Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut

Projection of land use and land cover changes based on land change modeler and integrating both land use land cover and climate change on the hydrological response of Big Creek Lake Watershed, South Alabama

Changing land use/land cover (LULC) and climate substantially affect the hydrological components of a watershed. This study explored the future impact of the hydrological responses due to the changing LULC and climate on the Big Creek Lake watershed in Alabama, USA, from 2021 to 2050 using the Soil and Water Assessment Tool (SWAT). Five climate model datasets were used under the moderate scenario (Representative Concentrative Pathways 4.5) and the extreme scenario (Representative Concentrative Pathways 8.5), and the datasets were downscaled and bias-corrected. In addition, changing the LULC of five categories was predicted by Cellular Automata Markov (CA- Markov). With these data combined with the elevation (Digital Elevation Model), soils, and weather data, the SWAT model was calibrated and validated for the studied watershed to quantify how climate change will affect streamflow, nitrogen, and phosphorus. Our results indicate streamflow will increase due to the 50-acre increase in urban LULC. As streamflow increases, the percolation, surface runoff, lateral flow, groundwater flow, and water yield will also increase because the streamflow impacts these hydrological components. Moreover, the increase rate in streamflow is the same for all the components for January, February, and March. Therefore, there is a strong correlation between these months. On the contrary, evaporation will be high in May, June, and July because of the increasing temperature and streamflow. However, the changes in the water hydrological parameters and total nitrogen and phosphorus will be more intense in RCP8.5 than in RCP4.5.

Assessing land use changes' effect on river water quality in the Dez Basin using land change modeler

Changes in land use due to urbanization, industrialization, and agriculture will adversely affect water quality at all scales. This study examined the possible effects of future land use on the water quality of the Dez River located in Iran. The QUAL2Kw dynamic model was used to simulate the water quality of the Dez River. Data and information available in July 2019 and 2013 were used for calibration and validation. According to the comparison of the RMSE, RMSE%, and percent bias error indices for the model during the calibration and validation period, the QUAL2Kw model of Dez River had high accuracy with acceptable values of errors. The land use changes in the Dez river basin were modeled and predicted by the LCM model after simulating water quality. The images from Landsat 8/OLI were used for 2013, 2016, and 2019, respectively. Based on the accurate evaluation of classified images, Kappa coefficients for 2013, 2016, and 2019 were 88.19, 87.46, and 89.91, respectively. Modeling land use and land cover changes was conducted to predict 2030. As a result of the study, agricultural and built-up areas and water bodies will increase in 2030. The possible effects of land use changes in 2030 on river water quality were examined as a final step. Based on the results of the water quality simulation in 2030, biochemical oxygen demand, chemical oxygen demand, and NO₃ parameters exceeded the maximum permissible level of drinking standard. This study recommends frequent water quality monitoring and LULC planning and management to reduce pollution in river basins.

Past and Future Land Use/Land Cover Changes in the Ethiopian Fincha Sub-Basin

The increasing human pressure on African regions is recognizable when looking at Land Use Land Cover (LULC) change maps, generally derived from satellite imagery. Using the Ethiopian Fincha watershed as a case study, the present work focuses on (i) identifying historical LULC change in the period 1989–2019; (ii) estimating LULC in the next thirty years, combining Geographical Information Systems (GIS) with Land Change Modelling (LCM). Landsat 5/8 images were combined with field evidence to map LULC in three reference years (1989, 2004, 2019), while the Multi-Layer Markov Chain (MPL-MC) model of LCM was applied to forecast LULC in 2030, 2040, and 2050. The watershed was classified into six classes: waterbody, grass/swamp, built-up, agriculture; forest; and shrub. The results have shown that, in the past 30 years, the Fincha watershed experienced a reduction in forest and shrubs of about −40% and −13%, respectively, mainly due to ever-increasing agricultural activities, and such a trend is also expected in the future. In fact, for the period 2019–2050, LCM simulated a significant decrease in both forest and shrubs (around −70% and −20%, respectively), in favor of more areas covered by grass (19%) and built-up (20%). It is worth noting that a decrease in natural forests can drive an increase in soil erosion, fostering siltation in the water reservoirs located in the sub-basin. The study pointed out the urgency of taking actions in the sub-basin to counteract such changes, which can eventually lead to a less sustainable environment.

