Assessing driving forces of land use and land cover change by a mixed-method approach in north-eastern Ghana, West Africa

Prediction of land use for the next 30 years using the PLUS model's multi-scenario simulation in Guizhou Province, China

Land use changes significantly impact the structure and functioning of ecosystems. The current research focus lies in how to utilize economic and policy instruments to regulate conflicts among stakeholders effectively. The objective is to facilitate rational planning and sustainable development of land utilization resources. The PLUS model integrates a rule-based mining method for land expansion analysis and a CA model based on multi-type stochastic seeding mechanism, which can be used to mine the driving factors of land expansion and predict the patch-level evolution of land use landscapes. Using the PLUS model, a simulation was conducted to study the future land use distribution in the research area over the next 30 years. Based on land use data from Guizhou Province in 2000, 2010, and 2020, a total of 16 driving factors were selected from three aspects: geographical environment, transportation network, and socio-economic conditions. Four scenarios, namely natural development, urban development, ecological conservation, and farmland rotection, were established. Comparative analysis of the simulated differences among the various scenarios was performed. (1) The overall accuracy of the land use simulation using the PLUS model in the study area was 0.983, with a Kappa coefficient of 0.972 and a FoM coefficient of 0.509. The research accuracy meets the simulation requirements. (2) Through the simulation of four different scenarios, the study investigated the land use changes in Guizhou Province over the next 30 years. Each scenario exhibited distinct impacts on land utilization. Comprehensive comparison of the different simulation results revealed that the farmland protection scenario aligns with the sustainable development goals of the research area. Currently, there is a relative scarcity of research on land use simulation, particularly in model application, for Guizhou Province. This study aims to provide a reference for the rational planning of land resources and high-quality urban construction in Guizhou, promoting the high-quality economic development in tandem with advanced ecological and environmental protection.

Soil organic carbon and nutrient characteristics of Anogeissus groves in old Opara forest reserve, Nigeria

Forest-savanna transition zones of West Africa are uniquely characterized by forest groves, forest patches, or forest islands, the importance of which for sustainable resource management and their potential for carbon sequestration and nutrient cycling is often underrated. Our study conducted a comparative analysis of the soil organic carbon and nutrient characteristics of the Anogeissus groves in the old Opara forest reserve and their adjoining arable lands. We established 30 sampling frames of 100 m × 100 m plots with 15 frames per land use type. For each sampling frame, six observation points were randomly selected, and composite soil samples were collected at soil depths of 0-20 cm and 20-50 cm per observation point. Our results showed Anogeissus groves and their adjoining arable lands to exist on similar landscapes while the groves have enriched soil morphological characteristics (e.g., soil color), higher soil organic carbon (SOC), and better nutrient characteristics. There were strong positive relationships between SOC, effective cation exchange capacity, total nitrogen, calcium, magnesium and calcium, zinc, electrical conductivity, and copper. The significant soil organic matter accumulation in the groves accounts for the overall improved soil characteristics over the adjoining arable lands. Preserving the groves and similar African ecosystems may be important in climate regulation, resources and biodiversity conservation, and ethnopharmacology for rural communities. Thus, a question arises: should more land be set aside for ecological conservation or for agricultural productivity?

Land cover changes and carbon dynamics in Central India's dry tropical forests: A 25-year assessment and nature-based eco-restoration approaches

Anthropogenic land use and land cover changes are major drivers of environmental degradation and declining soil health across heterogeneous landscapes in Central India. To examines the land cover changes and spatio-temporal variations in forest carbon stock and soil organic carbon (SOC) over the past 25 years in central India. Geospatial techniques, coupled with ground measurements were employed to detect changes in land cover, carbon stocks in vegetation, and soil carbon in various vegetation types. The results indicate that forested areas have decreased, while agriculture and habitation have expanded between 1997 and 2022. Vegetation C stocks varied significantly (P < 0.05) from 39.42 to 139.95 Mg ha-1 and the SOC varied from 7.02 to 17.98 Mg ha-1 under different soil profiles across vegetation types, which decreased with soil depth, while the pH and bulk density increased. The maximum bulk density in the soil was found at a depth of 40-60 cm (lower profile) in Bamboo Brake, while the minimum was observed under Dense Mixed Forest at a depth of 0-20 cm (top profile). The topsoil profile contributed 33.6%-39%, the middle profile (20-40 cm) was 33.6%-34.4%, and the lower profile was 26.5%-30.8% of soil organic carbon. The study site has experienced rapid carbon losses due to changes in land cover, such as illegal expansion of agriculture, encroachments into forest fringes, and activities like selective logging and overgrazing, which have degraded dense forests. The ecological engineering of degraded ecosystems poses a great challenge and application of complex biological, mechanical and engineering measures is highly cumbersome, expensive, uneconomical and practically not feasible for upscaling. Nevertheless, proposed nature-based solutions mimic natural reparation and processes provide sustainable interventions for the reclamation of ruined landscapes besides improving ecological integrity and rendering many co-benefits to ecosystems and human societies.

Land cover change in global drylands: A review

As a sensitive region, identifying land cover change in drylands is critical to understanding global environmental change. However, the current findings related to land cover change in drylands are not uniform due to differences in data and methods among studies. We compared and judged the spatial and temporal characteristics, driving forces, and ecological effects by identifying the main findings of land cover change in drylands at global and regional scales (especially in China) to strengthen the overall understanding of land cover change in drylands. Four main points were obtained. First, while most studies found that drylands were experiencing vegetation greening, some evidence showed decreases in vegetation and large increases in bare land due to inconsistencies in the datasets and the study phases. Second, the dominant factors affecting land cover change in drylands are precipitation, agricultural activities, and urban expansion. Third, the impact of land cover change on the water cycle, especially the impact of afforestation on water resources in drylands, is of great concern. Finally, drylands experience severe land degradation and require dataset matching (classification standards, resolution, etc.) to quantify the impact of human activities on land cover.

