The Morphology of Urban Agriculture of Marisa District, Indonesia

Abstract

Activities of most of the population inMarisa district and Paguat district generally revolve around primary agricultural production in suburban and hinterland. This research was purposed (1) to examine the causes of the urban agglomeration of farmer settlements, thus resulting in a spatial form or urban morphology; (2) to analyze the development process of city morphology due to the economic strength of the agricultural commodity export sector, specifically in hinterland farming areas; (3) to analyze the economic growth due to the export base of the agricultural commodity with an emphasis on the population of Marisa. A quantitative-qualitative method based on the post-positivism philosophy was employed. This research employed several techniques in the data collection process, such as observation, document review, and interview. In the data analysis, several stages were also performed, such as analysis of Leading Commodities (Location Quotient (LQ) Analysis; LQ share & LQ Shift Analysis) and Spatial Analysis. The result showed that: (1) the urban agglomeration led to the settlement of farmer communities, which also formed a mutual relationship among the residents. (2) Marisa, according to the classification of urban morphology, resembled a star-shaped or octopus layout. This result indicated that the dynamics of Marisa as a region started from the establishment process of the region, and the study suggested further research related to this matter.

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“…This approach is by the background that highlights the importance of industrial sector development as part of long-term economic efforts to achieve a stronger and more balanced economic structure, as well as harmonization with sustainable environmental management. Article (Nie et al, 2022;Tanjung et al, 2021;Wunarlan et al, 2023) discusses the use and improvement of Location Quotient (LQ) in the evaluation of water consumption. The study shows distortions in conventional LQ models and proposes improved LQ models to make evaluations more realistic and accurate, particularly in water resources management.…”

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