Climate change-induced invasion risk of ecosystem disturbing alien plant species: An evaluation using species distribution modeling

Species distribution modeling is widely used for evaluating invasion risk, and for prioritizing areas for the control and management of invasive species. However, selecting a modeling tool that accurately predicts species invasion risk requires a systematic approach. In this study, five species distribution models (SDMs), namely, artificial neural network (ANN), generalized linear model (GLM), multivariate adaptive regression splines (MARS), maximum entropy (MaxEnt), and random forest (RF), were performed and evaluated their model performance using the mean value of area under the curve (AUC), true skill statistics (TSS), and Kappa scores of 12 ecosystem disturbing alien plant species (EDAPS). The mean evaluation metric scores were highest in RF (AUC = 0.924 ± 0.058, TSS = 0.789 ± 0.109, Kappa = 0.671 ± 0.096, n = 12) and lowest in ANN. The ANOVA of AUC, TSS, and Kappa metrics revealed the RF model was significantly different from other SDMs and was therefore selected as the relatively best model. The potential distribution area and invasion risk for each EDAPS were quantified. Under the current climate conditions of South Korea, the average potential distribution area of EDAPS was estimated to be 13,062 km2. However, in future climate change scenarios, the average percentage change of EDAPS distribution relative to the current climate was predicted to be increased over 219.93%. Furthermore, under the current climate, 0.16% of the area of the country was estimated to be under a very high risk of invasion, but this would increase to 60.43% by 2070. Invasion risk under the current climate conditions was highest in the northwestern, southern, and southeastern regions, and in densely populated cities, such as Seoul, Busan, and Daegu. By 2070, invasion risk was predicted to expand across the whole country except in the northeastern region. These results suggested that climate change induced the risk of EDAPS invasiveness, and SDMs could be valuable tools for alien and invasive plant species risk assessment.

Urban Form Dynamics and Modelling towards Sustainable Hinterland Development in North Cianjur, Jakarta–Bandung Mega-Urban Region

The urban form is the physical configuration of a city, developed over time and space. Urban form can be considered at different scales, from region to neighborhood, each carrying a different focus. North Cianjur serves as the hinterland and one of the conurbation corridors of the Jakarta–Bandung Mega-Urban Region, meaning that the balance between its function as an environmental buffer area and the destination of urban growth needs to be planned carefully. This paper explores the dynamics in North Cianjur and employs several model scenarios as a planning intervention using landscape dynamic tools and land-change modeling, with three scenarios employed: Business as Usual (BAU), Spatial Planning Policy (SPP), and Urban Containment (UCT). The result show that North Cianjur has transformed into a polycentric region with two urban zones, a peri-urban zone, and a rural zone in the northernmost part of the region. Urban form trends show a sprawling built-up pattern outside urban zones, and a compacted trend in urban zones due to expansion from the Jakarta and Bandung Metropolitan Area. UCT models appear to be the most optimal for implementation in North Cianjur, representing a way to accommodate urban growth and expansion inside the urban center while still maintaining regional sustainability.

Assessment of the Spatial Invasion Risk of Intentionally Introduced Alien Plant Species (IIAPS) under Environmental Change in South Korea

Predicting the regions at risk of invasion from IIAPS is an integral horizon-scanning activity that plays a crucial role in preventing, controlling, and eradicating invasive species. Here, we quantify the spatial distribution area and invasion risk of IIAPS using a species distribution model under different levels of environmental change in South Korea. From the model predictions, the current average spatial extent of the 10 IIAPS is 33,948 km², and the individual spatial extents are estimated to change by -7% to 150% by 2050 and by -9% to 156% by 2070. The spatial invasion risk assessment shows that, currently, moderate-to-high invasion risk is limited to coastal areas and densely populated metropolitan cities (e.g., Seoul, Busan, and Gwangju), but that the area with this level of risk is expected to spread toward the central and northern regions of the country in the future, covering 86.21% of the total area of the country by 2070. These results demonstrate that the risk of invasion by IIAPS is estimated to enlarge across the whole country under future environmental changes. The modeling system provided in this study may contribute to the initial control and strategic management of IIAPS to maintain the dynamic ecosystems of South Korea.

