Performance Evaluation of the SLEUTH Model in the Shenyang Metropolitan Area of Northeastern China

Abstract Performance evaluation is crucial for the development and improvement of an urban cellular automata model, such as SLEUTH. In this paper, we employed multiple methods for map comparison and model validation to evaluate the simulation performance of the SLEUTH urban growth model in the Shenyang metropolitan area of China. These multiple methods included the relative operating characteristic (ROC) curve statistic, multiple-resolutions error budget, and landscape metrics. They were used to quantitatively examine model performance in terms of the amount and spatial location of urban development, urban spatial pattern and prediction ability. The assessment results showed that SLEUTH performed well in the way of the quantitative simulation of urban growth for this case study. Similar to other urban growth models, however, the simulation accuracy for spatial location of new development at the pixel scale and urban spatial pattern still needs to be improved greatly. These inaccuracies might be attributed to the structure and nature of SLEUTH, local urban development characteristics, and the temporal and spatial scale of its application. Finally, many valuable suggestions had been put forward to improve simulation performance of SLEUTH model for spatial location of urban development in the Shenyang metropolitan area

Spatiotemporal Variations in Satellite-Derived Vegetation Phenological Parameters in Northeast China

Vegetation phenology does not only serve as a key index of terrestrial ecosystem response to worldwide climate change but also has a major influence on plant productivity and the carbon cycle. In the current research, the change of vegetation phenological parameters was studied and the impact exerted by climate change on phenological phases in northeast China for 1982–2014 was explored using the latest edition of the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS NDVI3g) dataset. The results showed that the start of the growing season (SOS) slightly advanced, the end of the growing season (EOS) showed a significant delay, and the length of the growing season (LOS) exhibited a significant prolonging at the regional scale. At the different vegetation types scale, there existed diverse responses of vegetation phenological phases to climate change for forest, grassland, and cultivated land. Significant decreasing trends in the SOS occupied 19.1% of the entire research area, whereas pixels with significantly increasing trends in the SOS accounted for 13.1%. The EOS was delayed in most of the study region (approximately 72.1%). As the result of the variations of SOS and EOS, the LOS was obviously enhanced (p < 0.05) in 29.7% of the research area. According to the correlation of vegetation phenology with climate factors, the SOS had a significant negative relationship with the average temperature in springtime, while the EOS was notably negatively connected to summer total precipitation at the regional scale. At the pixel scale, the correlation of phenological parameters with climate variables showed strong spatial heterogeneities. This study contributes to the comprehension of the responses of vegetation phenology to climate change

Change of impervious surface area and its impacts on urban landscape: an example of Shenyang between 2010 and 2017

Introduction One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area (ISA). However, the extent of the contribution of various environmental factors, especially the growth of 3D space to ISA expansion, and the scope and mechanism of their influences in dramatically expanding cities, are yet to be determined. The boosted regression tree (BRT) model was adopted to analyze the main influencing factors and driving mechanisms of ISA change in Shenyang, China between 2010 and 2017. Outcomes The nearly complete-coverage ISA (≥0.7) increased from 42% in 2010 to 47% in 2017. The percentage of landscape with a high ISA fraction increased, while the landscape evenness and diversity of ISA decreased. The BRT analysis revealed that elevation, regional population density, and landscape class had the largest influences on the change of urban ISA, contributing 22.55%, 18.16%, and 11.18% to the model, respectively. Conclusion Overall, topographic and socioeconomic factors had the greatest influence on urban ISA change in Shenyang, followed by land use type and building pattern indices. The trend of high aggregation was strong in large commercial and residential areas. The 3D expansion of the city had an influence on its areal expansion

Ecological and Environmental Effects of Estuarine Wetland Loss Using Keyhole and Landsat Data in Liao River Delta, China