Analysis of land cover dynamics in Mozambique (2001–2016)

Land cover change (LCC) is a complex and dynamic process influenced by social, economic, and biophysical factors that can cause significant impacts on ecological processes and biodiversity conservation. The assessment of LCC is particularly relevant in a country like Mozambique where livelihood strongly depends on natural resources. In this study, LCC was assessed using a point-based sampling approach through Open Foris Collect Earth (CE), a free and open-source software for land assessment developed by the Food and Agriculture Organization of the United Nations. This study aimed to conduct an LCC assessment using CE for the entire Mozambique, and according to three different land classifications: administrative boundaries (provinces), ecoregions, and protected vs unprotected areas. A set of 23,938 randomly selected plots, with an area of 0.5 hectares, placed on a 4 × 4 km regular grid over the entire country, was assessed using CE. The analysis showed that Mozambique has gone through significant loss of forest (− 1.3 Mha) mainly to the conversion to cropland. Deforestation is not occurring evenly throughout the country with some provinces, such as Nampula and Zambezia, characterized by higher rates than others, such as Gaza and Niassa. This result can be explained considering a combination of ecological and socio-economic factors, as well as the conservative role played by the protected areas. Our study confirmed that LCC is a complex phenomenon, and the augmented visual interpretation methodology can effectively complement and integrate the LCC analyses conducted using the traditional wall-to-wall mapping to support national land assessment and forest inventories and provide training data for environmental modeling.

Soil quality cannot be improved after thirty years of land use change from forest to rangeland

Soil quality can be assessed by measuring its physical, chemical and biological properties. In terrestrial ecosystems, the knowledge of the status of soil quality under different land use/cover can increase our understanding of processes related to soil functioning and help to properly managing ecosystems and increase their services. Conversion of the forest to rangelands is one of the most common forms of land use change having a significant effect on soil quality indicators. Here, we addressed the following objectives: (ii) to study the current status of soil physical, chemical and biological characteristics after more than thirty years of land use change from forest (dominated by Carpinus betulus and Parrotia persica) to rangeland, and (ii) to provide an overview of the spatial distributions of soil properties in forest and rangeland covers using a geostatistical method. For this, two sites (i.e., forest and rangeland) were selected in northern Iran. Within each site, 50 soil samples were collected at 0-10 cm depth along two sampling lines (250 m length) with a total of 100 soil samples for each site. Results showed that following the change of land use from forest to rangeland soil porosity, aggregate stability, pH, electrical conductivity and nutrient (i.e., total N and available P, K, Ca and Mg) contents increased, whereas soil bulk density and C/N ratio decreased. In addition, the population of soil biota (i.e., earthworms, acarina, collembola, nematode, protozoa, bacteria and fungi), microbial and enzyme activities decreased after more than thirty years of land use change from forest to rangeland. Principal component analysis confirmed that forest site had a more fertile soil and a higher biological activity than rangeland cover. Based on heat plots of soil properties, forest ecosystems created hot spots of soil quality indicators in the study area. Based on the geostatistical approach, most of the soil variables in the rangeland site followed a linear model, while in the forest site, most models were exponential and spherical. The fractal dimension values of the soil properties in the forest (1.62-1.99) had larger variations than in the rangeland (1.75-1.99) site. As a general conclusion, soil quality was not improved after more than thirty years of land use change from forest to rangeland, suggesting that degraded forest habitats should be restored by native tree species rather than converted to other land uses.

Identification and Assessment of the Driving Forces behind Changes in the Foothill Landscape: Case Studies of the Mysłakowice and Jelenia Góra Communities in Poland

The main objective of this study was to determine the driving forces behind landscape change and the perceptions of change by the residents of selected research areas. The communities used for the study were Mysłakowice and Jelenia Góra, located in the Lower Silesia region in Poland. Mysłakowice is a rural community, and Jelenia Góra is an urban community. The landscape of both municipalities is dominated by forest-covered mountains surrounding dispersed built-up and agricultural areas. The time range of the analysis was 2005-2020, covering the period after Poland's accession to the European Union, and was divided into the following three time periods: 2005-2010, 2010-2015, and 2015-2020. The research methodology consisted of the following three stages: (1) the identification of landscape changes on the basis of land cover data and the calculation of the landscape change index (LCI), (2) the characterization and classification of the identified landscape changes, and (3) the identification of the driving forces of landscape changes through surveys with the residents of both municipalities. The results obtained based on the surveys were often consistent with the results from the GIS analysis. The respondents were able to identify the most important changes and proposed the driving forces affecting them. According to the residents of Mysłakowice and Jelenia Góra, the changes in the landscape between 2005 and 2020 were primarily the result of political and socio-economic driving forces, accompanied by forces from other groups. However, each time period was distinctive. The analysis showed which types of changes in the landscape were viewed positively and negatively by the people during the analyzed periods of time, and what the influence of the different driving forces was on the formation of changes in the landscape.

Linking Pattern to Process: Intensity Analysis of Land-Change Dynamics in Ghana as Correlated to Past Socioeconomic and Policy Contexts

Spatio-temporal analysis of transitions in land cover is critical to understanding many ecological challenges, especially in environmentally vulnerable regions. For instance, in Sub-Saharan Africa, large-scale cropland expansion is expected due to the increasing demand for fuel, food, and fibre. Clearing land for cropland expansion is a driving factor in the degradation of natural ecosystems. We present a spatio-temporal analysis of land-cover change in Ghana’s Northern, Upper East, and Upper West provinces using Intensity Analysis on the periods from 1992 to 2003 and 2003 to 2015. The objectives of this study were to determine whether the intensity of land-use and land-cover (LULC) change is consistent between the two periods and to investigate the direction and extent of change for different LULC categories in northern Ghana. The methodology measures land-cover changes at the interval, category, and transition levels. The results suggest that the annual rate of land change was higher between 1992 and 2003 compared to that between 2003 and 2015. Furthermore, the category-level analysis reveals that the gains in the arable land and tree/forest-cover classes during both time intervals were higher than the uniform intensity. The transition-level analysis results indicate that most of the gains in arable land and tree/forest-cover came at the cost of semi-arid shrublands during both periods. There is also evidence of local increases in forest-cover, likely linked to afforestation policies established by the Ghanian government; however, overall, there has been a loss of natural habitat. The study provides data to improve our understanding of the magnitude and direction of land-cover change, essential for the development of policies designed to mitigate the impact of land-cover change on the livelihoods of local people and the environment at the national and sub-national levels.

