Analisis Tutupan Lahan dengan Menggunakan Metode Break for Additive Seasonal and Trend (BFAST) Berdasarkan Indeks Vegetasi
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Date
2016Author
Tobing, Ramos Lumban
Advisor(s)
Zarlis, Muhammad
Zarlis, M
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Remote sensing methods (Remote Sensing) has been widely used in various fields including the field of land cover / vegetation, including plantations. Remote sensing products from the many available include NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), which is a proxy indicator of a location or condition of land cover that location. From some research, NDVI has been widely used but EVI is still not widely used. We compared the effect of using NDVI and EVI on the amount and timing changes recorded by using BFAST (Breaks For Additive Seasonal and Trend). The data used is the MODIS (Moderate Resolution Imaging Spectroradiometer) daily 16 NDVI and EVI form a composite image (April 6, 2000 till 16 November 2014) of the four pixels (pixel 293,294,295 and 296) around the tower flux Aek Loba. Results BFast method of the data NDVI and EVI in the validation of the map Landsat LAI (Leaf Area Index) and a map of google earth are verified with field data on plantation PT.Socpin Aek Loba. Of the overall amount and timing of changes detected in four different pixels with both vegetation indices because of the quality of the data due to cloud cover. It was found that EVI is more sensitive than NDVI to detect sudden changes such as index data LAI October 2013-November 2013, and a data field where there is progress in the plantation land clearing PT.Socpin Aek Loba. The results showed that EVI for monitoring land cover in tropical plantation area covered by intense clouds better than NDVI it. Nevertheless, further research by increasing the spatial resolution of the satellite imagery is highly recommended for applications NDVI Metode penginderaan jarak jauh (Remote Sensing) telah banyak digunakan dalam berbagai bidang termasuk diantaranya bidang tutu-pan lahan/vegetasi termasuk perkebunan. Produk dari penginderaan jauh tersebut banyak tersedia diantaranya NDVI (Normalized Difference Vegetation Index) dan EVI (Enhanced Vegetation Indeks) yang merupakan indikator proxy dari suatu lokasi atau kondisi tutupan lahan lokasi tersebut. Dari beberapa penilitian, NDVI telah banyak digunakan namun EVI masih belum banyak digunakan. Kami membandingkan pengaruh dari penggunaan NDVI dan EVI pada jumlah dan waktu perubahan yang terekam dengan menggunakan metode BFAST (Breaks For Additive Seasonal and Trend). Data yang digunakan adalah MODIS (Moderate Resolution Imaging Spectroradiometer)16 harian NDVI dan EVI berupa gambar komposit (06 April 2000 s.d. 16 November 2014) dari empat piksel (pixel 293,294,295 dan 296) disekitar menara fluks Aek Loba. Hasil metode BFAST dari data NDVI dan EVI di validasi kan dengan peta landsat LAI (Leaf Area Indeks) dan peta dari google earth yang diverifikasi dengan data lapangan pada perkebunan PT.Socpin Aek Loba. Dari keseluruhan jumlah dan waktu perubahan terdeteksi pada empat piksel berbeda dengan kedua indek vegetasi karena kualitas data karena tutupan awan. Ditemukan bahwa EVI lebih sensitif dibandingkan NDVI untuk mendeteksi perubahan mendadak seperti data indeks LAI Oktober 2013-Nopember 2013 dan data lapangan dimana ada pengerjaan land clearing di perkebunan PT.Socpin Aek Loba. Hasil penelitian menunjukkan bahwa EVI untuk pemantauan tutupan lahan di kawasan perkebunan tropis yang ditutupi oleh awan intens lebih baik dari NDVI itu. Meskipun demikian, penelitian lebih lanjut dengan meningkatkan resolusi spasial dari citra satelit untuk aplikasi NDVI sangat dianjurkan.
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