydroloGIS)
In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to: preprocessing of LiDAR raw data (LAS), creation of raster derived products, normalization of the intensity values and tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach and implemented the extraction of tops and crowns from local maxima, the region growing method and the watershed method, all can be applied on LiDAR derived raster datasets as well as point clouds of raw data. An automatic validation procedure has been developed considering an Optimizer Algorithm based on Particle Swarm (PS) and a matching procedure which takes the position and the height of the extracted trees respect to the measured ones and iteratively tries to improve the candidate solution changing the models' parameters. On a watershed level, the resulting extracted trees with position and main characteristics, can be used for forestry management or for the evaluation of natural hazards (hillslopes stability, large wood transportation during floods).
 Okay, let's start with the last talk of the session. This is Celia Franceschi from Italy, of the company Hydrologist. She's going to talk about spatial tools that she brought into her research. She also is a PhD student at the Free University of Polzano, and where she does some water management and forestry tools based on light data. And thanks for coming to this presentation. As Andrea already introduced me, I am an environmental engineer, specialized in hydrology and hydraulics and gemmorphology. I'm a co-founder of Hydrologist, which is a small engineering company based in Italy, the very northern part of Italy. And from this year, we are part of the GVCG Association. My work is mainly dedicated to the development of scientific models in the fields of hydrology, hydrology and forestry. I'm also a PhD student and an OSDO charter member. The tools that we develop in hydrology are integrated in a library, it's a free and open source library, that it is called JAGRAS tools. This is an open source, just a special library, focused on almost on hydrogeomorphological analysis and environmental modeling in general, also forestry and some geological tool. The JAGRAS tool library has been developed since 2002 with the contribution of the University of Trento of the auto machine package in Gras. Then some important step of the evolution of the code in 2005 with the foundation of hydrology, the main development and coordination of the project passed from the University to hydrology. And then we continued to develop this library with integrating the full supports of shapefiles and post-GIS since before all the modules were raster based. In 2007 we decided to move to the UDIC framework and we integrated these JAGRAS tools in UDIC. Then we continued in general to develop the library, integrating new models but also new formats like NETCDF and also some environmental framework to link scientific models and to obtain a simulation to finalize some environmental analysis. Recently, in 2013, we integrated some tools for the connection with mobile phones and preparing and reading the data for digital field mapping. And finally in 2014, when I started my PhD, we started to implement the LESTO library, which is a library dedicated to LiDAR analysis in the field of forestry. And then the last step has been done at the end of 2015 and 2016 with the integration of the library in GVC. As this integration is done, making the library as a plugin in GVC. If you can download the JAGRAS tool library and then use the standard plugin installation of GVC, once you install this library, you will find another voice in the menu that it is the JAGRAS tool menu and in which you will find some other entries. One of these entries is the special toolbox. If you select the special toolbox, a dedicated window will appear on the main program window. As you see here, in the left side of the window, there is the list of the modules. The modules are divided in sections and subsections. You can select the module or you can search the module in the special field in the top of this section. And in the bottom, here you cannot see them, but there is the possibility to select some different options which are to select to run an experimental module. These modules are modules that work, but they did not finish yet the complete testing procedure. Then there is the possibility to run in the bug mode, which can help you to find possible problems in the models or can help you to ask for a support in the community mailing list. And then the most important option is to set the maximum memory. If you have more memory available on your computer, you can give the memory to the modules and then so you can run modules on bigger areas or on data with higher resolution. When you select a module on the left side, in the right side of this panel, you will have all the parameters to fill and the possibility to select directly the layer that are loaded in the GVC view. Then finally, you can run the model using one of the options there, running options, which is running the model as it is or creating a script with a model so you then can edit this script or make some loop in the script or you can run an external script that you already edited. These modules, during the next month, we will also integrate the modules in a way that they will be available also in the standard script and language of GVC that it is in Python. So maybe some of you is more practical on this. So let's see some of the tools that can be helpful for analysis, for watch and analysis and in particular for the analysis of natural hazards in a watershed. The first section I will present to you is the Horta machine. This is the core section of the Jegras tools and it has mainly modules regarding geomorphology. For example, there are modules for the extraction of the drainage directions, the total contributing areas, it is possible to extract the network, the