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Spatial tools for LiDAR based watershed management and forestry analysis
- 1. Spatial tools for LiDAR based watershed management and forestry analysis Antonello Andrea, Franceschi Silvia, Tonon Giustino and Comiti Francesco FOSS4G-EU Como 16 July 2015
- 2. WHO AM I? ● co-founder of HydroloGIS with Andrea Antonello ● environmental engineer specialized in hydrology, hydraulics and geomorphology ● PhD student of Science and Technology at the Free University of Bolzano (Italy) ● developed scientific models contained in the JGrassTools library in the field of: – hydrology – hydraulics – forestry ● OSGeo Charter Member
- 3. JGRASSTOOLS ● geospatial library containing modules for: – vector and raster processing – geomorphology – forestry – mobile mapping connection ● it is the core behind the Spatial Toolbox of uDig GIS ● it can be used stand alone using the application Stage (http://bit.ly/stage_downloads): Spatial Toolbox And Geoscripting Ennvironment tool for environmental modelling
- 4. JGRASSTOOLS
- 5. JGRASSTOOLS
- 6. JGRASSTOOLS
- 7. JGRASSTOOLS
- 8. JGRASSTOOLS
- 9. JGRASSTOOLS
- 10. WHAT IS LESTO? ● Open Source ● GIS aware ● library dedicated to ● sciences that make use of ● LiDAR data Developed and maintained by HydroloGIS and the team of prof. Tonon at the Faculty of Science and Technology of the Free University of Bolzano (Italy). Contains tools for handling high resolution LiDAR data (LAS) and for LiDAR analysis related to forestry.
- 12. MODULES OVERVIEW IN STAGE
- 13. MODULES OVERVIEW IN STAGE
- 14. PREPROCESSING Packages including the available pre-processing operations are: ● Utilities – LasIndexer: creates indexes for LAS files
- 15. LasIndexer
- 16. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer: creates indexes for LAS files – LasInfo: prints out information of a LAS file/folder
- 17. LasInfo
- 18. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer: creates indexes for LAS files – LasInfo: prints out information of a LAS file/folder – LasOverviewCreator: creates a shp with overview
- 20. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer: creates indexes for LAS files – LasInfo: prints out information of a LAS file/folder – LasOverviewCreator: creates a shp with overview – LasPointDensityExtractor: creates a shp with point cloud density on a given grid
- 22. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer – LasInfo – LasOverviewCreator – LasPointDensityExtractor ● Filter – LasHeightDistribution: analyze the height distribution and categorize the forest type
- 25. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer – LasInfo – LasOverviewCreator – LasPointDensityExtractor ● Filter – LasHeightDistribution – LasHistogram: creates an histogram of the elevation or intensity of all the points in the LAS file
- 27. LasHistogram
- 28. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer – LasInfo – LasOverviewCreator – LasPointDensityExtractor ● Filter – LasHeightDistribution – LasHistogram – LasMerger: merges all the LAS file contained in a folder in a single one
- 29. PREPROCESSING Packaging including the available pre-processing operations are: ● Utilities – LasIndexer – LasInfo – LasOverviewCreator – LasPointDensityExtractor ● Filter – LasHeightDistribution – LasHistogram – LasMerger – LasThresholder: extracts the points with values interval
- 30. RASTER Raster package contains all the available modules to interpolate and create a raster (DTM, DSM) from raw point cloud. The different interpolation algorithms are ● AdaptiveTinFilter: the implementation of the adaptive TIN method of Axelsons ● Las2BivariateRasterMosaic: uses the bivariate function to interpolate a raster from the point cloud and creates a mosaic of TIF ● Las2RasterInterpolator: interpolates a raster from LAS points using the Inverse Distance Weight method ● LasOnRasterMapper: creates a raster by mapping max/min elevation point in each pixel ● LasTriangulation2Dsm: creates a DSM from the triangulation of the point cloud
- 34. BUILDINGS This package contains a module to extract the vector data of the buildings from a LAS file. ● LasOnDtmBuildingExtractor: based on the identification of the holes in the ground generated by cutting all the points with an elevation on the ground over a given threshold ● the output shapefile can be cleaned from noise data and smoothed on the boundaries
- 35. BUILDINGS
- 36. BUILDINGS
- 37. FLIGHTLINES Modules to separate different flightlines inside a LAS file: ● FlightLinesExtractor: creates different las files for each of the different flightlines inside the single las ● FlightLinesIntensityNormalizer: normalize intensity values between different flightlines considering the position of the aircraft (x,y,z)
- 38. FLIGHTLINES
- 39. VEGETATION Extrapolation of the whole forest biometric data (e.g. forest biomass) can be obtained through two approaches: ● area-based approaches (AB): forest attributes are estimated by relating plot data to ALS data by statistically procedure ● individual tree crown (ITC) approaches: ITC approaches can use both raster CHM and point ALS data and are aimed to detect position and main characteristics of each single tree. Single-tree records can then be aggregated at plot, forest, watershed or regional scale.
