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Raster Processing & Remote Sensing · LearnSpace
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Raster Processing & Remote Sensing

Курс от Coursera
Начальный≈ 9.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Develop skills in raster data processing and remote sensing analysis using industry tools. This course covers working with raster datasets using Rasterio and GDAL, along with foundational concepts in satellite imagery. You will learn how to process multispectral and SAR data, calculate indices like NDVI, and perform change detection. By the end of the course, you will be able to analyze satellite imagery and extract meaningful insights from raster data.

Навыки, которые вы освоите

Data ProcessingImage AnalysisSpatial Data AnalysisEnvironmental MonitoringGeospatial Information and TechnologySpatial AnalysisData AnalysisGeographic Information SystemsData TransformationVerification And ValidationEnvironmental ScienceModel EvaluationTechnical CommunicationGIS Software

Программа курса

13 модулей · 59 учебных материалов

01Decode Rasters with Rasterio: Read and Understand Raster Data5 материалов
Why Raster Metadata Is the First Thing Professionals CheckDIALOGUEKey Raster Metadata Fields You Must UnderstandЧтениеThinking in Rasters: From Images to Structured DataВидеоReading GeoTIFF Metadata Using RasterioВидео

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Professionals from the Industry

Преподаватель курса

Raster Processing & Remote Sensing
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9.7 ч

13 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Hands-On Learning: Inspect a GeoTIFF Before AnalysisЗадание
02Decode Rasters with Rasterio: Clip Rasters to Your Area of Interest4 материалов
How Analysts Decide What Part of a Raster to UseDIALOGUEWhy Clip Rasters Before AnalysisВидеоBounding Boxes, Windows, and Spatial ExtentЧтениеHands-On Learning: Prepare a Study-Area Raster for NDVIЗадание
03Decode Rasters with Rasterio: Stack Bands for Multiband Analysis5 материалов
Why NDVI Depends on Correct Band StackingDIALOGUEUnderstanding Raster Array Shapes and Band OrderЧтениеStacking Raster Bands with NumPy and RasterioВидеоHands-On Learning: Create a Multiband Raster Ready for NDVIЗаданиеValidating and Preparing Raster Data for AnalysisЗадание
04Master GDAL CLI: Understanding Raster Data with GDAL4 материалов
Why Inspection Comes First DIALOGUEKey Raster Concepts You’ll See in gdalinfo OutputЧтениеExploring Raster Structure with gdalinfoВидеоHands-On Learning: Raster Inspection ChecklistЗадание
05Master GDAL CLI: Reprojecting Raster Data with gdalwarp3 материалов
How gdalwarp Reprojects Raster DataВидеоReprojection Pitfalls and Best Practices for Elevation DataЧтениеHands-On Learning: Reproject a DEM Using gdalwarpЗадание
06Master GDAL CLI: Creating Cloud-Optimized GeoTIFFs5 материалов
Translating GeoTIFFs to COGs with gdal_translateВидеоTranslating GeoTIFF to Cloud-Optimized GeoTIFF: Beyond File ConversionDIALOGUETranslating and Validating Cloud-Optimized GeoTIFFs for Performance ЧтениеHands-On Learning: Convert a Reprojected DEM to COGЗаданиеGraded Assessment: Professional Raster Processing and Cloud Optimization with GDAL CLIЗадание
07Start Remote Sensing: Landsat vs. Sentinel5 материалов
Why Sensors MatterDIALOGUELandsat and Sentinel BasicsЧтениеComparing Landsat and SentinelВидеоHands-on Learning: Match the Sensor to the ScenarioЗаданиеDefending Your Sensor ChoiceDIALOGUE
08Start Remote Sensing: Calculating NDVI from Satellite Bands4 материалов
Understanding Spectral BandsЧтениеCalculating NDVIВидеоHands-on Learning: Calculate and Interpret NDVI from Satellite Bands ЗаданиеReflecting on NDVI Calculation and InterpretationDIALOGUE
09Start Remote Sensing: Preparing Satellite Imagery for Analysis5 материалов
Atmospheric Effects ExplainedЧтениеTOA vs Surface ReflectanceВидеоHands-on Learning: Select the Correct Imagery Product for NDVI Analysis ЗаданиеReflecting on Imagery Readiness for NDVIDIALOGUESelecting the Right Dataset for Long-Term Forest MonitoringЗадание
10Process SAR & Multispectral: Make SAR Usable: Speckle Filtering for Interpretation6 материалов
What You’re Seeing and Why It Looks "Noisy”ВидеоYour Flood Response BriefDIALOGUESpeckle Filtering: What It Improves, What It Can Destroy, and How to ChooseЧтениеFiltering With Intent: Applying a Speckle Filter and Reading the DifferenceВидеоHands-on Learning: Apply Speckle Filtering to SAR Flood ImageryЗадание Would You Trust This SAR View Yet?DIALOGUE
11Process SAR & Multispectral: Detect Flood-Extent Change With Multispectral Stacks5 материалов
Change Detection That Means Something: Comparing Before and AfterВидео Interpreting Multispectral Change: What Counts as Evidence and What Counts as NoiseЧтениеHands-on Learning: Detect Flood-Extent Change After a Storm Using a Multispectral StackЗадание Explain Your Change Map Like a ProfessionalDIALOGUEPractice Quiz: What Does This Change Signal Actually Mean?Задание
12Process SAR & Multispectral: Evaluate Classification Accuracy Before You Share Results5 материалов
Accuracy Isn’t Optional: How to Know If Your Map Is TrustworthyВидеоBeginner Accuracy Evaluation: Confusion Matrix Thinking Without the OverwhelmЧтениеHands-on Learning: Evaluate Classification Results for Flood DetectionЗаданиеWould You Send This to the Response Team?DIALOGUEGraded Assessment: Flood Extent Evidence: Process, Detect, EvaluateЗадание
13Project Module: Remote Sensing Analysis3 материалов
Why This Project MattersЧтениеProject RequirementsЧтениеRemote Sensing AnalysisЗадание