Pemetaan Kadar Air Tanah Berbasis NDVI, NMDI, dan Interpolasi pada Lahan Perkebunan Kelapa Sawit

Abstract

Ketersediaan air sering menjadi faktor pembatas dalam pencapaian produktivitas kelapa sawit. Luasnya lahan perkebunan sawit menyulitkan pengakuisisian data kadar air tanah sehingga ketersediaan data tersebut masih kurang. Data kadar air dapat dihubungkan dengan kerapatan tajuk melalui analisis dengan berbagai indeks. Selain menggunakan indeks, kadar air tanah juga dapat dipetakan menggunakan interpolasi. Penelitian ini bertujuan mengetahui persebaran data kadar air tanah berdasarkan kelas lereng, mengidentifikasi hubungan kadar air tanah dengan Normalized Difference Vegetation Index (NDVI), Normalized Multi-band Drought Index (NMDI), dan interpolasi, serta memetakan kadar air tanah berbasis ketiga metode tersebut, dan memilih metode terbaik untuk memetakan kadar air tanah. Hasil penelitian menunjukkan kadar air tertinggi didapatkan pada kemiringan lereng 0-3% dan terendah pada kemiringan lereng 8-15%. NDVI dan NMDI berkorelasi sangat lemah dengan kadar air tanah. Hal tersebut menunjukkan baik NDVI maupun NMDI kurang responsif dalam menggambarkan kondisi kadar air tanah di lapang. Nilai kadar air interpolasi memiliki hubungan yang cukup kuat dengan kadar air tanah dengan R² sebesar 0,65, serta memiliki kesesuaian tertinggi sebesar 28,50%, sehingga pada penelitian ini metode interpolasi dapat direkomendasikan untuk pemetaan kadar air tanah.

Water availability is often a limiting factor in achieving palm oil productivity. The extent of oil palm plantations makes it difficult to obtain soil moisture data, therefore, the availability of such data is still lacking. Soil moisture data can be related to canopy density through various indices analyses. In addition to using indices, soil moisture can also be mapped using interpolation. This study aims to determine the distribution of soil moisture based on slope class, identify the relationship between soil moisture with Normalized Difference Vegetation Index (NDVI), Normalized Multi-band Drought Index (NMDI), and interpolation, and map the soil moisture based on these three methods and selecting the best method for mapping soil moisture. The results showed that the highest soil moisture was found on slope gradient 0-3% and the lowest on slope gradient 8-15%. NDVI and NMDI correlate very weakly with soil moisture. This shows that both NDVI and NMDI are less responsive in describing the condition of field soil moisture. The interpolation soil moisture value has a fairly strong relationship with soil moisture with an R² of 0.65 and has the highest suitability of 28.50%, thereby in this study, the interpolation method is recommended for soil moisture mapping.