Pemetaan Kondisi Kesehatan Mangrove di Desa Daun, Kecamatan Sangkapura Pulau Bawean menggunakan Metode Mangrove Health Index (MHI)

Irmawan, Wahyu Dwi Irmawan and Dhira Kurniawan, S. S.Kel., M.Sc. and Defri Yona, S.Pi, M.Sc.stud., D.Sc (2022) Pemetaan Kondisi Kesehatan Mangrove di Desa Daun, Kecamatan Sangkapura Pulau Bawean menggunakan Metode Mangrove Health Index (MHI). Sarjana thesis, Universitas Brawijaya.

Abstract

Ekosistem mangrove yang ada di dunia mempunyai luas hingga sekitar 18 juta hektar. Indonesia sendiri memiliki luasan hutan mangrove 3,3 juta hektar. Hutan mangrove memiliki fungsi penting bagi suatu perairan menjadi tempat mencari makan biota akuatik, tempat bereproduksi dan berkembang biak dari kecil hingga dewasa. Mangrove juga menjadi pelindung dari proses abrasi serta menahan dari terjangan angin kencang yang mengarah ke daratan. Kesesuaian komponen biotik dan abiotik juga berpengaruh pada kerusakan ekosistem mangrove. Manusia juga berperan penting dalam menjaga ekosistem mangrove atau bahkan bisa menjadi faktor kerusakan yang utama bagi ekosistem mangrove itu sendiri. Diperlukan penelitian kesehatan mangrove untuk mengetahui kerusakan atau kesehatan mangrove di suatu wilayah. Kendala sarana dan pra-sarana menjadi faktor yang sering terjadi saat melakukan penelitian. Metode penginderaan jauh (Remote Sensing) sangat cocok digunakan untuk menghindari permasalahan tersebut. Stratiffied random sampling (SRS) juga digunakan untuk kondisi medan yang sulit serta area mangrove yang luas. Penelitian dilakukan di Desa Daun, Kecamatan Sangkapura, Kabupaten Gresik, Pulau Bawean pada bulan April 2022. Penelitian ini bertujuan mengidentifikasi kemampuan citra satelit sentinel-2A MSI-MultiSpectral untuk pengolahan data peta kesehatan mangrove menggunakan metode Mangrove Health Index (MHI) dan untuk mengidentifikasi kesehatan area mangrove pada wilayah kajian. MHI berfungsi untuk menentukan kesehatan mangrove disuatu wilayah dengan parameter penting tutupan mangrove (C), Diameter (DBH), dan Kerapatan pancang (Nsp). Kategori MHI antara lain kategori MHI Poor MHI 0 ≤ 33.33%, Moderate 33.33 < MHI ≤ 66.67, Excellent MHI > 66.67. Formulai MHI ini merupakan gabungan dari beberapa indeks vegetasi antara lain Normalized Burn Ratio (NBR), Green Chlorophyll Index (GCI), Structure Insensitive Pigment Index (SIPI), dan Atmospherically Resistant Vegetation Index (ARVI). Rumus MHI yang digunakan pada penelitian ini MHI = 102.12*NBR - 4.64*GCI + 178.15*SIPI + 159.53*ARVI - 252.39. Ground Check dan pengambilan data lapang menggunakan metode SRS dengan transek 10m x 10m. Jumlah plot yang digunakan yaitu 15 plot dengan 5 kali pengulangan setiap stratanya. Pengolahan citra satelit pada Google Earth Engine melalui proses pemotongan citra, false color area mangrove, koreksi awan menggunakan rumus dari sentinel-2A, indeks vegetasi dan tresholding didapatkan hasil luasan mangrove 69,23 Ha. Kategori poor sebesar 5,99 Ha, moderate yaitu 43,34 Ha, dan excellent yaitu 19,90 Ha. Visual peta MHI mampu mempermudah dalam menentukan area mana yang tergolong Poor, Moderate, maupun Excellent. Berdasarkan uji regresi data citra dan data lapang dihasilkan nilai determinan R Square / R ² sebesar 0,8384 atau 83 % yang berarti data lapang mempunyai hubungan kuat terhadap nilai citra MHI. Ditemukan 6 jenis mangrove sejati di seluruh plot, diantaranya yaitu jenis Rhizophora stylosa, Rhizophora apiculata, Rhizophora mucronata, Ceriops tagal, Sonneratia alba, dan Avicennia marina. Kesimpulan yang dapat diambil pada penelitian ini formula MHI mampu menggambarkan kondisi kesehatan mangrove pada wilayah kajian hingga 83 % yang tergolong hubungan kuat.

