Spatial Land Use Research Articles

Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.

An optimization-simulation modeling framework for exploring the dynamic correlation between the coordinated development of the human-nature nexus and land use under uncertainty

Sustainable land use optimization (LUO) requires simultaneously reconciling human development and nature conservation, and effectively adapting to changes in socioeconomic development. We proposed a modeling framework that includes stochastic simulation of population and GDP uncertainty, multidimensional LUO, and spatial land use simulation combining random forests and cellular automata. The framework can (1) balance the multidimensional contradictory conflicts between human-nature nexus (HNN); (2) obtain the dynamic correlation and probability distribution of land use with the dimensional objectives and the HNN; and (3) obtain the dynamic response of land use to changes in socioeconomic development and the elasticity space of land use. The framework was applied to Hubei Province in the middle reaches of the Yangtze River. The results indicated that by 2030, the land use intervals that can cope with uncertainty and achieve high levels of HNN coordination of 0.66–0.69 at 51,500–55,500 (km2) for cultivated land, 47,750–49,750 (km2) for forestland, 1,950–2,350 (km2) for grassland, 9,300–10,100 (km2) for construction land, 11,249–11,418 (km2) for water area, and 285–307 (km2) for unused land. This study elucidates the complex dynamic correlation between HNN and land use, and provides regions with LUO decisions that can respond to changing conditions and promote a harmonious HNN development.

The impact of vegetation reconstruction on soil erosion in the Loess plateau

Vegetation restoration not only extensively reshapes spatial land use patterns but also profoundly affects the dynamics of runoff and sediment loss. However, the influence of vegetation restoration on runoff and sediment yield from a regional perspective are scarce. This study therefore focused on 85 sites within the “Grain for Green” Project (GGP) region on the Loess Plateau, to investigate the impacts of the GGP on soil erosion. The results revealed a notable reduction in sediment loss and runoff due to vegetation restoration. Since the inception of the GGP in 1999, approximately 4.1 × 106 ha of degraded lands have been converted into forestlands, shrublands, and grasslands, resulting in an average annual reduction of 1.4 × 109 m3 in runoff and a decrease of 3.6 × 108 t in annual sediment loss on the whole Loess Plateau, with the GGP contributing approximately 26.7% of the sediment reduction in the Yellow River basin. The reduced soil erosion has mainly been regulated by vegetation cover, soil properties (clay, silt, and sand), slope, and precipitation on the Loess Plateau. The insights gained offer valuable contributions to large-scale assessments of changes in soil erosion in response to vegetation reconstruction and enhance our understanding of the spatial configurations associated with soil erosion control measures.

Response of river nitrogen and phosphorus output to spatial land use loads in the multi-watershed of the Xinjiang River

Response of river nitrogen and phosphorus output to spatial land use loads in the multi-watershed of the Xinjiang River

The Study of Settlement Preservation Pattern for Environmental Sustainability in Canggu Village, Badung Regency, Bali Province

Canggu is one of the settlements Village in the southern coastal community in Bali which is currently experiencing very rapid tourism development. This village has a relatively flat topographic condition, as well as being one of the areas of Majapahit descent. The rapid development of tourist accommodation that currently occurs in Canggu, has an impact on the high conversion of land use, and the disruption of local community settlements. Seeing this fact, it is considered necessary to make an evaluation study on the development of spatial planning which will later be used as input in determining spatial land use control policies in Canggu Village. This research uses qualitative methods, case studies using field observation techniques and interviews, which are then compared with literature reviews in the form of regional spatial policy studies and relevant theories. The analysis was conducted on the residential area of Canggu Village, which aimed to determine the main causes of land use change and displacement of local community settlements. From the results of the analysis, which is then compared with literature studies, it is expected to be able to find a solution to preserve the urgency of local community settlements. The results of the analysis show that the implementation of spatial concepts sourced from culture is more respected by the community compared to local government policies. The hulu-teben concept as the basis for the preservation of settlement spatial values derived from the Tri Hita Karana cultural philosophy, is considered very effective and feared by the community because it is related to social sanctions that must be borne by the community, which are outlined in pararem.

