This study explored the past and present land-use/land-cover (LULC) changes and urban expansion pattern for the cities of the Kathmandu valley and their surroundings using Landsat satellite images from 1988 to 2016. For a better analysis, LULC change information was grouped into seven time-periods (1988–1992, 1992–1996, 1996–2000, 2000–2004, 2004–2008, 2008–2013, and 2013–2016). The classification was conducted using the support vector machines (SVM) technique. A hybrid simulation model that combined the Markov-Chain and Cellular Automata (MC-CA) was used to predict the future urban sprawl existing by 2024 and 2032. Research analysis explored the significant expansion in urban cover which was manifested at the cost of cultivated land. The urban area totaled 40.53 km² in 1988, which increased to 144.35 km² in 2016 with an average annual growth rate of 9.15%, an overall increase of 346.85%. Cultivated land was the most affected land-use from this expansion. A total of 91% to 98% of the expanded urban area was sourced from cultivated land alone. Future urban sprawl is likely to continue, which will be outweighed by the loss of cultivated land as in the previous decades. The urban area will be expanded to 200 km² and 238 km² and cultivated land will decline to 587 km² and 555 km² by 2024 and 2032. Currently, urban expansion is occurring towards the west and south directions; however, future urban growth is expected to rise in the southern and eastern part of the study area, dismantling the equilibrium of environmental and anthropogenic avenues. Since the study area is a cultural landscape and UNESCO heritage site, balance must be found not only in developing a city, but also in preserving the natural environment and maintaining cultural artifacts.

Spatial–temporal analysis of land-use/land-cover (LULC) change as well as the monitoring and modeling of urban expansion are essential for the planning and management of urban environments. Such environments reflect the economic conditions and quality of life of the individual country. Urbanization is generally influenced by national laws, plans and policies and by power, politics and poor governance in many less-developed countries. Remote sensing tools play a vital role in monitoring LULC change and measuring the rate of urbanization at both the local and global levels. The current study evaluated the LULC changes and urban expansion of Jhapa district of Nepal. The spatial–temporal dynamics of LULC were identified using six time-series atmospherically-corrected surface reflectance Landsat images from 1989 to 2016. A hybrid cellular automata Markov chain (CA–Markov) model was used to simulate future urbanization by 2026 and 2036. The analysis shows that the urban area has increased markedly and is expected to continue to grow rapidly in the future, whereas the area for agriculture has decreased. Meanwhile, forest and shrub areas have remained almost constant. Seasonal rainfall and flooding routinely cause predictable transformation of sand, water bodies and cultivated land from one type to another. The results suggest that the use of Landsat time-series archive images and the CA–Markov model are the best options for long-term spatiotemporal analysis and achieving an acceptable level of prediction accuracy. Furthermore, understanding the relationship between the spatiotemporal dynamics of urbanization and LULC change and simulating future landscape change is essential, as they are closely interlinked. These scientific findings of past, present and future land-cover scenarios of the study area will assist planners/decision-makers to formulate sustainable urban development and environmental protection plans and will remain a scientific asset for future generations.

This study seeks to better understand the human-nature interface and to measure the variability of plant use knowledge among cultures, through inter- and intracultural analyses. We compared plant collection, use, and management of two culturally distinct groups (Baitadi and Darchula) of the Nepal Himalaya. They inhabit different physiographic regions, yet share the same ecological landscape, environmental resources, and livelihood challenges. We hypothesized that the elderly, native, and traditional healers living in remote and rural places possess more diverse and detailed knowledge of plant use and conservation than young, non-native, and non-healers. A total of 106 people were contacted for interviews, and 100 (68 men and 32 women) agreed to share ethnobotanical, demographic, and socioeconomic information. They were asked about the three most important plants for their socioeconomic benefit, culture, primary health care, and livelihood. The knowledge of plant collection, use, and its transfer was strongly associated with the cultural heritage whereas the ecogeographical condition influences the ways in which plants are collected and used. The divergent knowledge of plant collection, use, and transfer between the participants of Baitadi and Darchula was significantly (p < 0.001) attributed to the cultural heritage of the area. The low consensus of plant use (FiC 0–0.87; IASc 0–0.67) between Baitadi and Darchula district could be due to cultural divergence, varied accessibility, physiographic heterogeneity, and biodiversity uniqueness. Differences in plant use knowledge may help in diversifying the strategies of plant use in accordance with the livelihood, culture, and environment, and therefore, more studies measuring these aspects can further the ecosystem and cultural health of the region.

Ecosystems provide a wide range of goods, services or ecosystem services (ES) to society. Estimating the impact of land use and land cover (LULC) changes on ES values (ESV) is an important tool to support decision making. This study used remote sensing and GIS tools to analyze LULC change and transitions from 2001 to 2016 and assess its impact on ESV in a tropical forested landscape in the southern plains of Nepal. The total ESV of the landscape for the year 2016 is estimated at USD 1264 million year⁻¹. As forests are the dominant land cover class and have high ES value per hectare, they have the highest contribution in total ESV. However, as a result of LULC change (loss of forests, water bodies, and agricultural land), the total ESV of the landscape has declined by USD 11 million year⁻¹. Major reductions come from the loss in values of climate regulation, water supply, provision of raw materials and food production. To halt the ongoing loss of ES and maintain the supply and balance of different ES in the landscape, it is important to properly monitor, manage and utilize ecosystems. We believe this study will inform policymakers, environmental managers, and the general public on the ongoing changes and contribute to developing effective land use policy in the region.