Nothing Special   »   [go: up one dir, main page]
Scribd Logo
Upload

Welcome to Scribd!

  • 31 views

    SURFACE DEPRESSION MAPPING - LindaTheresB

    Uploaded by

    Ridwan Sultan
    This document provides a step-by-step procedure for mapping surface depressions or sinks using tools in ArcMap. It details extracting depressions from a digital elevation model (DEM) by filling imperfections, then taking the difference between the original and filled DEM. The depressions are further refined into polygons and filtered by minimum depth and area conditions to produce a final surface depression map. The method uses a Python package called 'lidar' to process LiDAR data and delineate depressions traditionally through filling and subtraction operations in the DEM. References are provided for further theoretical understanding of mapping surface features.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd

    SURFACE DEPRESSION MAPPING - LindaTheresB

    Uploaded by

    Ridwan Sultan
    31 views7 pages
    This document provides a step-by-step procedure for mapping surface depressions or sinks using tools in ArcMap. It details extracting depressions from a digital elevation model (DEM) by filling imperfections, then taking the difference between the original and filled DEM. The depressions are further refined into polygons and filtered by minimum depth and area conditions to produce a final surface depression map. The method uses a Python package called 'lidar' to process LiDAR data and delineate depressions traditionally through filling and subtraction operations in the DEM. References are provided for further theoretical understanding of mapping surface features.

    Original Description:

    Original Title

    SURFACE DEPRESSION MAPPING_LindaTheresB

    Copyright

    © © All Rights Reserved

    Available Formats

    PDF, TXT or read online from Scribd

    Did you find this document useful?

    Is this content inappropriate?

    This document provides a step-by-step procedure for mapping surface depressions or sinks using tools in ArcMap. It details extracting depressions from a digital elevation model (DEM) by filling imperfections, then taking the difference between the original and filled DEM. The depressions are further refined into polygons and filtered by minimum depth and area conditions to produce a final surface depression map. The method uses a Python package called 'lidar' to process LiDAR data and delineate depressions traditionally through filling and subtraction operations in the DEM. References are provided for further theoretical understanding of mapping surface features.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    31 views7 pages

    SURFACE DEPRESSION MAPPING - LindaTheresB

    Uploaded by

    Ridwan Sultan
    This document provides a step-by-step procedure for mapping surface depressions or sinks using tools in ArcMap. It details extracting depressions from a digital elevation model (DEM) by filling imperfections, then taking the difference between the original and filled DEM. The depressions are further refined into polygons and filtered by minimum depth and area conditions to produce a final surface depression map. The method uses a Python package called 'lidar' to process LiDAR data and delineate depressions traditionally through filling and subtraction operations in the DEM. References are provided for further theoretical understanding of mapping surface features.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    of 7

    See discussions, stats, and author profiles for this publication at: https://www.researchgate.

    net/publication/362413454

    LET'S MAP SURFACE DEPRESSIONS WITH TOOLS IN ARCMAP!

    Method · August 2022


    DOI: 10.13140/RG.2.2.11587.27681

    CITATIONS READS

    0 100

    1 author:

    Linda Theres
    SASTRA University
    6 PUBLICATIONS   2 CITATIONS   

    SEE PROFILE

    All content following this page was uploaded by Linda Theres on 02 August 2022.

    The user has requested enhancement of the downloaded file.


    LET’S MAP SURFACE DEPRESSIONS WITH TOOLS IN ARCMAP!
    Linda Theres B (lindatheres92@gmail.com)
    Surface depressions are the elevation differences found on landscapes. The causes of such
    depressions are wide: erosion or man-made activities. Depending on the depth and the areal
    spread of such depressions, their purposes are countless! As a part of my work, I faced the
    requirement of map surface depressions, but couldn’t find a reliable tutorial. Hence this article
    was, written to provide step by step procedure for mapping sinks/surface depressions. The work
    is deciphered from a python package ‘lidar ‘, to be executed in ArcMap, which uses the LiDAR
    dataset to map surface depression. For more theoretical understanding please look into the links
    provided in the references.
    Surface depressions are delineated from DEM using the traditional depression filling methods.
    DEM downloaded was smoothened with 3x3 mean filtering using the zonal statistics tool. Then
    fill operation was performed to fill the imperfections in the DEM. The difference in original
    DEM and pit-free DEM gives the actual depression as the output, which is further refined and
    converted to vector format. Then polygons were extracted with minimum area conditions to
    export the surface depression map as shown in the below figure.
    PROCEDURE:
    ▪ Pre pare DEM data by clipping to your study area extent, if necessary
    ▪ Open focal statistics tool, use 3x3 filter to find mean to smoothen the DEM data by
    removing elevated points, that are noise.

    ▪ Perform fill operation to fill in the noisy depressions.

    ▪ Next, we compute depressions, by subtracting focal statistics output from the fill output
    in raster calculator
    ▪ Then we extract depression by using conditional statement in raster calculator. Say if
    above step output name is ‘sink’, the conditional statement is Con (sink>0, 1). The
    output is basically raster with depth values.

    ▪ Next two steps will group cells to form polygons. First using region group tool, give
    abpve output as input and remaining values as default
    ▪ Then in the zonal statistics tool, input is the output of the above step and the original
    DEM file as the input value raster.

    ▪ Then filter depressions by giving minimum depth conditions. We use a raster calculator.
    If above output is ‘zonal_op’, the conditional statement is Con (zonal_op>2, 1). Note
    here we have given 2 as minimum depth. This condition value can be chosen according
    to the requirement.
    ▪ Then we convert the above output raster to a polygon using a conversion tool

    ▪ Then project the vector file to compute the area of the polygons derived. After
    projection, create a field ‘area_sqkm’ in the attribute table, and using the ‘calculate
    geometry’ option, compute the area of all the polygon features.
    ▪ Finally, we select the polygons by providing minimum area conditions and export data
    as the final output and display as a surface depression map.

    REFERENCES
    https://github.com/giswqs/lidar
    https://onlinelibrary.wiley.com/doi/10.1111/1752-1688.12689
    https://joss.theoj.org/papers/10.21105/joss.02965

    View publication stats

    You might also like