Predicting Impacts of Climate Change on Northward Range Expansion of Invasive Weeds in South Korea

Predicting the distribution of invasive weeds under climate change is important for the early identification of areas that are susceptible to invasion and for the adoption of the best preventive measures. Here, we predicted the habitat suitability of 16 invasive weeds in response to climate change and land cover changes in South Korea using a maximum entropy modeling approach. Based on the predictions of the model, climate change is likely to increase habitat suitability. Currently, the area of moderately suitable and highly suitable habitats is estimated to be 8877.46 km², and 990.29 km², respectively, and these areas are expected to increase up to 496.52% by 2050 and 1439.65% by 2070 under the representative concentration pathways 4.5 scenario across the country. Although habitat suitability was estimated to be highest in the southern regions (<36° latitude), the central and northern regions are also predicted to have substantial increases in suitable habitat areas. Our study revealed that climate change would exacerbate the threat of northward weed invasions by shifting the climatic barriers of invasive weeds from the southern region. Thus, it is essential to initiate control and management strategies in the southern region to prevent further invasions into new areas.

Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia

Change of land use land cover (LULC) has been known globally as an essential driver of environmental change. Assessment of LULC change is the most precise method to comprehend the past land use, types of changes to be estimated, the forces and developments behind the changes. The aim of the study was to assess the temporal and spatial LULC dynamics of the past and to predict the future using Landsat images and LCM (Land Change Modeler) by considering the drivers of LULC dynamics. The research was conducted in Nashe watershed (Ethiopia) which is the main tributary of the Upper Blue Nile basin. The total watershed area is 94,578 ha. The Landsat imagery from 2019, 2005, and 1990 was used for evaluating and predicting the spatiotemporal distributions of LULC changes. The future LULC image prediction has been generated depending on the historical trends of LULC changes for the years 2035 and 2050. LCM integrated in TerrSet Geospatial Monitoring and Modeling System assimilated with MLP and CA-Markov chain have been used for monitoring, assessment of change, and future projections. Markov chain was used to generate transition probability matrices between LULC classes and cellular automata were used to predict the LULC map. Validation of the predicted LULC map of 2019 was conducted successfully with the actual LULC map. The validation accuracy was determined using the Kappa statistics and agreement/disagreement marks. The results of the historical LULC depicted that forest land, grass land, and range land are the most affected types of land use. The agricultural land in 1990 was 41,587.21 ha which increased to 57,868.95 ha in 2019 with an average growth rate of 39.15%. The forest land, range land, and grass land declined annually with rates of 48.38%, 19.58%, and 26.23%, respectively. The predicted LULC map shows that the forest cover will further degrade from 16.94% in 2019 to 8.07% in 2050, while agricultural land would be expanded to 69,021.20 ha and 69,264.44 ha in 2035 and 2050 from 57,868.95 ha in 2019. The findings of this investigation indicate an expected rapid change in LULC for the coming years. Converting the forest area, range land, and grass land into other land uses, especially to agricultural land, is the main LULC change in the future. Measures should be implemented to achieve rational use of agricultural land and the forest conversion needs to be well managed.

Climate Variability, Land Cover Changes and Livelihoods of Communities on the Fringes of Bobiri Forest Reserve, Ghana

Climate variability coupled with land use and land cover changes have resulted in significant changes in forest reserves in Ghana with major implications for rural livelihoods. Understanding the link between climate variability, land use and land cover changes and rural livelihoods is key for decision-making, especially regarding sustainable management of forest resources, monitoring of ecosystems and related livelihoods. The study determined the extent to which climate variability drives land cover changes in the Bobiri forest reserve, Ghana. Landsat images from 1986, 2003, 2010 and 2014 were used to evaluate land cover changes of the Bobiri forest reserve in Ghana. Participatory research approaches including household questionnaire surveys, focus group discussions and key informant interviews were conducted in four fringe communities of the Bobiri forest reserve. Findings showed that local people perceived changes in rainfall and temperature patterns over the past years. Historical rainfall and temperature data for the study area showed increased variability in rainfall and an increasing temperature trend, which are consistent with the perception of the study respondents. Analysis of land cover satellite images showed that there has been significant transformation of closed forest to open forest and non-forest land cover types over the 28-year period (1986–2014), with an overall kappa statistic of 0.77. Between 2003 and 2014, closed forest decreased by 15.6% but settlement/bare ground and crop land increased marginally by 1.5% and 0.9%, respectively. Focus group discussions and key informant interviews revealed that increased land cover changes in the Bobiri forest reserve could partly be attributed to erratic rainfall patterns. Other factors such as logging and population growth were reported to be factors driving land cover changes. The study concluded that the Bobiri forest reserve has witnessed significant land cover changes and recommended that alternative livelihood sources should be provided to reduce the direct dependency of fringe communities on the forest for livelihood and firewood.

