Search Results (6)

Land use change and agricultural management have a considerable impact on land use patterns and greenhouse gas (GHG) emissions in dynamic urbanised landscapes. This study evaluated sustainable land allocation strategies in line with the European Green Deal. A constrained cellular automata land use model was employed to assess the impacts of Business-as-Usual (BAU), Land Sharing (LSH), and Land Sparing (LSP) scenarios, using open-access data from Flanders (Belgium). Under BAU, urban expansion reduced unregistered agricultural land by 495 km², leading to higher GHG emissions despite an 11% increase in green space. LSH increased green space by 36% and enhanced landscape diversity, while LSP improved habitat coherence by 24%. Livestock-related methane (3.09 Mt ${\mathrm{CO}}_2$e) dominated GHG emissions, comprising more than 75% of the total, with cattle responsible for 73% of methane emissions. Nitrous oxide emissions reduced from 1.60 Mt ${\mathrm{CO}}_2$e to 1.44 (BAU), 1.43 (LSP), and 1.42 (LSH) Mt ${\mathrm{CO}}_2$e. Forest sequestration offset up to 34% of total emissions, removing −1.35 Mt ${\mathrm{CO}}_2$e. Green Deal measures mitigated emissions in all scenarios, with LSH achieving the highest gains. The results highlight the need for spatial strategies that integrate sustainable agricultural practices and balance productivity, nature conservation, and climate action under the European Green Deal. Full article

The alteration of landscape spatial patterns (LSPs) and ecosystem services (ESs) in watersheds can have detrimental effects on the local environment and community. However, a comprehensive understanding of the current state of LSPs and ESs in watersheds around Winter Olympic venues in China is limited. Here, we assessed current LSPs and ESs and developed optimization strategies for the Xigou watershed around Winter Olympic venues in the northern agro-pastoral ecotone of China. The results indicated that the main land use type was grassland in the Xigou watershed, and landscape types were relatively homogenous. All three ESs (water yield, sediment retention, and carbon storage) generally improved from 2004 to 2020. For ESs, there was the lowest total volume of water yield in 2004 (637.44 × 10⁴ m³). But sediment retention (10.54 × 10⁶ t, 18.13 × 10⁶ t, 13.28 × 10⁶ t, and 16.85 × 10⁶ t) had an upward, then downward, then upward trend before and after ERP. Carbon storage grew steadily. Correlation analysis suggested that the three ESs were closely related to the landscape spatial indices of average patch area (AREA_MN), contagion index (CONTAG), and Shannon’s evenness index (SHEI). AREA_MN, CONTAG, and SHEI in the eastern part of the study area promoted sediment retention and carbon storage, while in the southwestern part of the study area, they inhibited water yield and sediment retention. The results suggest that improving sediment retention by optimizing land use and cover change (LUCC) and LSPs is the main approach to further enhance ESs in the study area. Our study suggests that the inclusion of multiple landscape pattern indices can provide a more comprehensive representation of regional ecosystem service. Full article

The rapid increase in population and economic activities has greatly influenced land use and spatial development. In urban agglomerations where socioeconomic activities are densely concentrated, the clash between ecological protection and economic growth is becoming more evident. Therefore, a thorough quantitative assessment of spatial changes driven by land use dynamics, alongside an examination of temporal and spatial driving factors, is crucial in offering scientific backing for the long-term and sustainable growth of urban agglomerations. This paper focuses on the major urban agglomerations in China’s Yangtze River Delta region, examining the spatiotemporal evolution of land use and landscape patterns from 2000 to 2020. By employing the standard deviation ellipse technique, coupled with multiple linear regression and the geographical detector model, we conduct a quantitative assessment of the directional trends in urban construction land expansion as well as the diverse impacts of temporal and spatial factors on this expansion across various periods and regions. The findings indicate that over the past 20 years, construction land in the Yangtze River Delta Urban Agglomeration expanded in concentrated patches, showing significant scale effects with relatively intact farmland and forest land being increasingly encroached upon. Landscape-type transitions predominantly occurred in cities around Taihu Lake and Hangzhou Bay, with the most significant transition being farmland converted to construction land, resulting in a greater number of patches and more pronounced land fragmentation. Throughout the 20 years, the standard deviation ellipse of construction land in the Yangtze River Delta Urban Agglomeration expanded and shifted, with the predominant expansion trending from the northwest toward the southeast, and the EN orientation being the most intense expansion area, covering 1641.24 km². The influence of temporal and spatial driving factors on the expansion of urban construction land differed across various periods and regions. This study thoroughly examines the driving factors that affect the evolution of urban construction land in the region, offering valuable scientific evidence and references for future planning and development of the Yangtze River Delta Urban Agglomeration, aiding in the formulation of more precise and efficient urban management and land use strategies. Full article

