Search Results (428)

In agro-pastoral transitional zones, monitoring vegetation fraction coverage (FVC) and understanding its relationship with land use and climate change are crucial for comprehending how complex land-use/land-cover change (LUCC) improves ecological restoration and land management. This study focuses on the agro-pastoral transitional zone of Inner Mongolia, aiming to analyze vegetation cover changes from 2000 to 2020 using the Mann–Kendall (MK) significance test, Theil–Sen median trend analysis, and coefficient of variation (CV) analysis. Additionally, the study explores the impacts of LUCC, precipitation, and temperature on vegetation cover using methods such as geo-detector, pixel-based statistical analysis, and univariate linear regression. Based on the PLUS land-use prediction model and linear regression results, vegetation cover was simulated under different land-use scenarios for the future. The main findings are as follows: first, from 2000 to 2020, the spatial distribution of vegetation cover in the study area showed a distinct pattern of higher vegetation cover in the east compared to the west, with significant spatiotemporal heterogeneity. Although the overall vegetation cover slightly increased, there were notable differences in the trend across regions, with some areas experiencing a decrease in FVC. Second, LUCC is the most significant explanatory factor for vegetation cover changes, and the interactions between LUCC and other factors have a particularly notable impact on vegetation cover. Third, scenario simulations based on the PLUS model indicate that, by 2040, vegetation cover will perform optimally under the farmland protection and sustainable development scenarios. Particularly under the farmland protection scenario, the conversion of cropland, forestland, and grassland is notably suppressed. In contrast, the unmanaged natural development scenario will lead to a decline in vegetation cover. The results of this study show that vegetation cover in the agro-pastoral transitional zone of Inner Mongolia exhibits substantial fluctuations due to land-use change. Future ecological restoration policies should incorporate land-use optimization to promote vegetation recovery and address ecological degradation. Full article

A simple statistical model capturing the degree to which different patterns of urban development intensify urban heat islands (UHIs) and stress human health would be useful but has remained elusive. Accurately predicting street-level urban air temperatures from land cover and thermal data is difficult due to (1) the coarse scale of common remote sensing data, which do not observe the key environments beneath urban tree canopies, and, (2) conversely, the immense labor of intense, location-specific, ground-based survey campaigns. This work tested whether remotely sensed urban heat merged with land cover heterogeneity and shade/sun fractions, if combined at a sufficiently fine scale so as to be linearly additive, would enable simple and accurate statistical modeling of street-scale urban air temperatures with minimal empirical fitting. We used ground-based thermography of a sample of 12 residential streetscapes in Portland, Oregon, to characterize the land surface temperatures (LST_g) of eleven common urban surface cover types when sun-exposed and in shade. Surfaces were cooler in shade than sun, but with surface-specific differences not explained by greenery nor (im)perviousness. Also, surfaces on streetscapes with more canopy cover, even when sun-exposed at midday, remained significantly cooler than comparable sun-exposed surfaces on streets with less canopy cover, indicating the key significance of partial diurnal shading, not typically accounted for in urban thermal statistical models. We used high-resolution orthoimagery to quantify the area of each surface cover type within each streetscape and computed an area-weighted average surface temperature (T_s), accounting for sun/shade heterogeneity. The data revealed a significant, nearly 1:1 relationship between calculated T_s values and sun-shielded air temperatures (T_a). In contrast, relationships of T_a to tree coverage, impervious area, or the LST_g of dominant surface cover types were all statistically insignificant. These results suggest that statistical models may more reliably bridge the gap between remote sensing urban surface temperatures and reliable predictions of street-scale air temperatures if (1) analysis is at a sufficiently high resolution (e.g., <10 m) to avoid some of the known scale-dependence of urban thermal environments and enable simple weighted linear models, and (2) distinctions between thermal contributions of sunlit and shaded surfaces are included along with the influence of diurnal shading. Such models may provide effective and low-cost predictions of local UHIs and help inform effective street-level approaches to mitigating urban heat. Full article