How do varying socio-economic factors affect the scale of land transfer? Evidence from 287 cities in China

With the rapid development of China's social economy, the scale of land transfer has also increased, which has led to a new pattern of urban land space. This article uses global regression of ordinary least squares (OLS), spatial lag model (SLM), spatial error regression model (SEM) and local regression of geographically weighted regression model (GWR), and multi-scale geographically weighted regression model (MGWR) to explore the influence of socio-economic factors on the scale of land transfer. The relationship between these factors and the scale of land transfer varies greatly from region to region. The local model (MGWR) can express the non-stationary relationship between variables, and the regression estimation results are more robust. The results show that total investment in fixed assets (TIFA) and the non-agricultural population (NAP) had significant effects on the scale of land transfer in 2005, with regression coefficients of 0.964 and -0.247, respectively. In 2010, per capita GDP (PCG), population density (PD), proportion of tertiary industry in GDP (PTIG), and TIFA had significant impacts on the scale of land transfer, and the corresponding impact coefficients were 0.413, -0.085, -0.081, and 0.322. In 2015, the variable of PCG had significant impact on land transfer, with the coefficient of 0.048. The influencing factors of the scale of land transfer are changing at different points in time, and the formulation of land transfer policies should be treated differently according to the different socio-economic conditions in each period.

Land Cover Change Detection and Subsistence Farming Dynamics in the Fringes of Mount Elgon National Park, Uganda from 1978–2020

Analyzing the dominant forms and extent of land cover changes in the Mount Elgon region is important for tracking conservation efforts and sustainable land management. Mount Elgon’s rugged terrain limits the monitoring of these changes over large areas. This study used multitemporal satellite imagery to analyze and quantify the land cover changes in the upper Manafwa watershed of Mount Elgon, for 42 years covering an area of 320 km2. The study employed remote sensing techniques, geographic information systems, and software to map land cover changes over four decades (1978, 1988, 2001, 2010, and 2020). The maximum likelihood classifier and post-classification comparison technique were used in land cover classification and change detection analysis. The results showed a positive percentage change (gain) in planted forest (3966%), built-up (890%), agriculture (186%), and tropical high forest low-stocked (119%) and a negative percentage change (loss) in shrubs (−81%), bushland (−68%), tropical high forest well-stocked (−50%), grassland (−44%), and bare and sparsely vegetated surfaces (−14%) in the period of 1978–2020. The observed changes were concentrated mainly at the peripheries of the Mount Elgon National Park. The increase in population and rising demand for agricultural land were major driving factors. However, regreening as a restoration effort has led to an increase in land area for planted forests, attributed to an improvement in conservation-related activities jointly implemented by the concerned stakeholders and native communities. These findings revealed the spatial and temporal land cover changes in the upper Manafwa watershed. The results could enhance restoration and conservation efforts when coupled with studies on associated drivers of these changes and the use of very-high-resolution remote sensing on areas where encroachment is visible in the park.

Farmer Heterogeneity and Land Transfer Decisions Based on the Dual Perspectives of Economic Endowment and Land Endowment

Guiding qualified farmers to transfer their land is an important way to alleviate the problem of land abandonment, improve land use efficiency, and achieve moderately large-scale land management. Based on the dual perspectives of economic endowment and land endowment, this paper uses the 2015 data of the China Household Finance Survey (CHFS), using the semilogarithmic ordinary least-squares method and the logit model, to explore differences in land transfer decisions under the effect of farmer heterogeneity. The circulation trading market was further improved to provide a reference. The heterogeneity of economic endowment and land endowment significantly affects the decision-making behavior of farmers in transferring land. The higher the land endowment is, the greater the probability that farmers transfer the land out and successfully trade, and they are more inclined to transfer the cultivated land to cooperatives, village collectives, and other institutions through formal channels, leading to a higher unit income of the transfer. Further research shows that land endowment has no significant difference in the impact of land endowment on whether farmers with different livelihood endowments transfer their land, but under the same land endowment, farmers with economic endowment advantages are more able to use their own endowment advantages to transfer their land out through formal channels and obtain higher gains income. Therefore, focusing on improving the conditions of land resources and increasing the endowment of farmers are important means to promote successful transactions in the land transfer market, ensure its sustainable operation, and promote further increase in the income of transfer farmers.

Citizens' Perceptions of Landscape Changes and Their Driving Forces: Evidence from Poland

The main aim of our studies was to explore the driving forces of landscape change and their impact on the landscape as perceived by citizens in our study. We use quantitative tools for unravelling processes of landscape change over time and a qualitative tool aimed at capturing people's perceptions about those changes. We use the two municipalities of Ostrów Wielkopolski and Kąty Wrocławskie as illustrative examples of urban and urban-rural municipalities in two time periods, 2006-2021 and 2012-2018, in Poland. We apply a three-stage approach: (1) to identify the main landscape changes based on land-cover data, (2) to characterize those changes with the use of orthophoto maps and (3) to identify the driving forces of landscape changes with the use of an online survey and interviews. The results show a large agreement between the perceived and actual level of changes. We identified key landscape change processes in both municipalities, and we conclude that citizens' perceptions concerning those processes in both municipalities differed depending on the context, the level of changes, and the way this process was planned and implemented. In both municipalities, the respondents pointed out political driving forces of landscape change as key underlying drivers. Future landscape planning should consider citizens' approaches towards landscape change to achieve better societal approval and improve the quality of life of the inhabitants.

Dynamic Landscape Fragmentation and the Driving Forces on Haitan Island, China

Island ecosystems have distinct and unique vulnerabilities that place them at risk from threats to their ecology and socioeconomics. Spatially exhibiting the fragmentation process of island landscapes and identifying their driving factors are the fundamental prerequisites for the maintenance of island ecosystems and the rational utilization of islands. Haitan Island was chosen as a case study for understanding landscape fragmentation on urbanizing Islands. Based on remote sensing technology, three Landsat images from 2000 to 2020, landscape pattern index, transect gradient analysis, and moving window method were used in this study. The results showed that from 2000 to 2020, impervious land increased by 462.57%. In 2000, the predominant landscape was cropland (46.34%), which shifted to impervious land (35.20%) and forest (32.90%) in 2020. Combining the moving window method and Semivariogram, 1050 m was considered to be the best scale to reflect the landscape fragmentation of Haitan Island. Under this scale, it was found that the landscape fragmentation of Haitan Island generally increased with time and had obvious spatial heterogeneity. We set up sampling bands along the coastline and found that the degree of landscape fragmentation, advancing from the coast inland, was decreasing. Transects analysis showed the fragmentation intensity of the coastal zone: the north-western and southern wooded zones decreased, while the concentration of urban farmland in the north-central and southern areas increased. The implementation of a comprehensive experimental area plan on Haitan Island has disturbed the landscape considerably. In 2000, landscape fragmentation was mainly influenced by topography and agricultural production. The critical infrastructure construction, reclamation and development of landscape resources have greatly contributed to the urbanisation and tourism of Haitan Island, and landscape fragmentation in 2013 was at its highest. Due to China’s “Grain for Green Project” and the Comprehensive Territorial Spatial Planning policy (especially the protection of ecological control lines), the fragmentation of Haitan Island was slowing. This study investigated the optimal spatial scale for analyzing spatiotemporal changes in landscape fragmentation on Haitan Island from 2000 to 2020, and the essential influencing factors in urban islands from the perspective of natural environment and social development, which could provide a basis for land use management and ecological planning on the island.

