Sholikah, Dinna Hadi and Prof. Dr. Ir. Soemarno and Dr. Kurniawan Sigit Wicaksono (2022) Pemanfaatan Penginderaan Jauh Untuk Menduga Indeks Produktivitas Tanaman Dan Keberlanjutan Lahan Kopi Rakyat Di Kecamatan Wajak, Kabupaten Malang. Magister thesis, Universitas Brawijaya.
Abstract
Kecamatan Wajak memiliki karakteristik lahan berpasir dan lereng beragam yang terletak di lereng Gunung Semeru. Saat ini, di Kecamatan Wajak juga sedang dilakukan pengembangan komoditas pertanian khususnya tanaman kopi. Hal ini didukung dengan bertambahnya luasan lahan kopi dari tahun 2018 ke 2019 sebesar 31,20%. Sedangkan kondisi lahan dengan lereng beragam dan didominasi lereng curam akan menimbulkan permasalahan lahan, meliputi bahaya erosi maupun longsor, serta adanya perbedaan kandungan hara tanah yang signifikan. Maka perlu upaya pendugaan produksi kopi dan keberlanjutan lahan untuk budidaya tanaman kopi melalui pemodelan indeks produksi kopi maupun indeks keberlajutan lahan kopi. Metode penilaiannya secara terrestrial, yang memiliki tingkat akurasi tinggi. Selain itu, monitoring secara cepat juga dapat digunakan untuk menilai keberhasilan kebun kopi rakyat melalui penginderaan jauh yang memanfaatkan transformasi spektral citra beresolusi tinggi berupa Citra Sentinel 2A. Penelitian ini bertujuan untuk menganalisis hubungan keterkaitan faktor indeks tanaman, indeks tanah, dan indeks vegetasi maupun indeks tanah dalam menganalisis produksi kopi rakyat. Metode penentuan titik pengamatan berupa stratified random sampling, dengan strata berupa luas lahan kopi, umur produktif kopi, dan aksesbilitas. Terdapat 33 titik pengamatan, di mana luas plot pengamatan data produksi sebesar 10×10 m sesuai ukuran pixel citra Sentinel 2A. Penelitian dilakukan dengan mengambil data produksi kopi (ton/ha) 1 kali musim panen sebagai variabel terikat. Penelitian dilakukan dengan menganalisis berdasarkan data satelit, tanah, dan tanaman. Data citra Sentinel 2A diunduh tanggal 22 Juli 2022. Data citra Sentinel 2A digunakan untuk transformasi spektral ke dalam berbagai indeks vegetasi maupun indeks tanah. Data indeks produktivitas tanaman diperoleh berdasarkan parameter meliputi diameter batang (DB), diameter kanopi (DK), jumlah cabang produktif (JCP), panjang cabang produktif (PCP), leaf area index (LAI), dan total klorofil (TK). Data indeks keberlanjutan lahan diperoleh menggonakan pendekatan data erodibilitas tanah (K) (stuktur tanah, tekstur tanah, permeabilitas, dan bahan organik) dan indeks produktivitas tanah (kedalaman efektif, lereng, tekstur tanah lapisan 0-30 cm dan 30-60 cm, drainase, KB, KTK, pH dan % C-Organik). Analisis data statistik berupa uji normalitas, korelasi, regresi linier, multi linier berganda, dan eksponensial. Penyusunan model menggunakan software ArcGIS 10.8 dan RStudio. Hubungan antara indeks keberlanjutan lahan, indeks produktivitas tanaman, SR dan NDSI terhadap produksi kopi apat dinyatakan dalam bentuk triple bottom line yang tergolong berlanjut, karena memiliki hubungan yang signifikan terhadap produksi kopi. Hubungan antara SR terhadap produksi kopi menghasilkan model berupa Ŷ= (0,27×SR)-0,74 (r=0,88; R2=0,77, ρ(value)<0,05). Hubungan NDSI terhadap produksi kopi menghasilkan model berupa Ŷ= 0,13e3.06×NDSI (r=0,50; R2=0,27, ρ(value)<0,05). Hubungan indeks erodibilitas tanah dengan produksi kopi menghasilkan model berupa Ŷ= 0.032e6.0737×Erodibilitas Tanah (r=0,81; R2=0,67, ρ(value)<0,05). Hubungan antara indeks produktivitas lahan dengan produksi kopi menghasilkan model berupa Ŷ= 0,42e0.02×Indeks Produktivitas Lahan (r=0,57; R2=0,36, ρ(value)<0,05). Indeks produksi kopi berbasis parameter tanaman dengan produksi kopi mengahsilkan model berupa Ŷ=(0.163×LAI)+(0.035×NPB)+(0.792×LPB)+(0.974*SD)+(0.032*CD)-(0.0002×TC))–1.135 (r=0,93;R2=0,82, ρ(value)<0,05). Hubungan antara indeks produktivitas tanaman dengan produksi kopi menghasilkan model berupa Ŷ= (0,02×Indeks Produktivitas Tanaman)+0,51(r=0,87; R2=0,76, ρ(value)<0,05).
