Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal

Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.

CA-Markov prediction modeling for the assessment of land use/land cover change in two sub-basins of the Tocantins-Araguaia River Basin

Due to the anthropogenic pressures of expansion areas for livestock and agricultural production in the Brazilian Cerrado, it is of paramount importance to understand the dynamics of land use/land cover (LULC) changes in this region. Thus, we investigated LULC changes in two sub-basins of the Tocantins-Araguaia River basin from 1997 to 2015 and consequently projected future changes for the timespan between 2030 and 2050. The Formoso sub-basin experienced significant expansion of agricultural and pasture areas, whereas the Sono sub-basin limited farmland expansion (more stable native vegetation) due to substantial protected areas, trends that were also observed for future projections (2030 and 2050). Pastureland in the Formoso sub-basin increased by 5.8%, while the Sono sub-basin saw significant gains in cultivated land, according to change detection analyses during the 1997-2015 period. High stability probabilities of no change (> 70%) for grassland areas in the Sono River sub-basin and pasturelands in the Formoso River sub-basin were computed. The CA-Markov model demonstrated a high consistency level with actual LULC classes for both sub-basins, as indicated by an overall Kappa coefficient above 0.8. Future projections for 2030 and 2050 show a substantial expansion of agriculture and pasture in both sub-basins, driven by specific factors such as soil organic carbon stocks, distance from rural settlements, and proximity to rivers. Short- and mid-term simulations indicate substantial expansion of agriculture and pasture in both basins, with potential adverse impacts on water erosion. Consequently, developing policies for soil management and sustainable land use planning is essential for agroecosystem sustainability, promoting a balanced approach to economic development while addressing climate change and anthropogenic challenges.

Spatiotemporal Analysis of Land Cover and the Effects on Ecosystem Service Values in Rupandehi, Nepal from 2005 to 2020

Land cover (LC) is a crucial parameter for studying environmental phenomena. Cutting-edge technology such as remote sensing (RS) and cloud computing have made LC change mapping efficient. In this study, the LC of Rupandehi District of Nepal were mapped using Landsat imagery and Random Forest (RF) classifier from 2005 to 2020 using Google Earth Engine (GEE) platform. GEE eases the way in extracting, analyzing, and performing different operations for the earth’s observed data. Land cover classification, Centre of gravity (CoG), and their trajectories for all LC classes: agriculture, built-up, water, forest, and barren area were extracted with five-year intervals, along with their Ecosystem service values (ESV) to understand the load on the ecosystem. We also discussed the aspects and problems of the spatiotemporal analysis of developing regions. It was observed that the built-up areas had been increasing over the years and more centered in between the two major cities. Other agriculture, water, and forest classes had been subjected to fluctuations with barren land in the decreasing trend. This alteration in the area of the LC classes also resulted in varying ESVs for individual land cover and total values for the years. The accuracy for the RF classifier was under substantial agreement for such fragmented LCs. Using LC, CoG, and ESV, the paper discusses the need for spatiotemporal analysis studies in Nepal to overcome the current limitations and later expansion to other regions. Studies such as these help in implementing proper plans and strategies by district administration offices and local governmental bodies to stop the exploitation of resources.

Climate Change and Its Impacts on Farmer's Livelihood in Different Physiographic Regions of the Trans-Boundary Koshi River Basin, Central Himalayas

The impact of climate change on farmers’ livelihoods has been observed in various forms at the local and regional scales. It is well known that the Himalayas region is affected by climate change, as reflected in the basic knowledge of farmers in the region. A questionnaire-based survey involving a total of 747 households was conducted to gather information on climate change and its impact, where the survey addressed four physiographic regions of the trans-boundary Koshi River Basin (KRB). Moreover, climatic data were used to calculate climatic trends between 1980 and 2018. The Mann–Kendall trend test was performed and the Sen’s slope calculated to analyze the inter-annual climatic trends over time. The survey noted that, for the basin, there was an increase in temperature, climate-induced diseases of crops, an increase in the frequency of pests as well as drought and floods and a decrease in rainfall, all which are strong indicators of climate change. It was perceived that these indicators had adverse impacts on crop production (89.4%), human health (82.5%), livestock (68.7%) and vegetation (52.1%). The observed climatic trends for all the physiographic regions included an increasing temperature trend and a decreasing rainfall trend. The rate of change varied according to each region, hence strongly supporting the farmers’ local knowledge of climate change. The highest increasing trend of temperature noted in the hill region at 0.0975 °C/a (p = 0.0002) and sharpest decreasing trend of rainfall in the mountain region by −10.424 mm/a (p = 0.016) between 1980 and 2018. Formulation of suitable adaptation strategies according to physiographic region can minimize the impact of climate change. New adaptation strategies proposed include the introduction of infrastructure for irrigation systems, the development of crop seeds that are more tolerant to drought, pests and disease tolerance, and the construction of local hospitals for the benefit of farming communities.

Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model

Urban growth in various cities across the world, especially in developing countries, leads to land use change. Thus, predicting future urban growth in the most rapidly growing region of Nigeria becomes a significant endeavor. This study analyzes land use and land cover (LULC) change and predicts the future urban growth of the Lagos metropolitan region, using Cellular Automata (CA) model. To achieve this, the GlobeLand30 datasets from years 2000 and 2010 were used to obtain LULC maps, which were utilized for modeling and prediction. Change analysis and prediction for LULC scenario for 2030 were performed using LCM and CA Markov chain modeling. The results show a substantial growth of artificial surfaces, which will cause further reductions in cultivated land, grassland, shrubland, wetland, and waterbodies. There was no appreciable impact of change for bare land, as its initial extent of cover later disappeared completely. Additionally, artificial surfaces/urban growth in Lagos expanded to the neighboring towns and localities in Ogun State during the study period, and it is expected that such growth will be higher in 2030. Lastly, the study findings will be beneficial to urban planners and land use managers in making key decisions regarding urban growth and improved land use management in Nigeria.

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

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.

Assessment of Ecosystem Services Value Based on Land Use and Land Cover Changes in the Transboundary Karnali River Basin, Central Himalayas

Land use and land cover change (LUCC) and its spatio-temporal characteristics are essential for natural resource management and sustainable development. LUCC is one of the major factors that affect the ecosystem and the services it provides. In this study, we used remote sensing techniques and a geographical information system to extract the land cover categories based on the Object-Based Image Analysis (OBIA) technique from Landsat TM/ETM/OLI satellite images in the transboundary Karnali River Basin (KRB, China and Nepal) of central Himalayas from 2000 to 2017. Spatio-temporal integrated methodology—Tupu was used to spatially show the LUCC as well as spatial characteristics of the arisen Tupu and shrunken Tupu. In addition, the ecosystem services value (ESV) were obtained and analyzed for each land cover category. In 2017, forest covered the highest area (33.45%) followed by bare area (30.3%), shrub/grassland (18.49%), agriculture (13.12%), snow/ice (4.32%), waterbody (0.3%) and built-up area (0.04%) in the KRB. From 2000 to 2017, the areas of forest, waterbody and snow/ice have decreased by 0.59, 6.14, and 1072.1 km2, respectively. Meanwhile, the areas of shrub/grassland, agriculture, barren land, and built-up categories have increased by 82.21, 1.44, 991.97, and 3.11 km2, respectively. These changes in the land cover have led to an increase in the ESV of the basin, especially the increase in shrub/grassland, agriculture, and water bodies (in the higher elevation). The total ESV of the basin was increased by $1.59 × 106 from 2000 to 2017. Anthropogenic factors together with natural phenomena drive LUCC in the basin and thus the ESV. The findings of this study could facilitate the basin-level policy formulation to guide future conservation and development management interventions.

Spatially Explicit Mapping of Soil Conservation Service in Monetary Units Due to Land Use/Cover Change for the Three Gorges Reservoir Area, China

