Analysis Of Spatio-temporal Changes Research Articles

Multi-scale population analysis unit construction method considering scene feature variability and long/short-term patterns in spatiotemporal population activities

ABSTRACT Differences in the spatial scale and component elements of urban scenes affect the analysis of spatiotemporal changes in population distribution (PD) patterns. Fixed scales and geometric forms constrained previous analyses of PD and spatiotemporal changes, which neglected the realistic characteristics of urban scenarios. These limitations hinder the ability to capture the diversity and spatiotemporal representation of PD patterns across multiple spatial scales. This study developed a multi-spatial scale population analysis unit (PAU) construction method considering the scenario heterogeneity and long/short-term patterns of spatiotemporal population changes (PC). Initially, we decompose the multi-scale changes in population time series patterns and their relationships with scene features along the temporal dimension to analyze the primary and secondary factors. Starting from the temporal characteristics of the PD and PC, we established a validation and correction method for the factors. Finally, combined with a multi-feature clustering method, a multi-scale PAU construction method driven by scene feature factors is proposed. Experiments were conducted at different spatial scales in both routine and emergent scenarios. The results indicated that this method can help to obtain more homogeneous analysis regions and enhance the stability and phase pattern representations of changes in PDs, thereby improving the interpretability of analytical results.

Analysis of spatio-temporal changes in net primary productivity and their driving factors in ecological functional areas of the Yellow River Basin

The Yellow River Basin (YRB) is an important region for both ecological and economic growth in China, and a healthy and stable ecological environment is fundamental to achieving high-quality development. Investigating the spatio-temporal changs of vegetation carbon sinks in the YRB is necessary to improve understanding of the regional carbon cycle. This study analyzed the YRB using the Google Earth Engine (GEE) platform. The basin was divided into sections based on ecological function regionalization schemes. We applied Theil-Sen median trend analysis and Spearman correlation analysis, along with the lasso regression model, to examine the NPP's temporal and spatial patterns and its driving factors in these regions. The objective was to examine the NPP’ s temporal and spatial patterns and its driving factors in these regions, identifying commonalities within regions and differences between regions, while analyzing in a targeted manner the lack of vegetation carbon sequestration in ecological areas. This study highlighted the importance of ecological engineering in ecological civilization and carbon neutrality, providing scientific theoretical support and a decision-making basis for the realization of carbon neutrality. The research results indicate significant upward trends (p<0.001) in both the average annual NPP (AANPP) growth rate (57.98%) and the total annual NPP (TANPP) growth rate (41.9%) in the YRB from 2001 to 2020. The multi-year average NPP (MYANPP) exhibit a spatial distribution with high values in the south and low values in the north. The spatial distribution of NPP exhibits notable spatial aggregation and heterogeneity, where regions demonstrating improvement trends constitute 93.01% of the area, and approximately 79.73% of this region displays low volatility. A high-value area is concentrated in the Agroecological Zone of the Fenwei Basin (I-11), the Loess Plateau Agriculture and Grassland Ecological Zone (I-12), and the Qinba Mountains Deciduous and Evergreen Broad-leaved Forest Ecological Zone (I-15), with significant spatial differences. Temperature, precipitation, and forests are the foremost elements affecting NPP in the YRB, exhibiting positive correlations. Conversely, farmland displays negative correlations. Overall, NPP shows an increasing trend in all ecological function areas, and the NPP of the YRB shows a trend of improvement as a whole, as the ecological environment of the YRB has improved significantly.

