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    Development Of Et Sebal Model In Google Earth Engine

    Posted By: ELK1nG
    Development Of Et Sebal Model In Google Earth Engine

    Development Of Et Sebal Model In Google Earth Engine
    Published 6/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 6.02 GB | Duration: 10h 42m

    Step by step guide for croplands

    What you'll learn

    SEBAL

    Evapotranspiration

    Google Earth Engine

    Remote Sensing

    NDVI, SAVI, LAI

    Surface Temperature

    Incoming Longwave Radiation

    Incoming Shortwave Radiation

    Surface Emissivity

    Momentum Roughness Length

    Sensible Heat Flux

    Soil Heat Flux

    Outgoing longwave radiation

    Net radiation flux

    Requirements

    Basic (or better Intermediate) knowledge of Google Earth Engine

    Good Internet Connection

    Description

    In this course, you will master a step-by-step guide to developing a script in Google Earth Engine for the most famous Evapotranspiration model - Surface Energy Balance Algorithm for Land (SEBAL) for agricultural areas. Before starting a course, please read the requirements for the course - you need to have a Google Earth Engine profile (free to open), and a basic or better intermediate level of scripting in GEE or JavaScript. As a research study area an agricultural field that is located in Dubai Emirate, the UAE was taken. You can apply this course to your study area by making minor changes. It is good if you also have some knowledge/ experience of evapotranspiration. The course is divided into a theoretical part and a practical part, the latter of which constitutes almost 90 % of the course. Each practical part of the course contains an attached script in txt format. After finishing the course, besides developing the SEBAL model, you can apply different parts of the course in your other projects, that involve remote sensing. The course also contains two QGIS plugins ( to calculate instantaneous reference evapotranspiration and correlation coefficients) developed deliberately for the course which is free to download. Get ready to boost your knowledge in remote sensing and Google Earth Engine!

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Manual

    Section 2: Fundamental theory

    Lecture 3 Evapotranspiration

    Lecture 4 Surface energy balance

    Lecture 5 SEBAL model

    Lecture 6 Net radiation flux (Rn)

    Lecture 7 Soil heat flux(G)

    Lecture 8 Sensible heat flux(H)

    Lecture 9 Cold and Hot anchor pixels

    Lecture 10 Air density

    Section 3: Before starting the script

    Lecture 11 Image Collections of GEE that will be used

    Lecture 12 Necessary functions that will be used.Part 1

    Lecture 13 Necessary functions that will be used.Part 2

    Section 4: Net Radiation Flux (Rn)

    Lecture 14 Starting the project in GEE

    Lecture 15 Adding Landsat 8 Image collection

    Lecture 16 Dataset subdivided by path and row

    Lecture 17 Creating newDataset function

    Lecture 18 Starting newDataset, defining parameters, defining geometry

    Lecture 19 Computation of spectral radiance for each band

    Lecture 20 Inverse squared relative earth sun distance

    Lecture 21 Computation of reflectivity for each band

    Lecture 22 Top of the atmopshere albedo

    Lecture 23 Surface albedo

    Lecture 24 Incoming shortwave radiation

    Lecture 25 Outgoing longwave radiation - NDVI, SAVI, LAI

    Lecture 26 Surface emissivity

    Lecture 27 Surface temperature

    Lecture 28 Outgoing longwave radiation

    Lecture 29 Finishing newDataset

    Lecture 30 Correcting the errors

    Lecture 31 Image bounds for image path and row

    Lecture 32 Chosing cold and hot pixels

    Lecture 33 Importing the location of a cold pixel for incoming longwave radiation

    Lecture 34 Incoming Longwave Radiation

    Lecture 35 Creating newDataset2

    Lecture 36 Computing Rn

    Lecture 37 Adding a geometry

    Lecture 38 Test Rn

    Lecture 39 All images with computed bands and dates

    Lecture 40 Export to drive and assets

    Lecture 41 Discovering Rn image in ArcGIS or QGIS

    Section 5: Momentum roughness length (z)

    Lecture 42 Copernicus land cover classes areas

    Lecture 43 Momentum roughness length for the study area

    Lecture 44 Sampling

    Lecture 45 Pixel count and export

    Lecture 46 Correcting Zom -import of LAI

    Lecture 47 Correcting zom for agricultural fields with LAI values

    Section 6: Soil Heat Flux (G)

    Lecture 48 Importing our hot and cold pixels

    Lecture 49 Visualization parameters

    Lecture 50 Defining bands to be sampled

    Lecture 51 Add layers to corraborate where cold and hot pixels are

    Lecture 52 Function for G and Rn ratio

    Lecture 53 Soil heat flux (G) and Rn and G ratio computation

    Lecture 54 Adding layers

    Lecture 55 Sampling bands for hot and cold pixels

    Lecture 56 Basic undertanding of variables for H and their values

    Lecture 57 Momentum roughness length for a weather station

    Lecture 58 Friction velocity at the weather station

    Lecture 59 Wind velocity at 200 meters for a weather station

    Lecture 60 Air density for hot and cold pixels

    Lecture 61 Exporting data in CSV format

    Section 7: Sensible Heat Flux (H)

    Lecture 62 Theory of Iteration processs of H

    Lecture 63 The weather data we need for Etr

    Lecture 64 Adding ECMWF Climate Reanalysis collection

    Lecture 65 Selecting necessary climate data

    Lecture 66 u,v, surface net solar radiation and dewpoint temperature

    Lecture 67 Conversion to Feature Collection from Image Collection

    Lecture 68 Weather station elevation and export climate data

    Lecture 69 Calculation of reference evapotranspiration

    Lecture 70 Time issues around weather data and ETr

    Lecture 71 Developing script for instantenous wind and ETr. Part 1

    Lecture 72 Developing script for instantenous wind and ETr. Part 2

    Lecture 73 Developing script for instantenous wind and ETr. Part 3

    Lecture 74 Instantenous wind speed and ETr in QGIS plugin

    Lecture 75 Working with getsebal plugin

    Section 8: Finishing the SEBAL model

    Lecture 76 Part 1

    Lecture 77 Part 2

    Lecture 78 Part 3

    Lecture 79 Part 4

    Section 9: Сhanging the developed script for other images of the year

    Lecture 80 Re-computing the momentum roughness length corrected for January 13

    Lecture 81 Re-computing the soil heat flux, values for hot and cold pixels and weather d

    Lecture 82 Export weather parameters for a new image

    Lecture 83 Computation ofr hourly ETr

    Lecture 84 Instantenous wind speed and ETr for the new image

    Lecture 85 Obtaining Correlation coefficients

    Lecture 86 Calculating SEBAL for January 13

    Remote sensing specialists,GIS specialists,Remote sensing master students,GIS master students,Hydrologists,Ecologists,Crop scientists,Ecologists,Environmentalists