Assessment of land use cover changes, carbon sequestration and carbon stock in dry temperate forests of Chilas watershed, Gilgit-Baltistan

Abstract Land use and land cover change are affecting the global environment and ecosystems of the different biospheres. Monitoring, reporting and verification (MRV) of these changes is of utmost importance as they often results in several global environmental consequences such as land degradation, mass erosion, habitat deterioration as well as micro and macro climate of the regions. The advance technologies like remote sensing (RS) and geographical information system (GIS) are helpful in determining/ identifying these changes. In the current study area, changes in carbon stocks, notably in forest areas, are resulting in considerable dynamics of carbon stocks as a result of climate change and carbon sequestration. This study was carried out in the Diamer district of the Gilgit Baltistan (GB) Pakistan to investigate the change in cover change/land use change (particularly Forest Land use) as well as carbon sequestration potential of the forests in the district during almost last 25years. The land cover, temporal Landsat data (level 1, LIT) were downloaded from the USGS EROS (2016), for 1979-1989, 1990-2000 and 2001-2012. Change in land uses, particularly forest cover was investigated using GIS techniques. Forest inventory was carried out using random sampling techniques. A standard plot of size 0.1 ha (n=80) was laid out to determine the tree density, volume, biomass and C stocks. Simulation of C stocks was accomplished by application of the CO2FIX model with the data input from inventory. Results showed a decrease in both forest and snow cover in the region from 1979-2012. Similarly decrease was seen in tree volume, tree Biomass, dynamics of C Stocks and decrease was in occur tree density respectively. It is recommended we need further more like project such as BTAP (Billion Tree Afforestation Project) and green Pakistan project to increase the forest cover, to control on land use change, protect forest ecosystem and to protect snow cover.

Land use planning to support climate change adaptation in threatened plant communities

Among the many causes of habitat loss, urbanization coupled with climate change has produced some of the greatest local extinction rates and has led to the loss of many native species. Managing native vegetation in a rapidly expanding urban setting requires land management strategies that are cognizant of these impacts and how species and communities may adapt to a future climate. Here, we demonstrate how identifying climate refugia for threatened vegetation communities in an urban matrix can be used to support management decisions by local government authorities under the dual pressures of urban expansion and climate change. This research was focused on a local government area in New South Wales, Australia, that is undergoing significant residential, commercial and agricultural expansion resulting in the transition of native forest to other more intensive land-uses. Our results indicate that the key drivers of change from native vegetation to urban and agriculture classes were population density and the proximity to urban areas. We found two of the most cleared vegetation community types are physically restricted to land owned or managed by council, suggesting their long-term ecological viability is uncertain under a warming climate. We propose that land use planning decisions must recognize the compounding spatial and temporal pressures of urban development, land clearing and climate change, and how current policy responses, such as biodiversity offsetting, can respond positively to habitat shifts in order to secure the longevity of important ecological communities.

Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea

North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001–2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% ± 1.6%), with corresponding kappa coefficients (0.959 ± 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.

Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach

The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study, we have focused on understanding the association of COVID-19 cases with environmental and socioeconomic factors in Zambia - a sub-Saharan African country. We used Zambia's district-level COVID-19 data, covering 18 March 2020 (i.e., from first reported cases) to 17 July 2020. Geospatial approaches were used to organize, extract and establish the dataset, while a classification tree (CT) technique was employed to analyze the factors associated with the COVID-19 cases. The analyses were conducted in two stages: (1) the binary analysis of occurrences of COVID-19 (i.e., COVID-19 or No COVID-19), and (2) a risk level analysis which grouped the number of cases into four risk levels (high, moderate, low and very low). The results showed that the distribution of COVID-19 cases in Zambia was significantly influenced by the socioeconomic factors compared to environmental factors. More specifically, the binary model showed that distance to the airport, population density and distance to the town centres were the most combination influential factors, while the risk level analysis indicated that areas with high rates of human immuno-deficient virus (HIV) infection had relatively high chances of having many COVID-19 cases compared to areas with low HIV rates. The districts that are far from major urban establishments and that experience higher temperatures have lower chances of having COVID-19 cases. This study makes two major contributions towards the understanding of COVID-19 dynamics: (1) the methodology presented here can be effectively applied in other areas to understand the association of environmental and socioeconomic factors with COVID-19 cases, and (2), the findings from this study present the empirical evidence of the relationship between COVID-19 cases and their associated environmental and socioeconomic factors. Further studies are needed to understand the relationship of this disease and the associated factors in different cultural settings, seasons and age groups, especially as the COVID-19 cases increase and spread in many countries.

The Spatiotemporal Dynamics of Land Use Land Cover Change, and Its Impact on Soil Erosion in Tagaw Watershed, Blue Nile Basin, Ethiopia

The Blue Nile basin is one of the hot-spots of soil erosion areas in Ethiopia. However, the impact of land use changes on soil erosion is poorly understood in the Tagaw watershed. Hence, the objective of the study is to assess the impact of land use changes on soil erosion in Tagaw watershed over the last 31 years. Rainfall, soil, satellite images and topographic data are acquired from field survey and secondary sources. A Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The mean annual and total potential soil losses of the watershed are 19.3, 22.9, 26 and 0.06-503.56, 0.11-516.67, and 0.00-543.5 tons ha-1 yr-1 for 1995, 2006 and 2016 respectively. The highest soil loss is found for bare land. The RUSLE model further showed that the highest soil erosion occurred in 2016 whereas the lowest soil erosion occurred in 1995.

