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All Journal Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Journal of Applied Agricultural Science and Technology
Novandi Rizky Prasetya
Brawijaya University
Agriculture, Biological Sciences & Forestry Engineering

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Analysis and Prediction of Water Availability Criteria in Potato Using High-Resolution Aerial Photography Istika Nita; Aditya Nugraha Putra; Shofie Rindi Nurhutami; Michelle Talisia Sugiarto; Novandi Rizky Prasetya
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 1 (2026): February 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i1.198-212

Abstract

Indonesia’s potato fields are typically small and fragmented, making coarse resolution moisture products prone to spatial mismatch and limiting their usefulness for precision water management. This study developed plot scale, water based suitability information for potato by integrating UAV multispectral imagery with field measurements of soil water availability and plant height response. UAV imagery was processed into four vegetation indices, namely NDWI, SAVI, MSAVI, and SR, followed by geostatistical mapping. Relationships between indices and measured water availability were evaluated using correlation, linear regression, paired t test, and principal component analysis to examine inter index structure and redundancy. NDWI showed the most consistent performance, with a moderate positive correlation with measured water availability (r = 0.47), while SAVI and MSAVI were negatively correlated (r = −0.46) and SR showed the weakest association (r = −0.33). The NDWI based regression for water availability estimation was y = 0.50x + 29.68 with R² = 0.22. The paired t test indicated no significant difference between NDWI based estimates and field measurements, with mean values of 30.09 percent and 30.52 percent, respectively, across 17 observations. Water based land suitability classes were then refined using boundary line analysis linking water availability to plant height response, producing plot scale criteria suitable for precision zoning rather than landscape level evaluation.
Land-Use Scenario Modeling Using Remote Sensing and Cellular Automata and Its Impact on the Drought Hazard at the Sub-catchment Area Level Suryanta Junjungan Tua Sitio; Novandi Rizky Prasetya; Michelle Talisia Sugiarto; Aditya Nugraha Putra
Journal of Applied Agricultural Science and Technology Vol. 10 No. 2 (2026): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v10i2.467

Abstract

Rapid land-use change in upland watersheds alters hydrological processes and increases drought vulnerability. The Upper Brantas and Kali Konto sub-watersheds in East Java serve as important rainfall catchment and water storage areas, yet ongoing land conversion has progressively reduced their capacity to regulate water availability. However, the implications of future land-use trajectories for drought hazards at the sub-catchment scale remain insufficiently understood. This study aims to analyze land-use dynamics, simulate future land-use change, and evaluate alternative land-use planning scenarios to assess their potential influence on drought hazard distribution. Multi-temporal land-use data from 2017, 2019, 2021, and 2025 were analyzed using remote sensing, and future land-use patterns were projected for 2030 using the Artificial Neural Network–Cellular Automata–Markov (ANN–CA–Markov) model. The simulated land-use distribution was then evaluated under Regional Spatial Planning (RSP) and Land Capability Classification (LCC) scenarios to examine their implications for drought hazards. The results showed a substantial decline in natural forest from 12,600.35 ha (31.4%) in 2017 to 9,975.70 ha (24.9%) in 2025—a reduction of more than 20%—accompanied by the expansion of plantation systems, dryland farming, and built-up areas. Under the 2030 Business-as-Usual (BAU) scenario, moderate drought hazard areas increased from 44.0% to approximately 50.2% of the watershed area. Among the evaluated scenarios, the Land Capability Classification (LCC)-based planning approach showed the greatest potential to mitigate drought risk, reducing high drought hazard areas from 25.1% under the BAU scenario to 15.2%. These findings highlight the importance of integrating land capability considerations into spatial planning to support drought-resilient watershed management.
Co-Authors Aditya Nugraha Putra Istika Nita Michelle Talisia Sugiarto Nurhutami, Shofie Rindi Suryanta Junjungan Tua Sitio