Land-Use Changes of Historical Rural Landscape—Heritage, Protection, and Sustainable Ecotourism: Case Study of Slovak Exclave Čív (Piliscsév) in Komárom-Esztergom County (Hungary)

The landscape surrounding the village of Čív (Piliscsév in Hungarian) in the north of the Komárom-Esztergom County is part of the cultural heritage of the Slovaks in Hungary. This paper discusses the issue of the Čív landscape changes in the context of its use (historical land use). Between 1701 and 1709, new inhabitants began cultivating the desolated landscape of the Dorog Basin, which is surrounded by the Pilis Mountains. This paper aims to characterize the Slovak exclave Čív land use with an emphasis on the period from the beginning of the 18th century (Slovak colonization of the analyzed territory) to 2019. These findings subsequently lead to the evaluation of the stability of the cultural-historical landscape as an essential condition for the development of ecotourism in the cultural landscape. The study results show that a long-term stable cultural landscape has a similar potential for the development of ecotourism as a natural landscape (wilderness). Research conclusions were aimed at creating three proposals for the cultural landscape management of the study area, conceived by the fundamental pillars of ecotourism, which would lead to its stable and sustainable use in ecotourism.

Land Use and Land Cover Dynamics Analysis of the Togodo Protected Area and Its Surroundings in Southeastern Togo, West Africa

Assessing land use and land cover (LULC) change is essential for the sustainable management of natural resources, biodiversity conservation, monitoring food security, and research related to climate change and ecology. With increasingly rapid changes in LULC in response to human population growth, a better assessment of land use changes is more necessary than ever. Although a multitude of LULC assessment methods exists, none alone provides a clear understanding of changes and their underlying factors. This study analysed historical LULC changes over a temporal extent of 42 years (1974–2016) in the Togodo Protected Area and its surroundings, in Togo, by associating intensity and trajectory analyses, that are complementary but rarely associated in the literature. Our results show that LULC change in our study site is linked to the combined effects of human activities, climate, and invasive plants, particularly Chromolaena odorata. While each type of analysis provides useful insights, neither intensity nor trajectory analysis alone provides a full picture of changes and their causes. This study highlights the usefulness of associating intensity and trajectory analyses when implementing any management policy.

Contemporary Landscape Structure within Monumental Zone-1 at Bagan Cultural Heritage Site, Myanmar

This study examines the contemporary landscape structure of the Monumental Zone (MZ)-1 at the Bagan Cultural Heritage Site in the Dry Zone of Myanmar. With respect to hundreds of medieval monuments, how local residents in the residential areas within the MZ-1 manage the landscape was the focus of the current study, conducted with two objectives: (1) Identifying land covers as features of the contemporary landscape on the basis of land use and (2) evaluating how the features interrelate. The landscape features were identified by the analysis of Landsat 8 satellite imagery, followed by variance analysis for comparison of the features’ areas, and interrelationships of features were evaluated by multivariate analysis. Vegetated features were identified in coexistence with non-vegetated ones, while crop coverage and non-vegetated features were smaller than the area of the other two vegetated features. Semi-natural woody vegetation was found in proximity to monuments and was dependent on the occurrence of the shrub-prone patch that, in turn, was triggered by the expansion of exposed land containing a large segment of cultivatable area. The current study suggests the need to prioritise timely land use and management, focusing on local agricultural activity for safeguarding the heritage as well as the historical settings.

Forest Fire Trend and Influence of Climate Variability in India: A Geospatial Analysis at National and Local Scale

Climate change and its severity play an important role in forest fire regime. Analysing the forest fires events becomes a prerequisite for safeguarding the forest from further damage. We have made an assessment of the long-term forest fire events at the district level in India and identified the forest fire hotspot districts. The spatial seasonal (January to June) district wise pattern and forest fire trend were analysed. In the second part of the study area (central part of India), we have evaluated the forest fire events in grid format with respect to the climatic/weather datasets, and the statistical analysis Cramer V coefficient (CVC) was performed to understand its association/relationship with forest fire events.

