Perbandingan Metode Koreksi Topografi Pada Citra Satelit Landsat 8 Di Wilayah Gunung Telomoyo, Jawa Tengah

Widhaningtyas, Tantri Utami; Putra, Akbar Cahyadhi Pratama; Fariz, Trida Ridho

doi:10.15294/jg.v17i2.22863

Cited by 2 publications

(3 citation statements)

References 10 publications

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“…Peta DTA Rawa Pening DTA Rawa Pening dikelilingi oleh kompleks gunung serta pegunungan dengan didominasi oleh bentuk lahan asal vulkanik (Gambar 6.4). Pada bagian utara, selatan dan barat merupakan area Gunung Ungaran, pegunungan medan lava, kompleks Gunung Telomoyo, dan Gunung Merbabu, sedangkan di bagian Timur terdapat pegunungan struktural antiklinal (Mardiatno et al, 2021;Widhaningtyas et al, 2020). DTA Rawa Pening memiliki kemiringan lereng yang beragam dari landai hingga terjal, elevasi tertinggi adalah 3076 mpdl dan elevasi terendah adalah sekitar 445 mdpl.…”

Section: Kondisi Lingkungan Abiotikunclassified

Kondisi Lingkungan Danau Rawa Pening

Amalia,

Fariz,

Atunnisa

et al. 2023

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Indonesia adalah negara yang memiliki jumlah danau yang banyak. Diantara jumlah danau tersebut, ada beberapa danau yang memiliki kerusakan lingkungan yang parah sehingga perlu direvitalisasi. Danau Rawa Pening menjadi salah satu danau prioritas penanganan oleh pemerintah. Revitalisasi danau adalah kegiatan untuk mengembalikan fungsi alami danau sebagai tampungan air melalui beberapa kegiatan yang bersifat struktural maupun non-struktural. Dalam perumusan kebijakan dan strategi revitalisasi danau Rawa Pening dibutuhkan data dan informasi supaya hasilnya tepat sasaran. Hal tersebut adalah lingkungan yang mana terdiri dari komponen abiotik, biotik dan budaya. Pemahaman kondisi lingkungan secara komprehensif dirasa akan mempermudah dalam penentuan strategi dan kebijakan pengelolaan Danau Rawa Pening. Setelah memahami kondisi lingkungan, kita bisa mengdentifikasi bentuk pengelolaan Danau Rawa Pening. Bentuk pengelolaan Danau Rawa Pening sebaiknya adalah dengan tindakan preventif, bukan tindakan seperti rehabilitasi. Bentuk pengelolaan bisa difokuskan pada pengendalian erosi-sedimentasi dan eutrofikasi yang tak hanya disekitar Danau Rawa Pening tetapi juga bagian hulu sub-DAS yang berada di DTA Rawa Pening.

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Section: Kondisi Lingkungan Abiotikunclassified

Kondisi Lingkungan Danau Rawa Pening

Amalia,

Fariz,

Atunnisa

et al. 2023

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“…Soil samples were analyzed in the laboratory to determine texture (Gee and Bauder, 1986), bulk density (Tan, 2005), particle density (Blake and Hartge, 1986), porosity (Blake and Hartge, 1986), permeability (LPT, 1979), and soil penetration (Armbruster et al, 1990).…”

Section: Soil Analysismentioning

confidence: 99%

“…Landsat 8 is the latest generation of satellite imagery replacing Landsat 7, which has an Onboard Operational Land Imager (OLI) sensor and a Thermal Infrared Sensor (TIRS) with 11 channels with a resolution of 15 m. The pre-processing was divided into radiometric correction and haze-cloud removal to clear up the dust in the image (Widhaningtyas et al, 2020). The next step was to transform satellite images using a soil-index transformation consisting of EVI and MSAVI.…”

Section: Image Processing and Soil-vegetation Index Transformationmentioning

confidence: 99%

Comparison of soil physical properties and soil-vegetation indices to predict rice productivity in Malang Regency of East Java

Putra

Sudarto

Ridwan

et al. 2021

J.Degrade.Min.Land Manage.

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Rice has become the leading food commodity in Indonesia, with total production reached +54.60 million tons in 2019. However, the production tended to decrease by around 8% from 2018 to 2019, while the rice consumption increased by +1.53 tons. This study aims to develop a rice production estimation model using the soil-vegetation index transformation (MSAVI and SAVI) and soil physical properties, which has the advantage of being faster, cheaper, and more accurate than conventional methods. The soil physical properties were taken based on soil mapping units and analyzed with soil physical parameters. The results showed strong relationships between rice productivity - soil physical characteristics and rice productivity – MSAVI and EVI with r values of 0.97, 0.83, and 0.74, respectively. The soil physical properties have a better coefficient of determination and accuracy than soil-vegetation index. The prediction model of rice production by soil physical properties is formulated inward γ = -8.96+0.01 (Top Soil Sand) + 0.01 (Top Soil Silt) + 6.28 (Bulk Density) - 14.07 (Penetration) - 0.13 (Sub Soil Permeability). There is no difference in the productivity value between model and laboratory analysis result. These results indicate that the rice yield prediction model can be used for estimation purposes.

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Perbandingan Metode Koreksi Topografi Pada Citra Satelit Landsat 8 Di Wilayah Gunung Telomoyo, Jawa Tengah

Cited by 2 publications

References 10 publications

Kondisi Lingkungan Danau Rawa Pening

Kondisi Lingkungan Danau Rawa Pening

Comparison of soil physical properties and soil-vegetation indices to predict rice productivity in Malang Regency of East Java

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