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All Journal Jurnal Hutan Pulau-Pulau Kecil : Jurnal Ilmu-Ilmu Kehutanan dan Pertanian MAKILA: Jurnal Penelitian Kehutanan
Papilaya, Patrich Phill Edrich
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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POLA SPASIAL PENUTUPAN/PENGGUNAAN LAHAN MENGGUNAKAN PENDEKATAN SPATIAL METRIC DI DAS WAE RIUAPA Leatomu, Olvan; Papilaya, Patrich Phill Edrich; Boreel, Aryanto
MAKILA Vol 18 No 1 (2024): Makila: Jurnal Penelitian Kehutanan
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/makila.v18i1.10699

Abstract

The purpose of this study is to employ a spatial metric approach to analyse land cover/land use patterns in the Wae Riuapa watershed from 2015 to 2022. This study was carried out using two levels of analysis. First, a spatial analysis utilising Geographic Information System (GIS) software was used to identify the land cover/land use classes at the research locations in 2015 and 2022. Landsat 8 imagery from 2015 and Landsat 9 imaging from 2022 are the data used. Using spatial metrics techniques, the second step of analysis in this study examined spatial patterns of land cover and land use. With an area of 15184.70 Ha in 2015 and 13587.09 Ha in 2022, secondary dryland forests led the land cover/land use class, according to the statistics. Density and continuity are seen to be declining in spatial patterns, whereas fragmentation indicators are rising. This demonstrates that because of the fragmentation of the greatest land cover/land use class resulting from several land use conversion activities, the spatial link between patches tends to be disconnected and the distance between clusters rises.
ANALISIS TUTUPAN/PENGGUNAAN LAHAN KAWASAN HUTAN LINDUNG DI KOTA AMBON MENGGUNAKAN INTEGRASI TEKNOLOGI PENGINDERAAN JAUH DAN SIG Harmusial, Falery; Papilaya, Patrich Phill Edrich; Boreel, Aryanto
JURNAL HUTAN PULAU-PULAU KECIL Vol 8 No 2 (2024): JHPPK
Publisher : Program Studi Manajemen Hutan, Pascasarjana Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jhppk.v8i2.15297

Abstract

This research aims to analyze land cover/use classes in protected forest areas in Ambon City. The method used in this research is guided classification Maximum Likelihood Classification (MLC), where this method classifies images based on the similarity of the image spectrum to conditions in the field. Based on research results, land cover in the Mount Sirimau protected forest in 2024 consists of 7 land cover classes, namely: primary dry land forest, secondary dry land forest, open land, settlements, dry land agriculture, mixed dry land agriculture, and shrubs. The Mount Nona protected forest in 2024 will have 4 land cover classes, namely: secondary dry land forest, dry land agriculture, mixed dry land agriculture, and shrubs. The image accuracy test was carried out using a confusion matrix (comparison of image interpretation with field conditions) with an accuracy level of 92%.
Aplikasi Google Earth Engine Dalam Menyediakan Citra Satelit Sumberbedaya Alam Bebas Awan Papilaya, Patrich Phill Edrich
MAKILA Vol 16 No 2 (2022): Makila: Jurnal Penelitian Kehutanan
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/makila.v16i2.6586

Abstract

translator Ketersediaan Citra Satelit yang berkualitas menjadi salah satu syarat keberhasilan penelitian sumberdaya alam, secara khusus dibidang kehutanan. Google Earth Engine (GEE) adalah salah satu platform berbasis awan (cloud) yang disediakan oleh Google. GEE bekerja berbasis Bahasa program Java Script. Hasil penelitian menunjukan bahwa aplikasi GEE mampu menyediakan citra satelit yang memiliki tutupan awan sangat rendah atau bebas awan (clouds free). Aplikasi GEE merupakan salah satu solusi penelitian sumberdaya alam terutama pada pulau-pulau kecil di Provinsi Maluku. Afrikaans Albanian - shqipe Arabic - ‎‫العربية‬‎ Armenian - Հայերէն Azerbaijani - azərbaycanca Basque - euskara Belarusian - беларуская Bengali - বাংলা Bulgarian - български Catalan - català Chinese - 中文（简体中文） Chinese - 中文 (繁體中文) Croatian - hrvatski Czech - čeština Danish - dansk Dutch - Nederlands English Esperanto - esperanto Estonian - eesti Filipino Finnish - suomi French - français Galician - galego Georgian - ქართული German - Deutsch Greek - Ελληνικά Gujarati - ગુજરાતી Haitian Creole - kreyòl ayisyen Hebrew - ‎‫עברית‬‎ Hindi - हिन्दी Hungarian - magyar Icelandic - íslenska Indonesian - Bahasa Indonesia Irish - Gaeilge Italian - italiano Japanese - 日本語 Kannada - ಕನ್ನಡ Korean - 한국어 Latin - Lingua Latina Latvian - latviešu Lithuanian - lietuvių Macedonian - македонски Malay - Bahasa Melayu Maltese - Malti Norwegian - norsk Persian - ‎‫فارسی‬‎ Polish - polski Portuguese - português Romanian - română Russian - русский Serbian - Српски Slovak - slovenčina Slovenian - slovenščina Spanish - español Swahili - Kiswahili Swedish - svenska Tamil - தமிழ் Telugu - తెలుగు Thai - ไทย Turkish - Türkçe Ukrainian - українська Urdu - ‎‫اردو‬‎ Vietnamese - Tiếng Việt Welsh - Cymraeg Yiddish - יידיש Double-click Select to translate
ANALISIS SPASIAL PERUBAHAN TUTUPAN LAHAN PULAU SAPARUA DAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA Pitono, Aurora Agnesia Pramuthia; Papilaya, Patrich Phill Edrich; Boreel, Aryanto
JURNAL HUTAN PULAU-PULAU KECIL Vol 9 No 2 (2025): JHPPK
Publisher : Program Studi Manajemen Hutan, Pascasarjana Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jhppk.v9i2.20008

Abstract

Penelitian ini bertujuan untuk menganalisis tutupan lahan Pulau Saparua dari tahun 2019 hingga 2024. Metode yang digunakan melibatkan analisis spasial berbasis Google Earth Engine (GEE) dan Analitycal Hiearchy Process (AHP). Dalam studi ini dilakukan tahap identifikasi kelas penutupan lahan di lokasi penelitian pada tahun 2019 dan 2024 menggunakan Google Earth Engine (GEE). Selanjutnya, faktor-faktor pendorong perubahan tutupan lahan diidentifikasi dan dianalisis menggunakan metode Analytical Hierarchy Process (AHP) untuk menentukan tingkat pengaruh relatif dari variabel. Menurut hasil penelitian, pertanian mendominasi kelas penutupan lahan dengan luasa 8332,45 ha pada tahun 2019 dan 8883,63 ha pada tahun 2024. Sedangkan, hutan mengalami penurunan. Pertanian menjadi faktor pendorong utama. Ini disebabkan karena tingginya ketergantungan masyarakat terhadap sektor pertanian sebagai sumber penghidupan.
Co-Authors Boreel, Aryanto Harmusial, Falery Leatomu, Olvan Pitono, Aurora Agnesia Pramuthia