watershed and give also hierarchical enumeration of network and watershed. Then there are modules for the evaluation of the scale distance to the outlet and other for the evaluation of some hydrological and geomorphological attributes and indexes. Some important tools are also available inside the statistics section. We have almost module for interpolating metadata. One is the Kriging. We implemented two modules, two different algorithms for Kriging. One is based on a given variogram that you can also create with your data inside the Jegras tools and the other one is called Jemi because it is just another meta interpolator and can be used especially for temperature, pressure, humidity and wind velocity because it takes in account both the position of the metro station but also the different elevation. So with this kind of metadata, the different elevation between the station is very important for the interpolation. Then next module is PICFLOW. PICFLOW is a semi-distributed hydrological model for the evaluation of the maximum discharge within four small catchments. It works for a given precipitation event but also for using some statistical information of rainfalls like the output of the intensity duration curves and it can create the maximum discharge for the river section at different retron times. So it is useful for creating the data for the flood directive at least here in Europe. We have also a very simple one-dimensional hydraulic model integrated in the Jegras tools library. This is based on the Sanvenant equations and it consists of all the input and output data are GIS based so you have the geometries with a lot of attributes, the one that are needed by the program and also the output of the program is given as attributes to the river sections for the SanctuPaul. It calculates the water depth, the velocity and the fluid parameters in each section. It is very simple but in fact it is not so simple because it can handle also lateral attributes of inflow and like conferences and outtakes, maybe some power plants or some stuff like that. In the section of hydraulic we also have modules to prepare the data for the Jegras 1D model. Always in the field on natural hazard we have the possibility also a module to evaluate the hill slope stability. It's a Charleston. With this module it is possible to obtain a map with the stability condition for a given precipitation but also a map with a critical precipitation in each pixel. You can know which pixels are always stable, unconditionally stable, unconditionally unstable. Another one, since we live in a mountain region we have a lot of events with flood with high volume of sediment. We implemented also a very simple module. It is not a bidimensional hydraulic module but it is based on geomorphology. It's a module for the evaluation of the triggering points, the propagation in the network and then the spread of the debris on the alluvial fans. As you can see here, this module, even if it is very simple, it gives the idea of where the debris will flow and also the amount of the sediment, the transported sediment. Here is the result of the simulation and in Magenta you will find a previous event simulated with this software. Then in the Jgrastool library we have also a lot of tools for the evaluation for analysis and extraction of data on rasters and vectors. For example, we have tools for raster converter, map calculation, mosaic of rasters and for vectors also for analysis of last data, the ones of LiDAR, LiDAR point cloud, victorialization and also tools to connect raster data and vector data and give attributes to one or rasterize tools. Two tools that are at least very useful in the analysis of our watershed are this one. One is this and then I will present the other one. The first one is the profile extractor. This tool is a bit different from other GIS. You can give an input shapefile with all the line strings that you want to have the profile and the output is a CSV file with all the profiles for each of these lines. Then you can use this CSV file in your spreadsheet to see the profile. This tool is very interesting. It is called Bob the Builder. We use it for modeling artifacts in the evaluation models so you can create an artifact and then make a simulation considering this in your simulation, artifacts that are not still in the DTM and you can build things but also erode things so you can definitely insert whatever you want in a digital terrain model. Then there is the mobile section where you can prepare your own data to use as background in the application for digital field mapping. Then you can extract the data from the project and directly transform it in shapefiles. Then we have one of the last parts we implemented is the LESTO library. LESTO is the Stairs for LiDAR Empower Science Toolbox open source. It is developed in collaboration with the Free University of Bolzano and it is mainly dedicated to the analysis of LiDAR data. It contains different sections as you can see here dedicated to filtering, analyzing and managing of LiDAR data but also tools to rasterize the LiDAR point cloud. For example, based on different algorithms like the adaptive team or the inverse distance weight and so on to create digital terrain models and also digital surface models. These buildings usually make some confusion in the analysis of vegetation. We decided also to extract, to make a model to extract the buildings from the LiDAR dataset. This model is the one, this is a result of the model. There is the possibility to make, it is a two step model and the red polygons are the buildings in output of the second step of the model that are quite, the results are quite good. And then there is the main section of the LESTO library that is dedicated to the extraction of the vegetation and in particular we decided to follow the approach of individual tree. So we changed to detect the position and the main