SDG- and GMAG-oriented analysis of multi scenarios spatiotemporal changes and evaluation of the effectiveness and potential of mangrove forests

ABSTRACT It is crucial to mangrove management by understanding its conservation efforts. This study proposed a spatiotemporal analysis model to evaluate mangrove changes in the Guangxi Beibu Gulf (GBG) and the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), focusing on past, present, and future dynamics. The analysis covered mangrove loss, stability, and gain from 1990 to 2020 and provided projections for 2020 to 2035 across multiple scenarios. Then further assessed the efficacy of past mangrove conservation with the Sustainable Development Goals (SDGs) and the prospective conservation potential with the Global Mangrove Alliance Goal (GMAG) indicators. Findings indicate that by 2020, the GBG and GBA had 81.65 km² and 40.92 km² of mangroves, respectively, with increases of 31.51% and 164.09% since 1990. Projected expansions are anticipated under all three scenarios during 2020- 2035, with the highest growth projected under the trend continuation scenario, followed by ecological restoration and protection, and economic development. While mangrove protection in these regions met SDG targets 6.6.1 and 14.5.1 from 2015 to 2020, the 80% conservation milestone set by GMAG for 2030 was not achieved, necessitating the establishment of nature reserves. The study offers novel insights for sustainable governance of mangrove forests at local, regional, and global levels.

Analysis of recent trends and spatiotemporal changes of droughts over Serbia using high-resolution gridded data

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E-OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia.

Analysis of Spatiotemporal Changes, Influencing Factors, and Coupling Coordination Degree of Urban Human Settlements Efficiency: A Case Study of Megacities and Supercities in China

Analysis of Spatiotemporal Changes, Influencing Factors, and Coupling Coordination Degree of Urban Human Settlements Efficiency: A Case Study of Megacities and Supercities in China

Green Neighbourhood Sustainability Index – A measure of the balance between anthropogenic pressure and ecological relevance

Peri-urban landscapes grow more urbanised due to suburbanisation. This, in turn, makes them environmentally and culturally susceptible to changes. Keen demand for residential areas threatens the sustainability of the peri-urban landscape. Green spaces are at particular risk of conversion. Recently, researchers focused on the function of green sites in urban environments. What is more, research on green spaces involves mainly their mapping and analysis of spatiotemporal changes. Nevertheless, there is a research gap in the multi-criteria research on the hypothetical sustainability of green spaces and the identification of areas that are the most at risk of conversion. Therefore, the present study is an attempt to develop a simple technique tool for objective measurement of the sustainability of green spaces in peri-urban areas. To this end, we developed the Green Neighbourhood Sustainability Index (GNSI), with which one can assess the sustainability of the landscape and green spaces using spatial data and GIS technology. The GNSI was then put to the test in the peri-urban zone of Kraków (Poland). The research shows that as the area of agricultural land increases, the sustainability of nearby green spaces decreases. Forest land, on the other hand, improves sustainability. The structure of land use types in the peri-urban zone of Kraków is well balanced. It is both desirable and good for landscape sustainability and harmony. The GNSI can be among the aids used by decision-makers to take science-informed strategic spatial planning decisions to ensure the sustainability of green spaces and the proper functioning of the ecosystem in peri-urban areas, especially in post-socialist transformation countries.

Evaluating the future risk of coastal Ramsar wetlands in India to extreme rainfalls using fuzzy logic

Wetlands are often found in areas that undergo periodic flooding, such as coastal seas, lakes, and rivers. Coastal wetlands are particularly vulnerable to climate change effects, such as changes in precipitation patterns, risk of extreme rainfall, and cyclones/storms. This study assessed the uncertainties associated with extreme rainfalls in terms of return levels (RLs; 20 and 50 years) and quantified the potential risk level of these events in the future for coastal wetlands in India. The extreme precipitation indices (EPIs) were evaluated using a non-stationary approach, and the results showed that Thane Creek had the highest RLs, followed by Kolleru Lake. The risk level for each wetland was assessed using the fuzzy logic approach, which considered parameters such as exposure, vulnerability, and threat. The overall risk assessment showed that Thane Creek, Kolleru Lake, Pallikaranai Marsh Reserve Forest, and Tampara Lake are at a “High” risk level for both RLs of EPIs. Furthermore, the automated Shortwave Infrared (SWIR) thresholding technique was employed in Google Earth Engine to create inundation maps of wetlands. This study also indicated that Thane Creek is at risk of flooding based on the analysis of spatiotemporal changes. The impact evaluation of Thane Creek showed that rapid urbanization has encroached upon the creek's boundaries. Therefore, the variability of EPIs may be affected by climatic oscillations, leading to an upsurge in extreme rainfalls, causing the coastal wetlands to flood. Policymakers can use these findings to develop effective strategies for the proper management of coastal wetlands.