Studies of land use/cover change (LUCC) and its impact on ecosystem service (ES) in monetary units can provide information that governments can use to identify where protection and restoration is economically most important. Translating ES in monetary units into decision making strongly depends on the availability of spatially explicit information on LUCC and ES. Yet such datasets are unavailable for the Three Gorges Reservoir Area (TGRA) despite its perceived soil conservation service value (SCSV). The availability of remote sensing-based datasets and advanced GIS techniques has enhanced the potential of spatially explicit ES mapping exercises. Here, we first explored LUCC in the TGRA for four time periods (1995–2000, 2000–2005, 2005–2010, and 2010–2015). Then, applying a value transfer method with an equivalent value factor spatialized using the normalized difference vegetation index (NDVI), we estimated the changes of monetary SCSV in response to LUCC in a spatially explicit way. Finally, the sensitivity of SCSV changes in response to LUCC was determined. Major findings: (i) Expansion of construction land and water bodies and contraction of cropland characterized the LUCC in all periods. Their driving factors include the relocation of residents, construction of the Three Gorges Dam, urbanization, and the Grain for Green Program; (ii) The SCSV for TGRA was generally stable for 1995–2015, declining slightly (<1%), suggesting a sustainable human–environment relationship in the TGRA. The SCSV prevails in regions with elevations (slopes) of 400–1600 m (0°–10°); for Chongqing and its surrounding regions it decreased significantly during 1995–2015; (iii) SCSV’s sensitivity index was 1.04, 0.53, 0.92, and 1.25 in the four periods, respectively, which is generally low. Chongqing and its surrounding regions, with their pervasive urbanization and dense populations, had the highest sensitivity. For 1995–2015, 70.63% of the study area underwent increases in this sensitivity index. Our results provide crucial information for policymaking concerning ecological conservation and compensation.

Land Use and Land Cover Dynamics and Assessing the Ecosystem Service Values in the Trans-Boundary Gandaki River Basin, Central Himalayas

Land use and land cover is a fundamental variable that affects many parts of social and physical environmental aspects. Land use and land cover changes (LUCC) has been known as one of the key drivers of affecting in ecosystem services. The trans-boundary Gandaki River Basin (GRB) is the part of Central Himalayas, a tributary of Ganges mega-river basin plays a crucial role on LUCC and ecosystem services. Due to the large topographic variances, the basin has existed various land cover types including cropland, forest cover, built-up area, river/lake, wetland, snow/glacier, grassland, barren land and bush/shrub. This study used Landsat 5-TM (1990), Landsat 8-OLI (2015) satellite image and existing national land cover database of Nepal of the year 1990 to analyze LUCC and impact on ecosystem service values between 1990 and 2015. Supervised classification with maximum likelihood algorithm was applied to obtain the various land cover types. To estimate the ecosystem services values, this study used coefficients values of ecosystem services delivered by each land cover class. The combined use of GIS and remote sensing analysis has revealed that grassland and snow cover decreased from 10.62% to 7.62% and 9.55% to 7.27%, respectively compared to other land cover types during the 25 years study period. Conversely, cropland, forest and built-up area have increased from 31.78% to 32.67%, 32.47–33.22% and 0.19–0.59%, respectively in the same period. The total ecosystem service values (ESV) was increased from 50.16 × 108 USD y−1 to 51.84 × 108 USD y−1 during the 25 years in the GRB. In terms of ESV of each of land cover types, the ESV of cropland, forest, water bodies, barren land were increased, whereas, the ESV of snow/glacier and grassland were decreased. The total ESV of grassland and snow/glacier cover were decreased from 3.12 × 108 USD y−1 to 1.93 × 108 USD y−1 and 0.26 × 108 USD y−1 to 0.19 × 108 USD y−1, respectively between 1990 and 2015. The findings of the study could be a scientific reference for the watershed management and policy formulation to the trans-boundary watershed.

The impact of drought on vegetation conditions within the Damqu River Basin, Yangtze River Source Region, China

Drought and vegetation conditions within the Damqu River Basin, part of the Yangtze River Source Region (YRSR), are assessed here using the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the normalized difference vegetation index (NDVI), and the leaf area index (LAI). We utilized Sen’s method, least squares regression method, linear regression and Pearson’s correlation analysis to study variations in drought and vegetation indices and the drought effect on vegetation between 1988 and 2015. Results reveal that droughts occurred at a 25% frequency over this period; SPI and SPEI analyses show that 1994, 1999, 2005, and 2010 were change points and that the basin was characterized by varying drought and humidity trends. Subsequent to 2010, both SPI and SPEI decreased within the basin, while 1995, 2000, 2004, and 2010 were change points for NDVI and LAI while the watershed exhibited variable trends in vegetation reduction and increase. The NDVI-annual values of 63.36% regions and the LAI-summer values of 68.39% areas within the basin were decreased during 1988–2015 and 2000–2015, respectively. Subsequent to 2010, both NDVI and LAI decreased within the basin and significant positive correlations at inter-annual and inter-summer time scales were seen in both drought and vegetation indices; drought has exerted a lag effect on vegetation as shown by significant positive correlations between annual SPI/SPEI values and following year NDVI/LAI values.