Build-up Land Research Articles

Ecological Footprint for Environmental Sustainability at the University of Juba, South Sudan

Given the growing population of students and the new infrastructural development at the University of Juba, it is environmentally significant to investigate the ecological footprint of the University campus ecosystem in light of environmental sustainability. This study aims to assess and quantify the ecological footprint at University of Juba campus and compare them to the environmental sustainability. In this study cross sectional survey of 180 students and component based methods by Rees and Wackernagel were employed to obtain results of ecological footprint of water, food, land, transport, waste and energy at the University of Juba. Considering Ecological Footprint of students and staff on campus, Biocapacity was 1.16, ecological footprint remainder was 1.06 and ecological footprint index was 0.92. While the ecological footprint of Water, food, transportation, waste, energy and built-up land footprint were 0.04, 0.03, 0.03, 0.01, 0.0003 and 0.0002 gha/capita respectively. The result of the environmental sustainability practices on the campus revealed that 11 out of 44 environmental sustainable programs were not practiced on campus implying 27.7% of the university operation was unsustainable. Although, University of Juba was found to be environmentally sustainable, reducing its ecological footprint per capita by 0.89 gha/capita. Based on the study result, the Ecological Footprint per capita of water, energy, transportation, food, waste and build-up land at the University were environmentally sustainable (0.11 gha/capita). If, all people were living the lifestyle of the University of Juba, we would require only one planet Earth.

Assessment of eco-environment quality using multi-source remote sensing data

ABSTRACT Accurate analysis of regional eco-environment quality (EEQ) changes is essential for urban sustainability. Most of the widely used EEQ indicators ignore the impact of air pollution caused by urbanization and economic growth. This study proposed a remote sensing-based approach using a time-series comprehensive evaluation index (CEI), which was developed by PM2.5 concentration, Land surface temperature (LST), and vegetation coverage (VC) to assess the EEQ in the Demonstration Zone of Green and Integrated Ecological Development of The Yangtze River Delta (demonstration zone) from 2000 to 2020. The EEQ changes of all districts and townships were classified into five levels. The results suggested that from 2000 to 2020, the CEI was significantly decreased (p < 0.01) in the demonstration zone, indicating an overall improvement of the EEQ. Differences in the mean annual CEI values and EEQ changes were found among districts and to wnships. Higher CEI values, which indicated a lower degree of EEQ were found in areas where build-up land comprised a higher percentage of the total area. Townships with degraded EEQ change exhibited a higher percentage of increase in build-up land (32.3%) than others (8.67% to 16.68%) from 2000 to 2020. Moreover, the change of annual CEI at the administrative district scale was found to be strongly correlated with the proportion of the secondary sector in GDP in three districts. The results of our study indicated the importance of land use optimization, air pollution reduction, and vegetation coverage enhancement to improve the regional EEQ in the urban wetland ecosystems with rapid urbanization.

Exploring the impacts of urbanization on vegetation growth from the perspective of urban expansion patterns and maturity: A case study on 40 large cities in China

Rapid urbanization replaces vegetation with build-up land, which threatens green spaces and the well-being of residents. In this study, the urban expansion patterns (UEPs) of build-up land from 2000 to 2020 were identified for 40 typical large cities in China, and their urban maturity (UM) was quantified. The different UEPs and UM types were used to analyze the comprehensive impacts of different types of cities on vegetation growth at different urbanization expansion intensity gradients. Finally, the relationship between different driving forces and the urban ecological effects was explored. The results showed that mature cities and the infilling cities experienced vegetation loss while other UEPs and UM levels resulted in increased vegetation growth. In particular, laggard cities and looser UEPs were able to effectively offset the direct vegetation loss caused by urbanization. The UM level had a high driving effect on the urban ecological offset. In the future, the scale and speed of urbanization can be optimized to reasonable levels and the urban ecological restoration should be strengthened to meet the needs of ecological security. This study contributes to explore the effectiveness of the urbanization process and land management.