Water Framework Directive micropollutant monitoring mirrors catchment land use: Importance of agricultural and urban sources revealed

River monitoring programs worldwide consistently unveil micropollutant concentrations (pesticide, pharmaceuticals, and industrial chemicals) exceeding regulatory quality targets with deteriorating effects on aquatic communities. However, both the composition and individual concentrations of micropollutants are likely to vary with the catchment land use, in particular regarding urban and agricultural area as the primary sources of micropollutants. In this study, we used a dataset of 109 governmental monitoring sites with micropollutants monitored across the Federal State of North Rhine-Westphalia, Germany, to investigate the relationship between high-resolution catchment land use (distinguishing urban, forested and grassland area as well as 22 different agricultural crop types) and 39 micropollutants using Linear Mixed Models (LMMs). Ecotoxicological risks were indicated for mixtures of pharmaceutical and industrial chemicals for 100 % and for pesticides for 55 % of the sites. The proportion of urban area in the catchment was positively related with concentrations of most pharmaceuticals and industrial chemicals (R2 up to 0.54), whereas the proportions of grassland and forested areas generally showed negative relations. Cropland overall showed weak positive relationships with micropollutant concentrations (R2 up to 0.29). Individual crop types, particularly vegetables and permanent crops, showed higher relations (R2 up to 0.46). The findings suggest that crop type-specific pesticide applications are mirrored in the detected micropollutant concentrations. This highlights the need for high-resolution spatial land use to investigate the magnitude and dynamics of micropollutant exposure and relevant pollution sources, which would remain undetected with highly aggregated land use classifications. Moreover, the findings imply the need for tailored management measures to reduce micropollutant concentrations from different sources and their related ecological effects. Urban point sources, could be managed by advanced wastewater treatment. The reduction of diffuse pollution from agricultural land uses requires additional measures, to prevent pesticides from entering the environment and exceeding regulatory quality targets.

Spatial-Land use planning system data model proposal for edition II of LADM

Spatial plan decisions guide both the future use of the lands and many activities from protection to construction and permit. Due to its functions, spatial plan decisions play a key role in land administration. Spatial planning information for integrated land administration systems (LASs) should be associated with land registration systems. The Land Administration Domain Model (LADM) standard offers components to enable this structure. Integrating spatial plan data with LASs will provide standardization for plan data and assurance of plan decisions. Although the spatial planning mission differs across various administrative regions, planning activities produce land use decisions, albeit in different ways. The study aims to establish the common points in planning activities and design a joint spatial planning system data model using various countries’ spatial planning systems and international standardization studies. The spatial plans in the model that has been proposed are depicted as a system, not merely by the rights, restrictions, and responsibilities (RRRs) that they establish on the land. The results point out that spatial planning systems have some similarities but also some limitations to support conceptual model design. Based on joint data and relationships, the proposed spatial planning system data model can be adapted for different country practices. The study’s results are expected to support the LADM second version development studies.

Assessment of Karachi as an Urban Heat Island Threat through Remote Sensing and GIS Techniques

The present study aimed to assess the threat of transformation of Karachi into an Urban Heat Island, so, ambit was having calculated temperature, buildup areas, and normalized difference vegetation index through remote sensing and GIS techniques. The Landsat satellite data was used to differentiate the temperature in different years. These images were processed through Envi 4.7, Erdas Imagine, and ArcGIS 10.3.1. The results revealed that the maximum temperature was found up to 30.52, 35.25, 33.60, 46.73 °C; the buildup area was 23, 34, 26, 45 %; the NDVI results showed ranging from 0.224-1, 0.07-0.43, 0.201-1, 0.29-0.7 during this years. The average spatial land use temperature and buildup area increased by 1.03 and 1.9 times from 1990 to 2019. The maximum NDVI was observed during 2019, because of heavy rainfall as a result which supports promoting more greenery. With an increase in the buildup area, a significant change in the temperature of the territory was simultaneously observed. Therefore, this indicates a major task for urban developers extenuating the subsequent urban heat island occurrence. That is, for the first time it is scientifically substantiated and confirmed by the results that when creating a city development plan, it is extremely important to exclude the possibility of the urban heat island occurrence through preliminary studies. The practical value of the study lies in sound recommendations, one of which is the need for future urban development to emphasize urban plantings, including vertical forests to prevent UHI occurrence in the area of Karachi city.