- 40. VEGETATION Extrapolation of the whole forest biometric data (e.g. forest biomass) can be obtained through two approaches: ● area-based approaches (AB): forest attributes are estimated by relating plot data to ALS data by statistically procedure ● individual tree crown (ITC) approaches: ITC approaches can use both raster CHM and point ALS data and are aimed to detect position and main characteristics of each single tree. Single-tree records can then be aggregated at plot, forest, watershed or regional scale.
- 41. VEGETATION MODULES The available modules for single tree extraction are based on the identification of local maxima: ● RasterMaximaFinder: identifies local maxima on raster input data
- 47. VEGETATION MODULES The available modules for single tree extraction are based on the identification of local maxima: ● RasterMaximaFinder: identifies local maxima on raster input data ● PointCluodMaximaFinder: identifies local maxima on point cloud input data
- 51. VEGETATION MODULES The available modules for single tree extraction are based on the identification of local maxima: ● RasterMaximaFinder: identifies local maxima on raster input data ● PointCluodMaximaFinder: identifies local maxima on point cloud input data ● WatershedAlgorithm: delineates the crowns of the trees based on raster data
- 54. DATA VISUALIZATION TOOLS ● profiles of the LAS data considering 4 main directions ● position of the measured trees ● position of the extracted trees with highlighted the type of the tree: true positive, false positive
- 58. APPLICATION: STUDY AREA high local variety in forest structure AURINA VALLEY VEGETATION: ●Norway spruce (Picea abies) ●Larch (Larix decidua) ●Stone pine (Pinus cembra) AREA = 10 km2
- 59. points classification points difference DTM DTM + DSM points density = 10 p/m2 APPLICATION: LiDAR SURVEY (2012)
- 60. 12 CIRCULAR PLOTS RADIUS = 15 m BUFFER 150 m ROADS FOREST STRUCTURES: ● young ● biplane ● adult ● multilayer APPLICATION: FIELD SURVEY (2013)
- 62. method T1: local maxima, raster based method T11: local maxima, point cloud based APPLICATION: RESULTS
- 65. WATERSHEAD MANAGEMENT ● GIS-based tool for predicting the magnitude of LW transport during flood events at any given section within a river basin ● two main processes related to wood debris: – LW recruitment from hillslopes – LW transport/propagation along the network
- 66. SHALSTAB model Unstable slopes connected to fluvial network CONNECTIVITY model AREAS THAT PROVIDES LW Channel widening Slope instability EXTREME EVENTS INPUTS AND PROCESSES OUTPUTSLEGEND LW TRANSPORT DURING FLOODS
- 67. SHALSTAB model Unstable slopes connected to fluvial network CONNECTIVITY model AREAS THAT PROVIDES LW TREE HEIGHT AND FOREST STAND VOLUME CHM and semi-empirical model Channel widening Slope instability EXTREME EVENTS INPUTS AND PROCESSES OUTPUTSLEGEND LW TRANSPORT DURING FLOODS
- 68. LW TRANSPORT DURING FLOODS SHALSTAB model Unstable slopes connected to fluvial network CONNECTIVITY model AREAS THAT PROVIDES LW TREE HEIGHT AND FOREST STAND VOLUME CHM and semi-empirical model CRITICAL SECTIONS AND LW VOLUME Channel widening Slope instability EXTREME EVENTS INPUTS AND PROCESSES OUTPUTSLEGEND Volume and dimensions of available LW LW propagation Field data monitoring LW transport
- 69. LW TRANSPORT DURING FLOODS
- 70. JGRASSTOOLS: INPUT ● digital models of the terrain and vegetation: DTM, DSM, FSV ● DTM derived geomorphology attributes: TCA, slope, connectivity, watershed delineation ● extension of the bankfull area: area covered by water during standard flow conditions ● position and dimensions of bridges and dams: field survey or available cadaster ● superficial geology: rock and deposits (erodible)
- 72. LW PROPAGATION ● identifies the critical section for the transit of LW in the given stream network ● based on the comparison between the length of the logs and channel width
- 74. ● finalize the implementation of a Particle Swarming Optimizer for automatic calibration of the models ● improve the propagation algorithm to consider also the height of the water in the rivers ● connect the results of the elaboration of LiDAR data for the evaluation of the volume, height and diameter of the logs in each section FUTURE PLANS