Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University,

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Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 1 Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) V1, March 2015 Creative Commons License Module developers: Carlos Souza, Imazon Sandra Brown, Winrock International Frédéric Achard, EC – Joint Research Centre Exercises: Monitoring degradation processes: logging  Part 1: Introducing ImgTools  Part 2: Forest Change Detection using SMA fractions and NDFI  Part 3: Decision Tree Classification using a time-series of SMA and NFDI images

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 2 Monitoring Degradation Processes: Logging 1. Introduction  We will used ImgTools software for this Exercise ● ImgTools is multi-sensor image processing software developed by Imazon to facilitate operational forest monitoring in BrazilImazon ● Several NGOs and graduate students of Universities from different countries are using ImgTools ● ImgTools and references can be obtained from the folder ImgTools in the training materials ● ImgTools requires Windows operating system

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 3 Monitoring Degradation Processes: Logging 2. Objectives  The tutorial exercises for this module is organized to accomplish the following objectives: 1. Introduce the main functionalities of ImgTools to generate SMA fractions and NDFI 2. Use SMA fractions and NDFI to detected forest degradation caused by selective logging 3. Apply the image classification algorithms in ImgTools to map forest degradation

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 4 Monitoring Degradation Processes: Logging Part 1: Introducing ImgTools ● In this exercise you will learn: ● How to install ImgTools ● Launch ImgTools ● Run Spectral Mixture Analysis (SMA) ● Explore data visualization tools ● Create Masks ● Calculate NDFI

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 5 Part 1: Introducing ImgTools 1. How to install ImgTools 1.1 In the ImgTools folder you will find two version of ImgTools: ● Compatible with IDL71: this version requires ENVI 4.7 and IDL 7.1 for running decision trees ● Compatilbe with IDL82: this version requires ENVI 5.0 and IDL 8.2 for running decision trees NOTE: If you don’t use decision trees, you won’t need to have ENVI and IDL installed. In this case, ImgTools runs as a stand alone application.

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 6 Part 1: Introducing ImgTools 1. How to install ImgTools (cont.) 1.3 For this tutorial we will use ImgTools compatible with IDL82. Select this folder and click on ImgTools_10x8632_setup.exe to download it 1.4 After downloading ImgTools instalation file, double click it to intall the sofware 1.5 Click the Run button and follow the instructions to complete the installation...

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 7 Part 1: Introducing ImgTools 2. Launching ImgTools 2.1 After installation, the ImgTools icon will be created in your desktop; Double clik this icon to launch ImgTools 2.2 The ImgTools main screen appears on your desktop indicating the software is ready to be used Note: ImgTools screen was designed to implent the image processing framework presented in this figure

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 8 Part 1: Introducing ImgTools 3. Run Spectral Mixture Analysis (SMA) 3.1 Data preparation. ● We will use a sub-set (900 x 600 pixels) of Landsat 5 imagery acquired of the 226/68 path/row for part of the Sinop region in Mato Grosso state, Brazil ● The imagery dataset is available from the folder ImgData Please, download the ImgData folder to your computer. ● In this folder, you will find all data used in the tutorial exercises. Here, we will use the data in the “Exercise1” folder: “C:\YOUR FOLDER...\ImgData\Exercise1\img\ref”, where “YOUR FOLDER...” is the location you chose to copy the data to. ● In the Exercise1 folder you will find two files: 226_68_000626sub_rf - the Landsat reflectance data 226_68_000626sub_rf.hdr – the ENVI header file (*.hdr) ● The sub-set imagery data was pre-processed for haze and atmospheric corrections and image registration

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 9 Part 1: Introducing ImgTools 3. Run Spectral Mixture Analysis (SMA) 3.1 Click in the “Get Fractions” button of ImgTools Spectral Mixture Analysis” application deck. This will launch the xSMA application 3.2 Enter the following information: Sensor: Landsat. Input Image Path: “...\ImgData\Exercise 1\” folder. Path: 226 and Row: 68 Keep the default options for image file name (suffix) 3.3 Click the Add button to load the image 3.4 Select the image loaded and click the Execute button to run SMA. Afer running it, the SMA results will show up in the Fraction Images list. Choose Exit xSMA under File menu

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 10 Part 1: Introducing ImgTools 4. Explore Data Visualization Tools  We will use the Water mask application to explore some of the data visualization tools available in ImgTools 4.1 Click the “Water Mask “ button from the Spectral Mixture Analysis deck. This will lauch the xWaterMask application. Then, enter the path location of your exercise data (... l\ImgData\Exercise 1\), path 226 and Row Click the Add button. This will show SMA image results in the Fraction Images file list 4.3 Double clik the SMA filename (226_68_000626sub_sma) to load the image

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 11 Part 1: Introducing ImgTools 4. Explore Data Visualization Tools  ImgTools has three image displays: image, scroll and zoom (4x)  You can explore the image data by moving arround the red boxes in the Scroll and Image displays Image Display Zoom Display Scroll Display

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 12 Part 1: Introducing ImgTools 4.1 You can right-click the mouse button and select “Show Values” option. This will bring up the a tool tip interface with GV, NPV, Soil and Shade pixel values 4.2 Select a logging site (see example on the button figure beside) in the Image Display and explore SMA fraction values for logging landings, roads and intact forests

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 13 Part 1: Introducing ImgTools 4.3 When exploring SMA values for water surface on rivers, we observe high Shade fraction values and low GV and Soil fractions. We will use these fractions to generate a water mask 4.4 Right click the mouse button on the Image Display and select the Preview option. This will create a default water mask (white pixels) based on GV, Shape adn Soil values showed in the historgrams below

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 14 Part 1: Introducing ImgTools 5. Creating Water Mask 5.1 Right-click the mouse button on the Image Display and select Spatial Filter. Enter 1 for Minimum Area and 10 for Maximum Area. Then, Click Apply and OK when Done. This will remove noise isolated pixels using a labol region based spatial filter 5.2 Move the histogram values of GV for 40, by clicking and dragging the left mouse btton on GV histogram. Do the same for Shade (65) and Soil (4). This will interactively show the water mask results on the Image and Zoom Displays 5.3 To save the display results of your water mask, right-click the fraction image filename, select Add to List. Then, click the Execute button. Select the Exercise1 folder to save the results

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 15 Part 1: Introducing ImgTools 6. Calculating NDFI  Water mask (and cloud/shade mask when occurring in the image) should be obtained and applied to NDFI results. We will use the SMA fractions and water mask calculated previously to calculate NDFI 6. 1 Click the “Calculate NDFI” button in the main ImgTools window. This will launch the xNDFI application 6.2 Enter the Input Image Path, Water mask file, Path (226) and Row (68). Then, click the Add button and select “226_68_000626sub_sma” image 6.3 To calculate NDFI, click the Execute button. The result will be showed in the NDFI Image file list

Module 2.2 Monitoring activity data for forests remaining forests (incl. forest degradation) REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 16 Recommended modules as follow up  Module 2.2: Continue with Exercise ImgTools Part 2 to use SMA fractions and NDFI to detected forest degradation caused by selective logging