scholarly journals Data-Driven Forest Cover Change and Its Driving Factors Analysis in Africa

2022 ◽  
Vol 9 ◽  
Author(s):  
Han Xiao ◽  
Jianbo Liu ◽  
Guojin He ◽  
Xiaomei Zhang ◽  
Hua Wang ◽  
...  
Keyword(s):  
West Africa ◽  
North Africa ◽  
Forest Cover ◽  
Arable Land ◽  
Forest Area ◽  
Target Area ◽  
Forest Cover Change ◽  
African Region ◽  
Unequal Distribution ◽  
Area Reduction

Forest cover plays an important role in sustaining ecological security to realize Sustainable Development Goals (SDGs). The research target area is composed of the African region which is experiencing unprecedented deforestation based on the data collection from 54 countries and regions between 2000 and 2020. Spatial autocorrelation analysis, global principal component analysis, and geographic detector model have been used as the core research tool. The temporal and spatial patterns of forest cover change in Africa and the driving effects of population growth, economic and trade, social development, arable land expansion, and other factors on forest cover change in different periods have been demonstrated. The findings are as follows: 1) extremely unequal distribution of Africa forest has caused forest area reduction in 20 years. The reduction quantity of forest has been illustrated from strong to weak: Central Africa (strongest), East Africa (higher strong), West Africa (medium), South Africa (higher weak), and North Africa (weakest). However, the forest reduction area in West Africa with the original ratio is the most significant. More than 80% of the forest area reduction in Africa has occurred in 14 countries, just five national forest areas to achieve the net growth, but the increase amount was only 1% of loss amount. 2) The spatial pattern of forest cover change in Africa contracted and clustered gradually, especially after 2012. Algeria was the hotspot cluster of Morocco and Tunisia, forming the increase area of forest cover in North Africa. Zambia, the coldest point, gathers Angola significantly, while the Democratic Republic of the Congo and Tanzania form a significantly reduced forest cover area. 3) Total population, land area, cultivated land, urban population, consumer price index, and birth rate are the main factors influencing the temporal evolution of forest cover change in Africa. It can be divided into four stages to interpret the different explanations and significance of each factor for forest cover change in the study area.

Simulating forest cover change in the northeastern U.S.: decreasing forest area and increasing fragmentation

2019 ◽  
Vol 34 (10) ◽  
pp. 2401-2419
Author(s):  
Alison B. Adams ◽  
Jennifer Pontius ◽  
Gillian Galford ◽  
David Gudex-Cross
Keyword(s):  
Forest Cover ◽  
Forest Area ◽  
Forest Cover Change

Trajectory Analysis of Forest Cover Change in the Tropical Dry Forest of Burkina Faso, West Africa

2011 ◽  
Vol 36 (3) ◽  
pp. 303-320 ◽  
Author(s):  
Issa Ouedraogo ◽  
Patrice Savadogo ◽  
Mulualem Tigabu ◽  
Roy Cole ◽  
Per Christer Oden ◽  
...  
Keyword(s):  
West Africa ◽  
Burkina Faso ◽  
Trajectory Analysis ◽  
Forest Cover ◽  
Tropical Dry Forest ◽  
Dry Forest ◽  
Forest Cover Change

scholarly journals Forest cover monitoring of Bara district (Nepal) using remote sensing and geographic information systems

1970 ◽  
Vol 20 (1) ◽  
pp. 30-36
Author(s):  
CM Kandel ◽  
M Caetano ◽  
P Cabral
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Area ◽  
Geographical Information ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Spatial Metrics ◽  
Land Cover Maps