Multi-Scenario Simulation of Land System Change in the Guangdong–Hong Kong–Macao Greater Bay Area Based on a Cellular Automata–Markov Model

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA.

The spatiotemporal changes and trade-off synergistic effects of ecosystem services in the Jianghan Plain of China under different scenarios

Disturbance from human activities has intensified the evolution of ecosystem structure in the Jianghan Plain of China, leading to intensified conflicts between ecosystem services. It is essential to clarify the trade-off synergies between ecosystem services in the Jianghan Plain of China to better coordinate the economic and social development and ecological protection of the region. Based on historical data and scenario predictions using the GeoSOS-FLUS model, the InVEST model was applied to five key ecosystem services: Carbon storage, crop production, habitat quality, soil conservation and water yield from 2000 to 2020. Spearman correlation analysis was used to explore the trade-off synergies between different ecosystem services in space and time. The results showed that arable land and water land areas are the most important land types in the Jianghan Plain of China. From 2000 to 2020, the increase in build-up land and water land areas was accompanied by a decrease in arable land, forest land and unused land, and an increase in forest land. The natural development scenario in 2035 continues this trend except forest land reduction, while the ecological protection scenario reverses this trend. From 2000 to 2020, crop production, water yield, and soil conservation increased in the Jianghan Plain of China, while carbon storage and habitat quality declined significantly, showing a spatial distribution pattern of higher in the northwest and lower in the southeast. The comprehensive ecosystem services simulated in 2035 showed a downward trend compared with 2020, and the ecological protection scenario has the smallest decrease. There is an overall synergistic relationship between the five ecosystem services in the Jianghan Plain of China, and the strongest synergistic relationship is between soil conservation and water yield. The spatiotemporal relationship between the ecosystems in the Jianghan Plain of China is dynamic and requires sustainable management. Thus, it is necessary to rationally utilize land resources and enhance the ecological functions of the area to minimize trade-offs based on scientific land and spatial planning to maximize synergy.

ENVINet5 deep learning change detection framework for the estimation of agriculture variations during 2012-2023 with Landsat series data.

Remote sensing is one of the most important methods for analysing the multitemporal changes over a certain period. As a cost-effective way, remote sensing allows the long-term analysis of agricultural land by collecting satellite imagery from different satellite missions. Landsat is one of the longest-running world missions which offers a moderate-resolution earth observation dataset. Land surface mapping and monitoring are generally performed by incorporating classification and change detection models. In this work, a deep learning-based change detection (DCD) algorithm has been proposed to detect long-term agricultural changes using the Landsat series datasets (i.e., Landsat-7, Landsat-8, and Landsat-9) during the period 2012 to 2023. The proposed algorithm extracts the features from satellite data according to their spectral and geographic characteristics and identifies seasonal variability. The DCD integrates the deep learning-based (Environment for visualizing images) ENVI Net-5 classification model and posterior probability-based post-classification comparison-based change detection model (PCD). The DCD is capable of providing seasonal variations accurately with distinct Landsat series dataset and promises to use higher resolution dataset with accurate results. The experimental result concludes that vegetation has decreased from 2012 to 2023, while build-up land has increased up to 88.22% (2012-2023) for Landsat-7 and Landsat-8 datasets. On the other side, degraded area includes water (3.20-0.05%) and fallow land (1-0.59%). This study allows the identification of crop growth, crop yield prediction, precision farming, and crop mapping.

Electrification policy impacts on land system in British Columbia, Canada

British Columbia (BC) is committed to transitioning to a low-carbon energy system to meet its CO2 emission reduction targets, but this shift towards renewable energy sources may have significant implications for land use. This paper investigates the land-use impacts of different electrification pathways and technology choices in BC's energy system using the BC Nexus model. Our analysis highlights the potential increase in land-use requirements associated with transitioning from fossil fuels to renewable energy sources, with the occupied land of the power system potentially increasing up to six times larger than the current total build-up land (depending on the scale of electrification and technology choice). These findings have important implications for policymakers in terms of balancing the trade-offs between energy security, economic development, and environmental sustainability. By understanding the physical footprint of the energy transition, decision-makers can develop more effective climate policies and sustainable development strategies.

