Cover Change Data Research Articles

Refined Landslide Susceptibility Mapping Considering Land Use Changes and InSAR Deformation: A Case Study of Yulin City, Guangxi

Landslide susceptibility maps (LSMs) are valuable tools typically used by local authorities for land use management and planning activities, supporting decision-makers in urban and infrastructure planning. To address this, we proposed a refined method for landslide susceptibility assessment, which comprehensively considered both static and dynamic factors. Neural network methods were used for susceptibility analysis. Land use and land cover (LULC) change and InSAR deformation were then integrated into the traditional susceptibility zoning to obtain a refined susceptibility map with higher accuracy. Validation was conducted on the improved landslide susceptibility map using site landslide data. The results showed that the LULC were proven to be the core driving factors for landslide occurrence in the study area. The GRU model achieved the highest model performance (AUC = 0.886). The introduction of InSAR surface deformation and land use and land cover change data could rationalize the inappropriateness of traditional landslide susceptibility zoning, correcting the false positive and false negative areas in the traditional landslide susceptibility map caused by human activities. Ultimately, 12.25% of the study area was in high-susceptibility zones, with 3.10% of false positive and 0.74% of false negative areas being corrected. The proposed method enabled refined analysis of landslide susceptibility over large areas, providing technical support and disaster prevention and mitigation references for geological hazard susceptibility assessment and land management planning.

Woody plant encroachment drives population declines in 20% of common open ecosystem bird species.

Grassy ecosystems cover more than 40% of the world's terrestrial surface, supporting crucial ecosystem services and unique biodiversity. These ecosystems have experienced major losses from conversion to agriculture with the remaining fragments threatened by global change. Woody plant encroachment, the increase in woody cover threatening grassy ecosystems, is a major global change symptom, shifting the composition, structure, and function of plant communities with concomitant effects on all biodiversity. To identify generalisable impacts of encroachment on biodiversity, we urgently need broad-scale studies on how species respond to woody cover change. Here, we make use of bird atlas, woody cover change data (between 2007 and 2016) and species traits, to assess: (1) population trends and woody cover responses using dynamic occupancy models; (2) how outcomes relate to habitat, diet and nesting traits; and (3) predictions of future occupancy trends, for 191 abundant, southern African bird species. We found that: (1) 63% (121) of species showed a decline in occupancy, with 18% (34) of species' declines correlated with increasing woody cover (i.e. losers). Only 2% (4) of species showed increasing population trends linked with increased woody cover (i.e. winners); (2) Open habitat specialist, invertivorous, ground nesting birds were the most frequent losers, however, we found no definitive evidence that the selected traits could predict outcomes; and (3) We predict open habitat loser species will take on average 52 years to experience 50% population declines with current rates of encroachment. Our results bring attention to concerning region-wide declining bird population trends and highlight woody plant encroachment as an important driver of bird population dynamics. Importantly, these findings should encourage improved management and restoration of our remaining grassy ecosystems. Furthermore, our findings show the importance of lands beyond protected areas for biodiversity, and the urgent need to mitigate the impacts of woody plant encroachment on bird biodiversity.

Evapotranspiration increment was underestimated in China due to underrepresented land cover changes

Numerous evapotranspiration (ET) products have been produced using various approaches and diverse forcing data even as the magnitude and trends of ET show divergence. We simulated ET using updated land use and cover change (LUCC) data in China from 1900 to 2020. We found that China’s ET increased slightly from 1900 to 1980, but it increased rapidly after 1980 due to LUCC characterized by forest expansion (2.05 mm yr−1, P < 0.01). We also found that the ET trends derived from our simulation were significantly higher than other ET products (−0.70–1.47 mm yr−1, P < 0.01), implying that existing, long-term ET products might have underestimated ET trends in China during the post-1980 period because of underrepresented LUCC. These underestimated ET trends could introduce biases in the regional water budget and water resources management. We advocate for future studies to take into account the impacts of LUCC in global ET simulations.

