Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India

Jayan Wijesingha (), Thomas Astor, Sunil Nautiyal and Michael Wachendorf
Additional contact information
Jayan Wijesingha: Grassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, Germany
Thomas Astor: Grassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, Germany
Sunil Nautiyal: Centre for Ecological Economics and Natural Resources, Institute for Social and Economic Change, Nagarabhavi, Bengaluru 560072, India
Michael Wachendorf: Grassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, Germany

Land, 2025, vol. 14, issue 2, 1-21

Abstract: Globally, the agricultural landscape is the most exposed due to urbanisation. Therefore, finding the spatial and temporal patterns of changes in agricultural landscapes is essential for sustainable development. This study developed a workflow to address this information gap and determine the spatial patterns and characteristics of agricultural landscapes along an urban–rural gradient. The workflow comprised three steps. First, remote sensing data were classified to map crop types. Second, landscape metrics were used to examine the spatial patterns of agricultural land cover concerning urbanisation levels. Finally, unsupervised clustering was applied to categorise agricultural landscape types along the urban–rural interface. The workflow was tested using WorldView-3 satellite data in Bengaluru, India. It identified four major herbaceous crop types (millet, maize, pulses, and cash crops) and woody plantations as agricultural land cover. An analysis revealed that agricultural land cover increased from urban to rural areas, with diverse patterns in transition zones. The cluster analysis characterised four agricultural landscapes. The findings imply that changes in an agricultural landscape along an urban–rural gradient are not linear. The newly developed integrated workflow empowers stakeholders to make informed and well-reasoned decisions, and it can be periodically implemented to maintain the ongoing monitoring of urbanisation’s effect on food systems.

Keywords: agricultural land cover (ALC); urban–rural; WorldView; landscape analysis; Bengaluru (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/2/208/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/2/208/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:2:p:208-:d:1572249

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().