Mesolandform classification and its relationship with smallholder coffee production in the Malang Regency, Indonesia
Mesolandform analysis is necessary for smallholder coffee land management because it can clearly distinguish landform boundaries. Automatic mesolandform classification utilizes geographic information system (GIS) and remote sensing technology using the topographic position index (TPI), slope, curvat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sebelas Maret University - Department of Soil Science, Faculty of Agriculture
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/121054/ http://psasir.upm.edu.my/id/eprint/121054/1/121054.pdf |
| Summary: | Mesolandform analysis is necessary for smallholder coffee land management because it can clearly distinguish landform boundaries. Automatic mesolandform classification utilizes geographic information system (GIS) and remote sensing technology using the topographic position index (TPI), slope, curvature, lithology, land use, and normalized difference vegetative index (NDVI). This study aims to classify the mesolandform of smallholder coffee plantations and determine its relationship attributes with coffee production. The data included the Digital Elevation Model, lithology map, Sentinel 2 A harmonized image, and actual coffee production. The spatial analysis was performed using ArcGIS 10.8 and QGIS 3.1.6, and the statistical data analysis was performed using RStudio. Mesolandform affects coffee production (p < 0.0001) and was significantly related to it. The highest production was found on the open slope mesolandform, with coffee production ranging from 7.13 to 9.95 tons/ha. Mesolandform attributes have a significant effect on coffee production increase (R2 = 0.69) on land characteristics with high coffee vegetation density (NDVI > 0.6), topographic position in open slope to flat (TPI 0–2), dominant slope is flat to undulating (<8%), and land curvatures are level or convergent foot slope (<2). The research results can support the sustainable management of smallholder coffee plantations based on mesolandform attributes. |
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