Spatio-temporal patterns and population exposure risks of urban heat island in megacity Shanghai, China

Accompanied by global warming and rapid urbanization, the urban heat island (UHI) effect has been intensifying, which leads to an increased risk of population heat exposure, especially in mega-cities. However, there are fewer studies on the identification of UHI ranges and the associated population heat exposure risks, particularly on the fine scale. Therefore, this study took Shanghai as a case study and explored the spatio-temporal evolution characteristics of the UHI ranges and population heat exposure risks, based on five-period MODIS land surface temperature (LST) product, population density distribution data, and land use and cover change data from 2000 to 2020, combined with the temperature attenuation mutation (TAM) method, breakpoint regression model, population heat exposure relative risk assessment method, and spatial autocorrelation analysis. The results showed that: (1) From 2000 to 2020, the UHI range in Shanghai was continuously expanding, and the intensity of the surface UHI was gradually increasing. The overall pattern was characterized by a stable large heat island in the central urban area and new small heat islands that continued to emerge in the peripheral suburbs. (2) The population heat exposure risks in Shanghai intensified from 2000 to 2020, with an increasing number of people exposed to high-intensity UHI ranges, doubling the population coverage in these areas. By the end of 2020, the population exposed to UHI ranges accounted for approximately 81 % of the total population of Shanghai. (3) The spatial pattern of population heat exposure risks from 2000 to 2020 was generally similar. Population heat exposure regions of high risk level were primarily concentrated in the central urban areas, showing typical spatial clustering characteristics, while population heat exposure regions of low risk level were mainly dispersed in the peripheral suburbs, and showed a gradual transformation trend into population heat exposure regions of high risk level. Our findings can provide scientific basis and decision support for precise and refined urban heat risk control and planning management.

Impact of Landuse Change on The Inundations in The Ciberes Watershed

Whenever the rainy season approaches, the Ciberes River always inundates a number of regions. This research was conducted to determine the effect of land use change on the inundation in the Ciberes Watershed, given the aforementioned context. Using land cover change data from 2000 to 2023, a hydrological and hydrodynamic analysis of the Ciberes Watershed is conducted to determine the impact of landuse change. This investigation employs HEC-HMS for hydrological modeling and HEC-RAS for 1D and 2D hydrodynamic modeling. The simulation results demonstrate that the change in CN value is directly proportional to the flood discharge, and the flood discharge is directly proportional to the height of the flood inundation. Based on these findings, it can be concluded that the river’s cross section can accommodate flood discharges with a return period of 50 years, except in coastal areas. whereas the floods that occurred in 2018 and 2022 have a 10-year return period. It can be concluded that the topographical condition of the river in the downstream segment, which has a higher elevation than the surrounding land and flat soil conditions, is the primary cause of inundation in the Ciberes Watershed.

Impacts of Spatio-Temporal Changes in Anthropogenic Disturbances on Landscape Patterns in the Nandu River Basin, China

We explored the characteristics of landscape pattern (LP) changes in the Nandu River Basin (NRB) and its dynamic response mechanism to anthropogenic disturbance (AD). This is important for ecological protection and for land use decision-making in the basin in the context of the construction of a free trade port. Land use and land cover change (LULCC) data of 1990, 2000, 2010, and 2020 were analyzed with the help of the LP index, moving window method, hemeroby index, geo-information atlas, and geographic information system (GIS) spatial analysis to reveal the dynamic changes in LP characteristics in the NRB. Furthermore, this paper discusses into the correlation between LP and AD. The results indicate that over the past three decades, the NRB showed a staggered LP, dominated by forestland and cropland, whose total area has decreased by 25.27 km2 and 62.75 km2, respectively. On the other hand, the built-up land increased by 91.37%. The overall landscape fragmentation, landscape patch homogeneity, and landscape diversity have increased in the NRB. AD is the main reason for the dramatic changes in the LP of urban agglomerations centered in Haikou city. The area of minor disturbance (over 34%) occupies the largest proportion of the land, followed by higher (about 13~25%) and moderate disturbances (about 17~22%). The area of minor and strong disturbances has increased significantly, whereas those of moderate and higher disturbances have significantly decreased. The spatial distribution pattern of AD is gradually increasing from the southwest (natural landscape) to the northeast (human landscape). A transition in areas of low disturbance levels to higher levels is obvious. The area of the atlas that has transitioned from “minor → lighter disturbance (12)” and “higher → minor disturbance (41)” changed changed most significantly during 2000 to 2010 and from 2010 to 2020, occupying 26.79% and 11.99% of the transfer atlas, respectively. All regions encountering disturbances were significantly correlated with the largest patch index (LPI) from 1990 to 2020. The overall AD in the NRB has increased, especially in Haikou. Urbanization is the main factor for an increase in AD. The ecological and environmental management and monitoring in the basin need to be strengthened.

Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil erosion has received continuous attention. Different conservation measures such as restoring low-function forests, closing hillsides for afforestation, planting trees and grass, and constructing terraces on slope land have been implemented for controlling soil erosion problems and promoting vegetation cover change. One important task is to understand the effects of different conservation measures on reducing water and soil erosion problems. However, directly conducting the evaluation of soil erosion reduction is difficult. One solution is to evaluate the patterns and magnitudes of vegetation cover change due to implementing these measures. Therefore, this research selected Changting County, Fujian Province as a case study to examine the effects of implementing conservation measures on vegetation cover change based on time series Landsat images and field survey data. Landsat images between 1986 and 2021 were used to produce time series vegetation cover data using the Google Earth Engine. Sentinel-2 images acquired in 2021 and Landsat images in 2010 were separately used to develop land cover maps using the random forest method. The spatial distribution of different conservation measures was linked to annual vegetation cover and land cover change data to examine the effects on the change in vegetation cover. The results showed a significant reduction in bare lands and increase in pine forests. The vegetation coverage increased from 42% in 1986 to 79% in 2021 in the conservation region compared with an increase from 73% to 87% in the non-conservation region during the same period. Of the different conservation measures, the change magnitude was 0.44 for restoring low-function forests and closing hillsides for afforestation and 0.65 for multiple control measures. This research provides new insights in terms of understanding the effects of taking proper measures for reducing soil and water erosion problems and provides scientific results for decisionmaking for soil erosion controls. The strategy and method used in this research are valuable for other regions in understanding the roles of different conservation measures on vegetation cover change and soil erosion reduction through employing remote sensing technologies.

Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020

Most current research on aquaculture ponds focuses on coastal areas, leaving a gap in understanding of inland regions, such as the strategically significant Yangtze River Economic Belt in China. This study introduces an intelligent extraction method for extensive monitoring of aquaculture ponds in Yangtze River Economic Belt, using Landsat and Sentinel data from 1985 to 2020 with five-year intervals based on the Google Earth Engine (GEE) platform. Land cover change data were also analyzed to understand the impact of aquaculture-related changes. Results indicate a significant increase in aquaculture ponds in the Yangtze River Economic Belt from 3235.51 km2 to 14,207.08 km2 between 1985 and 2020. Aquaculture activity primarily shifted eastward from 1985 to 2015, then westward from 2015 to 2020. Approximately 2018.36 km2 of aquatic areas underwent conversion, mainly to water bodies or croplands, with fewer transitions to impervious surfaces, grasslands, or forests. This study highlights that inland areas can also experience significant increases in aquaculture ponds, particularly alongside large rivers, and that the environmental impacts of these changes differ from those in coastal areas, warranting specific attention.

Towards tree-based systems disturbance monitoring of tropical mosaic landscape using a time series ensemble learning approach