Response of Urban Ecosystem Carbon Storage to Land Use/Cover Change and Its Vulnerability Based on Major Function-Oriented Zone Planning

Vigorous emphasis has been placed on optimizing land spatial planning to protect carbon storage and enhance ecosystem resilience. What is the effectiveness of the Major Function-Oriented Zone (MFOZ) planning implemented to achieve this goal in China? Especially in urbanized areas where there are more pronounced conflicts between humans and land. Taking the Beijing-Tianjin-Hebei (BTH) urban agglomeration as the target area, this study explored the response of carbon storage to land use/cover change (LUCC) and its vulnerability to ecological service functions under MFOZ planning. The 30 m × 30 m spatially resolved Landsat TM/ETM remote sensing images from 2000 to 2020 were used. The data preprocessing was performed mainly through radiometric calibration, clipping, and reclassification through the ArcGIS 10.7 software. Applying the InVEST model, which uses the LUCC map and carbon storage density of the four carbon pools, including above-ground carbon density, below-ground carbon density, dead organic carbon density, and soil organic carbon density, to evaluate the carbon storage under the current landscape or in the future, the results show that: (1) The BTH ecosystem experienced a carbon storage reduction of about 7.25 × 107 Mg from 2000 to 2020 due to the expansion of construction land, which crowded out cropland. Carbon storage in the BTH showed a high concentration in the “northeast-southwest” direction and a tiny distribution in the “middle-east” direction. (2) From 2015, the initial effects of the MFOZ planning were seen, with the ecological land in the Central Core Zone and Eastern Coastal Development Zone decreasing while the proportion of high-carbon storage areas in the Eastern Coastal Development Zone increasing. (3) Over the two decades, the land use intensity index improved by 4.65 overall, and vulnerability worsened from 2000 to 2015 and was alleviated from 2015 to 2020. This study will provide a scientific reference for optimizing urban spatial land use planning and promoting carbon sequestration in ecosystems.

Spatial correlation analysis and prediction of carbon stock of “Production-living-ecological spaces” in the three northeastern provinces, China

The “Production-Living-Ecological Space” (PLES) is a paramount indicator in the filed of territory space development and optimization in China, under the new era. Exploring the driving factors of the PLES'land expansion is of great significance for improving space utilization, mitigating severe climate changes, and promoting green, healthy and sustainable development. In the background of the “Carbon Emissions Peak and Carbon Neutrality” strategy, analyzing and predicting the carbon stock of PLES is effective to boosting the achievement of ‘Dual-Carbon’ vision. Based on the above research questions， this study constructs the PLES based on statistics about land use (Year 1990, 2000, 2010 and 2020) in three northeastern provinces, and reveals the spatial correlation of PLES’ carbon stock in the research area through ArcGIS spatial analysis and InVEST model. Then, the PLUS model was used to clarify the contribution of each driver to the conversion of space land, and to predict the distribution of the PLES pattern and the carbon stock's spatial correlation in 2030 and 2060 under the Natural-Development Scene and Ecological-Protection-Development Scene. Results show that: (1) The PLES in the three northeastern provinces of China is primarily green ecological space (55.71%) and agricultural production space (38.10%), while industrial production space (3.60%) and urban living space (2.76%) expand significantly, and green ecological space (−0.17%) and blue ecological space (−0.89%) are on a recession trend. Besides, 2000–2010 is the most intense period of all kinds of space land transformation in the study area. (2) Population density, proximity to roads at all levels, annual average temperature and elevation are the prime drivers of PLES’ profile within the scope of the study region, but the contribution rate is significant difference. (3) The urban living space decreases and the green and blue ecological space increases significantly in the predicted years under the scene of Natural-Development and Ecological-Protection development; the pattern of PLES is relatively stable in the predicted years under both scenarios. (4) The spatial correlation of carbon stock is closely related to the distribution of PLES, with the high-value significant regions primarily in the distribution region of green ecological space, otherwise, the low-value significant regions mostly concentrated in the region with complex spatial land use types and large spatial development intensity; the overall structure within the scope of the study region shows a layout of high value areas surrounding low value areas. It can show that insisting on the ecological civilization construction is an effective way to achieve sustainable development and practice the “double carbon” strategy; in the future spatial land use control, ecological protection measures should still be adopted to ensure the sustainable development and positive operation of the study area.

Modeling of land use and cover changes (LUCC) in Deli Serdang Regency, North Sumatra Province

Land use/cover (LUC) is a substantial factor in land management and can influence policy in an area. LUC has the potential to change due to physical, economic, and social aspects. This study aims to analyze the spatialland use and cover changes (LUCC) in Deli Serdang Regency for the 2010 to 2020 period and predict LUC in 2030. The analysis was run by applying the Cellular Automata-Markov Chain method. The driving factors used in this modeling are the distance to the road, the distance to the river, population density, the distance to the district capital, and the distance to Medan city. The results showed that Kappa for image classification was 0.86. The dominant type of LUC in Deli Serdang Regency is a plantation, with a total area of more than 45%, followed by paddy fields, dryland agriculture, forests, and settlements/built-up areas. LUCC model validation obtained a kappa value of 0.89 (very good category) and can be applicated for predicting land use change models in 2030. By 2030, the settlements/built-up area and dryland agriculture will increase significantly, which 21,060 ha and 4,587 ha, respectively, while forests, plantations, and paddy fields will decrease significantly by around 9,266 ha, respectively, respectively 8,306 ha and 7,806 ha.