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Analysis of Spatiotemporal Changes in the Gravitational Structure of Urban Agglomerations in Northern and Southern Xinjiang Based on a Gravitational Model

The urban agglomeration plays a significant role in enhancing integrated regional development. Nevertheless, the expansion of urban agglomerations has demonstrated a lackluster ability to attract cities. Presently, finding solutions to stabilize the existing urban strength and effectively extend attraction to neighboring cities has become a crucial matter. This study adopts the enhanced comprehensive attraction model, fracture point model, and radiation radius model to examine the level of city attraction, intensity of radiation, and range of radiation in the northern and southern Xinjiang city clusters between 2010 and 2020. Based on the analysis, the following conclusions are drawn: (1) the comprehensive strength and city attraction of cities in the northern Xinjiang region is higher than that of the southern Xinjiang region; (2) the intensity of spatial connection between cities in the northern and southern Xinjiang regions is gradually increasing, and the intensity of spatial connection of cities in the northern Xinjiang region is significantly greater than that in the southern Xinjiang region. The intensity of spatial connection between cities in the northern and southern Xinjiang regions is significantly greater than that in the southern Xinjiang region; (3) the central role of the central cities in the northern and southern Xinjiang regions is weakening, the development of cities in the region is gradually becoming unified and coordinated, and regional integration is gradually being strengthened. This study reveals the similarities and differences in urban development in the north and south of Xinjiang and provides important theoretical reference value for regional urban development.

Analysis of long-term spatio-temporal changes of plateau urban wetland reveals the response mechanisms of climate and human activities: A case study from Dianchi Lake Basin 1993–2020

Wetlands serve many functions, including conserving water, providing habitats for animals and plants, and regulating climate change. Their unique ecological effects on the natural environment are indispensable in the whole ecosystem. Dianchi Lake Basin is located in Yunnan-Guizhou Plateau, China, and mainly in Kunming. It is a typical plateau urban wetland area. Based on spatio-temporal hotspot mining, spatio-temporal geographically weighted regression, and adaptive multidimensional grey prediction, we conducted correlation analyses of the wetland changes in Dianchi Lake Basin from 1993 to 2020 under the influence of human activities and natural conditions. The results show that (1) the active wetland change zone in Dianchi Lake Basin is mainly located around Dianchi Lake, and (2) the wetlands in some areas on the north and south of Dianchi Lake declined in the early 21st century, but under the protection policy in recent years, the wetlands in these areas gradually recovered. Meanwhile, the wetlands in most areas around Dianchi Lake showed a significant growth trend from 2018 to 2020. The results suggest that the wetland change in Dianchi Lake Basin is mainly related to the urbanization of Kunming, and it can be divided into five regions (strong negative correlation, weak negative correlation, weak correlation, weak positive correlation, and strong positive correlation) according to the different correlation of human activity intensity, among which the main factors affected by nature are different, but they are all related to temperature. This study shows that, although wetlands in plateau cities can be properly restored under proper protection, wetland protection should be kept in step with the development of plateau cities to support sustainable urban development and carbon neutrality.