Tree clearing and degradation inside and outside forest ecosystems in Africa are important contributors to global carbon budget and emissions. Part of the uncertainties in emission estimates, among other things, is related to the non-inclusion of disturbances across all tree-based systems and limitations in the capacity of existing methodologies to detect subtle changes or degradation. Here, we present a tree-based system (TBS) disturbance monitoring approach in a mosaic landscape in East Africa. For this purpose, high- and low-intensity disturbance detection time series algorithms, namely Breaks for Additive Season and Trend monitor (BFASTmonitor), Continuous Degradation Detection (CODED), and Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr), were used. These algorithms were tested in three approaches based on reference canopy cover change data from repeated airborne laser scanning. Data processing was performed using Collection 2 Landsat (5, 7, and 8) time series in Google Earth Engine. The approaches were based on testing the accuracy of 1) the algorithms' magnitude of change outputs using multispectral information (i.e., several vegetation indices and bands); 2) multispectral ensemble learning approach applied at each of the three algorithms; and 3) combining the multiple algorithms in an ensemble learning approach. Our results showed an improvement in the accuracy of detecting a TBS disturbance from approach 1 to 3. The best result (44% omission error and 31% commission error against reference airborne laser scanning data) was obtained when BFASTmonitor and CODED were combined in an ensemble learning approach. The shortwave infrared bands were more important for detecting TBS disturbance than green, red, and near-infrared bands. The application of the best model in TBS disturbance monitoring in the region revealed that disturbances were more dominant outside forest ecosystems than inside. Improved disturbance monitoring in TBS can contribute to more accurate emission estimates in Africa and elsewhere in the tropics.

Correlation modelling between land surface temperatures and urban carbon emissions using multi-source remote sensing data: A case study

Global warming has imposed substantial global negative impacts on different sectors of human societies, such as extreme weather events. In this sense, it is imperative to ascertain whether the rise in global temperature will accelerate carbon emissions simultaneously. The land surface temperature (LST) serves as a common indicator to represent the spatial temperature. In addition, urban areas account for a majority portion of global emissions. To fill this gap, selecting the central urban area of Fuzhou City as a study case, this paper aims to examine the potential correlation between LST and overall carbon emissions, based on the land use and cover change (LUCC) data and nighttime lighting remote sensing data in three years (2012, 2016, and 2020). A spatially explicit distribution model of carbon source is presented in this paper. Based on remote sensing data and land use and cover change data, this model used inverse distance weighting spatial interpolation to calculate urban carbon emissions and retrieve LST. Moreover, the potential statistical correlation between land surface temperature (LST) and urban carbon emissions is explored by both polynomial and spline regressions and a potential positive statistical correlation between LST and carbon emissions is observed in this case.urban carbon emissions generally

CO2 emissions in the Amazon: are bottom-up estimates from land use and cover datasets consistent with top-down estimates based on atmospheric measurements?

Amazon forests are the largest forests in the tropics and play a fundamental role for regional and global ecosystem service provision. However, they are under threat primarily from deforestation. Amazonia's carbon balance trend reflects the condition of its forests. There are different approaches to estimate large-scale carbon balances, including top-down (e.g., CO2 atmospheric measurements combined with atmospheric transport information) and bottom-up (e.g., land use and cover change (LUCC) data based on remote sensing methods). It is important to understand their similarities and differences. Here we provide bottom-up LUCC estimates and determine to what extent they are consistent with recent top-down flux estimates during 2010 to 2018 for the Brazilian Amazon. We combine LUCC datasets resulting in annual LUCC maps from 2010 to 2018 with emissions and removals for each LUCC, and compare the resulting CO2 estimates with top-down estimates based on atmospheric measurements. We take into account forest carbon stock maps for estimating loss processes, and carbon uptake of regenerating and mature forests. In the bottom-up approach total CO2 emissions (2010 to 2018), deforestation and degradation are the largest contributing processes accounting for 58% (4.3 PgCO2) and 37% (2.7 PgCO2) respectively. Looking at the total carbon uptake, primary forests play a dominant role accounting for 79% (−5.9 PgCO2) and secondary forest growth for 17% (−1.2 PgCO2). Overall, according to our bottom-up estimates the Brazilian Amazon is a carbon sink until 2014 and a source from 2015 to 2018. In contrast according to the top-down approach the Brazilian Amazon is a source during the entire period. Both approaches estimate largest emissions in 2016. During the period where flux signs are the same (2015–2018) top-down estimates are approximately 3 times larger in 2015–2016 than bottom-up estimates while in 2017–2018 there is closer agreement. There is some agreement between the approaches–notably that the Brazilian Amazon has been a source during 2015–2018 however there are also disagreements. Generally, emissions estimated by the bottom-up approach tend to be lower. Understanding the differences will help improve both approaches and our understanding of the Amazon carbon cycle under human pressure and climate change.