Assessing Land Use and Land Cover Change and Farmers’ Perceptions of Deforestation and Land Degradation in South-West Côte d’Ivoire, West Africa

Deforestation and land degradation remain two major economic and environmental threats in Côte d’Ivoire. This study assessed land use and land cover (LULC) change and farmers’ perceptions of the drivers and effects of deforestation and land degradation in south-western Côte d’Ivoire. We used remotely sensed data to determine LULC change trends, and a household survey to collect farmers’ perceptions of deforestation and land degradation. A total of 411 households were interviewed using a structured questionnaire and the focus group discussions involved 25 farmers. Landsat image analysis reported a drastic LULC change and a conversion of forestlands into agriculture from 1987 to 2015 at a rate of 1.44%/year and 3.44%/year for dense forests and degraded forests, respectively. The household survey revealed that the major causes of deforestation perceived by farmers included population growth (79.3%), extensive agriculture (72.9%), migration (54.2%) and logging (47.7%). Land degradation evolved, from a shortened fallow period (46.7%) and an inappropriate application of inputs (31.4%). The perceived major effects linked to deforestation encompassed land degradation (70.6%), loss of biodiversity (63.8%), global warming (56.9%) and loss of livelihood assets (54.3%). Therefore, this study recommends participatory landscape planning, reforestation and capacity building of stakeholders for sustainable intensification of the production systems to reduce LULC challenges for enhanced productive and protective functions of remaining forests.

Benefits and Critical Knowledge Gaps in Determining the Role of Floating Photovoltaics in the Energy-Water-Food Nexus

Floating solar photovoltaic (FPV) systems have become an increasingly attractive application of photovoltaics (PV) because of land-use constraints, the cost of land and site preparation, and the perceived energy and environmental co-benefits. Despite the increasing interest in FPV systems, a robust validation of their suggested co-benefits and impacts on the nexus of energy, water, and food (EWF) systems is lacking. This information gap makes it challenging for decision makers to justify its adoption—potentially suppressing FPV deployment. To address this gap and to help de-risk this PV deployment opportunity, we (1) review the suggested co-benefits of FPV systems with a focus on the impacts that could alleviate pressures on EWF systems and (2) identify areas where further research is needed to reduce uncertainty around FPV system performance. Our review reveals that EWF nexus-relevant co-benefits, such as improved panel efficiency and reduced land usage, are corroborated in the literature, whereas others, such as water quality impacts, lack empirical evidence. Our findings indicate that further research is needed to quantify the water-related and broader economic, environmental, social, sustainability, justice, and resilience co-benefits and impacts of FPV systems.

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.

The Hidden Characteristics of Land-Use Mix Indices: An Overview and Validity Analysis Based on the Land Use in Melbourne, Australia

The land-use mix index is a way to quantify the mixture of land-use patterns. Due to practical limitations, few studies have highlighted the validity of land-use mix indices. This paper aims to explore the potential characteristics of land-use mix indices using a three-step screening method. The data precision of indices was concluded after the first-step screening. A total of 10 virtual blocks and 217 blocks in Melbourne city center served as a case study and reflected the various land-use structures. The randomized controlled comparative trial was incorporated into the second- and third-screening to indicate the applicable condition and validity. The results illustrate that the value Herfindahl–Hirschman index related to the diversity of land-use types. The results also confirmed that Dissimilarity index-I was significantly associated with the balance status of the land-use mix. Entropy index reflects the evenness but did not correlate to the diversity or balance of the land-use mix. In addition, the study also provides a set of general recommendations for the application conditions of land-use mix indices.

Approaches to interdisciplinary mixed methods research in land-change science and environmental management

Combining qualitative and quantitative methods and data is crucial to understanding the complex dynamics and often interdisciplinary nature of conservation. Many conservation scientists use mixed methods, but there are a variety of mixed methods approaches, a lack of shared vocabulary, and few methodological frameworks. We reviewed articles from 2 conservation-related fields that often incorporate qualitative and quantitative methods: land-change science (n = 16) and environmental management (n = 16). We examined how authors of these studies approached mixed methods research by coding key methodological characteristics, including relationships between method objectives, extent of integration, iterative interactions between methods, and justification for use of mixed methods. Using these characteristics, we created a typology with the goal of improving understanding of how researchers studying land-change science and environmental management approach interdisciplinary mixed methods research. We identified 5 types of mixed methods approaches, which we termed simple nested, informed nested, simple parallel, unidirectional synthesis, and bidirectional synthesis. Methods and data sources were often used to address different research questions within a project, and only around half of the reviewed papers methodologically integrated different forms of data. Most authors used one method to inform the other, rather than both informing one another. Very few articles used methodological iteration. Each methodological type has certain epistemological implications, such as the disciplinary reach of the research and the capacity for knowledge creation through the exchange of information between distinct methodologies. To exemplify a research design that can lead to multidimensional knowledge production, we provide a methodological framework that bidirectionally integrates and iterates qualitative and quantitative methods.

Land Cover Change in the Blue Nile River Headwaters: Farmers’ Perceptions, Pressures, and Satellite-Based Mapping

The headwaters of the Blue Nile River in Ethiopia contain fragile mountain ecosystems and are highly susceptible to land degradation that impacts water quality and flow dynamics in a major transboundary river system. This study evaluates the status of land use/cover (LULC) change and key drivers of change over the past 31 years through a combination of satellite remote sensing and surveying of the local understanding of LULC patterns and drivers. Seven major LULC types (forest land, plantation forest, grazing land, agriculture land, bush and shrub land, bare land, and water bodies) from Landsat images of 1986, 1994, 2007, and 2017 were mapped. Agriculture and plantation forest land use/cover types increased by 21.4% and 368.8%, respectively, while other land use/cover types showed a decreasing trend: water body by 50.0%, bare land by 7.9%, grassland by 41.7%, forest by 28.9%, and bush and shrubland by 38.4%. Overall, 34.6% of the landscape experienced at least one LULC transition over the past 31 years, with 15.3% representing the net change and 19.3% representing the swap change. The percentage change in plantation forest land increased with an increasing altitude and slope gradient during the study period. The mapped LULC changes are consistent with the pressures reported by local residents. They are also consistent with root causes that include population growth, land tenure and common property rights, persistent poverty, weak enforcement of rules and low levels of extension services, a lack of public awareness, and poor infrastructure. Hence, the drivers for LULC should be controlled, and sustainable resources use is required; otherwise, these resources will soon be lost and will no longer be able to play their role in socioeconomic development and environmental sustainability.

Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos

Land use/cover change (LUCC) is one of the causes of global climate and environmental change. Understanding rapid LUCC in urbanized areas is vital for natural resources management for sustainable development. This study primarily considered Vientiane, the capital of Laos, which experienced rapid LUCC due to both natural and anthropogenic factors. The study used geographical information system (GIS) combined with ERDAS and TerrSet technologies to objectively process the ground surveyed and remotely obtained data in order to investigate the historical LUCC as well as predict future LUCC in the study area during the periods of 1995–2018 and 2030–2050, respectively. A comprehensive list of assessment factors comprised of both natural and anthropogenic factors was used for analysis using the cellular automata–Markov (CA–Markov) model. The results show a historical loss of intact forest of 24.36% and of bare land of 1.01%. There were also tremendous increases in degraded forest (11.36%), agricultural land (8.91%), built-up areas (4.49%) and water bodies (1.16%). Finally, the LUCC prediction results indicate the conversion of land use from one type to another, particularly from natural to anthropogenic use, in the near future. These changes demonstrate that the losses associated with ecosystem services will destructively impact human wellbeing in the city and other areas of the country. The study results provide the basic scientific knowledge for LUCC planners, urban designers and natural resources managers. They serve as a decision-making support tool for the establishment of sustainable land resource utilization policies in Vientiane and other cities of similar conditions.

Ecological Risk Assessment Based on Land Cover Changes: A Case of Zanzibar (Tanzania)

Land use and land cover (LULC) under improper land management is a major challenge in sub-Saharan Africa and has drastically affected ecological security. Addressing environmental impacts related to this challenge requires efficient planning strategies based on the measured information of land use patterns. This study assessed the ecological risk index (ERI) of Zanzibar based on LULC. A random forest classifier was used to classify three Landsat images of Zanzibar for the years 2003, 2009, and 2018. Then, a land change model was employed to simulate the LULC changes for 2027 under a business-as-usual (BAU), conservation, and extreme scenarios. Results showed that the built-up areas and farmland of Zanzibar Island have increased constantly, while the natural grassland and forest cover have decreased. The forest, agricultural, and grassland were highly fragmented into several small patches. The ERI of Zanzibar Island increased at a constant rate and, if the current trend continues, this index will increase by up to 8.9% in 2027 under an extreme scenario. If a conservation scenario is adopted, the ERI will increase by 4.6% whereas if a BAU policy is followed, this value will increase by 6.2%. This study provides authorities with useful information to understand better the ecological processes and LULC dynamics and prevent unmanaged growth and haphazard development of informal housing and infrastructure.

Does Land-Use Policy Moderate Impacts of Climate Anomalies on LULC Change in Dry-Lands? An Empirical Enquiry into Drivers and Moderators of LULC Change in Southern Ethiopia

The study set out to understand drivers of Land-Use Land Cover (LULC) changes in dry-land areas and investigate factors helping mitigate the adverse impacts of climate anomalies on LULC changes. By employing a mixed-methods design, it combined LULC data with socioeconomic and climatic data, to analyze the pattern of LULC changes and its socioeconomic and climatic driving forces along with moderating factors. It was found that rangeland decreased by 764 km2 (13% of total area) between 1986 and 2015. The results from the Seemingly Unrelated time series regression models confirmed preliminary evidence that climate variability, as well as adaptive land-use policies lacking components of sustainability increase the likelihood of degradation and contraction of rangelands. We also found an indication from the qualitative data that a widening power gap between the customary and statutory governance system reinforces unsustainable land use by obscuring the values of the customary land governance system. However, those policies encompassing economic and natural resource development objectives abate adverse effects of climate variability on land degradation and shrinkage of rangelands. The results suggest that a land governance system with natural resource development objectives fitting to the local context could be an effective policy instrument to lessen the adverse effects of climate anomalies on LULC changes. Although this study focused on analyzing the LULC changes and its drivers in dry-land area, the findings may well have a bearing on the formulation and implementation of effective adaptation and sustainable land-use policies.

Small Reservoirs, Landscape Changes and Water Quality in Sub-Saharan West Africa

Small reservoirs (SRs) are essential water storage infrastructures for rural populations of Sub-Saharan West Africa. In recent years, rapid population increase has resulted in unprecedented land use and land cover (LULC) changes. Our study documents the impacts of such changes on the water quality of SRs in Burkina Faso. Multi-temporal Landsat images were analyzed to determine LULC evolutions at various scales between 2002 and 2014. Population densities were calculated from downloaded 2014 population data. In situ water samples collected in 2004/5 and 2014 from selected SRs were analyzed for Suspended Particulate Matter (SPM) loads, an integrative proxy for water quality. The expansion of crop and artificial areas at the expense of natural covers controlled LULC changes over the period. We found a very significant correlation between SPM loads and population densities calculated at a watershed scale. A general increase between the two sampling dates in the inorganic component of SPM loads, concomitant with a clear expansion of cropland areas at a local scale, was evidenced. Results of the study suggest that two complementary but independent indicators (i.e., LULC changes within 5-km buffer areas around SRs and demographic changes at watershed scale), relevantly reflected the nature and intensity of overall pressures exerted by humans on their environment, and locally on aquatic ecosystems. Recommendations related to the re-greening of peripheral areas around SRs in order to protect water bodies are suggested.

Landscape Management through Change Processes Monitoring in Iran

The presented research investigated and predicted landscape change processes (LCPs) in the Talar watershed, northern Iran. The Land Change Modeler was used for change analysis, transition potential modeling, and prediction of land use/land cover (LULC) map. The evaluation of projected LULC map was performed by comparing the real and predicted LULC maps for the reference year, 2014. Landscape metrics and change processes were investigated for the period 1989–2014 and for exploring the situation in 2030. Results illustrated that the increase in agricultural land and residential areas took place at the expense of forest and rangeland. The distance from forests was the most sensitive parameter for modeling the transition potentials. The modelling of the LULC change projected the number of patches, the landscape shape index, interspersion and juxtaposition index, and edge density, Euclidean nearest-neighbor distance, and area-weighted shape index will amount to 65.3, 7.63, 20.1, 8.77, −1.35, and 0.61% as compared to 2014, respectively. Our findings indicated that the type of change processes that occurred was not entirely the same in 1989–2000 and 2000–2014. In addition, change processes in the creation of dry farming, orchard, and residential classes, attrition of forest and rangeland categories, and dissection in irrigated farming are projected. The dynamics of landscape metrics and change processes combined in one analytical framework can facilitate understanding and detection of the relationship between ecological processes and landscape pattern. The finding of current research will provide a roadmap for improved LULC management and planning in the Talar watershed, southern coast of the Caspian Sea.