Effect of planning policies on land use dynamics and livelihood opportunities under global environmental change: Evidence from the Mekong Delta

The Mekong Delta faces significant challenges in supplying Vietnam and its export market countries with agricultural commodities, while ensuring livelihoods and providing living space to its growing population in the context of climate change and the country’s agrarian transition. Anthropogenic factors, such as the construction of dykes to control river flooding, river sand mining, the further development of triple-cropping rice production, and infrastructure development, together with climate change impacts on sediment and water availability, are all combining to threaten agricultural production. One of the key challenges in sustainable development is the need to identify plausible future states of agricultural-based socio-ecological systems which draw upon differing strategies of land management, and to characterise the impacts of these systems on both the landscape and employment. It was hypothesised from the literature and rapid rural appraisals that each land system can only provide a certain number of jobs, which was further demonstrated using binomial regressions. We show that the odds of being employed are lower for intensive agricultural systems (OR=0.78 for triple rice; 0.91 for intensive aquaculture) than for diversified systems (OR=1.16 for rice-aquaculture; OR=1.63 for mixed fruit trees). Drawing from workshops with local and national stakeholders, we then used Earth observation and national census data in a spatial land use systems dynamic framework to simulate two alternative Mekong Delta futures based upon the climate pathway RCP 4.5 in combination with two existing policies (i) Resolution No. 124 (Specialisation) which promotes triple crop rice and aquaculture intensification and (ii) Resolution No. 639 (Diversification), which states that there should be a development of sustainable rice aquaculture and crop diversification. Based on the quantitative objectives of each policy, we estimated likely changes of services provided by land use systems if either policy were to dominate. The estimated impacts of each future scenario on the provision of employment ultimately indicate that policies with a diversification development paradigm will provide more employment (+0.9%) than policies with a specialisation paradigm (−46%), and that current policies have potentially conflicting consequences. Decisions driving towards intensive farming risk triggering rural unemployment and outmigration, potentially exacerbating urban poverty in major cities such as Can Tho and Ho Chi Minh City. On the other hand, decisions aiming at increasing diversified agricultural systems can help secure more job opportunities. Our results indicate that spatial planning policies should rely on a broad-based assessment of land system services that include employment and environmental impacts to ensure a just transition towards resilient and environmentally sustainable rural territories.

Land Use Misclassification Results in Water Use, Economic Value, and GHG Emission Discrepancies in California’s High-Intensity Agriculture Region

California’s San Joaquin Valley is both drought-prone and water-scarce but relies on high-intensity agriculture as its primary economy. Climate change adaptation strategies for high-intensity agriculture require reliable and highly resolved land use classification data to accurately account for changes in crop water demand, greenhouse gas (GHG) emissions, and farmgate revenue. Understanding direct and indirect economic impacts from potential changes to high-intensity agriculture to reduce groundwater overdrafts, such as reductions in the cultivated area or switching to less water-intensive crops, is unachievable if land use data are too coarse and inconsistent or misclassified. This study quantified the revenue, crop water requirement, and GHG emission discrepancies resulting from land use misclassification in the United States’ most complex agricultural region, California’s San Joaquin Valley. By comparing three commonly used land use classification datasets—CropScape, Land IQ, and Kern County Agriculture—this study found that CropScape led to considerable revenue and crop water requirement discrepancies compared to other sources. Crop misclassification across all datasets resulted in an underestimation of GHG emissions. The total revenue discrepancies of misclassified crops by area for the 2016 dataset comparisons result in underestimations by CropScape of around USD 3 billion and overestimation by LIQ and Kern Ag of USD 72 million. Reducing crop misclassification discrepancies is essential for crafting climate resilience strategies, especially for California, which generates USD 50 billion in annual agricultural revenue, faces increasing water scarcity, and aims to reach carbon neutrality by 2045. Additional investments are needed to produce spatial land use data that are highly resolved and locally validated, especially in high-intensity agriculture regions dominated by specialty crops with unique characteristics not well suited to national mapping efforts.

Developing an integrated land allocation model based on linear programming and game theory.