Study on the Spatiotemporal Evolution of the Ecological Landscape and Construction of an Ecological Network: A Case Study of Hebei Province

Research on the establishment of a regional ecological network can provide a scientific basis and valuable guidance for the protection of regional animals and plants, water conservation, sustainable resource utilization, and optimization of land use patterns. This study investigated the impacts of land use changes on the ecological security pattern using morphological spatial pattern analysis (MSPA), the minimum cumulative resistance (MCR) model, and the analysis of spatiotemporal changes and fragmentation of land use types. The results indicate that from 2000 to 2020, the dominant trend in land use types was the expansion of cultivated land, grass land, and wood land. Although the proportion of cultivated land was the largest and was concentrated in the southern part of Hebei Province, the total area of cultivated land showed a decline. Landscape index calculations revealed an increase in fragmentation of the overall landscape ecological patches, while the spatial and quantitative distribution of landscape types gradually became more uniform. Furthermore, 52 patches with the highest landscape index were identified as ecological sources, mainly located in northern Hebei Province in 2020. MSPA calculations showed that elevation, slope, and land use type contributed significantly to the comprehensive resistance surface. Using the MCR model, an ecological network for Hebei Province was constructed, consisting of 114 ecological corridors and 28 ecological nodes. The ecological corridors exhibited a distribution pattern of high density in the north and low density in the south, while the ecological nodes enhanced overall ecological connectivity in the region. Based on the current ecological environment, it is recommended to increase the number of ecological corridors and ecological nodes to enhance ecosystem stability.

Analysis of Spatio-Temporal Pattern Changes and Driving Forces of Xinjiang Plain Oases Based on Geodetector

Water and soil resources are the key elements required to maintain the stability and sustainable development of oases in inland drylands. This study takes oases in Xinjiang as an example, and reveals the spatial and temporal distribution characteristics of oases across Xinjiang, as well as the dynamic migration and transformation process of oases and the mutual influence of human activities on oasis resources, through a combination of land movement and attitude indicators, use of a gravity model, and Geodetector. The results show that: (1) the area containing the oases in the study has expanded, increasing by 24.0% between 1990 and 2020; (2) both artificial oases (AO) and natural oases (NO) were tilted in a northeast–southwest direction, with the center point of AOs moving slightly to the northeast, and the centripetal force and dispersion degree did not change significantly; the center point of NO moved significantly to the northeast, and the dispersion degree weakened, showing spatial convergence; (3) cultivated land and grassland were the main land types of oasis evolution, and their contribution to evolution was over 70%; and (4) the Geodetector results show that the three main factors driving the evolution of oases were vegetation cover, population density, and GDP. The research results have practical implications for land-use management planning and ecological environmental protection in arid zones.

Quantitative analysis of spatiotemporal changes and driving forces of vegetation net primary productivity (NPP) in the Qimeng region of Inner Mongolia

Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global warming and human activities in Inner Mongolia. The net primary productivity (NPP) was used as an indicator to study the spatial and temporal changes in vegetation in the Qimeng Region (QR). The residual trend analysis method was used to analyze the relative contributions of climate variations (CV) and human activities (HA) to NPP changes across the QR, while their drivers were explored using a geographical detector approach to quantify the driving forces of NPP. The results show that (1) NPP exhibited a fluctuating growth trend from 2003 to 2020, with an overall growth rate of 2.91%/year. (2) Precipitation, GDP and population density were the dominant driving factors for the spatial distribution of NPP. The combined explanatory power of any two dominant factors exceeded the power of any dominant individual factor, and the interaction between climate and human factors had a significant effect on NPP. (3) The change in NPP was influenced by the combined effect of HA and CV, accounting for 37.69% of the total area, with the relative contribution of HA being 51.75%. Finally, the relative contribution of human activities was slightly higher than that of climate change, confirming the initial success of the Grain to Green Program as well as ecological conservation projects. This paper provides a scientific basis for the local government to carry out the conversion of cropland to forest.