The internal response mechanism of vegetation change in fragile high-altitude ecosystems is pivotal for ecological stability. This study focuses on the Lhasa River Basin (LRB) on the Tibetan Plateau (TP), a typical high-altitude fragile ecosystem where vegetation dynamics are highly sensitive to climate change and human activities. Utilizing MODIS surface reflectance data (MOD09Q1), a general regression neural network (GRNN) was applied to create a 250 m resolution fractional vegetation cover (FVC) dataset from 2001 to 2022, whose accuracy was verified with field survey data. Through methods like the Theil–Sen Median trend analysis, Mann–Kendall significance test, Hurst exponent, and geographical detector, the collaborative mechanism of 14 driving factors was systematically explored. Key conclusions are as follows: (1) The FVC in the LRB evolved in stages, first decreasing and then increasing, with 46.71% of the basin area expected to show an improvement trend in the future. (2) Among natural factors, elevation (q = 0.480), annual mean potential evapotranspiration (q = 0.362), and annual mean temperature (q = 0.361) are the main determinants of FVC spatiotemporal variation. (3) In terms of human activities, land use type has the highest explanatory power (q = 0.365) for FVC. (4) The interaction of two factors on FVC is stronger than that of a single factor, with the elevation–land use interaction being the most significant (q = 0.558). These results deepen our understanding of the interactions among vegetation, climate, and humans in fragile high-altitude ecosystems and provide a scientific basis for formulating zoned restoration strategies on the TP. Full article

The high amount of sludge produced from wastewater treatment plants (WWTPs) requires final disposal, forcing plant operators to search for alternatives without exerting an excessive energy demand on the global plant balance. Future revisions of the WWTP Directive will probably set additional constraints regarding the land application of sludge. Therefore, thermal treatment may seem a logical solution based on the additional energy that can be extracted from the process. The purpose of the present manuscript is to assess the integration of anaerobic digestion of sewage sludge and subsequent gasification using SuperPro Designer V13. Mass and energy balances were carried out, and the net energy balance was estimated under different scenarios. The integration of the process showed an electricity power output of 726 kW (best scenario, equivalent to 4.84 W/inhab.) against 411 kW (2.7 W/inhab.) for the single digestion case. The thermal demand of the integrated approach can be fully covered by deviating a fraction of gaseous fuels for heat production in a burner. Transforming syngas into methane by biological conversion allows densifying the gas stream, but it reduces the total energy content. Full article

In recent decades, land abandonment due to socioeconomic issues has been a widespread process in different areas of the Mediterranean, altering landscapes and affecting soil properties and erosion processes. The aim of this research was to assess the impact of land use and land cover change on soil properties and sediment composition produced after seasonal rainfall. Mediterranean open forest (OF), pine afforestation (PA), thinned pine (TPA) and barren land (BL) land use/land covers were compared. We analyzed the soil characteristics and sediments that were collected under each form of land use and management across seven seasonal campaigns between July 2016 and September 2017. The relationships between soil particle size, soil organic carbon (SOC) and its fractions, key nutrients (nitrogen, phosphorous, potassium and sulfur) and rainfall characteristics were evaluated. Sediment loads from runoff, collected in trap MATs in monitoring areas under OF and PA, were similar in both quantity and composition. However, the amount of sediment increased after thinning, though it remained significantly lower than in BL. Sediment loads were driven by total rainfall in OF and in TPA, while rainfall erosivity had a clear impact in PA and BL. Afforestation helped to maintain SOC and nutrient levels comparable to those in OF, which were significantly higher than in BL. Nitrogen and phosphorous losses were mainly governed by the total amount of precipitation. However, the effect of rainfall on potassium and sulfur losses was not clearly evident. Full article