The study revealed that Karbi Anglong and North Cachar Hills districts of Assam of India have the highest forest fire percent among all districts equivalent to 3.4 and 3.2% respectively. Dantewada district of Chhattisgarh and Garhchiroli district of Maharashtra of India occupied 3rd and 4th rank with value 3.1 and 3.0% respectively. The grid-based evaluation (local scale) revealed that most of the fire equivalent of 80% was found in the month of March and April. Forest fire frequency of the month of April is spread over 88 % of the grids over the study area. The 11 years average seasonal month-wise (February to June) maximum temperature, wind velocity, relative humidity, and solar radiation were found in the range of (25.9 to 40.6), (1.69 to 2.7), (0.301 to 0.736) and (14.21 to 22.98) respectively. The percentage increase (in the month of March) of maximum temperature, wind velocity, and solar radiation were 36, 39 and 62% respectively, when compared with the preceding month; whereas, a 60% decrease to relative humidity that was observed in the same month is usually the major cause of forest fire events in the month of March onwards.

The evaluation of Cramer V coefficient (CVC) values of rainfall, relative humidity, potential evapotranspiration, maximum temperature, wind velocity, and solar radiation were in decreasing order and in the range of 0.778 to 0.293. The highest value of rainfall (0.778) showed its strongest association with the forest fire events. In the month of June, these areas receive adequate rainfall, which leads to an increase in the soil moisture and a reduction in forest fuel burning capacity by absorbing the moisture and it is a strong reason for less forest fire events during this month. Geospatial technology provides an opportunity to evaluate large datasets over various spatial and temporal scales and help in decision making/formulating various policies.

Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model

Rapid urbanization is occurring throughout China, especially in megacities. Using a land use model to obtain future land use/cover conditions is an essential method to prevent chaotic urban sprawl and imbalanced development. This study utilized historical Landsat images to create land use/cover maps to predict the land use/cover changes of Tianjin city in 2025 and 2035. The cellular automata–Markov (CA–Markov) model was applied in the simulation under three scenarios: the environmental protection scenario (EPS), crop protection scenario (CPS), and spontaneous scenario (SS). The model achieved a kappa value of 86.6% with a figure of merit (FoM) of 12.18% when compared to the empirical land use/cover map in 2015. The results showed that the occupation of built-up areas increased from 29.13% in 2015 to 38.68% (EPS), 36.18% (CPS), and 47.94% (SS) in 2035. In this context, current urbanization would bring unprecedented stress on agricultural resources and forest ecosystems, which could be attenuated by implementing protection policies along with decelerating urban expansion. The findings provide valuable information for urban planners to achieve sustainable development goals.

Land Use and Land Cover Change in the Qinghai Lake Region of the Tibetan Plateau and Its Impact on Ecosystem Services

Exploration of land use and land cover change (LULCC) and its impacts on ecosystem services in Tibetan plateau is valuable for landscape and environmental conservation. In this study, we conduct spatial analysis on empirical land use and land cover data in the Qinghai Lake region for 1990, 2000, and 2010 and simulate land cover patterns for 2020. We then evaluate the impacts of LULCC on ecosystem service value (ESV), and analyze the sensitivity of ESV to LULCC to identify the ecologically sensitive area. Our results indicate that, from 1990 to 2010, the area of forest and grassland increased while the area of unused land decreased. Simulation results suggest that the area of grassland and forest will continue to increase and the area of cropland and unused land will decrease for 2010–2020. The ESV in the study area increased from 694.50 billion Yuan in 1990 to 714.28 billion Yuan in 2000, and to 696.72 billion Yuan in 2020. Hydrology regulation and waste treatment are the top two ecosystem services in this region. The towns surrounding the Qinghai Lake have high ESVs, especially in the north of the Qinghai Lake. The towns with high ESV sensitivity to LULCC are located in the northwest, while the towns in the north of the Qinghai Lake experienced substantial increase in sensitivity index from 2000–2010 to 2010–2020, especially for three regulation services and aesthetic landscape provision services.