Estimasi Volume Oksigen Vegetasi Tegakan Menggunakan Citra Planetscope di Kecamatan Sidomukti Kota Salatiga

Gusti Riffat Priatmadja, Dr. Retnadi Heru Jatmiko, M.Sc.

2025 | Skripsi | KARTOGRAFI DAN PENGINDRAAN JAUH

Penelitian ini bertujuan menganalisis estimasi volume oksigen vegetasi tegakan di Kecamatan Sidomukti, Kota Salatiga menggunakan citra satelit PlanetScope. Tujuan utama meliputi pemetaan distribusi oksigen, perbandingan efektivitas indeks vegetasi (NDVI, EVI, SAVI), serta analisis korelasi antara above ground biomass (AGB) dan ketinggian pohon terhadap produksi oksigen. Hasil penelitian diharapkan berkontribusi secara teoritis pada pengembangan ilmu penginderaan jauh terkait analisis vegetasi, serta secara praktis mendukung pengelolaan ruang terbuka hijau dan kebijakan lingkungan berkelanjutan.

Citra yang digunakan adalah PlanetScope Level 3-B (koreksi geometrik, radiometrik, atmosferik). Identifikasi vegetasi tegakan dilakukan melalui klasifikasi algoritma Random Forest di Google Earth Engine, dengan evaluasi akurasi menggunakan confusion matrix dan indeks Kappa. Data lapangan diperoleh melalui purposive sampling pada vegetasi tegakan dengan pengukuran kerapatan kanopi (foto hemispherical + GLA), diameter batang (DBH), dan tinggi pohon (laser range finder). Estimasi biomassa dihitung dengan persamaan alometrik Brown (1997) untuk iklim lembab, sedangkan estimasi oksigen dilakukan melalui integrasi indeks vegetasi, Leaf Area Index (LAI), dan luas area vegetasi. Analisis regresi Random Forest diterapkan untuk menghubungkan indeks vegetasi dengan data lapangan, dilanjutkan uji normalitas, korelasi Spearman, serta uji akurasi menggunakan R² dan NRMSE.

Hasil penelitian menunjukkan estimasi oksigen vegetasi tegakan berkisar 0,58–1,18 g/m². Konsentrasi tertinggi berada di area vegetasi padat (taman kota, jalur hijau), sedangkan permukiman padat dan lahan terbangun memiliki nilai rendah. Distribusi oksigen cenderung terfragmentasi, mengurangi efektivitas ekosistem dalam mendukung kualitas udara. Perbandingan indeks vegetasi menunjukkan EVI paling stabil pada area vegetasi padat, SAVI efektif pada area dengan pengaruh tanah tinggi, sedangkan NDVI kurang optimal karena sensitif terhadap saturasi dan atmosfer. Uji korelasi memperlihatkan hubungan lemah antara AGB dan oksigen (r = 0,312) serta hampir tidak ada hubungan antara tinggi pohon dan oksigen (r = –0,011), menegaskan bahwa produksi oksigen lebih dipengaruhi kerapatan tajuk. Hasil ini menekankan pentingnya pemilihan indeks vegetasi yang tepat serta perencanaan vegetasi urban untuk menjaga keseimbangan oksigen di perkotaan.

This study aims to analyze estimates of vegetation oxygen volume in Sidomukti District, Salatiga City, using PlanetScope satellite imagery. The main objectives include mapping oxygen distribution, comparing the effectiveness of vegetation indices (NDVI, EVI, SAVI), and analyzing the correlation between above-ground biomass (AGB) and tree height on oxygen production. The results of this study are expected to contribute theoretically to the development of remote sensing science related to vegetation analysis, as well as practically support the management of green open spaces and sustainable environmental policies.

The imagery used was PlanetScope Level 3-B (geometric, radiometric, and atmospheric correction). Vegetation identification was carried out using Random Forest algorithm classification in Google Earth Engine, with accuracy evaluation using a confusion matrix and Kappa index. Field data were obtained through purposive sampling of standing vegetation with measurements of canopy density (hemispherical photo + GLA), stem diameter (DBH), and tree height (laser range finder). Biomass estimation was calculated using Brown's (1997) allometric equation for humid climates, while oxygen estimation was performed through the integration of vegetation indices, Leaf Area Index (LAI), and vegetation area. Random Forest regression analysis was applied to link vegetation indices with field data, followed by normality tests, Spearman's correlation, and accuracy tests using R² and NRMSE.

The results of the study show that the estimated oxygen production of vegetation stands ranges from 0.58 to 1.18 g/m². The highest concentrations are found in areas with dense vegetation (city parks, green belts), while densely populated residential areas and built-up land have low values. The distribution of oxygen tends to be fragmented, reducing the effectiveness of the ecosystem in supporting air quality. Comparisons of vegetation indices show that EVI is most stable in areas with dense vegetation, SAVI is effective in areas with high soil influence, while NDVI is less optimal due to its sensitivity to saturation and atmospheric conditions. Correlation tests show a weak relationship between AGB and oxygen (r = 0.312) and almost no relationship between tree height and oxygen (r = –0.011), confirming that oxygen production is more influenced by canopy density. These results emphasize the importance of selecting the appropriate vegetation index and urban vegetation planning to maintain oxygen balance in urban areas.

Kata Kunci : Oksigen, Indeks vegetasi, Leaf area index, PlanetScope, Salatiga.