Скачать с ютуб Land Use Land Cover Change (LULCC) between 2001 and 2019 in Google Earth Engine (Study Area: Dharan) в хорошем качестве

Land Use Land Cover Change (LULCC) between 2001 and 2019 in Google Earth Engine (Study Area: Dharan)

Classification and Regression Trees (CART): Machine learning technique in Google Earth Engine. In this tutorial learn how to: 1. Define sample points to train a classifier. 2. Classify the training points into different classes (Urban, Vegetation, Water, and Other Land) 3. Merge the four geometry layers into a single Feature Collection. 4. Sample the composite to generate training data. Note that the class label is stored in the ‘landcover’ property. 5. Train a CART classifier. 6. Do a Supervised Classification. 7. Split the data into 70% training, 30% testing. and classify the cloud-free composite. 8. Print the confusion matrix. 9. Determine the Land Cover Change between 2001 and 2019. code link: 1. For Landsat 7 & 8 Collection 1 Tier 1 TOA Reflectance: https://drive.google.com/file/d/13RFg... 2. For Landsat 7 Collection 1 Tier 1 Raw Scenes: https://docs.google.com/document/d/1V... 3. For Title and Legends: https://drive.google.com/file/d/162de...