Linking Land Tenure and Integrated Watershed Management—A Review

Land tenure is given attention in the general discussions on conservation and management of natural resources, but the necessary holistic approach to understand the linkages is less considered. Thus, we considered a watershed as a unit of reference and Integrated Watershed Management as a holistic land and water resources management approach with various roles and touchpoints with land tenure issues. To examine the role of land tenure on the management of natural resources in watersheds, we reviewed and compiled literature that captures watershed issues, integrating aspects of land tenure, and aiming to identify the key land tenure roles, dynamics, and its influences on integrated watershed management. Land tenure is observed playing various roles in watersheds and, thus, also on integrated watershed management as an approach—as a driver of change, influence for investment decisions, an incentive for adoption of practices, and leading to sustainability. Land tenure dynamics range from land tenure security, land tenure forms, land access and acquisition modalities, and how these aspects of land tenure relate with integrated watershed management.

Long-term land cover change in Zambia: An assessment of driving factors

Land cover change (LCC) has significant effects on the global ecosystem diversity and function. This topic has received increasing attention due, in part, to its relationship with climate change, and the availability of remotely-sensed imagery that is used to monitor LCC. However, studies analysing the factors that drive LCC at large spatial scales and over long temporal scales are uncommon. This study aimed to identify the factors driving long-term (44 years, 1972-2016) national level LCC in Zambia. Two analyses were conducted, with the first considering factors that led to any LCC. The second scenario identified factors associated with changes from forests to other land covers, and the reversion to forests from non-forested covers. Candidate factors considered in both analyses include accessibility, proximity, topography, climate, conservation and socioeconomics. A classification tree (CT) approach was used to relate the explanatory candidate factors to LCC. The results showed that the CT models predicted LCC with accuracies ranging from 71 to 85%. The first analysis showed that the major factors determining LCC were percentage of area under agriculture, distance to water bodies, change in crop yield, mean temperature and elevation. Meanwhile, the second analysis showed that primary, secondary and plantation forest cover losses were mainly influenced by human population density, crop yield per hectare and mean crop yield, respectively. Protection status was the most important factor for forest reversion and recovery, while a variety of factors including distance to the railway, elevation and total precipitation also influenced forest reversion and recovery. The findings from this study provide insights into the factors that influence LCC and are important for developing effective policies to reduce the negative impacts of LCC and to promote forest reversion and recovery through effective management of protected areas. While this study focused on factors associated with historical LCC, the findings will also help to predict and understand future LCC scenarios.

The Impact of Land Use/Land Cover Change (LULCC) on Water Resources in a Tropical Catchment in Tanzania under Different Climate Change Scenarios

Many parts of sub-Saharan Africa (SSA) are prone to land use and land cover change (LULCC). In many cases, natural systems are converted into agricultural land to feed the growing population. However, despite climate change being a major focus nowadays, the impacts of these conversions on water resources, which are essential for agricultural production, is still often neglected, jeopardizing the sustainability of the socio-ecological system. This study investigates historic land use/land cover (LULC) patterns as well as potential future LULCC and its effect on water quantities in a complex tropical catchment in Tanzania. It then compares the results using two climate change scenarios. The Land Change Modeler (LCM) is used to analyze and to project LULC patterns until 2030 and the Soil and Water Assessment Tool (SWAT) is utilized to simulate the water balance under various LULC conditions. Results show decreasing low flows by 6–8% for the LULC scenarios, whereas high flows increase by up to 84% for the combined LULC and climate change scenarios. The effect of climate change is stronger compared to the effect of LULCC, but also contains higher uncertainties. The effects of LULCC are more distinct, although crop specific effects show diverging effects on water balance components. This study develops a methodology for quantifying the impact of land use and climate change and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes (low flow and floods) and determines hot spots, which are critical for environmental development.

Optimization of the National Land Space Based on the Coordination of Urban-Agricultural-Ecological Functions in the Karst Areas of Southwest China

National land spatial planning is dominated by urban-agricultural-ecological functions and has become a Chinese national strategic issue. However, the three functional spaces have serious conflicts in the karst areas, causing inconsistencies in regional development and triggering poverty and a more serious situation for the ecological environment. In this study, we used the gray multi-objective dynamic programming model and the conversion of land use and its effects at small region extent model to simulate the developmental structures of future land use in the karst areas of Southwest China under a socioeconomic development scenario, an arable land protection scenario and an ecological security scenario. Finally, based on the coordination of the urban-agricultural-ecological functions, we used a functional space classification method to optimize the spatial structures of the national land space for 2035 year and to identify different functional areas. The results showed that the three scenarios with different objectives had differences in the quantities and spatial structures of land use but that the area of forestland was the largest and the area of water was the smallest in each scenario. The optimization of the national land space was divided into seven functional areas—urban space, agricultural space, ecological space, urban-agricultural space, urban-ecological space, agricultural-ecological space and urban-agricultural-ecological space. The ecological space was the largest and the urban-ecological space was the smallest among seven functional areas. The different types of functional spaces had significant differentiation characteristics in the layouts. The urban-agricultural space, urban-ecological space, agricultural-ecological space and urban-agricultural-ecological space can effectively alleviate the impacts of human activities and agricultural production activities in karst areas, promote the improvement of rocky desertification and improve the quality of the regional ecological environment. The results of this research can provide support for decisions about the balanced development of the national land space and the improvement of environmental quality in the karst areas.