Development, validation, and application of a microbial community-based index of biotic integrity for assessing the ecological status of a peri-urban watershed in China

This study represents the pioneering effort in employing 16S rRNA-bacteria and 18S rRNA-microeukaryotes to construct the microbial community-based index of biotic integrity (MC-IBI) for assessing the ecological health of riverine ecosystems. The MC-IBI was developed, validated, and implemented using water samples from the Changle River watershed, encompassing both wet and dry seasons. A total of 205 metrics, containing microbial diversity, composition, pollution tolerance/sensitivity, and functional categories, were selected as candidates for evaluation. Following a rigorous screening process, five core metrics were identified as key indicators, namely Pielou's evenness of microeukaryotes, %Cryptophyceae, %Proteobacteria, %Oxyphotobacteria, and % 16S rRNA gene-human pathogens. Moreover, redundancy analysis revealed three metrics (i.e., Pielou's evenness, % 16S rRNA gene-human pathogens, and % Proteobacteria) were positively correlated with impairment conditions. In contrast, two metrics (i.e., %Oxyphotobacteria and %Cryptophyceae) were associated positively with reference conditions. Notably, the developed MC-IBI demonstrates clear discrimination between reference and impaired sites and significantly correlates with environmental parameters and land use patterns. A path model analysis revealed that land use patterns (i.e., build-up land, cropland) negatively impacted the MC-IBI scores. The application of the MC-IBI method yielded an assessment of the ecological conditions at the 73 sampling locations within the Changle River watershed, assigning them into categories of “Very good” (4.1 %), “Good” (4.1 %), “Moderate” (5.5 %), “Poor” (21.9 %), and “Very poor” (64.4 %). This bioassessment framework presents an innovative approach toward the preservation, maintenance, and management of riverine ecosystems.

Multi-scenario dynamic prediction of ecological risk assessment in an arid area of northwest China

Ecological security is essential for the development of environmental health and human society. However, the driving mechanisms and spatial non-stationarity of ecological risks are still unknown, particularly in arid areas. Thus, this study constructed an ecological risk index (ERI) research framework in arid areas based on land use and socio-economic data from 1980 to 2020 to investigate the spatiotemporal evolution trend, driving mechanisms, and spatial non-stationarity of ecological risk and predict the ecological risk under business-as-usual, economic development, and ecological protection scenarios using a patch-generating land use simulation (PLUS) model. The results show that: (1) cropland and build-up land were expanding, whereas forestland and grassland water bodies were shrinking. Compared with the two development stages from 1980 to 2000 and from 2000 to 2020, cropland increased by 4.73% and 51.52%, respectively, whereas build-up land increased by 12.64% and 106.52%, respectively, indicating rapid development and drastic changes in the past 20 years. (2) With the change in landscape diversity, the regional ecological risks showed an increasing trend, whereas the future ecological risks showed an increasing trend because of the cumulative effect of landscape pattern changes caused by human activities. (3) Moreover, dramatic changes in ecological risk, particularly in areas of intense human activity in build-up land, agricultural land, artificial oases, and mountainous areas. Corresponding to the analysis of driving mechanisms, population, GDP, distance to government, water, and primary roads; have a significant effect on ecological risk, whereas DEM has direct and indirect effect paths. Ultimately, the proposed analysis framework can present the spatiotemporal changes of ecological risks and their influencing mechanisms, which can help develop sustainable development policies.

