Qualifying Land Use and Land Cover Dynamics and Their Impacts on Ecosystem Service in Central Himalaya Transboundary Landscape Based on Google Earth Engine

Abstract

Land use and land cover (LULC) changes are regarded as one of the key drivers of ecosystem services degradation, especially in mountain regions where they may provide various ecosystem services to local livelihoods and surrounding areas. Additionally, ecosystems and habitats extend across political boundaries, causing more difficulties for ecosystem conservation. LULC in the Kailash Sacred Landscape (KSL) has undergone obvious changes over the past four decades; however, the spatiotemporal changes of the LULC across the whole of the KSL are still unclear, as well as the effects of LULC changes on ecosystem service values (ESVs). Thus, in this study we analyzed LULC changes across the whole of the KSL between 2000 and 2015 using Google Earth Engine (GEE) and quantified their impacts on ESVs. The greatest loss in LULC was found in forest cover, which decreased from 5443.20 km2 in 2000 to 5003.37 km2 in 2015 and which mainly occurred in KSL-Nepal. Meanwhile, the largest growth was observed in grassland (increased by 548.46 km2), followed by cropland (increased by 346.90 km2), both of which mainly occurred in KSL-Nepal. Further analysis showed that the expansions of cropland were the major drivers of the forest cover change in the KSL. Furthermore, the conversion of cropland to shrub land indicated that farmland abandonment existed in the KSL during the study period. The observed forest degradation directly influenced the ESV changes in the KSL. The total ESVs in the KSL decreased from 36.53 × 108 USD y−1 in 2000 to 35.35 × 108 USD y−1 in 2015. Meanwhile, the ESVs of the forestry areas decreased by 1.34 × 108 USD y−1. This shows that the decrease of ESVs in forestry was the primary cause to the loss of total ESVs and also of the high elasticity. Our findings show that even small changes to the LULC, especially in forestry areas, are noteworthy as they could induce a strong ESV response.

Impact of Land Use/ Land Cover Changes on Ecosystem Service Values in the Cherangany Hills Water Tower, Kenya

“…Our results are in line with the findings of other researchers from different parts of the world, including Ethiopia ( Alebachew et al, 2022 ;Gashaw et al, 2018 ;Kindu et al, 2016 ;Muleta et al, 2021 ;Shiferaw et al, 2021 ), China ( Hu et al, 2008 ;Wang et al, 2015 ), Bangladesh ( Rahman and Szabó, 2021 ), Tanzania ( Msofe et al, 2020 ), Nepal ( Sharma et al, 2019 ) and a transboundary landscape in Asia ( Gu et al, 2021 ), who report a significant negative contribution of forest losses to the total ESV. On the other hand, an increase in forest area over time positively contributes to the total ESV and enhances ES supply ( Hou et al, 2021 ;Paudyal et al, 2019 ;Wang et al, 2014 ;Yuan et al, 2019 ;Zhao et al, 2022 ).…”

Land Use and Land Cover Change Analysis Using Google Earth Engine in Manamati Watershed of Kathmandu District, Nepal

“…Now, Google Earth Engine is a platform to detect changes, map trends, and quantify changes on the earth's surface by undertaking earth observation (Kumar and Mutanga, 2018). The spatiotemporal scales used for the analysis of agricultural land extent in South Asia (Gumma et al, 2020), land cover change in Singapore (Sidhu et al, 2018), land-use change in the Savannah River Basin (Zurqani et al, 2018), Land Use and Land Cover Dynamics in Central Himalaya Transboundary Landscape (Gu et al, 2021), temporal analysis of NDVI in Chitwan National Park of Nepal (Prasai, 2022), and land cover change in Kaski district of Nepal (Wagle et al, 2020). The methodology for this study is outlined in the workflow diagram in Figure 2.…”

Modelling vegetation land fragmentation in urban areas of Western Province, Sri Lanka using an Artificial Intelligence-based simulation technique

“…Therefore, the configuration and composition of vegetation lands are changing [ 7 ]. According to recent studies, anthropogenic activities have damaged 60 percent of ecological services worldwide [ 8 ]. Urban regions are home to 56.2 percent of the world’s population [ 9 ].…”