characteristics of each single tree. We implemented for now two modules based on the algorithm of local maxima. One is raster based and one is point cloud based. And the last part is a set of modules dedicated to the evaluation of the large wood contribution during flooding events that I developed during the summer of code of 2014 and 2016. And these tools are GIS based tools for predicting the magnitude of large wood of logs inside the rivers during flooding events. And they consider two kinds of main processes that are related to wood debris. One is the recruitment from the hill slopes and one is the transportation of the logs downstream in the network. These are the main characteristics of these modules. It is a structure that is the river section directly from the DTM, but there is also the possibility to insert a fixed section with fixed width, so like bridges and dams. And then they are based on an hydraulic, they consider the hydraulic conditions, so they run inside the hydraulic 1D model for the evaluation of the water depth and the velocity of the flow to be able to carry the logs. And the vegetation can be given as a contribution, as a model considering canopy height model and forest standard volume or as a vector of single trees. And then these trees will be propagated downstream. And the propagation is based on a double check on the length of the logs and the width of the section and on the diameter of the logs and the water depth. And these are almost the results. This is integration in GBC. You can see the input and output section and the sections are these where you can see the clogging section and the volume of the logs that are stopped in each section. So thank you. If you have any question or if you want to download the things, you can follow this link or ask directly to me. Thank you. Questions? Sure. Yeah, I had a question on the building detection algorithm. You said it's a two-step algorithm. Could you just give a bit more detail on how you're detecting your buildings? Okay. It is a two-step because the first step extracts almost the main polygons that could be, could be buildings, and the second step filters this polygon on considering how many, the percentage of the points that are on the ground and stuff like that. So it is definitely a simple algorithm, but it works like that. I was curious how well are you doing in defining single trees and finding single trees in your lighted outside? Does it also work well if you have a really forested area or is it more isolated trees? No, no. We work on forested area, and for now we have good results with these tools because we also integrated an auto particle swarming optimizer for this. So we run a lot of simulation automatically. And the detection of single trees in conifer of forest are almost 80% or much more than 80%, but at least 80%. And we are now finishing the implementation of another tool that it is not based on local maxima, but it is based on another algorithm. And with this, the performance is better on conifers, we are now testing it on broadleaf forest, but conifer forest, even if the structure is multi-layered, the results are good. And you are also able to get the size of the stem from it? No. Okay, we didn't try. We tried with the terrestrial ladder. So with this, it's a bit easier because you just cut it, but we didn't try with the air data. Are you filtering the data? So you only take the classified for the first return or when you are detecting single trees or do you take all points? So in general, we take all points, but it really depends on the kind of forest and on the density of forest, but we will use all. And we don't use the classification given by the provider. We just does some step for our tools. Have you tried in mixed areas or mixed trees? We are now trying with this. It is part of my PhD thesis. And I have good results, not so good like in conifer forest, but with the algorithm that is not still published, the results are definitely better. So in the next month, you will see also the other algorithms in the library. Thank you. Any other question? We have still a bit of time. How do these processes scale with like size of data sets? It depends. If you have big data sets, they will take a lot of time and a powerful computer. If you have small watershed 1, 2 square kilometers, they are fast. It depends also on the memory you give. So if you have more memory, much power, you can work it. Also on a laptop, I do some elaboration also there. Thank you. Regarding the last issue about log contribution to the stream, how do you define how do you find out the volume and how does that figure come in? It depends on the input vegetation data. If you have the canopy height model and forest stand, there is a simplified module to evaluate the volume of vegetation in each river section. We extract the sub-basin referring to each section of the river. So we have all the sub-basins and all the area. The area that is unstable inside this sub-basin or the area flooded will contribute to the wood. So the vegetation that is in these pixels contributes to the amount of wood that is in each section. We do a statistical elaboration on the height for the length of the logs and then on the volume. We calculate the volume with some allometric function that are input of the model. So if you have your allometric function, you can put it in there. And then we calculate the volume and the, let's say, average length of the vegetation in each section. And then with the 1D hydraulic model, we propagate these logs downstream and we verify the condition for the hydraulic condition and geometric condition for passing each section. If some logs will be bigger than the width of the section or the diameter is bigger than the water depth, so they stop and they force to stop almost a part of the things behind. So you have good algorithms for estimating the, how much materials will be loosened from the slopes and from the areas around? So we consider unstable and connected areas. So we have a stability algorithm, like the one I showed, and a connectivity model inside that is based on the slope and on the distance from each cell. Yeah. Okay. Okay, thank you very much to everyone and they're serving some food, so thanks Silvia.