Climate Change and Anthropogenic Factors Are Influencing the Loss of Habitats and Emerging Human–Elephant Conflict in the Namib Desert

Climate change and anthropogenic factors’ impact on habitat loss is a growing problem that is influencing unsustainable wildlife local-population home range shifts and triggering an increase in human–wildlife conflict (HWC). Yet, keystone species involved in HWC such as elephants play a vital role in nature-based ecosystem services and have important economic and cultural value to the people that are living with them. To understand how climate change and anthropogenic factors affect habitat loss and elephants’ home range shift, the movement of Namib desert-dwelling elephants was monitored and observed in the Ugab River basin between February 2018 and November 2020 at fortnight intervals. There are 87 elephants in the Ugab River basin that are distributed into two subpopulations: desert-dwelling elephants (N = 28) and semi-desert-dwelling elephants (N = 59). To achieve the objective of the study, land cover change, elephant movement, rainfall, and temperature data were analysed using ArcGIS spatial and statistical tools, such as image analysis, optimised hot spot analysis (OHSA), and cost distance analysis, to distinguish habitat vegetation changes and home range shifts and how these link to emerging human–elephant conflict (HEC) hot spots. Human farming activities, poor rainfall, and frequent droughts are responsible for the loss of habitat of around 73.0% in the lower catchment of the ephemeral river streams; therefore, the urgency of conserving and sustaining these habitats and desert-dwelling elephants is discussed here.

Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021

Precipitation is the major input of the hydrological cycle in tropical regions. Changes in the spatial and temporal patterns of precipitation should be investigated in order to provide in-time information for both water and land use planning. Climate and land use changes have been influencing modification in the water cycle, demanding adaptations and increasing the vulnerability of water-dependent systems. This study investigated spatial and temporal changes in precipitation patterns in the Paranapanema River Basin (PPRB), Brazil. The PPRB region is an important agricultural and hydroelectric power generation hub and has been suffering from water crises in recent years, and more intensely in the last 5–10 years. The analysis used remote sensing precipitations data from September 2000 to August 2021 (summing up twenty-one hydrological years) at 0.1° resolution. Exploratory Spatial and Temporal Data Analysis (ESTDA) were applied to verify spatial local autocorrelation and hot/cold spots clusters, and temporal trends, homogeneity, and change points in the time series at Hydrological Planning Unit (HPU) scale level. The significant results were discussed based on statistical tests and land use cover change data. There is a strong presence of precipitation spatial patterns in the PPRB. Also, the PPRB presented modifications in the precipitation regime over the analyzed period, with significant change points around 2015—2017. Further monitoring is recommended in order to confirm these results in the long term, however, the provided information can already be used as an award to local and regional water bodies installed in the river basin, supporting informative water management.

Forty-year multi-scale land cover change and political ecology data reveal a dynamic and regenerative process of forests in Peruvian Indigenous Territories

This article explores deforestation and reforestation dynamics over 415,749 hectares of 25 titled Indigenous Community Lands (ICLs) in the Peruvian Amazon over forty years at three scales: total area, regions, and communities. We focus on ICLs as the territorial unit of analysis, as they are increasingly discussed regarding their importance for conservation. Additionally indigenous communities (ICs) are a too-marginalized group in the Amazon that merit more attention. Analyses of this kind are often short-term and use only large-scale Earth Observation methodologies. We use a multi-method approach linking remote sensing with ground verification, and qualitative historical political ecology work with ICs. We find that overall accumulated deforestation was low at 5%, but that when reforestation is considered, net deforestation was only 3.5%. At the community level deforestation and afforestation dynamics are complex, except for one period that indicates a macro state driver in the region. Results suggest inadequate accounting for forest regeneration in deforestation analyses and challenge the notion that presenting stakeholders with accumulated forest loss values is helpful in tropical areas where forests and people are dynamic. Furthermore, our work with communities highlights that categorizing them and their lands as pro-environment or not in general terms is unhelpful for determining fund flows to ICLs for environmental or development purposes.