Vegetation dynamics and their underlying driving mechanisms have emerged as a prominent research focus in ecological studies of the Chinese Loess Plateau (CLP). Current investigations, however, employ simplified methodologies in analyzing the influencing factors, limiting their capacity to comprehensively elucidate the intricate and multidimensional mechanisms that govern vegetation transformations. Utilizing fractional vegetation cover (FVC) datasets spanning 2000 to 2021, this research applies both XGBoost-SHAP and Geodetector approaches for comparative analysis of the driving factors and precise quantification of climatic change (CC) and human activity (HA). The results indicate that: (1) The CLP has experienced an annual FVC increase of 0.62%, with 95.1% of the region demonstrating statistically significant vegetation improvement. (2) Precipitation and land use emerge as the primary determinants of FVC spatial distribution, with their interactive effects substantially exceeding the impacts of individual factors. (3) While both XGBoost-SHAP and Geodetector methodologies consistently identify the primary driving factors, notable discrepancies exist in their assessment of temperature’s relative importance, revealing complementary dimensions of ecological complexity captured by different analytical paradigms. (4) Approximately 94.3% of FVC variations are jointly influenced by HA and CC, with anthropogenic factors predominating at a contribution of 67%. Land use modifications, particularly transitions among cropland, grassland, and forests, constitute the principal mechanism of human influence on vegetation patterns. This investigation enhances the understanding of vegetation responses under combined natural and anthropogenic pressures, offering valuable insights for ecological rehabilitation and sustainable development strategies on the CLP. Full article

An ecological restoration assessment aims to evaluate whether ecological restoration projects (ERPs) have achieved predefined ecological objectives, such as improving fractional vegetation cover (FVC) and enhancing ecosystem services (ESs), as well as to optimize restoration strategies based on assessment outcomes. Despite recent advancements, current studies still fall short of fully capturing the trade-offs among ESs and identifying the underlying drivers of different vegetation trends. To address these challenges, we applied the Theil–Sen method to delineate vegetation change zones in the Qilian Mountain National Park (QLMNP) between 2000 and 2020, employed bivariate Moran’s I statistics to analyze the trade-offs and synergies among four ESs within these zones, including carbon sequestration (CS), soil conservation (SC), water conservation (WC), and biodiversity maintenance (BIO), and utilized a spatial random forest (SRF) model to explore the main socio-ecological driving factors of vegetation trends and their spatial distribution. Our results revealed significant vegetation recovery in the QLMNP between 2000 and 2020, particularly in regions with initially low FVC. Positive trends in the CS, SC, and BIO highlighted the success of restoration efforts, primarily driven by land conversion to forests and increased precipitation. However, 8.82% of the QLMNP exhibited stagnation or degradation due to rising temperatures and overgrazing, leading to declines in the SC and BIO. Notably, vegetation restoration introduced trade-offs among the ESs, especially in the high FVC areas, where a strong trade-off emerged between FVC and WC. These findings highlight the need for refining restoration strategies to balance water resource allocation. Finally, we integrated vegetation trends, ES relationships, and driving factors to propose grid-based zonal governance plans for the QLMNP, prioritizing WC and FVC enhancement as critical components of future ecological planning. This study serves as a foundation for optimizing restoration strategies in the QLMNP, maintaining and enhancing ESs, while offering actionable insights for fine-grained restoration evaluation and sustainable development planning in other regions. Full article

Wetland vegetation is vital for ecological purification and climate mitigation. This study analyzes the spatiotemporal characteristics and influencing factors of water areas, fractional vegetation cover (FVC), and land use types in Poyang Lake wetland across wet and dry seasons (1990–2022) using remote sensing technology. The results showed that the water area remained overall stable during the wet seasons but decreased significantly in the dry seasons (19.27 km²/a). FVC exhibited an overall increasing trend, with vegetation expanding from lake margins to central areas. The land use areas of shallow water, bare ground, and Phalaris arundinacea–Polygonum hydropiper (P. arundinacea–P. hydropiper) communities showed interannual fluctuating decreases, while other land use types areas increased. From 1990 to 2020, land use changes were mainly characterized by the transformation of shallow water into deep water and bare ground, other vegetation into Carex cinerascens (C. cinerascens) community and bare ground, bare ground into deep water, as well as P. arundinacea–P. hydropiper community to C. cinerascens community. Rising temperatures enhanced FVC in both seasons, stimulated the expansion of C. cinerascens community area and total vegetation area, and reduced the dry season water area. Decreasing accumulated precipitation exacerbated water area loss and the decline of P. arundinacea–P. hydropiper communities. These findings provide critical insights for wetland ecological conservation and sustainable management. Full article