Land use configuration in any given landscape is the result of a multi-objective optimization process, which takes into account different ecological, economic, and social factors. In this process, coordinating stakeholders is a key factor to successful spatial land use optimization. Stakeholders need to be modeled as players who have the ability to interact with each other towards their best solution, while considering multiple goals and constraints at the same time. Game theory provides a tool for land use planners to model and analyze such interactions. In order to apply the spatial allocation model and address stakeholder conflicts, an integrated model based on linear programming and game theory was designed in this study. For implementing such model, we conducted an optimal land use allocation process through multi-objective land allocation (MOLA) and linear programming methods. Then, two groups of environmental and land development players were considered to implement the optimization model. The game algorithm was used to select the appropriate constraint so that the result would be acceptable to all stakeholders. The results showed that during the third round of the game, the decision-making process and the optimization of land uses reached the desired Nash Equilibrium state and the conflict between stakeholders was resolved. Ultimately, in order to localize the results, a suitable solution was presented in a GIS environment.

Assessing Urban Flooding Extent of the Baunia Khal Watershed in Dhaka, Bangladesh

Due to the gradual encroachment of natural drainage channels (also known as khals) and the poor management of drainage infrastructures, any rainfall of higher intensity for a few hours causes urban flooding in Dhaka, Bangladesh, hindering the daily lives of city dwellers, especially in slum areas. The Intensity–Duration–Frequency (IDF) curves with return intervals of 2, 5, 10, 25, 50, and 100 years were estimated for a 3 h duration of rainfall using the Gumbel statistical method to assess urban flooding extent around the Baganbari slum within the Baunia Khal watershed. The spatial land use changes of the Baunia Khal were also delineated through the analysis of the areal changes of the khal from 2004 to 2020. The area of the khal was found to be 7.00 km2, 2.17 km2 and 0.41 km2 for the years 2004, 2010, and 2020, respectively. It appears that a gradual massive areal decrease of the khal (impervious land segment) was in progress during this period for high encroachments driven by various governmental agencies and other private entities’ urban developmental projects. The runoff coefficient was computed as 0.76 based on the existing land use pattern, slope, and soil type of the study area. The average runoff generated from the catchment was estimated using the rational method and was 103.41 m3/hr. The drainage length was calculated as 9.1 km using the Kirpich method, whereas the present drainage length was reported as only 6.95 km. The multiple rainfall intensities with return periods of 2, 5, 10, 25, 50, and 100 years were also applied to replicate a heightened extent of urban flooding in the Baunia Khal watershed. The study suggests that the depth, length and width of the Baunia Khal need to increase to hold the generated runoff to manage urban flooding around the Baunia Khal watershed.

Optimization of Ecological Land Use Layout Based on Multimodel Coupling

Rapid urbanization is intensifying land use transitions in China by shrinking cropland and increasing land development, exacerbating land abuse, and causing environmental degradation. There are clear needs to improve land use and address these problems; however, most previous studies focused on either structural or layout optimization. In contrast, this paper proposed a method for comprehensive optimization of land use areas, layout, and structure. This involved coupling multiobjective dynamic planning (MODP), Conversion of Land Use and its Effects at Small regional extent (CLUE-S), and minimal cumulative resistance (MCR) models. In this approach, the MODP model predicted future changes that were based on areas of current land use, and the CLUE-S model simulated various future types that were based on the analysis of geographic land use and economic data. In addition, the MODP and CLUE-S models optimized the amounts and spatial distributions of land use types, respectively. The MCR model could then partition the simulation results for ecological optimization. In this paper, an illustrative application was presented that partitioned Changchun City, Jilin Province, China into construction-prohibited, restricted construction, suitable for construction, and key construction areas (which accounted for 17.41%, 30.24%, 25.32%, and 27.04%, respectively of the total area). The optimization result met expectations and provided potentially valuable reference data for spatial land use planning and ecological protection in the focal region. The proposed method to optimize the ecological layout of land use that was based on multimodel coupling considered operability and objectivity; therefore, facilitating practical applications of the results in Changchun and the presented methodology elsewhere.

