Method of InstructionThe course has four elements ...



Course title: NRES 498/898: Introduction to Google Earth Engine for Analysis of Remote Sensing and Geospatial Data (2 Credits)Three Week Mini-Course – January 3 – January 20, 2021Credit Hours: Two CreditsClass Meets: Monday, Wednesday and Friday – 12 pm to 2:50 pmInstructor: Dr. Ayse KilicOffice location: 311 Hardin HallContact information: Dr. Ayse Kilic akilic@unl.edu 402 420 2562 (cell)Office hours: TBARequired materials: Computer with fast internet access; Chrome browser; an extra monitor is recommended to simultaneously view lecture, lecturer and write scripts on GEE; a GMAIL account; a spreadsheet application. No textbook. Reading materials will come from the web.Course prerequisites: Previous experience with Earth Engine or JavaScript is not necessary, but some sort of programming experience is recommended. Willingness to learn programming is required. Basic knowledge of GIS is recommended, but not required. Prior experience with remote sensing data will be useful, but not required. Lack of knowledge and/or experience will require students to conduct additional, independent remedial reading as directed by the instructor.Course Description:This is an interactive course that will introduce students to the Google Earth Engine (GEE) playground and JavaScript (similar to Python) scripting language where they can perform geospatial processing using the?Google Cloud.?Students will utilize GEE Public Datasets and repositories that include data on climate, satellite imagery (Landsat, MODIS, Sentinel), aerial imagery (i.e. NAIP, UAV), Geophysical (Terrain, Land Cover, Cropland data) and other data types. Conduct Geoprocessing and analysis on vector (feature) and raster (image) datasets. Apply analysis-based functions on image and feature collections. Calculate land cover change, land cover indices, and natural system processes. Overview of satellite imagery processing, projection and coordinate systems. Introduction to advanced features of the Earth Engine API with applications in deforestation, stream systems, gridded weather and mapping water use.Measurable Behavioral Objectives: Students at the end of the class will be able to Navigate and control Google Earth Engine through scripting to characterize the natural environment using common geographical and satellite datasets; Calculate land cover change, land cover indices, and natural system processes,Utilize functions related to geometries (Clipping, Buffering, Dissolving, Length/Area/Distance calculations etc.), Conduct operations on raster/image collections (mapping, filtering, masking, reducers)Conduct operations on features and feature collectionsCreate Graphs to display time series dataCalculate statistics Cloud masking to filter clear parts of an imageImport/Export Data from GEE. Create user interfacesHave familiarity with commonly used satellite imagery (Landsat, MODIS, Sentinel) and analysis for even global applications. Understand fundamentals of projection and coordinate systemsWhitelisting (registering) Gmail on GEE: Link for GEE Playground (code editor): : Tentative Lecture and Exercise TopicsWeek/DayTopics1-1Introduction to the GEE playground: Whitelisting gmail account to GEE (How to do it): Gmail account Whitelisting - code editor locations and navigation in GEE (including Assets)- data types (vectors, shapes, rasters)- fundamentals of remote sensing processing - bands, indices, projection, coordinate systems 1-2Introduction to Javascript syntax on the Google playground part I:Creating functions1-3Introduction to Javascript syntax on the Google playground part IIClient vs server sides in programming1-4Geometry functionsFunctions on Geometry (area, length,simplify, centroid, buffer, intersection, union)1-5Types of Datasets, Repositories and Collections in GEE Satellite Data: Sentinel, NAIP, Landsat, MODIS, VIIRSData Types- Rasters/Features/Tables:Rasters:Image vs Image CollectionGridded weather data setsOperations on Images (Part I)(Selecting the bands, creating masks, Arithmetic pixelwise calculations2-1Operations on Image collections (Part II)(mapping, filter by date, filterbound, filter by metadata, masking, pixelwise calculations) 2-2Operations on Image collections (Part III)Reducers (minmax, min, mean, median)Reduce Region2-3Features: Features vs FeatureCollectionOperation (Feature)Buffer, Distance, Difference, Dissolve (Example of watershed on Nebraska)2-4Computing indexes (NDVI, NDWI, etc) Creating color composites:False and True color composites2-5Terrain applications (Slope, aspect, hillshade, products) 3-1 Charting (time series of NDVI, GRIDMET precipitation)3-2 Exporting (Google Drive, Asset)3-3Cloud masking (quality band)3-4Advanced application:-Deforestation-Mapping water use-Estimating the extent of floods (Platte River)3-5 Creating User interfacesMethod of InstructionThe course has four elements: lectures, assigned reading materials, homework (labs) exercises (twice per week), and take home examinations. The course is taught as a three-week mini course. We will