Long-term spatio-temporal changes of wetlands in Tibetan Plateau and their response to climate change

Understanding the changes of wetlands on the Tibetan Plateau (TP) is important for action to ensure ecosystem resilience in Asia. However, mapping long-term changes of wetlands at high resolutions remains challenging. Here, we quantify the spatio-temporal changes of TP wetlands from 1990 to 2019, by combining Landsat imagery with deep learning to map TP wetlands. The deep learning model combined with transfer learning strategies achieves high classification performance using a few class samples. The validation results show that the user’s accuracy is 95.5% and the producer's accuracy is 90.1% for wetland extraction, satisfying with subsequent analysis of wetland spatio-temporal changes. Based on the wetland extraction model, we have created annual wetland map in the TP for the first time. We find that the areal extent of TP wetlands has increased by 31.2 ± 6.6 % over the past 30 years. The growth is particularly noticeable (by 22.5 ± 6.2 %) during 2015–2019. Spatially, the wetland areal extent on the Qiangtang Plateau (in the inner part of TP and as habitats of various birds and rare wild animals) and the source region of Yangtze River show the largest expansions by 55.3 ± 9.3 % and 44.0 ± 8.9 %, respectively. Such rapid wetland expansions are associated with increasing rainfall and temperature which have heterogeneous influences on wetland changes across the TP. Our findings provide evidence for the impact of climate change on wetland area. The marked wetland changes highlight that climate mitigation is a priority for high-latitude ecosystems.

Пространственно-временные изменения макрофитобентоса в прибрежных ландшафтах у мыса Коса Северная (Севастополь)

Using a landscape approach, the paper presents for the first time the results of a comparative analysis of spatiotemporal changes in the macrophytobenthos, performed at Cape Kosa Severnaya for the period from 1964 to 2020 with landscape maps compiled by the authors. In addition, it describes the distribution of the bottom natural complexes (BNC) with key Black Sea phytocoenoses (Ericaria crinita, Gongolaria barbata и Phyllophora crispa). It was found that during this period a dramatic increase in the biomass of the phytocoenosiswas recorded in the BNC block-boulder bench with dominance of E. crinita, while the proportion of its edificator remained high. The maximum contribution of epiphytic sinusia to biomass of algocoenosis over the entire study period was recorded in 2006. For the BNC upper shoreface slope consisting of coarse-grained deposits with dominance of E. crinita и G. barbata, an increase in phytocoenosis biomass was recorded only at the upper boundary during the study period. For the BNC of gently dipping accumulation plain consisting gravel-psammitic sediments with inclusion of shell fragments and dominance ofPhyllophora crispa, a catastrophic decline in the productivity of the phytocenosis and its edificator is typical. The total biomass of macrophytes decreased by more than an order of magnitude during the study period. It was found that over a span of 50 years, the plant components of bottom natural complexes at Cape Kosa Severnaya underwent significant restructuring and degradation due to natural factors and anthropogenic activity in the coastal zone. The high degree of preservation of indigenous phytocenoses, the presence of red book species (P. crispa and Stilophora tenella) allow us to recommend the site at the Cape Kosa Severnaya as a promising reserve.

Remote Sensing Monitoring and Analysis of Spatiotemporal Changes in China’s Anthropogenic Carbon Emissions Based on XCO2 Data