The Xinjiang Uygur Autonomous Region, characterized by its complex and fragile ecosystems, has faced ongoing ecological degradation in recent years, challenging national ecological security and sustainable development. To promote the sustainable development of regional ecological and landscape conservation, this study investigates Fractional Vegetation Cover (FVC) dynamics in Xinjiang. Existing studies often lack recent data and exhibit limitations in the selection of driving factors. To mitigate the issues, this study utilized Google Earth Engine (GEE) and cloud-free MOD13A2.061 data to systematically generate comprehensive FVC products for Xinjiang from 2000 to 2024. Additionally, a comprehensive and quantitative analysis of up to 15 potential driving factors was conducted, providing an updated and more robust understanding of vegetation dynamics in the region. This study integrated advanced methodologies, including spatiotemporal statistical analysis, optimized spatial scaling, trend analysis, and Geographical Detector (GeoDetector). Notably, we propose a novel approach combining a Theil–Sen Median trend analysis with a Hurst index to predict future vegetation trends, which to some extent enhances the persuasiveness of the Hurst index alone. The following are the key experimental results: (1) Over the 25-year study period, Xinjiang’s vegetation cover exhibited a pronounced north–south gradient, with significantly higher FVC in the northern regions compared to the southern regions. (2) A time series analysis revealed an overall fluctuating upward trend in the FVC, accompanied by increasing volatility and decreasing stability over time. (3) Identification of 15 km as the optimal spatial scale for FVC analysis through spatial statistical analysis using Moran’s I and the coefficient of variation. (4) Land use type, vegetation type, and soil type emerged as critical factors, with each contributing over 20% to the explanatory power of FVC variations. (5) To elucidate spatial heterogeneity mechanisms, this study conducted ecological subzone-based analyses of vegetation dynamics and drivers. Full article

Urbanization in large cities has altered the urban thermal balance, creating urban heat islands. In this context, green areas are crucial in regulating the urban climate. This study uses remote sensing data to evaluate their performance using the fractional vegetation cover (FVC) and its impact on land surface temperature (LST) in Metropolitan Lima, Peru, between 1986 and 2024. The spatial and temporal relationship between FVC and LST is analyzed, and districts are classified based on their effectiveness in thermal regulation. The Mann–Kendall test was applied to identify trends along with a Spearman correlation analysis and a clustering analysis to group districts according to the cooling effectiveness of their urban green areas. The results show that urban expansion has increased LST by an average of 6.43 °C since 1990, and there is a significant negative correlation (p < 0.001) between FVC and LST, indicating positive impacts of vegetation regulating LST at a spatial level. However, it does not reduce LST at a temporal level. This suggests that, while effective locally, green areas are insufficient to counteract the overall warming of LST over time. Based on FVC and LST characteristics, the districts have been classified into four groups: those with well-preserved green areas, such as La Molina and San Isidro, which have a lower LST, compared to areas where urbanization has replaced vegetation, such as Carabayllo and Lurigancho (Chosica). Finally, this study highlights the importance of integrating green area management into urban planning to mitigate urban warming and promote sustainable development. Full article

The Wenchuan earthquake, an unexpected magnitude 8.0 mega-earthquake that struck on 12 May 2008, significantly changed land cover (LC), particularly affecting vegetation and rock cover. However, the long-term effects of LC changes on ecosystem services (ESs) remain unclear in earthquake-affected regions, especially across different spatial scales. This study, focusing on Wenchuan County, employs a multi-model framework that integrates fractional vegetation coverage (FVC), rock exposure rate (FR), and ecosystem services (ESs), combining correlation analysis, geographically weighted regression (GWR), Self-organizing map (SOM) clustering, and XGBoost-SHAP model, to analyze the spatiotemporal dynamics, interrelationships, and driving mechanisms of land cover (LC) and ESs before and after the earthquake. Results show that: (1) From 2000 to 2020, FVC and FR fluctuated markedly under earthquake influence, with slight declines in habitat quality (HQ) and carbon storage (CS) and notable improvements in soil conservation (SC) and water yield (WY). (2) With increasing elevation, the FVC–CS–SC group exhibited a downward trend and synergy, while the FR–HQ–WY group increased and also showed synergy; trade-offs and synergies became more pronounced at larger scales, displaying strong spatiotemporal heterogeneity. (3) Elevation (explaining 10–60% of variance) was the main driver for LC and ESs, with land use, slope, human activities, climate, and geological conditions significantly impacting individual indicators. At the same time, the existing geological hazard points are mainly concentrated along both sides of the river valleys, which may be associated with intensified human–land conflicts. These findings offer valuable insights into ecological restoration and sustainable development in earthquake-affected regions. Full article