A Comparative Study on Land Use/Land Cover Change and Topographic Gradient Effect between Mountains and Flatlands of Southwest China

Topography plays an important role in restricting the formation of and change in land use/land cover (LULC) patterns. To compare the LULC change and topographic gradient effects between mountains and flatlands, the geo-informatic atlas, terrain position index, distribution index and diversity index were used to analyze the LULC patterns in Yuxi from 2000 to 2020. The results were as follows: (1) the temporal–spatial variation in LULC was obviously different. From 2000 to 2020, land use change in the flatlands was more severe than that in the mountains. The transfer amount of forestland in the mountains was the largest, with the transfer-out and transfer-in accounting for 48.53% and 31.05%. However, in the flatlands, the biggest changes were found in the transfer-out of cultivated land and the transfer-in of build-up land, which were 46.91% and 38.20%, respectively. The LULC types in the mountains changed dramatically from 2000 to 2010, while those in the flatlands changed dramatically from 2010 to 2020. (2) There were obvious differences in the topographic gradient effects. The dominant distributions of land use types in the low-terrain area were the same, but the dominance of build-up land in the flatlands and that of wetland in the mountains were the largest. In the mountains, the dominant distribution of grassland was in the medium-terrain position, while that of forestland was in the high position, and the opposite was found in the flatlands. In addition, the variation trend of the diversity index in the mountains was relatively simple, but the variation range was large, ranging from 0 to 1.677, and high diversity was mainly found in the medium- and high-terrain positions. However, the variation trend in the flatlands was complex, but only ranged from 0.918 to 1.994, and high diversity was found in the low-terrain positions. The differences in the LULC change and terrain gradient effects between the mountains and flatlands were mainly caused by natural, socio-economic and policy factors, which can provide a certain reference for differentiated land use policies for regional coordinated and sustainable development.

Land capability and carrying capacity analysis against land use change in the Motaain Border Region (Indonesia-Timor Leste)

Changes in land use in the border regions of the Motaain state (Indonesia-Timor Leste) are caused by population growth and a variety of activities of the population. Thus, changes in land use that are not controlled affect the ability and carrying capacity of the land. Moreover, the research objective is to assess the characteristics of the region from the physical aspects of the environment to spatial changes, as a reference for controlling spatial use. The analytical methods are used population density and activity density (Kernel density); analysis of activity patterns (cluster and outlier analysis and spatial auto-correlation Moran’s I); class analysis of land capability and carrying capacity (overlay); and quantitative statistical quantitative analysis. The results of the analysis explain that from the year 2013 until 2017 the border area of the Motaain state experienced population growth and activities, these affected spatial patterns that change in land use from non-developed land to build-up land. It is also explained that overlay analysis results are more dominant land capability classes are very low as well as the carrying capacity to land that is predominantly a potential and protected development area. The difference in capability and carrying capacity to land is a product of social activities that cannot be controlled.

Identification of priority conservation areas based on ecosystem services and systematic conservation planning analysis.

In order to reverse the trend of ecological deterioration and resolve the conflict between ecological conservation and economic development, it is necessary to evaluate the trends of ecosystem services (ESs) and unravel the relationship between ESs and environmental drivers and identify the priority areas for ESs. In this research, we used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to quantify the variation of four important ESs (water purification, water yield, soil conservation, and habitat quality) in the Dongting Lake Basin from 2000 to 2015. During the past 15years, water yield was declined by 3.38% and soil conservation was increased by 1.45%. Water quality purification was deteriorated with the rise in phosphorus export (5.32%) and nitrogen export (4.09%). Meanwhile, habitat quality was decreased by 3.27%. Trade-offs occurred primarily among water yield and other ESs. Social-ecological drivers importance analysis found that water yield was primarily influenced by precipitation and temperature. By contrast, water purification and habitat quality were more affected by the distribution of land use and land cover (LULC). Soil conservation was closely related to precipitation and geographical factor. Based on the distribution of ESs and the intensity of human activities, we delineated priority areas for each ESs using the systematic conservation planning tool (Marxan). LULC shifted most dramatically in water yield reserves (6.49%) with a large amount of lands conversed to cropland (4.4%) and build-up land (0.27%), which further increased the risk of water scarcity, while LULC changed less in other ESs priority areas due to human activities. Our study helps develop conservation strategies within specific area cost-effectively and provides scientific support for future conservation program of ESs formulation and adjustment.

