Abstract
Monitoring the changing pattern of vegetation across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment. Land use pattern in the state of Himachal Pradesh in the Indian Western Himalayas has been undergoing rapid modifications due to changing cropping patterns, rising anthropogenic pressure on forests and government policies. We studied land use change in Solan Forest Division of Himachal Pradesh to assess species wise area changes in the forests of the region. The supervised classification (Maximum likelihood) on two dates of IRS (LISS III) satellite data was performed to assess land use change over the period 1998–2010. Seven land use categories were identified namely, chir pine (Pinus roxburghii) forest, broadleaved forest, bamboo (Dendrocalamus strictus) forest, ban oak (Quercus leucotrichophora) forest, khair (Acacia catechu) forest, culturable blank and cultivation. The area under chir pine, cultivation and khair forests increased by 191 ha (4.55 %), 129 ha (13.81 %) and 77 ha (23.40 %), whereas the area under ban oak, broadleaved, culturable blank and bamboo decreased by 181 ha (16.58 %), 152 ha (6.30 %), 71 ha (2.72 %) and 7 ha (0.47 %), respectively. The study revealed a decrease in the area under forest and culturable blank categories and a simultaneous increase in the area under cultivation primarily due to the large scale introduction of horticultural cash crops in the state. The composition of forests also exhibited some major changes, with an increase in the area of commercially important monoculture plantation species such as pine and khair, and a decline in the area of oak, broadleaved and bamboo which are facing a high anthropogenic pressure in meeting the livelihood demands of forest dependent communities. In time deforestation, forest degradation and ecological imbalances due to the changing forest species composition may inflict irreversible damages upon unstable and fragile mountain zones such as the Indian Himalayas. The associated common property externalities involved at local, regional and global scales, necessitate the monitoring of land use dynamics across forested landscapes in developing future strategies and policies concerning agricultural diversification, natural forest conservation and monoculture tree plantations.
Highlights
Monitoring the changing pattern of vegetation across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment
Land use land cover (LULC) change is the primary modifier of landscapes, affecting a wide range of socioeconomic, biological, climatic, and hydrological systems (Sohl and Sohl 2012)
Understanding the spatial extent and distribution of LULC change is vital to the study of environmental changes at various levels (Ojima et al 1994)
Summary
Monitoring the changing pattern of vegetation across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment. Land use land cover (LULC) change is the primary modifier of landscapes, affecting a wide range of socioeconomic, biological, climatic, and hydrological systems (Sohl and Sohl 2012). LULC change is one of the key drivers of local and regional climate change (Chase et al 1999), biodiversity decline (Sala et al 2000), soil degradation (Tolba and El-Kholy 1992) and the loss of ecosystem services, thereby affecting the ability of ecosystems to support human needs (Vitousek et al 1997). It is imperative that regular periodic assessments of forest cover change in tropical regions are carried out to recognize previous patterns, assist proper planning and predict future trends. The use of remote sensing data has been instrumental in monitoring the changing pattern of vegetation across diverse landscapes. The capacity for large geographical coverage, high temporal frequency and wide selection of spatial and spectral resolution options, further enhances the use of remotely sensed imagery for LULC change detection
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