Vegetation and Biomass Indices Estimation with QGIS 3 - Tutorial

hi everyone how are you this is Mary Carmen and I am translating a tutorial made by Gabriela carita in this tutorial we will talk about the determination of the vegetation and biomass indices we know that the use of satellite images and aerial photos are included need to analyze the vegetation this allows to get quantitative information of the state of the vegetation and the spatial viability of a study area the indices are used to estimate different changes in the vegetation biomass and chlorophyll for example in this tutorial we will learn how to estimate the relation of biomass with the NDVI and the green red normalized difference index we have selected the study area of a lake in California ok so I'll show you the lake in California this is the study area and we downloaded the satellite images from the semi automatic classification plugin you can download the plug-in by going to plugins manage and install plugins and then look for semi automatic classification plug-in you will find a button that says install plug-in you click on that button and that's all we have per process the images as well we downloaded them with the SCP plug-in and they are sent in all two images and we have purposes them we have now the reflectance values of each image and we applied the atmospheric correction as well and then we have clicked a images to the study area region you can find the input data in the article published in Hatari labs okay as you can see the study area is a forest and it has a good coverage of vegetation we can combine these bands to get a false color image a false color image will enhance the areas of vegetation and it will contrast it as well in the image so we can go to the SE p plugin then show plugin and now kill in band set we are going to add the bands objects and light image in this case we have several bands they are sending out two images we can select Sentinel - okay quick wavelength settings and the center wavelength will change QGIS will name the bands with these numbers the numbers on the left side so the Sentinel band tube will be QGIS band 1 1 3 will be band 2 and so on as it appears in this list so to create a false color image we need band-aid of sentinels then near-infrared one this one so this is band aid in Sentinel band 7 in QGIS we also need their bread the red band in Sentinel which is band for for QGIS will be band 3 and we have the Green the green band as well which is the third one for Sentinel and number 2 in QGIS so to create a false color image we are going to to write the combination in this in this option of the SCP plugin so here it says RGB and we are going to say 7 3 and 2 then we activate the virtual band set and here we have the false color image as you can see there a vegetated areas are the ones in red okay so we also have used the reflectance of each band to calculate the different vegetation indices we have calculated a nd bi and a and G Rd I which is an in the index of visible reflectance and it is used with that RGB red green blue of an IRL camera this index is not very used in comparison to the NDVI the NDVI tends to be more used because it it uses the infrared region of the spectrum as well okay so to calculate NDVI we are going to use the SCP plug-in and we are going to band calculator in this band calculator we are going to write the expression of the formula and the NDVI formula is the near infrared region or near infrared band which is band number eight this one then we use - the red band which is Bank for incentive and then we're going to divide this by the sum of bank eight the new infrared 1 plus Bank for the red one okay and now we are going to run and we're going to save it as and DVI and now here we have the NDVI raster we can change the properties of the NDVI raster single band through the color and then use a different color right so the values closer to one are going to be the values with vegetation and the values closer to zero are the sounds of bare soil so I'll invert color ramp and the red areas will be there as with more vegetation okay so as you can see the red areas are the areas with more vegetation the NDVI is the normalized differentiated vegetation index and the results displayed a relative biomass through the NDVI we can survey survey the intensity and the density of the vegetation now we can calculate the energy RDI and we are going to use the raster calculator again so SCP ban calculator and the formula is similar to the NDVI but in this case we're not going to be using 1:8 we're going to be using bun-bun 3 because we are using the green bag so we are using the green band which is 1/3 - band 4 which is the red one divided by band 3 the green one plus the red one okay so run and we will save it as ng and here we can see the ng RTI we can change this the color and apply a different color so here with this index you can see that that the vegetation is the one with positive values and the non vegetated area areas have negative values but you can see that we can differentiate it better with the NDVI okay so we also have a raster of biomass this raster tells us the biomass in tones per hectare there are several sensors that can obtain obtain the biomass data and there are some drones as well these methods are used in the field and the biomass can indicate as well the amount of carbon in the study area the unit of biomass is tons per hectare and for this instance we are going to to relate the biomass values with the NDVI values and their ng RDI values to do so we are we have selected some random points that are in the first area and we are going to use the point sampling tool where we can associate the values of the rosters with the sampling points to install the point sampling tool we have to go to plugins manage any so plugins and then look for point sampling tool I've already installed it but you're going to have a button that says install poly you just have to click on that and you will have the point sampling tool so in this tool we are going to select the layer containing sampling points which is the random points or puntos aleatory and then we are going to select the layers with fields or bands to get values from so we're going to be using biomass the NDVI and the ng RDI we're going to save the virtual layer and here we're going to save it as runner points shaped fires I'll save it as say comma-separated values and we can also be desde to file so first a shape file [Music] [Music] okay so I was selecting the random point field I have to activate and grd I and the NDVI as well and then open again the the point sampling tool and select their rosters so the ones that say roster biomass and gr TI and NDVI and save it again and then I'll save it as a CSV file okay now we can open the attribute table of the point and here you can see that we have biomass and gr di and NDB I and now we are going to open this this table in Excel to do some statistics I'll save this one as an excel file and now we can create a graph a dispersion one and we have the biomass in here and the engine archetype in the y-axis I am going to add the trending line and I'll present the value of our a linear tendon at least a linear change lines and he was she we have here we have a correlation value of 0.4 between the ng RT I and the biomass and now we can do the same with the MTB I so here we have the NDVI and to biomass in tones for pictures we can add a trendline as well percent a square value the square R value and we can also present an equation if we want to so here we can see that the correlation between NDVI and biomass is is Rader Dante ng RTI relation and now we can correlate ng r di and NDVI we can see that the NDVI and the ng Rd I have a higher correlation for the vegetated vegetated areas and almost perfect correlation almost one-to-one in this in this area and here we have the NDVI values and ng ng r te i palace so we can see that they hired the NDVI they hired the ng are the ayahs work and this helps us to identify the relationship between the parameters and the values and maybe if we are planning on doing some models we can we can try to use the ones that have a better correlation and we can estimate some values of ng r di from NDVI or the other way around so this is all for this tutorial I hope this was helpful for you and if you liked it please share this channel and I'll see you in the next tutorial

Channel: Hatari Labs

Views: 11,807

Rating: 4.9000001 out of 5

Keywords:

Id: Odm8A1myBaI

Length: 23min 10sec (1390 seconds)

Published: Thu Aug 02 2018