Terrain gradient response of landscape ecological environment to land use and land cover change in the hilly watershed in South China

There are abundant resources like climate, water, biological and tourism in the middle and upper reaches of the Ganjiang River (MU-GJR), which is an important ecological protection area in hilly areas of South China. The four periods of land use and land cover (LULC) data from 1980 to 2018 and DEM data are the main data support. The LULC change were analyzed with the area proportion, transfers chord diagram and change characteristics map, the response of ecological environment from LULC change was analyzed by using the landscape ecological environment quality (LEEQ) and contribution index. Then the terrain gradient was used to analyze the impact of LULC transfer on ecological environment under different terrain conditions. (1) The LULC characteristics in the study area show that was dominated by forest land and cultivated land (more than 90 %), various types of land transfer significantly from 2010 to 2018, especially the cultivated land, forest land and grassland. The stable type of LULC change was the most widely distributed, followed by the later change type (2010–2018) and mainly distributed in the flat valley, with the largest change range of cultivated land, forest land and grassland. (2) The LEEQ was generally well, but gradually deteriorates. The obvious change of LEEQ was found after 2010. The deterioration type of quality mostly occurs around the city, while the getting better type occurs in the transition area between the city and the mountains. (3) There are more deterioration categories than improvement categories of LULC transfer from 1980 to 2018. The improvement categories were mainly contributed by the transfer to other land to forest land and build-up land to other land. The deterioration categories were mainly contributed by the transfer of forest land to other land. (4) The impact of LULC change on the ecological environment decreases with the increase of elevation, slope and terrain position. There are differences in the impacts of various types of transfer on the ecological environment under the three gradients. In the elevation gradient, the improvement effect were dominant at −105–100 m and 200–500 m, and the deterioration effect were dominant at 100–200 m, 500–1000 m and 1000–2128 m. In the slope gradient, the improvement effect were dominant at 0–2°, 15–25° and 25–69.7°, and the deterioration effect were dominant at 2–6° and 6–15°. In terrain position gradient, improvement effect were dominant at 0–0.32, 0.32–0.51, 0.7–0.9 and 0.9–1.58, and deterioration effect were dominant at 0.51–0.7. Therefore, the specific conditions of different terrain gradients should be considered for land resource development in the middle and upper reaches of Ganjiang River region.

Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed

Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.

Urban land use change simulation and spatial responses of ecosystem service value under multiple scenarios: A case study of Wuhan, China

Simulation of changes in ecosystem service value (ESV) caused by land use change in Wuhan under multiple scenarios is of great significance for ensuring urban ecological security and enhancing regional ecosystem service values. The city of Wuhan was selected as the study area, and the changes in land use and ESV in Wuhan over the past 31 years were analyzed and calculated based on five-phase remote sensing images and statistical yearbooks for 1990, 1998, 2006, 2014 and 2021. On this basis, the CA-Markov model and the multi objective planning (MOP) model were used to simulate the land use change in the study area in 2040 under four scenarios (natural development scenario, cultivated land protection scenario, ecological protection scenario and urban development scenario), and the total ESV was estimated under each scenario. The total value of ecosystem services was estimated under each scenario, and grid tools were applied to visualize the spatial distribution and degree of aggregation of ecosystem services. The results show that: (1) The most obvious feature of land use change in Wuhan from 1990 to 2021 is the sharp reduction in arable land area and the rapid expansion of build-up land area. Over the past 31 years, the arable land area decreased by 78322.4 hm2, and the build-up land area increased by 52559.28 hm2. (2) From 1990 to 2021, Wuhan’s total ESV at the five timepoints (1990, 1998, 2006, 2014, 2021) was 74.554 billion yuan, 71.512 billion yuan, 69.632 billion yuan, 73.433 billion yuan and 68.548 billion yuan, respectively. Overall, there has been a downward trend in volatility. (3) Under the four scenarios, the ESV in 2040 is projected to be 72.777 billion yuan, 70.969 billion yuan, 74.097 billion yuan or 70.620 billion yuan, respectively. Among them, the ecological protection scenario is the optimal simulation choice. (4) The cold and hot spots of ESV show an aggregated distribution over a large area, with the hot spots mainly concentrated in the central and southeastern parts of Wuhan and the cold spots mainly located in the northeastern and northwestern portions of Wuhan. Simulating the future land use change trends in Wuhan and exploring the responses of ecosystem service values under various scenarios are conducive to the construction of a new pattern of urban land space development and protection and can provide a scientific basis and a reference for decision-making for comprehensively promoting the sustainable development of Wuhan and other metropolitan areas in China in the future.