Spatiotemporal dynamics of urbanization and cropland in the Nile Delta of Egypt using machine learning and satellite big data: implications for sustainable development

The Nile Delta of Egypt is increasingly facing sustainability threats, due to a combination of nature- and human-induced changes in land cover and land use. In this paper, an analysis of big time series data from remotely sensed satellite images and the random forests classifier was undertaken to assess the spatial and temporal dynamics of urbanization and cropland in the Nile Delta between 2007 and 2017. Out of thirteen variables, five spectral indices were chosen to build 500 decision trees, with a resulting overall accuracy average of 91.9 ± 1.5%. The results revealed that the urban extent in the Nile Delta has increased, between 2007 and 2017, by 592.4 km² (1.92%). Particularly, the results indicated that the years 2011 and 2012, which coincided the 2011 political uprising in Egypt, so-called the Arab Spring, were associated with significant land-use changes in the Nile Delta, both in rate and scale. As a result, the cropland area in the region decreased between 2010 and 2011 by 1.63% (502.21 km²). Moreover, the results showed that during the period 2012-2017, the mean annual urbanization rate in the region stood at 60 km²/year. In contrast, croplands decreased during the same period at an average annual rate of 2 km²/year. At the governorates' level, the results suggested that top agricultural producing governorates in the Nile Delta, such as Elmonoufia, Elkalubia, Elbouhyra, and Elghrbia, witnessed the highest rates of decrease in cropland areas during the period 2012-2017. Over the same period, urban areas increased the most in Elkalubia, Domiate, and Elmonoufia by 1.98%, 1.72%, and 1.34%, respectively. The f indings from this analysis are discussed along with their implications for sustainable land-use and urban planning policies.

Short-Term Forecasting of Land Use Change Using Recurrent Neural Network Models

Land use change (LUC) is a dynamic process that significantly affects the environment, and various approaches have been proposed to analyze and model LUC for sustainable land use management and decision making. Recurrent neural network (RNN) models are part of deep learning (DL) approaches, which have the capability to capture spatial and temporal features from time-series data and sequential data. The main objective of this study was to examine variants of the RNN models by applying and comparing them when forecasting LUC in short time periods. Historical land use data for the City of Surrey, British Columbia, Canada were used to implement the several variants of the RNN models. The land use (LU) data for years 1996, 2001, 2006, and 2011 were used to train the DL models to enable the short-term forecast for the year 2016. For the 2011 to 2016 period, only 4.5% of the land use in the study area had changed. The results indicate that an overall accuracy of 86.9% was achieved, while actual changes in each LU type were forecasted with a relatively lower accuracy. However, only 25% of changed raster cells correctly forecasted the land use change. This research study demonstrates that RNN models provide a suite of valuable tools for short-term LUC forecast that can inform and complement the traditional long-term planning process; however, further additional geospatial data layers and considerations of driving factors of LUC need to be incorporated for model improvements.

Dynamic simulation of land use change based on logistic-CA-Markov and WLC-CA-Markov models: a case study in three gorges reservoir area of Chongqing, China

The construction of The Three Gorges Reservoir has changed land use structure and reconstituted landscape pattern as imparts significant influence upon the land use structure and ecological environment of Three Gorges Reservoir Regions. The ecological safety of reservoir area is extremely dependent on unique location and special geological conditions of Zhongxian County, the center of Three Gorges Reservoir Regions in Chongqing, and therefore, ecological environment of reservoir area will be changed with the transition of land use in Zhongxian County. Based on land use data in 2000, 2005, 2010, this paper chooses influencing factors from aspects of natural topographic and geomorphological conditions, accessibility to economic development and land use expansion, and then establishes Logistic-CA-Markov (Logistic-Cellular Automata-Markov) and WLC-CA-Markov (Weighted Linear Combination- Cellular Automata- Markov) models so as to simulate spatial pattern of land use of Zhongxian County. The results demonstrate that WLC-CA-Markov model established here has better controllability and higher simulation precision (the kappa coefficient is 0.9295). In the future development of Zhongxian County, the area of grassland and plow land will be reduced continuously, the area of construction land will be expanded obviously mostly because of the added area both near the water and in the north of Zhongxian county, the area of woodland will be increased to a little extent, the area of water area and unused land has gentle change. In the sustainable scenario, the area of grassland will be reduced slightly, the area of water area keeps steady, the area of plow land is reduced but higher than red line of plow land, the area of construction land is increased with significantly smaller increase amplitude than that in the natural development scenario, and the woodland is increased. This scenario coordinates ecological environment with economic development of regional society and turns out to be the best development scenario of land use.

Land Use and Land Cover Changes in the Owabi Reservoir Catchment, Ghana: Implications for Livelihoods and Management

Reservoir catchments in Ghana have undergone significant changes in recent years with major implications for socio-economic development and local livelihoods. We studied land use and land cover changes and their impacts on livelihoods in the Owabi reservoir catchment from 1970 to 2014 using Landsat, ERDAS Imagine and Arc Geographic Information System (ArcGIS 10.2) software supplemented with participatory approaches including focus group discussions, key informant interviews and questionnaire surveys with 400 households. Our results showed that, since 1970, 24.6% of high-density forests and 15.8% of sparse forests have disappeared, while the built-up area has increased from 9.8% to 56.6%. Additionally, the proportion of bare soil (areas that do not have vegetation cover due to forest clearing and other anthropogenic activities) has increased, while the areas of waterbodies have declined. We identified urbanisation and lack of community involvement in catchment management as the key factors driving the land cover changes that have adversely affected the livelihoods of the local fringe communities. This study highlights the threats from urbanisation to land cover changes and identifies the key drivers of land use change. For effective and sustainable management of natural resources, the local communities should be more actively involved in the decision-making process regarding the management of their individual catchments.

Defining Deforestation Patterns Using Satellite Images from 2000 and 2017: Assessment of Forest Management in Miombo Forests—A Case Study of Huambo Province in Angola

A few studies have recently been published on changes in land use/land cover (LU/LC) of Angolan Miombo forests, however, none have attempted to offer forest management solutions for degraded Miombo forests. Landscapes are witness to past and present natural and social processes influencing the environment, where each period in the past leaves footprints on the landscape’s development, which can be described by a continual decrease in forest area over time. The expansion of degraded areas from 2000 to 20017 began near urban areas where many Miombo forests have been eliminated or highly degraded, particularly in the southwest and northeast of the Huambo province. Large areas of degraded forests were observed along the Benguela railway (Caminho de ferro de Benguela). Our detailed analysis of the landcover map suggests that the impact has been devastating and there is no form of forest protection, which leads to unregulated exploitation. Descriptions of the Miombo forest dynamics are explained using height–diameter curves developed for different vegetation types that provide important insights about forest structures in the management zones. The height–diameter models differed for all vegetation types, and four management zones (MZ) were created based on a set of particular attributes. The vegetation types differed in each management zone, which included agricultural land and bare soil (MZ–E), grassland or savanna (MZ–C), open Miombo forests (MZ–B), and closed Miombo forests (Miombo forests). The four management zones were easily identified on the available maps and the height–diameter models developed represent a fundamental tool for future studies on forest planning.