This study uses Landsat TM of 1989 and ETM+ of 1999 and 2005 imagery to evaluateforest cover dynamics during 1989-2005 in the Bara district of Nepal. The aim of thestudy was to analyse the extent and trend of forest cover dynamics, spatial pattern offorest and their driving forces. Forest cover change analysis was performed using objectorientedclassification approach applying a standard nearest neighbour algorithm to classifythe image in recognition. The overall classification accuracies were 85.71% and 88.23%for the year 1999 and 2005, respectively. Land cover maps were produced with sevenland cover categories and were further reclassified as forest and non-forest areas toanalyse the forest cover dynamics. Post-classification and time series analysis were carriedout to detect the changes. Spatial metrics were computed for detecting the spatial patternof forest. The classifications suggested that the amount of forest land had decreased by11.56% during 1989-2005. Spatial metrics revealed that forest area has been fragmentedand deforested with an annual rate of 0.72%. The overall result demonstrates that forestarea has experienced a significant shrinkage and mostly transferred into agricultural andbare land. Expected change for the year 2021 was projected using Markov Chain Analysis(MCA). The MCA result showed that forest area would decrease by 8.5% in the period of2005-2021.Key words: Forest cover dynamics; geographical information systems; landsat; remotesensing; spatial metricsDOI: 10.3126/banko.v20i1.3506Banko Janakari, Vol. 20, No. 1 pp.30-36

scholarly journals Understanding Current and Future Fragmentation Dynamics of Urban Forest Cover in the Nanjing Laoshan Region of Jiangsu, China

2020 ◽  
Vol 12 (1) ◽  
pp. 155 ◽  
Author(s):  
Wenjuan Shen ◽  
Xupeng Mao ◽  
Jiaying He ◽  
Jinwei Dong ◽  
Chengquan Huang ◽  
...  
Keyword(s):  
Land Cover ◽  
Markov Model ◽  
Forest Cover ◽  
Urban Forest ◽  
Detection Algorithm ◽  
Forest Area ◽  
Spatiotemporal Pattern ◽  
Forest Cover Change ◽  
Forest Interior ◽  
Land Cover Maps

Accurate acquisition of the spatiotemporal distribution of urban forests and fragmentation (e.g., interior and intact regions) is of great significance to contributing to the mitigation of climate change and the conservation of habitat biodiversity. However, the spatiotemporal pattern of urban forest cover changes related with the dynamics of interior and intact forests from the present to the future have rarely been characterized. We investigated fragmentation of urban forest cover using satellite observations and simulation models in the Nanjing Laoshan Region of Jiangbei New Area, Jiangsu, China, during 2002–2023. Object-oriented classification-based land cover maps were created to simulate land cover changes using the cellular automation-Markov chain (CA-Markov) model and the state transition simulation modeling. We then quantified the forest cover change by the morphological change detection algorithm and estimated the forest area density-based fragmentation patterns. Their relationships were built through the spatial analysis and statistical methods. Results showed that the overall accuracies of actual land cover maps were approximately 83.75–92.25% (2012–2017). The usefulness of a CA-Markov model for simulating land cover maps was demonstrated. The greatest proportion of forest with a low level of fragmentation was captured along with the decreasing percentage of fragmented area from 81.1% to 64.1% based on high spatial resolution data with the window size of 27 pixels × 27 pixels. The greatest increase in fragmentation (3% from 2016 to 2023) among the changes between intact and fragmented forest was reported. However, intact forest was modeled to have recovered in 2023 and restored to 2002 fragmentation levels. Moreover, we found 58.07 km2 and 0.35 km2 of interior and intact forests have been removed from forest area losses and added from forest area gains. The loss rate of forest interior and intact area exceeded the rate of total forest area loss. However, their approximate ratio (1) implying the loss of forest interior and intact area would have slight fragmentation effects on the remaining forests. This analysis illustrates the achievement of protecting and restoring forest interior; more importantly, excessive human activities in the surrounding area had been avoided. This study provides strategies for future forest conservation and management in large urban regions.

scholarly journals FOREST COVER CHANGE ANALYSIS IN INNER MONGOLIA USING REMOTE SENSING DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 1951-1954
Author(s):  
S. Xie ◽  
J. Gong ◽  
X. Huang
Keyword(s):  
Protected Area ◽  
Inner Mongolia ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Shape Index ◽  
Forest Area ◽  
Forest Cover Change ◽  
Forest Change ◽  
Change Analysis ◽  
Forest Patches

Forest is the lung of the earth, and it has important effect on maintaining the ecological balance of the whole earth. This study was conducted in Inner Mongolia during the year 1990–2015. Land use and land cover data were used to obtain forest cover change of Inner Mongolia. In addition, protected area data, road data, ASTER GDEM data were combined with forest cover change data to analyze the relationship between them. Moreover, patch density and landscape shape index were calculated to analyze forest change in perspective of landscape aspect. The results indicated that forest area increased overall during the study period. However, a few cities still had a phenomenon of reduced forest area. Results also demonstrated that the construction of protected area had positive effect on protecting forest while roads may disturbed forest due to human activities. In addition, forest patches in most of cities of Inner Mongolia tended to be larger and less fragmented. This paper reflected forest change in Inner Mongolia objectively, which is helpful for policy making by government.