English Abstract

The mangrove ecosystem in the world has an area of about 18 million hectares. Indonesia itself has a mangrove forest area of 3.3 million hectares. Mangrove forests have an important function for a waters to become a place to forage for aquatic biota, a place to reproduce and breed from small to adult. Mangroves are also a protector from the abrasion process as well as withstand the brunt of strong winds that lead to land. The suitability of biotic and abiotic components also affects the damage to the mangrove ecosystem. Humans also play an important role in maintaining the mangrove ecosystem or can even be the main damage factor for the mangrove ecosystem itself. Mangrove health research is needed to determine the damage or health of mangroves in an area. Facilities and infrastructure constraints are factors that often occur when conducting research. Remote sensing method (Remote Sensing) is very suitable to be used to avoid these problems. Stratified random sampling (SRS) is also used for difficult terrain conditions and large mangrove areas. This research was conducted in Daun Village, Sangkapura District, Gresik Regency, Bawean Island, in April 2022. This study aims to identify the capability of MSI-MultiSpectral Sentinel-2A satellite imagery for processing mangrove health map data using the Mangrove Health Index (MHI) method and for processing mangrove health map data using the Mangrove Health Index (MHI) method. identify the health of the mangrove area in the study area. MHI functions for the health of mangroves in an area with important parameters of mangrove cover (C), Diameter (DBH), and Stake density (Nsp). MHI categories include MHI Poor MHI 0 33.33%, Moderate 33.33 < MHI 66.67, Excellent MHI > 66.67. This MHI formulation is a combination of several vegetation indices including the Normalized Burn Ratio (NBR), Green Chlorophyll Index (GCI), Structure Insensitive Pigment Index (SIPI), and Atmospherically Resistant Vegetation Index (ARVI). The MHI formula used in this study is MHI = 102.12*NBR - 4.64*GCI + 178.15*SIPI + 159.53*ARVI - 252.39. Ground Check and field data collection using the SRS method with a 10m x 10m transect. The number of plots used is 15 plots with 5 repetitions for each stratum. Processing of satellite imagery on Google Earth Engine through image cropping, false color mangrove area, cloud correction using the formula from sentinel-2A, vegetation index and thresholding, the result is 69,23 hectares of mangrove area. The poor category is 5,99 Ha. moderate is 43,34 Ha, and excellent is 19,90 Ha. The visual map of MHI makes it easier to find out which areas are classified as Poor, Moderate, or Excellent. Based on the regression test of image data and field data, the determinant value of R Square / R² is 0.8384 or 83%, which means that field data has a very high influence on the value of the MHI image. Six true mangrove species were found in all plots, including Rhizophora stylosa, Rhizophora apiculata, Rhizophora mucronata, Ceriops tagal, Sonneratia alba, and Avicennia marina. The conclusion that can be drawn in this study is that the MHI formula is able to describe the health condition of mangroves in the study area up to 83% which is classified as a strong correlation.

Item Type:	Thesis (Sarjana)
Identification Number:	0522080340
Subjects:	500 Natural sciences and mathematics > 551 Geology, hydrology, meteorology > 551.4 Geomorphology and hydrosphere > 551.46 Oceanography and submarine geology
Divisions:	Fakultas Perikanan dan Ilmu Kelautan > Ilmu Kelautan
Depositing User:	soegeng sugeng
Date Deposited:	13 Apr 2023 03:16
Last Modified:	13 Apr 2023 03:16
URI:	http://repository.ub.ac.id/id/eprint/198261

Text (DALAM MASA EMBARGO) Wahyu Dwi Irmawan.pdf Restricted to Registered users only until 31 December 2024. Download (7MB)

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