 Okay, let's start with the last talk of the session.  This is Celia Franceschi from Italy, of the company Hydrologist.  She's going to talk about spatial tools that she brought into her research.  She also is a PhD student at the Free University of Polzano, and where she does some water management  and forestry tools based on light data.  And thanks for coming to this presentation.  As Andrea already introduced me, I am an environmental engineer, specialized in hydrology and hydraulics  and gemmorphology.  I'm a co-founder of Hydrologist, which is a small engineering company based in Italy,  the very northern part of Italy.  And from this year, we are part of the GVCG Association.  My work is mainly dedicated to the development of scientific models in the fields of hydrology,  hydrology and forestry.  I'm also a PhD student and an OSDO charter member.  The tools that we develop in hydrology are integrated in a library, it's a free and  open source library, that it is called JAGRAS tools.  This is an open source, just a special library, focused on almost on hydrogeomorphological  analysis and environmental modeling in general, also forestry and some geological tool.  The JAGRAS tool library has been developed since 2002 with the contribution of the University  of Trento of the auto machine package in Gras.  Then some important step of the evolution of the code in 2005 with the foundation of  hydrology, the main development and coordination of the project passed from the University  to hydrology.  And then we continued to develop this library with integrating the full supports of shapefiles  and post-GIS since before all the modules were raster based.  In 2007 we decided to move to the UDIC framework and we integrated these JAGRAS tools in UDIC.  Then we continued in general to develop the library, integrating new models but also new  formats like NETCDF and also some environmental framework to link scientific models and to  obtain a simulation to finalize some environmental analysis.  Recently, in 2013, we integrated some tools for the connection with mobile phones and  preparing and reading the data for digital field mapping.  And finally in 2014, when I started my PhD, we started to implement the LESTO library,  which is a library dedicated to LiDAR analysis in the field of forestry.  And then the last step has been done at the end of 2015 and 2016 with the integration  of the library in GVC.  As this integration is done, making the library as a plugin in GVC.  If you can download the JAGRAS tool library and then use the standard plugin installation  of GVC, once you install this library, you will find another voice in the menu that it  is the JAGRAS tool menu and in which you will find some other entries.  One of these entries is the special toolbox.  If you select the special toolbox, a dedicated window will appear on the main program window.  As you see here, in the left side of the window, there is the list of the modules.  The modules are divided in sections and subsections.  You can select the module or you can search the module in the special field in the top  of this section.  And in the bottom, here you cannot see them, but there is the possibility to select some  different options which are to select to run an experimental module.  These modules are modules that work, but they did not finish yet the complete testing procedure.  Then there is the possibility to run in the bug mode, which can help you to find possible  problems in the models or can help you to ask for a support in the community mailing  list.  And then the most important option is to set the maximum memory.  If you have more memory available on your computer, you can give the memory to the modules and  then so you can run modules on bigger areas or on data with higher resolution.  When you select a module on the left side, in the right side of this panel, you will  have all the parameters to fill and the possibility to select directly the layer that are loaded  in the GVC view.  Then finally, you can run the model using one of the options there, running options,  which is running the model as it is or creating a script with a model so you then can edit  this script or make some loop in the script or you can run an external script that you  already edited.  These modules, during the next month, we will also integrate the modules in a way that they  will be available also in the standard script and language of GVC that it is in Python.  So maybe some of you is more practical on this.  So let's see some of the tools that can be helpful for analysis, for watch and analysis  and in particular for the analysis of natural hazards in a watershed.  The first section I will present to you is the Horta machine.  This is the core section of the Jegras tools and it has mainly modules regarding geomorphology.  For example, there are modules for the extraction of the drainage directions, the total contributing  areas, it is possible to extract the network, the watershed and give also hierarchical enumeration  of network and watershed.  Then there are modules for the evaluation of the scale distance to the outlet and other  for the evaluation of some hydrological and geomorphological attributes and indexes.  Some important tools are also available inside the statistics section.  We have almost module for interpolating metadata.  One is the Kriging.  We implemented two modules, two different algorithms for Kriging.  