Identifying a Period of Spatial Land Use Conflicts and Their Driving Forces in the Pearl River Delta

Spatial land use conflicts (SLUCs) are a critical issue worldwide due to the scarcity of land resources and diversified human demand. Despite many time-series studies of SLUCs, comprehensive research on SLUCs and their driving factors over a long period remain limited. This study was conducted in the Pearl River Delta urban agglomeration, Guangdong Province, China. We constructed a landscape ecological risk assessment model to calculate annual SLUC values and analyze their spatiotemporal distribution over 30 years. K-means clustering analysis was used to cluster SLUC values for 1990–2005 and 2006–2020, yielding comprehensive conflict intensity data for each period. The major factors driving the spatial differentiation of SLUCs and their interactions in each period were identified using an optimal parameter-based geographical detector model. The results show that SLUCs varied significantly over time, with an overall decreasing trend and distinct spatial heterogeneity. Comprehensive conflict intensity for each period was characterized by low values in the peripheral regions and high values in central parts of the study area, which tended to decrease from 1990–2005 to 2006–2020. SLUCs were heavily dependent on topographical (slope and elevation) and environmental (normalized difference vegetation index) factors. Socio-economic factors (gross domestic product and population density) were also major contributors to the spatial differentiation of SLUCs. The explanatory power of multiple interacting factors on SLUCs was enhanced compared with that of individual factors. The explanatory power of the driving factors varied, and their interactions decreased over time. The results may facilitate the rational government planning of regional land use and thus effectively mitigate SLUC intensity at the macro level.

Study on Land Use Changes in Changsha–Zhuzhou–Xiangtan under the Background of Cultivated Land Protection Policy

The Changsha–Zhuzhou–Xiangtan region has experienced rapid social and economic development over the past 40 years, and cultivated land has changed dramatically. The contradiction between built and cultivated land has intensified, for which the local government has implemented a series of policies related to cultivated land protection. However, thus far, it is not clear what the substantial effects of the cultivated land protection policies are. To this end, this paper quantitatively characterizes the changes in the Changsha–Zhuzhou–Xiangtan region during the 20 years before and after the implementation of the cultivated land occupation balance policy, based on land use data from 1980, 2000, and 2020 using intensity analysis. In this paper, we examine the types of spatial land use patterns occurring in Changsha–Zhuzhou–Xiangtan since 1980 and explore the transition path of land use types in urban–rural integration. After the cultivated land protection policy, the transformation relationship between land use types and the changing trend of the cultivated land area was analyzed from the landscape scale. The influence of policy factors on the transformation of land use types was revealed. The results show that, from 1980 to 2020, the changing intensity of construction land and unused land was relatively large and was in an active state; the amount of built land in the Changsha–Zhuzhou–Xiangtan region has been growing, with a net increase of 1101 km2, while the amount of cultivated land has been showing a net decrease, with a net reduction of 677 km2. Moreover, the cultivated land has mainly been converted into built land, and the lost cultivated land area in Changsha–Zhuzhou–Xiangtan has not been fully compensated elsewhere in the region, indicating that the cultivated land protection policy has not been able to maintain the cultivated land area in Changsha–Zhuzhou–Xiangtan. From 2000 to 2020, cultivated land change was mainly due to exchange, which indicates that the policy has had a particular effect on the protection of cultivated land. Still, if the government wants to achieve the “balance of cultivated land occupation and compensation” goal, it must establish a complete system for the allocation of cultivated land resources. This study can provide a scientific reference for further implementing the cultivated land protection policy, which is thus of great significance for promoting the construction of the Changsha–Zhuzhou–Xiangtan region and its high-quality economic and social development.

Role of reservoirs of urban heat island effect mitigation in human settlements: moderate climate zone

This paper presents the problem of the increasing negative impact of urban heat islands (UHI) on urban residents based on land surface temperature (LST). It is assumed that water bodies in the agglomeration remain cooler than the air and surrounding urban areas. The study aimed to determine the impact of water bodies and surrounding areas covered by trees on the temperature of an urban area and to minimise the impact of UHI on the life quality of people in the temperate climate zone at day temperatures 25°C (W day) and 29°C (H day). In the adopted research methodology, 167 reservoirs, larger than 1 ha, located within 300 m of urban areas, were analysed. Satellite thermal imagery, spatial land use data (Corine Land Cover), and local land characteristics were used. The average temperature of the reservoirs was appropriately at 4.69°C on W day and 1.9°C for H day lower than in residential areas. The average temperature of areas at a distance of 30 m from the reservoirs was 2.69°C higher onWand 0.32°C higher on H than the water of the reservoirs. The area covered by trees was 0.52°C lower on W day and 0.39°C lower on H day than the residential areas located at a distance of 300 m from the reservoir. On terrestrial areas, the lowest temperature was observed in the area covered by trees within 0–30 m from reservoirs both on warm and hot days. Based on the results of this study, UHI mitigation solutions can be suggested.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.