Analisa Citra satelit dan Machine Learning untuk Prediksi Abrasi Pantai
Studi Literatur
International Journal Publications
National Journal Publications
Tsunami Vulnerability and Risk
Assessment Using Machine
Learning and Landsat 8
Perubahan Konversi Lahan
Menggunakan NDVI, EVI, SAVI
dan PCA pada Citra Landsat 8
(Studi Kasus : Kota Salatiga)
MANGROVE MONITORING USING NORMALIZED
DIFFERENCE VEGETATION INDEX (NDVI): CASE STUDY
IN NORTH HALMAHERA, INDONESIA
Conference Publications
Compare and Contrast
Dataset
Data Preprocessing
Satelite Imagery Data
Satelit Landsat 8 OLI/TIRS memiliki sensor Onboard
Operational Land Imager (OLI)
Ekstraksi Data dari Citra Landat 8 OLI
Band 1
Band 2
Band 3
Band 4
Band 5
Band 6
Band 7
Band 8
Band 9
Radio Metric Correction
VHI
MNDWI
Kerapatan RTH (SAVI)
Vegetasi (NDVI)
MSAVI
Pendahuluan
Indonesia sebagai negara kepulauan memiliki potensi terhadap abrasi pantai
Kondisi abrasi pantai
Tingkat keparahan abrasi pantai
Testing Results of Accuracy and Validation
NDVI and MSAVI Prediction
RMSE
MSE
MAPE
ME
MPE
MNDWI Prediction Abration
RMSE
MSE
MPE
ME
MPE
Metode
Comparison Data Classification Using ML methods
Random Forest
CART (Classification and Regression Trees Aplines Algorithms)
K-NN
MARS (Multivariate Adaptive Regression Splines Algorithms)
Research Location
Pantai Utara Tangerang