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