Four decades of urban land cover change in Philadelphia

Given ambitious tree canopy goals, land cover change analyses in cities are imperative. Urban tree canopy change analyses have been hindered by data with low categorical resolution (e.g., canopy vs. not canopy), over relatively short time horizons (5–10 years), representing only two points in time, and scarce linkages to other temporal datasets (e.g., historical socioeconomic data). In this study, using a land cover change data set with five cover classes spanning 40 years (1970–2010) for Philadelphia, PA (US), we asked: which types of land cover changes are most common, and how do those relate to and co-vary with socioeconomic change? Specifically, we tabulated land cover changes (i.e., transition sequences), applied multinomial logistic regression with socioeconomic variables as predictors of land cover change, and used cluster analyses to characterize neighborhood changes associated with land cover change. Land cover stability dominated the transition sequences: the four most common sequences were stable road (e.g. road-road-road-road-road), stable building, tree canopy, and herbaceous vegetation, collectively accounting for 62.57% of all sequences. Multinomial logistic regression identified that increases in homeownership, income, and educational attainment were associated with a higher probability of tree canopy persistence. Cluster analyses via Affinity Propagation showed that some Census tracts have similar land cover change trajectories, and yet different socioeconomic trends. These findings point towards opportunities to focus on tree preservation alongside the importance of establishing new tree canopy through planting. Our study demonstrates the mix of stability and dynamism in multidecadal urban land cover change, and the importance of connecting land cover changes with socioeconomic changes.

Extended suburbanisation and land cover dynamics in post-socialist metropolitan areas

In post-socialist countries, suburbanisation of metropolitan areas has been the main pattern of urbanisation since 1990, especially under the form of urban sprawl by residential development. Privatisation processes, deregulation of the real estate market and greater sovereignty of local administrative units have led to specific challenges for post-socialist countries when managing suburbanisation. While specific case studies have been used to highlight the dynamics of urban areas in these countries after 1990, there has been little research done at a national level focusing on urbanisation patterns in post-socialist metropolitan areas. Using Romanian metropolitan areas as a case study, this paper proposes a ranking of metropolitan areas based on the dynamics of artificial surfaces and housing units. An analysis of 1990– 2018 CORINE Land Cover and Use Change data was carried out nationwide using ArcGIS Spatial Analyst tools, along with an analysis of ancillary data from the National Institute of Statistics regarding housing. The results illustrated that suburban development is concentrated around the largest Romanian cities, declared National Growth Poles during the programming period 2007–2013, also highlighting some limits in using CORINE data for 1990 and 2000. The proposed ranking of metropolitan areas could aid the design of tailored development policies and planning instruments for the most dynamic urban areas. Such analyses have the potential to be replicated in other post-socialist countries, as well as in countries experiencing metropolitan suburbanisation irrespective of their recent political history.

Analysis of Environmental, Social and Economic Conditions in the Ecosystem Restoration Area (Case Study in IUPHHK-RE PT. Sinar Mutiara Nusantara, Pelalawan Regency)

The problems that are often encountered in ecosystem restoration activities today are no longer just technical forestry issues such as planting and maintenance, but more importantly social issues as an important part of ecosystem restoration area management. Forest management must change from a physical definition to social interactions and spatial patterns so that the solutions taken must seek contextual efforts according to field conditions. Given the huge potential of the Kampar Peninsula ecosystem restoration area by PT. Sinar Mutiara Nusantara, it is necessary to carry out an in-depth analysis of environmental, social and economic conditions. The purpose of this study was to analyze the environmental, social and economic conditions of the Kampar Peninsula ecosystem restoration area by PT. Sinar Mutiara Nusantara. The environmental conditions observed consisted of land cover change data, vegetation and fauna data as well as mammals. While socio-economic data were obtained directly by observation (direct observation) and in-depth interviews with the people living around the concession and interacting with the IUPHHK-RE area of PT. Sinar Mutiara Nusantara in Pelalawan Regency. The results showed that the Kampar Peninsula ecosystem restoration area by PT. Sinar Mutiara Nusantara has high natural resources, as evidenced by the changing conditions of land cover, the potential for diverse vegetation and fauna and mammals. Not only environmental conditions, but socio-economic conditions which are also very closely related to environmental conditions in the Kampar Peninsula ecosystem restoration area by PT. The Best One United.

