Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/14/2/208 |
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| author | Jayan Wijesingha Thomas Astor Sunil Nautiyal Michael Wachendorf |
| author_facet | Jayan Wijesingha Thomas Astor Sunil Nautiyal Michael Wachendorf |
| author_sort | Jayan Wijesingha |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2a636a0329e64e00a88a4494b8d57292 |
| institution | DOAJ |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj-art-2a636a0329e64e00a88a4494b8d572922025-08-20T02:44:50ZengMDPI AGLand2073-445X2025-01-0114220810.3390/land14020208Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, IndiaJayan Wijesingha0Thomas Astor1Sunil Nautiyal2Michael Wachendorf3Grassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, GermanyGrassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, GermanyCentre for Ecological Economics and Natural Resources, Institute for Social and Economic Change, Nagarabhavi, Bengaluru 560072, IndiaGrassland Science and Renewable Plant Resources, Universität Kassel, Steinstraße 19, DE-37213 Witzenhausen, GermanyGlobally, 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.https://www.mdpi.com/2073-445X/14/2/208agricultural land cover (ALC)urban–ruralWorldViewlandscape analysisBengaluru |
| spellingShingle | Jayan Wijesingha Thomas Astor Sunil Nautiyal Michael Wachendorf Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India Land agricultural land cover (ALC) urban–rural WorldView landscape analysis Bengaluru |
| title | Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India |
| title_full | Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India |
| title_fullStr | Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India |
| title_full_unstemmed | Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India |
| title_short | Spatial Patterns and Characteristics of Urban–Rural Agricultural Landscapes: A Case Study of Bengaluru, India |
| title_sort | spatial patterns and characteristics of urban rural agricultural landscapes a case study of bengaluru india |
| topic | agricultural land cover (ALC) urban–rural WorldView landscape analysis Bengaluru |
| url | https://www.mdpi.com/2073-445X/14/2/208 |
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