Estimation of NDVI by Regression analysis using ArcGIS Software - A simple Case study

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  • Опубликовано: 26 ноя 2024

Комментарии • 12

  • @juliorobles5751
    @juliorobles5751 Год назад

    Excelente video….

  • @alankrithamaheshwaran1513
    @alankrithamaheshwaran1513 4 месяца назад

    Can this be performed on a time-series analysis where the datasets are not exactly around the same months across the chosen years? Like if the seasons are different, will the prediction still be accurate?

    • @cartogeospatialsolutions3890
      @cartogeospatialsolutions3890  4 месяца назад

      Not as accurate as it should be, though you can predict the general trend, it's advised to make sure your data is temporally matched first!

  • @annleticia6171
    @annleticia6171 10 месяцев назад

    is necessary to add forests and if yes how do i get for a full study area

    • @cartogeospatialsolutions3890
      @cartogeospatialsolutions3890  10 месяцев назад

      This is a case study to estimate vegetation density in forests, that's why I've used it. Yes of course you can download forest cover of any area from bbbike extracts

  • @Shabbir2749
    @Shabbir2749 Год назад

    Can you please make a video on how to collect data for NDVI?
    I do not have any Idea to collect data for NDVI

    • @cartogeospatialsolutions3890
      @cartogeospatialsolutions3890  Год назад

      Sure, we'll give it a thought. Long story short, you just need to download NIR and Red bands for your aoi from a data provider like USGS

  • @naphtalijr.1533
    @naphtalijr.1533 8 месяцев назад

    My attribute table has -9999 values? What might be the problem

    • @raghavmsj8226
      @raghavmsj8226 7 месяцев назад

      It means that your pixel has no data in it, try changing the location of your point

  • @hasinipramodya-zw8bs
    @hasinipramodya-zw8bs 6 месяцев назад

    This equation ,how to interpreted ? if have some reference plz give a link

    • @cartogeospatialsolutions3890
      @cartogeospatialsolutions3890  6 месяцев назад +1

      It's a simple linear regression equation (y = a +bx) used to find a dependent variable's (y) value from an independent variable (x). There are lots of references online that describes this equation in depth

    • @hasinipramodya-zw8bs
      @hasinipramodya-zw8bs 5 месяцев назад

      Thank you so much❤