Analysis of Environmental, Social and Economic Conditions of the Ecosystem Restoration Area of PT. The Best One Unitimber Kampar Peninsula

Kampar Peninsula ecosystem restoration activity by PT. The Best One Unitimber has the potential to create an innovative and creative conservation and protection of the peat swamp forest ecosystem in the Kampar Peninsula, namely establishing support from the private sector to increase the ability to maintain the peat swamp forest ecosystem, both physically and socially and economically. Given the huge potential of the Kampar Peninsula ecosystem restoration area by PT. The Best One Unit, it is necessary to carry out an in-depth analysis of its environmental, social and economic conditions. The purpose of this study was to analyze the environmental, social and economic conditions of the Kampar Peninsula ecosystem restoration area by PT. The Best One United. The environmental conditions observed consisted of land cover change data, vegetation and fauna data. While socio-economic data were obtained directly by observation (direct observation) and in-depth interviews with the people living around the concession and interacting with the IUPHHK-RE area of PT. The Best One Unit in Pelalawan Regency. The results showed that the Kampar Peninsula ecosystem restoration area by PT. The Best One Unitimber has high natural resources, as evidenced by the changing conditions of land cover, the diverse potential of vegetation and fauna in it. Not only environmental conditions, but socio-economic conditions which are also very closely related to environmental conditions in the Kampar Peninsula ecosystem restoration area by PT. The Best One United.

Effects of land use patterns on the interannual variations of carbon sinks of terrestrial ecosystems in China

Land use changes are thought to deeply impact the changes of terrestrial carbon sink, however, how the changes of land use pattern affect the carbon sink remains unclear. To investigate the response of Net Ecosystem Productivity (NEP) to the pattern of land use dynamics in China, a landscape pattern approach (with the 30 km moving window) was used to analyze the pattern dynamics with continuous Land Use and Land Cover Change (LUCC) data from 1981 to 2019 and the nonlinear trends of the NEP and the patterns of land use were explored from 1981 to 2019 using Ensemble empirical modal decomposition (EEMD) methods, and their interannual relationship was further explored using Pearson correlation. The results are as follows: (1) For NEP, nearly half of the regions did not experience significant changes. <6 % of the regions were monotonically decreasing and increasing to decreasing. The monotonical increasing only accounted for 15.49 % of the study area, while the trend shift from decreasing to increasing accounted for 23.96 %, most predominantly located in the southern part of the Southern Region (SR); (2) For land use patterns, the vast majority of areas (>90 %) have experienced significant changes in land use patterns, the fragmentation and shape complexity, diversity and evenness of land use types has increased, while the connection decreased, meanwhile, most of these changes are not monotonical, but experiencing trend shifts; (3) In most of the total area (>80 %), land use patterns showed insignificant relationship with NEP, especially in Qinghai-Tibetan Plateau. However, in Greater Khingan Range, Loess Plateau and southern Hilly area, it showed significant relationship with NEP. Our studies highlight the importance of nonlinear analysis for fully understanding the spatial–temporal changes of NEP and land use patterns, and deepened the understanding the impacts of land use changes on NEP.

Framework and Use Case for a Web-Based Interactive Analysis Tool to Investigate Urban Expansion and Sustainable Development Goal Indicators

Land cover changes have been mapped for decades to investigate urban expansion patterns. Under the UN Sustainable Development Goals (SDGs), several indices are employed to interpret urban growth trends quantitatively and comprehensively. However, landowners and the interested public usually have limited insights into these types of information as access to data and software is limited. Static maps and the inability to access special file formats increase the difficulty of viewing and investigating the data. This contribution presents a dedicated, interactive, web-based analysis tool for integrating land cover and land use maps as well as urban expansion indices. The tool’s concept, development and functionality are presented, and its general design is reviewed based on an actual implementation case. The setup allows integrating land use and land cover (LULC) change data alongside SDG indicators. The tool’s design aims to enhance user accessibility to information on urban expansion indices and LULC. We demonstrate that such a tool can be used to help disseminate results and to improve communication with the public in the context of other use cases.