{"id":2531,"date":"2024-11-15T15:49:44","date_gmt":"2024-11-15T15:49:44","guid":{"rendered":"https:\/\/geotech.co.id\/?p=2531"},"modified":"2024-11-15T15:49:44","modified_gmt":"2024-11-15T15:49:44","slug":"identifikasi-mangrove-menggunakan-citra-satelit-landsat-8-5","status":"publish","type":"post","link":"https:\/\/geotech.co.id\/?p=2531","title":{"rendered":"Identifikasi Mangrove Menggunakan Citra Satelit Landsat 8"},"content":{"rendered":"\n

Mangrove adalah ekosistem penting yang berperan dalam menjaga keseimbangan lingkungan pesisir, melindungi garis pantai dari abrasi, dan menjadi habitat bagi berbagai jenis flora dan fauna. Namun, keberadaan mangrove sering kali terancam oleh aktivitas manusia, seperti konversi lahan menjadi tambak, pemukiman, atau pertanian. Untuk memantau keberadaan dan kondisi mangrove, salah satu metode yang efektif dan efisien adalah menggunakan teknologi penginderaan jauh, khususnya dengan citra satelit Landsat 8<\/strong>.<\/p>\n\n\n\n

\n\n\n\n

Keunggulan Landsat 8 dalam Pemantauan Mangrove<\/strong><\/h3>\n\n\n\n

Landsat 8 adalah salah satu satelit penginderaan jauh yang diluncurkan oleh NASA dan USGS. Satelit ini dilengkapi dengan dua sensor utama, yaitu Operational Land Imager (OLI)<\/strong> dan Thermal Infrared Sensor (TIRS)<\/strong>. Beberapa keunggulan Landsat 8 dalam identifikasi mangrove meliputi:<\/p>\n\n\n\n

    \n
  1. Resolusi Spasial yang Memadai<\/strong>
    Dengan resolusi 30 meter pada kanal multispektral, Landsat 8 mampu mengidentifikasi cakupan vegetasi seperti mangrove dengan baik pada skala regional.<\/li>\n\n\n\n
  2. Cakupan Wilayah Luas<\/strong>
    Landsat 8 mampu merekam wilayah yang luas dalam satu kali perekaman, sehingga cocok untuk memantau ekosistem mangrove secara menyeluruh.<\/li>\n\n\n\n
  3. Ketersediaan Data Secara Gratis<\/strong>
    Data Landsat 8 dapat diunduh secara gratis dari platform seperti Earth Explorer, sehingga pengguna memiliki akses mudah untuk memanfaatkan data ini.<\/li>\n\n\n\n
  4. Spektrum Multispektral dan Inframerah Dekat (NIR)<\/strong>
    Kanal spektral OLI, khususnya inframerah dekat (NIR) dan inframerah pendek (SWIR), sangat efektif untuk membedakan vegetasi mangrove dari jenis tutupan lahan lainnya.<\/li>\n<\/ol>\n\n\n\n
    \n\n\n\n

    Tahapan Identifikasi Mangrove Menggunakan Landsat 8<\/strong><\/h3>\n\n\n\n
      \n
    1. Pengumpulan Data Citra<\/strong>
      Data Landsat 8 dapat diperoleh melalui portal seperti USGS Earth Explorer atau platform lainnya. Pilih data dengan kondisi tutupan awan minimal untuk mendapatkan hasil analisis yang optimal.<\/li>\n\n\n\n
    2. Prapemrosesan Data<\/strong>
      Prapemrosesan meliputi koreksi radiometrik, koreksi atmosferik, dan pemotongan area studi (clipping) agar data lebih siap untuk dianalisis.<\/li>\n\n\n\n
    3. Ekstraksi Indeks Vegetasi<\/strong>
      Untuk mengidentifikasi mangrove, berbagai indeks vegetasi dapat digunakan, seperti:\n
        \n
      • NDVI (Normalized Difference Vegetation Index)<\/strong>: NDVI=(NIR\u2212RED)(NIR+RED)NDVI = \\frac{(NIR – RED)}{(NIR + RED)}NDVI=(NIR+RED)(NIR\u2212RED)\u200b NDVI membantu membedakan vegetasi hijau dengan tutupan lahan lainnya. Nilai NDVI tinggi menunjukkan keberadaan vegetasi.<\/li>\n\n\n\n
      • NDMI (Normalized Difference Moisture Index)<\/strong>: NDMI=(NIR\u2212SWIR)(NIR+SWIR)NDMI = \\frac{(NIR – SWIR)}{(NIR + SWIR)}NDMI=(NIR+SWIR)(NIR\u2212SWIR)\u200b NDMI digunakan untuk mengidentifikasi vegetasi yang terkait dengan kelembaban, seperti mangrove yang hidup di lingkungan pasang surut.<\/li>\n<\/ul>\n<\/li>\n\n\n\n
      • Klasifikasi Tutupan Lahan<\/strong>
        Metode klasifikasi, seperti Klasifikasi Terbimbing (Supervised Classification)<\/strong> dengan algoritma seperti Maximum Likelihood atau Machine Learning<\/strong> (Random Forest, SVM), dapat digunakan untuk memisahkan mangrove dari jenis tutupan lahan lainnya.<\/li>\n\n\n\n
      • Validasi Data<\/strong>
        Validasi dilakukan dengan membandingkan hasil klasifikasi dengan data lapangan atau citra resolusi tinggi seperti Google Earth. Tingkat akurasi dapat diukur menggunakan matriks kesalahan (confusion matrix).<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

        Mangrove adalah ekosistem penting yang berperan dalam menjaga keseimbangan lingkungan pesisir, melindungi garis pantai dari abrasi, dan menjadi habitat bagi berbagai jenis flora dan fauna. Namun, keberadaan mangrove sering kali terancam oleh aktivitas manusia, seperti konversi lahan menjadi tambak, pemukiman, atau pertanian. Untuk memantau keberadaan dan kondisi mangrove, salah satu metode yang efektif dan efisien […]<\/p>\n","protected":false},"author":2,"featured_media":2225,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-2531","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"blocksy_meta":[],"yoast_head":"\nIdentifikasi Mangrove Menggunakan Citra Satelit Landsat 8 - Geotech Survey Services<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/geotech.co.id\/?p=2531\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Identifikasi Mangrove Menggunakan Citra Satelit Landsat 8 - Geotech Survey Services\" \/>\n<meta property=\"og:description\" content=\"Mangrove adalah ekosistem penting yang berperan dalam menjaga keseimbangan lingkungan pesisir, melindungi garis pantai dari abrasi, dan menjadi habitat bagi berbagai jenis flora dan fauna. Namun, keberadaan mangrove sering kali terancam oleh aktivitas manusia, seperti konversi lahan menjadi tambak, pemukiman, atau pertanian. 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Namun, keberadaan mangrove sering kali terancam oleh aktivitas manusia, seperti konversi lahan menjadi tambak, pemukiman, atau pertanian. Untuk memantau keberadaan dan kondisi mangrove, salah satu metode yang efektif dan efisien…","_links":{"self":[{"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/posts\/2531","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/geotech.co.id\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2531"}],"version-history":[{"count":1,"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/posts\/2531\/revisions"}],"predecessor-version":[{"id":2532,"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/posts\/2531\/revisions\/2532"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geotech.co.id\/index.php?rest_route=\/wp\/v2\/media\/2225"}],"wp:attachment":[{"href":"https:\/\/geotech.co.id\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2531"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geotech.co.id\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2531"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geotech.co.id\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2531"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}