One is based on a given variogram that you can also create with your data inside the  Jegras tools and the other one is called Jemi because it is just another meta interpolator  and can be used especially for temperature, pressure, humidity and wind velocity because  it takes in account both the position of the metro station but also the different elevation.  So with this kind of metadata, the different elevation between the station is very important  for the interpolation.  Then next module is PICFLOW.  PICFLOW is a semi-distributed hydrological model for the evaluation of the maximum discharge  within four small catchments.  It works for a given precipitation event but also for using some statistical information  of rainfalls like the output of the intensity duration curves and it can create the maximum  discharge for the river section at different retron times.  So it is useful for creating the data for the flood directive at least here in Europe.  We have also a very simple one-dimensional hydraulic model integrated in the Jegras tools  library.  This is based on the Sanvenant equations and it consists of all the input and output data  are GIS based so you have the geometries with a lot of attributes, the one that are needed  by the program and also the output of the program is given as attributes to the river  sections for the SanctuPaul.  It calculates the water depth, the velocity and the fluid parameters in each section.  It is very simple but in fact it is not so simple because it can handle also lateral  attributes of inflow and like conferences and outtakes, maybe some power plants or some  stuff like that.  In the section of hydraulic we also have modules to prepare the data for the Jegras  1D model.  Always in the field on natural hazard we have the possibility also a module to evaluate  the hill slope stability.  It's a Charleston.  With this module it is possible to obtain a map with the stability condition for a given  precipitation but also a map with a critical precipitation in each pixel.  You can know which pixels are always stable, unconditionally stable, unconditionally unstable.  Another one, since we live in a mountain region we have a lot of events with flood with high  volume of sediment.  We implemented also a very simple module.  It is not a bidimensional hydraulic module but it is based on geomorphology.  It's a module for the evaluation of the triggering points, the propagation in the network and  then the spread of the debris on the alluvial fans.  As you can see here, this module, even if it is very simple, it gives the idea of where  the debris will flow and also the amount of the sediment, the transported sediment.  Here is the result of the simulation and in Magenta you will find a previous event simulated  with this software.  Then in the Jgrastool library we have also a lot of tools for the evaluation for analysis  and extraction of data on rasters and vectors.  For example, we have tools for raster converter, map calculation, mosaic of rasters and for  vectors also for analysis of last data, the ones of LiDAR, LiDAR point cloud, victorialization  and also tools to connect raster data and vector data and give attributes to one or  rasterize tools.  Two tools that are at least very useful in the analysis of our watershed are this one.  One is this and then I will present the other one.  The first one is the profile extractor.  This tool is a bit different from other GIS.  You can give an input shapefile with all the line strings that you want to have the profile  and the output is a CSV file with all the profiles for each of these lines.  Then you can use this CSV file in your spreadsheet to see the profile.  This tool is very interesting.  It is called Bob the Builder.  We use it for modeling artifacts in the evaluation models so you can create an artifact and then  make a simulation considering this in your simulation, artifacts that are not still in  the DTM and you can build things but also erode things so you can definitely insert  whatever you want in a digital terrain model.  Then there is the mobile section where you can prepare your own data to use as background  in the application for digital field mapping.  Then you can extract the data from the project and directly transform it in shapefiles.  Then we have one of the last parts we implemented is the LESTO library.  LESTO is the Stairs for LiDAR Empower Science Toolbox open source.  It is developed in collaboration with the Free University of Bolzano and it is mainly  dedicated to the analysis of LiDAR data.  It contains different sections as you can see here dedicated to filtering, analyzing  and managing of LiDAR data but also tools to rasterize the LiDAR point cloud.  For example, based on different algorithms like the adaptive team or the inverse distance  weight and so on to create digital terrain models and also digital surface models.  These buildings usually make some confusion in the analysis of vegetation.  We decided also to extract, to make a model to extract the buildings from the LiDAR dataset.  This model is the one, this is a result of the model.  There is the possibility to make, it is a two step model and the red polygons are the  buildings in output of the second step of the model that are quite, the results are quite  good.  And then there is the main section of the LESTO library that is dedicated to the extraction  of the vegetation and in particular we decided to follow the approach of individual tree.  So we changed to detect the position and the main characteristics of each single tree.  We implemented for now two modules based on the algorithm of local maxima.  One is raster based and one is point cloud based.  And the last part is a set of modules dedicated to the evaluation of the large wood contribution  during flooding events that I developed during the summer of code of 2014 and 2016.  And these tools are GIS based tools for predicting the magnitude of large wood of logs inside  the rivers during flooding events.  