scholarly journals An Assessment of Forest Cover Change and Its Driving Forces in the Syrian Coastal Region during a Period of Conflict, 2010 to 2020

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 191
Author(s):  
Mohamed Ali Mohamed
Keyword(s):  
Forest Fires ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Resources ◽  
Climatic Conditions ◽  
Forest Area ◽  
Forest Cover Change ◽  
Landsat Images ◽  
Syrian Coast ◽  
Coast Region

In Syria, 76% of the forests are located in the Syrian coast region. This region is witnessing a rapid depletion of forest cover during the conflict that broke out in mid-2011. To date, there have been no studies providing accurate, reliable, and comprehensive data on the qualitative and quantitative aspects of forest change dynamics and the underlying drivers behind this change. In this study, changes in the dynamics of forest cover and its density between 2010 and 2020 were detected and analyzed using multi-temporal Landsat images. This study also analyzed the relationship between changes in forest cover and selected physical and socio-demographic variables associated with the drivers of change. The results revealed that the study area witnessed a significant decrease in the total forest area (31,116.0 ha, 24.3%) accompanied by a considerable decrease in density, as the area of dense forests decreased by 11,778.0 ha (9.2%) between 2010 and 2020. The change in forest cover was driven by a variety of different factors related to the conflict. The main drivers were changes in economic and social activities, extensive exploitation of forest resources, frequent forest fires, and weakness of state institutions in managing natural resources and environmental development. Forest loss was also linked to the expansion of cultivated area, increase in population and urban area. Fluctuating climatic conditions are not a major driver of forest cover dynamics in the study area. This decrease in forest area and density reflects sharp shifts in the natural environment during the study period. In the foreseeable future, it is not possible to determine whether the changes in forest cover and its density will be permanent or temporary. Monitoring changes in forest cover and understanding the driving forces behind this change provides quantitative and qualitative information to improve planning and decision-making. The results of this study may draw the attention of decision-makers to take immediate actions and identify areas of initial intervention to protect current the forests of the Syrian coast region from loss and degradation, as well as develop policies for the sustainable management of forest resources in the long term.

scholarly journals Processes of Forest Cover Change since 1958 in the Coffee-Producing Areas of Southwest Ethiopia

Land ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 278
Author(s):  
Tola Gemechu Ango ◽  
Kristoffer Hylander ◽  
Lowe Börjeson
Keyword(s):  
Population Density ◽  
Land Cover ◽  
Crop Production ◽  
Forest Cover ◽  
Spatial Relations ◽  
Forest Area ◽  
Forest Cover Change ◽  
Southwest Ethiopia ◽  
Forest Policies ◽  
Forest Sites

We investigated the spatial relations of ecological and social processes to point at how state policies, population density, migration dynamics, topography, and socio-economic values of ‘forest coffee’ together shaped forest cover changes since 1958 in southwest Ethiopia. We used data from aerial photos, Landsat images, digital elevation models, participatory field mapping, interviews, and population censuses. We analyzed population, land cover, and topographic roughness (slope) data at the ‘sub-district’ level, based on a classification of the 30 lowest administrative units of one district into the coffee forest area (n = 17), and highland forest area (n = 13). For state forest sites (n = 6) of the district, we evaluated land cover and slope data. Forest cover declined by 25% between 1973 and 2010, but the changes varied spatially and temporally. Losses of forest cover were significantly higher in highland areas (74%) as compared to coffee areas (14%) and state forest sites (2%), and lower in areas with steeper slopes both in coffee and highland areas. Both in coffee and highland areas, forest cover also declined during 1958–1973. People moved to and converted forests in relatively low population density areas. Altitudinal migration from coffee areas to highland areas contributed to deforestation displacement due to forest maintenance for shade coffee production in coffee areas and forest conversions for annual crop production in highland areas. The most rapid loss of forest cover occurred during 1973–1985, followed by 2001–2010, which overlapped with the implementations of major land and forest policies that created conditions for more deforestation. Our findings highlight how crop ecology and migration have shaped spatial variations of forest cover change across different altitudinal zones whilst development, land, and forest policies and programs have driven the temporal variations of deforestation. Understanding the mechanisms of deforestation and forest maintenance simultaneously and their linkages is necessary for better biodiversity conservation and forest landscape management.