English Abstract
Wajak Subdistrict has the characteristics of sandy land and diverse slopes located on the slopes of Mount Semeru. Currently, in Wajak District, the development of agricultural commodities, especially coffee plants, is also being carried out. This is supported by the increase in coffee land area from 2018 to 2019 by 31.20%. Meanwhile, land conditions with various slopes and dominated by steep slopes will cause land problems, including the danger of erosion and landslides, as well as significant differences in soil nutrient content. Therefore, efforts are needed to estimate coffee production and land sustainability for coffee crop cultivation by modeling the coffee production index and coffee land sustainability index. The assessment method is terrestrial, which has a high degree of accuracy. In addition, rapid monitoring can also be used to assess the success of community coffee plantations through remote sensing that utilizes high-resolution image spectral transformations in the form of Sentinel 2A Imagery. This study aims to analyze the relationship between plant index factors, soil index, vegetation index, and soil index in analyzing people's coffee production. The method of determining observation points is in the form of stratified random sampling, with strata in the form of coffee land area, coffee productive age, and accessibility. There are 33 observation points, where the area of the production data observation plot is 10×10 m according to the pixel size of the Sentinel 2A imagery. The study was conducted by taking coffee production data (tons/ha) 1 time during the harvest season as a bound variable. The study was conducted by analyzing based on satellite, soil, and plant data. Sentinel 2A image data was downloaded on July 22, 2022. Sentinel 2A imagery data is used for spectral transformations into various vegetation indices as well as soil indices. Data on the crop productivity index obtained based on parameters include stem diameter (SD), canopy diameter (CD), number (NPB) and length of productive branches (LPB), leaf area index (LAI), and total chlorophyll (TC). Land sustainability index data were obtained using the soil erodibility (K) data approach (soil structure, soil texture, permeability, and organic matter) and soil productivity index (effective depth, slope, soil texture layer 0-30 cm and 30-60 cm, drainage, BS, CEC, pH, and % C-Organic). Statistical data analysis in the form of normality, correlation, linear regression, multiple multi-linear, and exponential tests. Model building using ArcGIS 10.8 and RStudio software. The relationship between the land sustainability index, crop productivity index, SR, and NDSI to apat coffee production is expressed in the form of a triple bottom line which is classified as continuing because it has a significant relationship to coffee production. The relationship between SR and coffee production produces a model in the form of Ŷ= (0,27×SR)-0,74 (r=0,88; R2=0,77, ρ(value)<0,05). The relationship of NDSI to coffee production produces a model in the form of Ŷ= 0,13e3.06×NDSI (r=0,50; R2=0,27, ρ(value)<0,05). The relationship of soil erodibility index with coffee production produces a model of Ŷ= 0.032e6.0737×Soil Erodibility (r=0,81; R2=0,67, ρ(value)<0,05). The relationship between the land productivity index and coffee production produces a model in the form of Ŷ= 0,42e0.02×Land Productivity Index (r=0,57; R2=0,36, ρ(value)<0,05). The coffee production index is based on plant parameters with coffee production producing a model in the form of Ŷ=(0.163×LAI) +(0.035×NPB) +(0.792×LPB) +(0.974*SD) +(0.032*CD) -(0.0002×TC))–1.135 (r=0,93; R2=0,82, ρ(value)<0,05). The relationship between the crop productivity index and coffee production produces a model of Ŷ= (0,02× Plant Productivity Index) +0,51(r=0,87; R2=0,76, ρ(value)<0,05)
| Item Type: | Thesis (Magister) |
|---|---|
| Identification Number: | 0422040063 |
| Subjects: | 600 Technology (Applied sciences) > 631 Specific techniques; apparatus, equipment materials > 631.4 Soil science |
| Divisions: | S2/S3 > Magister Pengelolaan Tanah dan Air, Fakultas Pertanian |
| Depositing User: | Nur Cholis |
| Date Deposited: | 05 Jun 2023 07:49 |
| Last Modified: | 05 Jun 2023 07:49 |
| URI: | http://repository.ub.ac.id/id/eprint/200763 |
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