This study assesses the conservation effectiveness of 21 protected areas (PAs) in Northern Morocco, comprising 3 parks and 18 Sites of Ecological and Biological Interest (SBEIs), against five major landscape pressures (LSPs): deforestation, infrastructure extension, agricultural expansion, fires, and population growth. We propose a novel quantitative methodology using global remote sensing data and exploratory spatial data analysis (ESDA). Data were sourced from Global Forest Change (GFC), Global Land Analysis and Discovery (GLAD), Burned Area Product (MODIS Fire_CCI51), and World Population datasets. The combined impact of the five LSPs was measured using a cumulative effect index (CEI), calculated with the Shannon–Wiener formula at a 1 km² scale. The CEI was analyzed alongside the distance to the PAs’ network using Moran’s index, identifying four spatial association types: high–high (HH), high–low (HL), low–low (LL), low–high (LH), and non-significant (NS) cells. This analysis defined four zones: inner zone (IZ), potential spillover effect zone (PSEZ), statistically non-significant zone (SNSZ), and non-potential effect zone (NPEZ). Conservation effectiveness was quantified using the conservation ratio (CR), which compared the prevalence of LL versus HL units within IZs and PSEZs. Four disturbance levels (very high, high, medium, and low) were assigned to CR values (0–25%, 25–50%, 50–75%, 75–100%), resulting in sixteen potential conservation effectiveness typologies. Initial findings indicated similar deforestation patterns between protected and unprotected zones, with wildfires causing over half of forest losses within PAs. Conservation effectiveness results categorized the 21 PAs into nine typologies, from high conservation to very high disturbance levels. A significant positive correlation (71%) between CRs in both zones underscored the uniform impact of LSPs, regardless of protection status. However, protected natural area zones in the parks category showed minimal disruption, attributed to their advanced protection status. Finally, we developed a methodological framework for potential application in other regions based on this case study. Full article

With industrialization and urbanization, the competition among land production, living, and ecological (PLE) spaces has intensified. Particularly in ecological reserves, competition among various types of land use restricts the coordinated development of PLE space. To explore spatial sustainable development, this study starts from a PLE spatial perspective, based on Landsat long time series images. Object-based image analysis (OBIA) and landscape index analysis were selected to monitor the spatial and temporal land use and landscape pattern changes in the Poyang Lake region (PYL region) from 1989 to 2020. The RF-Markov-FLUS coupled model was used to simulate spatial changes in 2030 under four scenarios: production space priority (PSP), living space priority (LSP), ecological space priority (ESP), and an integrated development (ID). Finally, the goal-problem-principle was used to enhance PLE space. The results showed that: (1) production space and ecological spaces decreased in general from 1989 to 2020 by 3% and 7%, respectively; living space increased by 11%. (2) From 1989 to 2020, the overall landscape spread in the Poyang Lake (PYL) area decreased, connectivity decreased, fragmentation increased, landscape heterogeneity increased, and landscape geometry became more irregular. (3) Compared with the other three scenarios, the ID scenario maintained steady production space growth in 2030, the expansion rate of living space slowed, and the area of ecological space decreased the least. (4) Spatial pattern optimization should start with three aspects: the transformation of the agricultural industry, improving the efficiency of urban land use, and establishing communities of “mountains, water, forests, fields, lakes and grasses”. The results provide scientific planning and suggestions for the future ecological protection of Poyang Lake area with multiple scenarios and perspectives. Full article

Global change impacts including climate change, increased CO₂ and nitrogen deposition can be determined through a more precise characterisation of Land Surface Phenology (LSP) parameters. In addition, accurate estimation of LSP dates is being increasingly used in applications such as mapping vegetation types, yield forecasting, and irrigation management. However, there has not been any attempt to characterise Middle East vegetation phenology at the fine spatial resolution appropriate for such applications. Remote-sensing based approaches have proved to be a useful tool in such regions since access is restricted in some areas due to security issues and their inter-annual vegetation phenology parameters vary considerably because of high uncertainty in rainfall. This study aims to establish for the first time a comprehensive characterisation of the vegetation phenological characteristics of the major vegetation types in the Middle East at a fine spatial resolution of 30 m using Landsat Normalized Difference Vegetation Index (NDVI) time series data over a temporal range of 20 years (2000–2020). Overall, a progressive pattern in phenophases was observed from low to high latitude. The earliest start of the season was concentrated in the central and east of the region associated mainly with grassland and cultivated land, while the significantly delayed end of the season was mainly distributed in northern Turkey and Iran corresponding to the forest, resulting in the prolonged length of the season in the study area. There was a significant positive correlation between LSP parameters and latitude, which indicates a delay in the start of the season of 4.83 days (R² = 0.86, p < 0.001) and a delay in the end of the season of 6.54 days (R² = 0.83, p < 0.001) per degree of latitude increase. In addition, we have discussed the advantages of fine resolution LSP parameters over the available coarse datasets and showed how such outputs can improve many applications in the region. This study shows the potential of Landsat data to quantify the LSP of major land cover types in heterogeneous landscapes of the Middle East which enhances our understanding of the spatial-temporal dynamics of vegetation dynamics in arid and semi-arid settings in the world. Full article