An estuarine wetland is an area of high ecological productivity and biodiversity, and it is also an anthropic activity hotspot area, which is of concern. The wetlands in estuarine areas have suffered declines, which have had remarkable ecological impacts. The land use changes, especially wetland loss, were studied based on Keyhole and Landsat images in the Liao River delta from 1962 to 2016. The dynamics of the ecosystem service values (ESVs), suitable habitat for birds, and soil heavy metal potential ecological risk were chosen to estimate the ecological effects with the benefit transfer method, synthetic overlaying method, and potential ecological risk index (RI) method, respectively. The driving factors of land use change and ecological effects were analyzed with redundancy analysis (RDA). The results showed that the built-up area increased from 95.98 km2 in 1962 to 591.49 km2 in 2016, and this large change was followed by changes in paddy fields (1351.30 to 1522.39 km2) and dry farmland (189.5 to 294.14 km2). The area of wetlands declined from 1823.16 km2 in 1962 to 1153.52 km2 in 2016, and this change was followed by a decrease in the water area (546.2 to 428.96 km2). The land use change was characterized by increasing built-up (516.25%), paddy fields (12.66%) and dry farmland (55.22%) areas and a decline in the wetland (36.73%) and water areas (21.47%) from 1962–2016. Wetlands decreased by 669.64 km2. The ESV values declined from 6.24 billion US$to 4.46 billion US$ from 1962 to 2016, which means the ESVs were reduced by 19.26% due to wetlands being cultivated and the urbanization process. The area of suitable habitat for birds decreased by 1449.49 km2, or 61.42% of the total area available in 1962. Cd was the primary soil heavy metal pollutant based on its concentration, accumulation, and potential ecological risk contribution. The RDA showed that the driving factors of comprehensive ecological effects include wetland area, Cd and Cr concentration, river and oil well distributions. This study provides a comprehensive approach for estuarine wetland cultivation and scientific support for wetland conservation

Data in support of environmental controls on the characteristics of mean number of forest fires and mean forest area burned (1987–2007) in China

Fire frequency and size are two important parameters describing fire characteristics. Exploring the spatial variation of fire characteristics and understanding the environmental controls are indispensable to fire prediction and sustainable forest landscape management. To illustrate the spatial variation of forest fire characteristics over China and to quantitatively determine the relative contribution of each of the environmental controls to this variation, forest fire characteristic data (mean number of forest fires and mean burned forest area) and environmental data (climate, land use, vegetation type and topography) at provincial level were derived. These data sets can potentially serve as a foundation for future studies relating to fire risk assessment, carbon emission by forest fires, and the impact of climate change on fire characteristics. This data article contains data related to the research article entitled “Environmental controls on the characteristics of mean number of forest fires and mean forest area burned (1987–2007) in China” by chang et al. [1]

Evolutions of 30-Year Spatio-Temporal Distribution and Influencing Factors of Suaeda salsa in Bohai Bay, China

Suaeda salsa (L.) Pall. (S. salsa) acts as a pioneer species in coastal wetlands due to its high salt tolerance. It has significant biodiversity maintenance, socioeconomic values (e.g., tourism) due to its vibrant color, and carbon sequestration (blue carbon). Bohai Bay region, the mainly distributed area of S. salsa, is an economic intensive region with the largest economic aggregate and population in northern China. The coastal wetland is one of the most vulnerable ecosystems with the urbanization and economic developments. S. salsa in Bohai Bay has been changed significantly due to several threats to its habitat in past decades. In this paper, we analyzed all available archived Landsat TM/ETM+/OLI images of the Bohai Bay region by using a decision tree algorithm method based on the Google Earth Engine (GEE) platform to generate annual maps of S. salsa from 1990 to 2020 at a 30-m spatial resolution. The temporal-spatial dynamic changes in S. salsa were studied by landscape metric analysis. The influencing factors of S. salsa changes were analyzed based on principal component analysis (PCA) and a logistic regression model (LRM). The results showed that S. salsa was mainly distributed in three regions: the Liao River Delta (Liaoning Province), Yellow River Delta (Shandong Province), and Hai River Estuary (Hebei Province, Tianjin). During the past 31 years, the total area of S. salsa has dramatically decreased from 692.93 km2 to 51.04 km2, which means that 92.63% of the area of S. salsa in the Bohai Bay region was lost. In the 641.89 km2 area of S. salsa that was lost, 348.80 km2 of this area was converted to other anthropic land use categories, while 293.09 km2 was degraded to bare land. The landscape fragmentation of S. salsa has gradually intensified since 1990. National Nature Reserves have played an important role in the restoration of suitable S. salsa habitats. The analysis results for the natural influencing factors indicated that precipitation, temperature, elevation, and distance to the coastline were considered to be the major influencing factors for S. salsa changes. The results are valuable for monitoring the dynamic changes of S. salsa and can be used as effective factors for the restoration of S. salsa in coastal wetlands

Analysis of Three-Dimensional Space Expansion Characteristics in Old Industrial Area Renewal Using GIS and Barista: A Case Study of Tiexi District, Shenyang, China