scholarly journals A RETROSPECTIVE ANALYSIS OF THE SPREAD OF ISLAM IN WEST AFRICA UNTIL 11TH CENTURY CE

2021 ◽  
Vol 9 (12) ◽  
pp. 99-104
Author(s):  
Wan Mohd Amirol Ashraf Wan Mohd Badruddin ◽  
◽  
Ezad Azraai Jamsari ◽  
Mohamad Zulfazdlee Abul Hassan Ashari ◽  
Izziah Suryani Mat Resad ◽  
...  
Keyword(s):  
West Africa ◽  
North Africa ◽  
West African ◽  
Historical Study ◽  
Initial Contact ◽  
Ruling Class ◽  
African Region ◽  
Secondary Sources ◽  
West African Region ◽  
Research Findings

Islam spread in the African continent in phases and in different ages. The process occurred through either expansion of Muslim power as in North Africa, or trading as happened in West Africa. Falola argued that the process of spreading Islam in West Africa generally occurred peacefully through trading and preaching. In that regard, the purpose of this article is to examine the process of spreading Islam in West Africa until the 11th century CE. On the whole, this article is a qualitative research using historical study and content analysis to gather and analyse information from relevant primary and secondary sources. Research findings argue that initial contact of Muslims with the West African region began since the century 1H/7CE. From this contact, Islam began to be introduced to the inhabitants of West Africa through trade from the 2H/8CE century. This research finds that at the end of 4H/10CE and early 5H/11CE centuries, Islam was accepted by the ruling class of West African kingdoms, such as the conversion of rulers of Kanem, Songhay, Takrur and Malal. However, there were also West African rulers who did not embrace Islam such as the ruler of Ghana. Nevertheless, Muslims who resided in their territories were well-treated. Later on, this helped to spread Islam in these territories.

scholarly journals Forest Cover and Sustainable Development in the Lumbini Province, Nepal: Past, Present and Future

2021 ◽  
Vol 13 (20) ◽  
pp. 4093
Author(s):  
Bhagawat Rimal ◽  
Hamidreza Keshtkar ◽  
Nigel Stork ◽  
Sushila Rijal
Keyword(s):  
Sustainable Development ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Biodiversity Loss ◽  
Integrated Approach ◽  
Forest Area ◽  
Forest Cover Change ◽  
Landsat Images ◽  
The Sustainable Development ◽  
Forest Landscape Restoration

The analysis of forest cover change at different scales is an increasingly important research topic in environmental studies. Forest Landscape Restoration (FLR) is an integrated approach to manage and restore forests across various landscapes and environments. Such restoration helps to meet the targets of Sustainable Development Goal (SDG)–15, as outlined in the UN Environment’s sixth Global Outlook, which includes the sustainable management of forests, the control of desertification, reducing degradation, biodiversity loss, and the conservation of mountain ecosystems. Here, we have used time series Landsat images from 1996 to 2016 to see how land use, and in particular forest cover, have changed between 1996 and 2016 in the Lumbini Province of Nepal. In addition, we simulated projections of land cover (LC) and forest cover change for the years 2026 and 2036 using a hybrid cellular automata Markov chain (CA–Markov) model. We found that the overall forest area increased by 199 km2 (2.1%), from a 9491 km2 (49.3%) area in 1996 to 9691 km2 (50.3%) area in 2016. Our modeling suggests that forest area will increase by 81 km2 (9691 to 9772 km2) in 2026 and by 195 km2 (9772 km2 to 9966 km2) in 2036. They are policy, planning, management factors and further strategies to aid forest regeneration. Clear legal frameworks and coherent policies are required to support sustainable forest management programs. This research may support the targets of the Sustainable Development Goals (SDG), the land degradation neutral world (LDN), and the UN decade 2021–2031 for ecosystem restoration.

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