Determining the optimal vegetation cover threshold in a region for facilitating both high levels of ecosystem services (ESs) supply and synergistic sustainable development among different ESs is crucial. This study delineated the nonlinear relationship between the fractional vegetation cover (FVC) and the integrated synergy–supply capacity of ESs in Ji County, on China’s Loess Plateau (2000–2023). The FVC was quantified using Landsat remote sensing data. Assessments of carbon storage, soil conservation, water conservation, and habitat quality were conducted based on multi-source remote sensing datasets and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, which subsequently informed the evaluation of the integrated synergy–supply capacity of ESs. Spatial–temporal distribution characteristics were assessed via trend analysis methods and the spatial correlation relationship was assessed via bivariate local spatial autocorrelation analysis. The constraint line analysis and the restricted cubic spline method were combined to analyze the nonlinear relationship between the two and to quantify the FVC threshold. The results revealed that the spatial distribution of both the FVC and the integrated synergy–supply capacity of ESs was higher in the north, with a growth trend observed respectively. A highly significant positive spatial correlation existed between the two (Moran’s I > 0.6520, p < 0.01), dominated by the High–High agglomeration type (55.71%). The relationship between the regional FVC and the ISSC of ESs, the forest land FVC and the ISSC of ESs, and the grassland FVC and the ISSC of ESs all exhibited a positive convex function constraint line. The regional FVC threshold was 0.5, the forest land FVC threshold was 0.28, and the grassland FVC threshold was 0.77. When the FVC value was above the threshold, its facilitating effect on the ISSC of ESs diminished. This study advances vegetation threshold research by integrating the supply levels and synergy degrees of multiple ESs, providing a scientific foundation for formulating strategies for regional ecological restoration and adaptive management, and offering a reference for high-quality vegetation restoration in global arid, semi-arid, and erosion-prone regions. Full article

Surface soil moisture (SSM) plays a pivotal role various fields, including agriculture, hydrology, water environment, and meteorology. To investigate the impact of land use types and fractional vegetation cover (FVC) on the accuracy of SSM estimation, this study conducted a comprehensive analysis of SSM estimation performance across diverse land use scenarios (e.g., multiple land use combinations and cropland) and varying FVC conditions. Sentinel-2 NDVI and MOD09A1 NDVI were fused by the Enhanced Spatial and Temporal Adaptive Reflection Fusion Model (ESTARFM) to obtain NDVI with a temporal resolution better than 8 d and a spatial resolution of 20 m, which improved the matching degree between NDVI and the Sentinel-1 backscattering coefficient (σ⁰). Based on the σ⁰, NDVI, and in situ SSM, combined with the water cloud model (WCM), the SSM estimation model is established, and the model of each land use and FVC is validated. The model has been applied in Handan. The results are as follows: (1) Compared with vertical–horizontal (VH) polarization, vertical–vertical (VV) polarization is more sensitive to soil backscattering (${\mathsf{\sigma }}_{\mathrm{soil}}^0$). In the model for multiple land use combinations (Multiple-Model) and the model for the cropland (Cropland-Model), the R² increases by 0.084 and 0.041, respectively. (2) The estimation accuracy of SSM for the Multiple-Model and Cropland-Model is satisfactory (Multiple-Model, RMSE = 0.024 cm³/cm³, MAE = 0.019 cm³/cm³, R² = 0.891; Cropland-Model, RMSE = 0.023 cm³/cm³, MAE = 0.018 cm³/cm³, R² = 0.886). (3) When the FVC > 0.75, the accuracy of SSM by the WCM is low. It is suggested the model should be applied to the cropland where the FVC ≤ 0.75. This study clarified the applicability of SSM estimation by microwave remote sensing (RS) in different land uses and FVCs, which can provide scientific reference for regional agricultural irrigation and agricultural water resources management. The findings highlight that the VV polarization-based model significantly improves SSM estimation accuracy, particularly in croplands with FVC ≤ 0.75, offering a reliable tool for optimizing irrigation schedules and enhancing water use efficiency in agriculture. These results can aid in better water resource management, especially in regions with limited water availability, by providing precise soil moisture data for informed decision-making. Full article