Contradiction or coordination? The spatiotemporal relationship between landscape ecological risks and urbanization from coupling perspectives in China

Rapid urbanization in developing countries has been shown to have higher intensities of development and more frequent human-ecosystem interactions. Urbanization in China is highly representative of such development, and given its magnitude, poses severe risks if not irreversible consequences to the sustainability of natural ecosystem. The UN Sustainable Development Goals (SDGs) has highlighted the necessity for humanity to live in harmony with ecosystems for achieving a sustainable state. Evaluating the coupling states between urbanization and ecological risks and identifying the distribution of coordinated and unbalanced types are two crucial steps for ensuring sustainability. To date, nonetheless, there is a scarcity of macro and overall assessment of ecological risk for the whole China at a finer resolution. This study combined landscape pattern indices to better reveal the state of landscape ecological risk (LER) at a grid scale of 10km × 10km in 1990–2015 for entire China. Considering the geographical differences, this study further evaluated how the urbanization factors of population density (PD), GDP density (GDPD), build-up land proportion (BLP), comprehensive urbanization level (CUL) led to major LER changes in different regions, using a geographical detector model (GDM). Finally, the coupling coordination degree (CCD) between LER and its dominated urbanization factors of different regions was investigated. The results show that the urbanization intensified the LER, and risk hot-spots were mostly distributed in the southeast of China dominated with high levels of urbanization. In addition, LER hot-spots were more concentrated in aquatic, cultivated land and build-up land. The major urbanization factors affecting China's LER included PD, BLP and CUL. More important, the CCD level between three urbanization factors and LER improved with time, but most parts of China remained in an unbalanced development state. Through the identified regional differences of coupling coordination types, the degree of contradiction between local urbanization and LER can be known, so as to harmonize the environment and humanity.

Mixed spatial scale effects of landscape structure on water quality in the Yellow River

Scientific understanding of the scale effects of landscape structure on water quality is essential for national land planning and water environment management. However, there is no consensus on the optimal spatial landscape scale affecting water quality. To this end, we developed a novel mix scale division method, which is consist of the intersection of sub-basin, stream buffer zone and circular buffer zone. Based on the water quality data from 113 monitoring stations of the Yellow River Basin, we quantitatively identified the spatial scale effects of various landscape indexes on water quality, as well as the nonlinear response of the water quality along the gradient of landscape indicators in the Yellow River, by using the Redundancy analysis (RDA) and Generalized Additive Model (GAM). We show that landscape indexes related to buildup and agricultural lands had significant impact on water quality changes, and this impact was more influential during the rainy season compared with the dry season. We also identified that the optimal scale and landscape pattern corresponding to the main non-point source factors, i.e., CODCr, total nitrogen (TN), and total phosphorus (TP). The variations of these three water quality indicators were predominated by buildup land (B-CA) at sub-basin (with a contribution percentage of 43.7%), agricultural land (A-CA) at the scale of stream buffer (bs) = 1000 m and circular buffer (bc) = 20 km (50.2%), and the largest patch index of agriculture (A-LPI) at the scale of bs = 1000m and bc = 25 km (41.7%), respectively. The B-CA>50000 ha at the sub-basin scale and A-LP = 50% at the mixed scale (bs = 1000m, bc = 25 km) would accelerate the deterioration of water quality. Results implied that water quality could be improved by implementing landscape regulation within an appropriate scale and considering the non-linear effects of landscape structure on water quality.