With rapid urban development in China in the last two decades, 3D characteristics have been the main feature of urban morphology. Nevertheless, the vast majority of urban growth research has only focused on area expansion horizontally, with few studies conducted in a 3D perspective. In this paper, the characteristics of 3D expansion that occurred in Tiexi from 1997 to 2011 were evaluated based on geographic information system (GIS) tools, remote-sensing images, and Barista software. Landscape index, the spatiotemporal distribution of changes in buildings’ renewal modes and variations in city skylines as well as the relationship between number and size of high-rise buildings are the specific phenomena and data utilized to quantify the 3D urban expansion. The results showed that the average height of Tiexi increased by 0.69 m annually, the average urban capacity increased by 490.15 m3 annually, and space congestion degree increased by 0.11% annually. The average annual increase of the building evenness index was 36.43. The renewal area occupied up to 75.38% of the total area. The change of the skyline was more consistent with the east–west direction. The change in the south direction was significant, while in the north direction it was relatively slow. The overall shape of the city was that of a weak pyramid, with the angle of the top of the pyramid gradually becoming larger. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes

Evolutions of 30-Year Spatio-Temporal Distribution and Influencing Factors of <i>Suaeda salsa</i> in Bohai Bay, China

Suaeda salsa (L.) Pall. (S. salsa) acts as a pioneer species in coastal wetlands due to its high salt tolerance. It has significant biodiversity maintenance, socioeconomic values (e.g., tourism) due to its vibrant color, and carbon sequestration (blue carbon). Bohai Bay region, the mainly distributed area of S. salsa, is an economic intensive region with the largest economic aggregate and population in northern China. The coastal wetland is one of the most vulnerable ecosystems with the urbanization and economic developments. S. salsa in Bohai Bay has been changed significantly due to several threats to its habitat in past decades. In this paper, we analyzed all available archived Landsat TM/ETM+/OLI images of the Bohai Bay region by using a decision tree algorithm method based on the Google Earth Engine (GEE) platform to generate annual maps of S. salsa from 1990 to 2020 at a 30-m spatial resolution. The temporal-spatial dynamic changes in S. salsa were studied by landscape metric analysis. The influencing factors of S. salsa changes were analyzed based on principal component analysis (PCA) and a logistic regression model (LRM). The results showed that S. salsa was mainly distributed in three regions: the Liao River Delta (Liaoning Province), Yellow River Delta (Shandong Province), and Hai River Estuary (Hebei Province, Tianjin). During the past 31 years, the total area of S. salsa has dramatically decreased from 692.93 km2 to 51.04 km2, which means that 92.63% of the area of S. salsa in the Bohai Bay region was lost. In the 641.89 km2 area of S. salsa that was lost, 348.80 km2 of this area was converted to other anthropic land use categories, while 293.09 km2 was degraded to bare land. The landscape fragmentation of S. salsa has gradually intensified since 1990. National Nature Reserves have played an important role in the restoration of suitable S. salsa habitats. The analysis results for the natural influencing factors indicated that precipitation, temperature, elevation, and distance to the coastline were considered to be the major influencing factors for S. salsa changes. The results are valuable for monitoring the dynamic changes of S. salsa and can be used as effective factors for the restoration of S. salsa in coastal wetlands

Impacts of Changing Forest Management Areas on Forest Landscapes and Habitat Patterns in Northeastern China

The management of multi-use forests often drives forest fragmentation, which leads to decreased habitat areas and quality. We explored suitable habitat distributions of cervids to evaluate the conflict between small-scale human management and large-scale habitat conservation in human-disturbed forest landscapes. We estimated the potential habitat of roe deer (Capreolus pygargus) and determined the contribution of multiple environmental factors to habitat distribution using the presence of roe deer (N = 106) in a maximum entropy (MaxEnt) model. We simulated changes in the suitable habitat and characteristics of landscape patterns based on three forest management area scenarios. The results showed that the potential suitable habitat for roe deer was located mainly in the east. The variables affecting habitat suitability were similar in different scenarios, and included distance to farmland, settlements, rivers and management areas, and elevation. Distance to the management area was found to affect habitat suitability with a contribution probability from 4% to 6%. With an increase in the management area, the suitable habitat decreased. Landscape indexes showed that habitat quality decreased with management area expansion, but patch fragmentation was not aggravated. The expansion of the management area increased the range of human disturbance and had a negative impact on habitat area and quality, which adversely affected the environmental suitability for roe deer