Kazakhstan’s pasture, as a spatially extended agricultural resource for sustainable animal husbandry, requires effective monitoring with connected rational uses. Ranking number nine globally in terms of land size, Kazakhstan, with an area of about three million square km, requires proper assessment technologies for climate change and anthropogenic impact to track the pasture lands’ degradation. Remote sensing (RS)-based adaptive approaches for assessing pasture load, combined with field cross-checking of pastures, have been applied to evaluate the quality of vegetation cover, economic potential, service function, regenerative capacity, pasture productivity, and changes in plant species composition for five pilot regions in Kazakhstan. The current stages of these efforts are presented in this project report. The pasture lands in five regions, including Pavlodar (8,340,064 ha), North Kazakhstan (2,871,248 ha), Akmola (5,783,503 ha), Kostanay (11,762,318 ha), Karaganda (19,709,128 ha), and Ulytau (18,260,865 ha), were evaluated. Combined RS data were processed and the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Fraction of Vegetation Cover (FCover), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Canopy Chlorophyll Content (CCC), and Canopy Water Content (CWC) indices were determined, in relation to the herbage of pastures and their growth and development, for field biophysical analysis. The highest values of LAI, FCOVER, and FARAR were recorded in the Akmola region, with index values of 18.5, 126.42, and 53.9, and the North Kazakhstan region, with index values of 17.89, 143.45, and 57.91, respectively. The massive 2024 spring floods, which occurred in the Akmola, North Kazakhstan, Kostanay, and Karaganda regions, caused many problems, particularly to civil constructions and buildings; however, these same floods had a very positive impact on pasture areas as they increased soil moisture. Further detailed investigations are ongoing to update the flood zones, wetlands, and swamp areas. The mapping of proper flood zones is required in Kazakhstan for pasture activities, rather than civil building construction. The related sustainable permissible grazing husbandry pasture loads are required to develop also. Recommendations for these preparation efforts are in the works. Full article

The COllaborative Carbon Column Observing Network has become a reliable source of high-quality ground-based remote sensing network data that provide column-averaged dry-air mole fractions of carbon dioxide (XCO₂), methane (XCH₄), and carbon monoxide (XCO). The fiducial reference measurements of these gases from the COCCON complement the TCCON and NDACC-IRWG data. This study shows the application of COCCON data for the validation of existing greenhouse gas satellite products. This study includes the validation of XCH₄ and XCO products from the European Copernicus Sentinel-5 Precursor (S5P) mission, XCO₂ products from the American Orbiting Carbon Observatory-2 (OCO-2) mission, and XCO₂ and XCH₄ products from the Japanese Greenhouse gases Observing SATellite (GOSAT). A total of 27 datasets contributed to this study; some of these were collected in the framework of campaign activities and covered only a short time period. In addition, several permanent stations provided long-term observations. The random uncertainties in the validation results, specifically for S5P with a lot of coincidences pairs, are found to be similar to the comparison with the TCCON. The comparison results of OCO-2 land nadir and land glint observation modes to the COCCON on a global scale, despite limited coincidences, are very promising. The stations can, therefore, expand on the coverage of the already existing ground-based reference remote sensing sites from the TCCON and the NDACC network. The COCCON data can be used for future satellite and model validation studies and carbon cycle studies. Full article