Water quality assessment and the influence of landscape metrics at multiple scales in Poyang Lake basin

Stream water quality has been increasingly deteriorated in recent decades because of anthropogenic activities. Assessing water quality via key environmental parameters and quantifying the respective influence of landscape metrics like landscape configuration, land use composition and topography, which can overall represent anthropogenic activities, can facilitate the development of improved water quality management strategies. However, few studies concentrate on the quantitative effect of these landscape metrics groups on the change of key water quality parameters. In this study, with Poyang Lake basin, we selected key factors of the 14 environmental variables for the cost-effective water quality evaluation model of the minimum water quality index (WQImin) by the random forest method and quantified the contribution of different groups of landscape metrics on key water quality parameters by redundancy analysis and variance partitioning analysis. The results indicated that six water quality parameters of ammonium (NH4+-N), total nitrogen (TN), permanganate index (CODMn), dissolved oxygen (DO), fecal coliforms (F.coli) and total phosphorus (TP) can significantly represent the overall water quality of the Poyang Lake basin. Based on WQImin, the water quality of Fuhe River and Xiushui River was significantly better than that of Ganjiang River, Raohe River, and Xinjiang River in Poyang Lake basin. The contribution of landscape metrics to water quality variation followed the order of landscape configuration (19.0–22.5%) > land use composition (5.2–20.2%) > topography (5.7–8.0%). Here, Build-up land was the environmental factor contributing most significantly to the variation in water quality at both spatial and seasonal scales (5.7–21%). Build-up land, Agricultural land, Contagion index and Cohesion index were positively correlated with TN, TP, CODMn, and NH4+-N and negatively with DO at different scales; Grassland, Forest land, Hypsometric Integral index, Slope, and Mean Shape index showed the opposite relationship. The influence of these landscape types changed with spatial and seasonal scales, more significantly explaining variations in water quality during the dry season and at buffer scale. Changes in water quality at the spatial scale were most sensitive to land use composition. Our results represent a basis for the improvement of water quality management.

GIS STUDY ON THE GREEN SPACES OF THE CITY OF BRAȘOV, ROMANIA

Abstract. Urban sprawl is often the result of the transformation of the vegetation – covered land into build-up land. This expansion is caused by economic development, population growth and changing in living standards. For the progress of a city, a vision is needed in what will be achieved and methods by which this will be made possible. Due to the development of the city, the increase of the population number and other external factors, a study was needed to determine the area of the existing green spaces in the city of Brașov, Romania, in relation with the population number. Brașov is the most representative city, located in the Center of Romania, for economic and structure change. To analyze the green areas, were used remote sensing data from 2017 and 2021. Sentinel-2A images provided the support to analyze the land cover and the changes. The images were classified using ArcGIS Pro. This process gave a better understanding of the changes that took place in Brașov. The results indicated that the green areas almost doubled from 2017 to 2021. As a result of this growth, the citizens benefit due to the spaces created for recreation and outdoor activities.

Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning

China’s urbanization has dramatically accelerated in recent decades. Land for urban build-up has changed not only in large cities but also in small counties. Land cover mapping is one of the fundamental tasks in the field of remote sensing and has received great attention. However, most current mapping requires a significant manual effort for labeling or classification. It is of great practical value to use the existing low-resolution label data for the classification of higher resolution images. In this regard, this work proposes a method based on noise-label learning for fine-grained mapping of urban build-up land in a county in central China. Specifically, this work produces a build-up land map with a resolution of 10 m based on a land cover map with a resolution of 30 m. Experimental results show that the accuracy of the results is improved by 5.5% compared with that of the baseline method. This notion indicates that the time required to produce a fine land cover map can be significantly reduced using existing coarse-grained data.