meet at a fixed time three days per week for three hours each day. All meetings will be remote using Zoom. There will be two hours of lecture on meeting days followed by one hour of recitation and lab. The course material is divided into modules with each module having one or two lectures and homework involving extensive use of GEE. Course ReadingsThere is no book required for this class. Readings for this course will be mostly from the Google Earth Engine Developer’s site: homeworks will be comprised of creating programming scripts that successfully run on GEE. Homeworks will provide an opportunity to practice writing scripts that are similar to those covered in the lectures. Recitation hours will be used to work through problems in student scripts and to answer questions. If needed, additional time with the instructor or assistant can be scheduled. Grading of homeworks will entail the instructor successfully running the scripts on her GEE system, the ability of the script to produce the desired and assigned outcome. The instructor may request students to test scripts of other students.Take Home Exams:There will be two take home exams on scripting. Exams will be comprised of a combination of:fixing some “broken code” to make it run. applying an available advanced script to a large area (even the globe) and adding a section to analyze a subregion, statistically. explaining, in your own words, what sections of an advanced script are doing.Producing graph or tables of time series data AssessmentCourse grades will be based on a weighted average of results as follows:1. Homework 70%2. Two Take Home Exams on Scripting 15% eachLetter grades will be assigned as follows:A = 95 – 100%; A- = 90 – 95%B+ = 87 – 90%; B = 83 – 87%; B- = 80 – 83%C+ = 77 – 80%; C = 73 – 77%; C- = 70 – 73%; D = 60 – 70%; F < 60%There will be no make-up grades in this course. We reserve the right to change the date of an exam or drop an exercise with notice in advance. Lectures may or may not be recorded, therefore, attendance is strongly encouraged.Course/Instructor Evaluation PlanCourse/Instructor evaluation will be conducted according to the policies of the university. Students will receive an email with a link to the evaluation website. In addition, there is going to be a link to the evaluation website via blackboard.I encourage students to speak to me regarding any problems related to the course during the semester.Course PoliciesAttendance is strongly encouraged, but not mandatory. All scripts produced by students to fulfill homework and exam requirements will be shared with the instructor and potentially other students for grading. Academic dishonesty. Each student is expected to write her/his own scripts on the Google Earth Engine. You can ask one another for help or for code debugging, but the basic script needs to be written independently. Do not copy scripts from the web. You can use them for ideas, but create your own customized code. The first offense of using another’s work will be a warning. Each additional offense will result in a 0.0 for that exercise and will include all individuals whom the instructor deems to have used the same script, including the person that originally wrote the script. Students can appeal to the instructor. Additional appeal can be made according to the following: Informational StatementsADA Statement:The University strives to make all learning experiences as accessible as possible. If you anticipate or experience barriers based on your disability (including mental health, chronic or temporary medical conditions), please let me know immediately so that we can discuss options privately. To establish reasonable accommodations, I may request that you register with Services for Students with Disabilities (SSD). If you are eligible for services and register with their office, make arrangements with me as soon as possible to discuss your accommodations so they can be implemented in a timely manner.SSD contact information: 117 Louise Pound Hall Bldg.;?402-472-3787Mental Health and Wellbeing Resources:UNL offers a variety of options to students to aid them in dealing with stress and adversity. Counseling and Psychological & Services (CAPS) is a multidisciplinary team of psychologists and counselors that works collaboratively with Nebraska students to help them explore their feelings and thoughts and learn helpful ways to improve their mental, psychological and emotional well-being when issues arise. CAPS can be reached by calling?402-472-7450. Big Red Resilience & Well-Being provides one-on-one well-being coaching to any student who wants to enhance their well-being. Trained well-being coaches help students create and be grateful for positive experiences, practice resilience and self-compassion, and find support as they need it. BRRWB can be reached by calling?402-472-8770.Emergency proceduresConsult UNL emergency planning site for current emergency procedures:? Drop PoliciesRefer to university Course drop policies and dates at ................
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