Oil palm land expansion and sustainable agriculture challenges in rural areas of Indonesia

doi:10.1016/j.regsus.2026.100347

Abstract

Abstract:

The expansion of oil palm land in Indonesia has led to the increase of land connectivity, posing significant challenges due to substantial and heterogeneous land use changes, particularly in the rural areas of Jambi Province, Indonesia. Identifying the social, environmental, and economic drivers is critical for understanding how land use changes shape the spatial pattern of oil palm land expansion. Therefore, this study employed the geographically and temporally weighted regression (GTWR) model to assess the spatiotemporal effects of staged and continuity indices on the oil palm land expansion in the six villages (Kumpeh, Kumpeh Ulu, Mujaro Sebo, Kota Madya, Jambi Luar, and Mestong) of Jambi Province during 2016-2022. The result revealed that the northern region—especially Mujaro Sebo, Kumpeh, and Kumpeh Ulu villages—contribute most significantly to gradual and continuous oil palm land movement. Staged index had positive influence on increasing oil palm land connectivity. Specifically, economic growth, oil palm agriculture, and medical and health infrastructure were the primary drivers with the positive influence on increasing oil palm land expansion during 2021-2022. Additionally, population flow and commodity land exhibited high connectivity with oil palm land expansion in the northern region, particularly in Kumpeh and Mujaro Sebo villages, collectively leading to 53.79% expansion of oil palm land. Moreover, continuity index reflected a transition from dual core to multi-core development. Oil palm land expansion was predominantly influenced by oil palm agriculture and investment development, though their impacts differed markedly. This empirical study confirms the spatial heterogeneous distribution of land connectivity drivers—represented by barycenter variation—across six villages in Jambi Province, offering essential insights for governmental policy prioritization to mitigate future conflicts arising from oil palm land shifts in the rural areas.

Key words: Oil palm land expansion, Geographically and temporally weighted, regression (GTWR) model, Staged index, Continuity index, Land connectivity, Jambi Province

Herdis HERDIANSYAH, Randi MAMOLA. Oil palm land expansion and sustainable agriculture challenges in rural areas of Indonesia[J]. Regional Sustainability, 2026, 7(3): 100347.

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Variable	Unit	Variable	Unit
Total population (X1)	persons	Gross agricultural output value (X12)	USD
Number of year-end social farmers (X2)	persons	Quantity of commodity transported by the distributor (X13)	t/month
Gross domestic product (GDP) (X3)	USD/person	Road freight volume (X14)	t/month
Primary palm oil output value (X4)	t/month	Primary commodity land yield (X15)	USD/km²
Secondary palm oil output value (X5)	t/month	Secondary commodity land yield (X16)	USD/km²
Tertiary palm oil output value (X6)	t/month	Tertiary commodity land yield (X17)	USD/km²
Total fixed asset investment of palm oil (X7)	USD	Capacity of primary and secondary school facility (X18)	-
Total distribution retail of Crude Palm Oil (CPO) (X8)	USD/t	Capacity of students attending school (X19)	persons
Financial revenue (X9)	USD/person	Capacity of village hospital (X20)	-
Financial expenditure for household (X10)	USD/person	Health technician (X21)	persons
Gross village output value (X11)	USD/person	Agricultural scheme (X22)	USD

Index	Driving factor	Variable
Staged index	Economic growth	X3, X8, and X9
	Financial development	X7 and X10
	Technology and education	X1, X19, and X21
	Oil palm agriculture	X4 and X12
	Population flow	X16 and X1
	Medical and health infrastructure	X20
	Commodity land	X15
Continuity index	Socio-economic level and infrastructure	X3, X11, X18, and X22
	Investment development	X7 and X10
	Oil palm agriculture	X4 and X12
	Transportation	X13 and X14

Village	2016-2017	2017-2018	2018-2019	2019-2020	2020-2021	2021-2022
Kumpeh	0.255	0.221	0.081	0.051	0.301	0.141
Kumpeh Ulu	0.143	0.008	0.034	0.084	0.076	0.168
Mujaro Sebo	0.125	0.006	0.014	0.157	0.034	0.099
Kota Madya	0.184	0.046	0.012	0.058	0.019	0.083
Jambi Luar	0.403	0.033	0.067	0.148	0.021	0.274
Mestong	0.231	0.370	0.301	0.410	0.604	0.512

Statistic parameter	Value	Statistic parameter	Value
Bandwidth	0.126	Coefficient of determination (R²)	0.732
Residual square	14.500	Adjusted R²	0.731
Sigma	0.622	Spatiotemporal distance ratio	1.281
Corrected (weighted) Akaike Information Criterion (AIC)	69.500

	2016	2017	2018	2019	2020	2021	2022
Local Moran’s I	0.28	0.31	0.37	0.32	0.36	0.47	0.55
Z-value	6.45	7.10	8.19	7.71	8.09	10.48	12.36