Assessing Land Use Land Cover of Srinagar Municipal Region Using Sentinel-2 Data for Urban Planning and Management
Understanding the changes in land use land cover mostly due to urbanization is crucial in the context of urban planning and management. LULC studies are also important in socioeconomic development, natural resource management, planning and preservation of green spaces, water and land resources. This study attempts mapping and analyzing LULC in the municipal region of Srinagar, Jammu & Kashmir to gain a better understanding of the patterns and drivers of changes. Sentinel-2 satellite data of2022 was used to delineatethe study area into 13 classes viz., agriculture, aquatic vegetation, barren land, built-up, forest, forest scrub, grassland, horticulture, institutional Farm, mixed green space, TOF, waterbody and wetland. Built up occupied the maximum area (8920.73 ha) forming 36.25% of the area, while Institutional farm class took up the least space of 30.74 ha (0.12%). Among other classes that that occupy prominent area include Agriculture (18.8%), Trees outside Forests (9.62%) and Waterbody (7.15%). The overall classification accuracy was observed as 94% with a kappa statistic of 0.93. This study shows that Srinagar city has experienced fast urbanization and loss of green space to builtup.The results of this study could help devise strategy for urban planning under smart city mission to enhance green spaces and ensure a balanced its balanced distribution.
Authors
- Sabreena Nazir
- Aasif Ali Gatoo (ORCID: https://orcid.org/0000-0002-7379-3609)
- Mohammad Kaif (ORCID: https://orcid.org/0000-0003-1042-9727)
- M A Islam
- Mohammad Iqbal Jeelani
- Akhlaq Amin Wani (ORCID: https://orcid.org/0000-0001-8205-275X)
- Humera Gulzar
- Khursheed Ahmad Sofi (ORCID: https://orcid.org/0000-0002-0098-480X)
- Shah Murtaza
Institutions
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (IN)
Publication Details
- Journal
- International Journal of Environment and Climate Change
- Published
- 2024-12-30
- DOI
- https://doi.org/10.9734/ijecc/2024/v14i124670
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Erasmus+