And they consider two kinds of main processes that are related to wood debris.  One is the recruitment from the hill slopes and one is the transportation of the logs  downstream in the network.  These are the main characteristics of these modules.  It is a structure that is the river section directly from the DTM, but there is also the  possibility to insert a fixed section with fixed width, so like bridges and dams.  And then they are based on an hydraulic, they consider the hydraulic conditions, so they  run inside the hydraulic 1D model for the evaluation of the water depth and the velocity  of the flow to be able to carry the logs.  And the vegetation can be given as a contribution, as a model considering canopy height model  and forest standard volume or as a vector of single trees.  And then these trees will be propagated downstream.  And the propagation is based on a double check on the length of the logs and the width of  the section and on the diameter of the logs and the water depth.  And these are almost the results.  This is integration in GBC.  You can see the input and output section and the sections are these where you can see the  clogging section and the volume of the logs that are stopped in each section.  So thank you.  If you have any question or if you want to download the things, you can follow this link  or ask directly to me.  Thank you.  Questions?  Sure.  Yeah, I had a question on the building detection algorithm.  You said it's a two-step algorithm.  Could you just give a bit more detail on how you're detecting your buildings?  Okay.  It is a two-step because the first step extracts almost the main polygons that could be, could  be buildings, and the second step filters this polygon on considering how many, the  percentage of the points that are on the ground and stuff like that.  So it is definitely a simple algorithm, but it works like that.  I was curious how well are you doing in defining single trees and finding single trees in your  lighted outside?  Does it also work well if you have a really forested area or is it more isolated trees?  No, no.  We work on forested area, and for now we have good results with these tools because we also  integrated an auto particle swarming optimizer for this.  So we run a lot of simulation automatically.  And the detection of single trees in conifer of forest are almost 80% or much more than  80%, but at least 80%.  And we are now finishing the implementation of another tool that it is not based on local  maxima, but it is based on another algorithm.  And with this, the performance is better on conifers, we are now testing it on broadleaf  forest, but conifer forest, even if the structure is multi-layered, the results are good.  And you are also able to get the size of the stem from it?  No.  Okay, we didn't try.  We tried with the terrestrial ladder.  So with this, it's a bit easier because you just cut it, but we didn't try with the air  data.  Are you filtering the data?  So you only take the classified for the first return or when you are detecting single trees  or do you take all points?  So in general, we take all points, but it really depends on the kind of forest and on  the density of forest, but we will use all.  And we don't use the classification given by the provider.  We just does some step for our tools.  Have you tried in mixed areas or mixed trees?  We are now trying with this.  It is part of my PhD thesis.  And I have good results, not so good like in conifer forest, but with the algorithm that  is not still published, the results are definitely better.  So in the next month, you will see also the other algorithms in the library.  Thank you.  Any other question?  We have still a bit of time.  How do these processes scale with like size of data sets?  It depends.  If you have big data sets, they will take a lot of time and a powerful computer.  If you have small watershed 1, 2 square kilometers, they are fast.  It depends also on the memory you give.  So if you have more memory, much power, you can work it.  Also on a laptop, I do some elaboration also there.  Thank you.  Regarding the last issue about log contribution to the stream, how do you define how do you  find out the volume and how does that figure come in?  It depends on the input vegetation data.  If you have the canopy height model and forest stand, there is a simplified module to evaluate  the volume of vegetation in each river section.  We extract the sub-basin referring to each section of the river.  So we have all the sub-basins and all the area.  The area that is unstable inside this sub-basin or the area flooded will contribute to the  wood.  So the vegetation that is in these pixels contributes to the amount of wood that is  in each section.  We do a statistical elaboration on the height for the length of the logs and then on the  volume.  We calculate the volume with some allometric function that are input of the model.  So if you have your allometric function, you can put it in there.  And then we calculate the volume and the, let's say, average length of the vegetation  in each section.  And then with the 1D hydraulic model, we propagate these logs downstream and we verify the condition  for the hydraulic condition and geometric condition for passing each section.  If some logs will be bigger than the width of the section or the diameter is bigger than  the water depth, so they stop and they force to stop almost a part of the things behind.  So you have good algorithms for estimating the, how much materials will be loosened from  the slopes and from the areas around?  So we consider unstable and connected areas.  So we have a stability algorithm, like the one I showed, and a connectivity model inside  that is based on the slope and on the distance from each cell.  Yeah.  Okay.  Okay, thank you very much to everyone and they're serving some food, so thanks Silvia.
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