The monitoring and analysis of the spatiotemporal distribution of anthropogenic carbon emissions is an important part of realizing China’s regional “dual carbon” goals; that is, the aim is for carbon emissions to peak in 2030 an to achieve carbon neutrality by 2060, as well as achieving sustainable development of the ecological environment. The column-averaged CO2 dry air mole fraction (XCO2) of greenhouse gas remote sensing satellites has been widely used to monitor anthropogenic carbon emissions. However, selecting a reasonable background region to eliminate the influence of uncertainty factors is still an important challenge to monitor anthropogenic carbon emissions by using XCO2. Aiming at the problems of the imprecise selection of background regions, this study proposes to enhance the anthropogenic carbon emission signal in the XCO2 by using the regional comparison method based on the idea of zoning. First, this study determines the background region based on the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) dataset and potential temperature data. Second, the average value of the XCO2 in the background area was extracted and taken as the XCO2 background. On this basis, the XCO2 anomaly (XCO2ano) was obtained by regional comparison method. Finally, the spatiotemporal variation characteristics and trends of XCO2ano were analyzed, and the correlations between the number of residential areas and fossil fuel emissions were calculated. The results of the satellite observation data experiments over China from 2010 to 2020 show that the XCO2ano and anthropogenic carbon emissions have similar spatial distribution patterns. The XCO2ano in China changed significantly and was in a positive growth trend as a whole. The XCO2ano values have a certain positive correlation with the number of residential areas and observations of fossil fuel emissions. The purpose of this research is to enhance the anthropogenic carbon emission signals in satellite observation XCO2 data by combining ODIAC data and potential temperature data, achieve the remote sensing monitoring and analysis of spatiotemporal changes in anthropogenic carbon emissions over China, and provide technical support for the policies and paths of regional carbon emission reductions and ecological environmental protection.

Analysis of spatiotemporal changes and driving factors of blue-green space in six metropolitan areas of the Yangtze River Delta based on the PLUS model

This study aims to examine the evolution of blue-green space and urban development in the Yangtze River Delta region using Arcgis spatial analysis, landscape pattern index, and PLUS model to inform urban planning and environmental protection efforts. The results indicate that:1) Blue space in the region's six metropolitan areas initially increased, then decreased significantly from 2000-2020, while green space continued to decline. However, recent environmental policies have mitigated this trend. 2) Improved living standards have led to increased green space within cities, but construction land occupation has reduced green space outside of cities. 3) Blue-green space is becoming more fragmented, scattered, and homogenized in shape, and that economic development influences green space, while different regional development patterns impact blue space. 4) Socioeconomic and natural factors both drive blue-green space to change. There is a "dual desirability" between blue-green space protection and urban development. In conclusion, the scale and landscape pattern of blue-green space have changed significantly in the last 20 years, which are greatly influenced by urban development, and the blue-green space differences among metropolitan areas are obvious. Therefore, it is necessary to protect and optimize the blue-green space pattern of the metropolitan areas.

Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China

In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs.

Spatiotemporal Landscape Pattern Analyses Enhanced by an Integrated Index: A Study of the Changbai Mountain National Nature Reserve

The analysis of spatiotemporal changes of landscape patterns is of great significance for forest protection. However, the selection of landscape metrics is often subjective, and existing composite landscape metrics rarely consider the effects of spatial correlation. A more objective approach to formulating composite landscape metrics involves proper weighting that incorporates spatial structure information into integrating individual conventional metrics selected for building a composite metric. This paper proposes an integrated spatial landscape index (ISLI) based on variogram modeling and entropy weighting. It was tested through a case study, which sought to analyze spatiotemporal changes in the landscape pattern in the Changbai Mountains over 30 years based on six global land-cover products with a fine classification system at 30 m resolution (GLC_FCS30). The test results confirm: (1) spatial structure information is useful for weighting conventional landscape pattern metrics when constructing ISLI as validated by correlation analysis between the incorporated conventional metrics and their variogram ranges. In terms of the range parameters of different land cover types, broadleaf forest and needleleaf forest have much larger range values than those of other land cover types; (2) DIVISION and PLAND, two of the conventional landscape metrics considered for constructing ISLI, were assigned the greatest weights in computing ISLI for this study; and (3) ISLI values can be used to determine the dominant landscape types. For the study area, ISLI values of broadleaf forests remained the largest until 2020, indicating that forest landscape characteristics were the most prominent during that period. After 2020, the dominance of needleleaf forest gradually increased, with its ISLI value reaching a maximum of 0.91 in 2025. Therefore, the proposed ISLI not only functions as an extension and complement to conventional landscape metrics but also provides more comprehensive information concerning landscape pattern dynamics.