WITHDRAWN: An empirical analysis of the driving forces of forest cover change in northeast China

For decades, the dynamics of tropical deforestation in sub-Saharan Africa (SSA) have defied easy explanation. The rates of deforestation have been lower than elsewhere in the tropics, and the driving forces evident in other places, government new land settlement schemes and industrialized agriculture, have largely been absent in SSA. The context and causes for African deforestation become clearer through an analysis of new, national-level data on forest cover change for SSA countries for the 2000–2005 period. The recent dynamic in SSA varies from dry to wet biomes. Deforestation occurred at faster rates in nations with predominantly dry forests. The wetter Congo basin countries had lower rates of deforestation, in part because tax receipts from oil and mineral industries in this region spurred rural to urban migration, declines in agriculture and increased imports of cereals from abroad. In this respect, the Congo basin countries may be experiencing an oil and mineral fuelled forest transition. Small farmers play a more important role in African deforestation than they do in southeast Asia and Latin America, in part because small-scale agriculture remains one of the few livelihoods open to rural peoples.

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Forest Cover Change Analysis Using Remote Sensing Techniques in Madhupur Sal Forest of Bangladesh

Journal of Environmental Science and Natural Resources ◽

10.3329/jesnr.v10i2.39015 ◽

2018 ◽

Vol 10 (2) ◽

pp. 73-78

Author(s):

MA Salam ◽

MAT Pramanik

Keyword(s):

Remote Sensing ◽

Forest Cover ◽

Driving Forces ◽

Forest Resources ◽

Forest Monitoring ◽

Forest Damage ◽

Landsat 8 ◽

Forest Cover Change ◽

Change Analysis ◽

Sal Forest

Deforestation, degradation, damages, transformation and over exploitation of forests are the common problem in different parts of the world. Timely monitoring and assessment of forest resources may help to address and identify the above mentioned problems and thus proper guidance may be given the forest resources manager for rational planning and management of forests. Apart from the conventional methods of forest monitoring, remote sensing with its unique capability of synoptic viewing, real time and repetitive nature offers a potential tool for monitoring and evaluation of forest resources and hence remote sensing technology has been successfully used in various studies like forest inventory, monitoring of forest cover changes and forest damage assessment. In the present research forest cover change analysis in ‘Madhupur Sal Forest’ located in central part of Bangladesh has been investigated using satellite remote sensing data and spatial analysis. Transformation of ‘Sal forest’ to other landuse has been studied using the Landsat MSS (Multi Spectral Scanner) data of 1973 and Landsat 8 OLI (Operational Land Imager) data of 2015. Driving forces behind the transformation of ‘Sal forest’ has also been investigated through GPS (Global Positioning System) based ground verification and interview with the people living in the locality.J. Environ. Sci. & Natural Resources, 10(2): 73-78 2017

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

Banko Janakari ◽

10.3126/banko.v20i1.3506 ◽

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

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TIPOLOGI PERUBAHAN TUTUPAN HUTAN DI KABUPATEN KUBU RAYA KALIMANTAN BARAT

Wahana Forestra Jurnal Kehutanan ◽

10.31849/forestra.v14i1.2460 ◽

2019 ◽

Vol 14 (1) ◽

pp. 63-69

Author(s):

Hanifah Ikhsani

Keyword(s):

Forest Cover ◽

Driving Forces ◽

Driving Factors ◽

Forest Cover Change ◽

Forest Change ◽

West Kalimantan ◽

Forest Cover Changes ◽

Clustering Approach ◽

Euclidean Distances ◽

The Village

Forest cover changes were influenced by many factors, some of which were biophysical characteristics, socio-economic conditions, and community cultural. The behavior of forest cover changes in each of Indonesia's regions varied, either its rate or its driving factors. The establishment of village typologies to categorize village administrative areas becomes important to see the driving factors that trigger forest change in each typology. The objective of this study was to develop the village typology and to identify the driving forces of forest cover change in each village in Kubu Raya Regency, West Kalimantan. The development of village typology was done by applying the clustering approach with standardized euclidean distances. Based on the proportion of forest in 2015, the study found that there are two village typologies within the study area with 81% OA. The study also recognized that the most significant driving forces of forest cover change in T1 were the distance from rivers (X2) and settlements (X3), whereas in T2 were the distance from roads (X1) and the edge of forest in 2015 (X9). The study concludes that the proximity from the center of the human activities holds a significant influence on the behavior of forest cover changes.

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Forest cover change and its driving forces in Fagita Lekoma District, Ethiopia

Journal of Forestry Research ◽

10.1007/s11676-018-0838-8 ◽

2018 ◽

Vol 31 (5) ◽

pp. 1567-1582

Author(s):

Yigez Belayneh ◽

Guo Ru ◽

Awoke Guadie ◽

Zebene Lakew Teffera ◽

Mengesha Tsega

Keyword(s):

Forest Cover ◽

Driving Forces ◽

Forest Cover Change

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

Land ◽

10.3390/land10020191 ◽

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.

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Assessment of Forest Cover Change of Dang, an Inner Terai District of Nepal

Journal of Forest and Natural Resource Management ◽

10.3126/jfnrm.v1i1.22651 ◽

2019 ◽

Vol 1 (1) ◽

pp. 40-51

Author(s):

Yam Bahadur K.C.

Keyword(s):

Land Cover ◽

Supervised Classification ◽

Forest Cover ◽

Driving Forces ◽

Forest Land ◽

Forest Cover Change ◽

Change Analysis ◽

Landsat Tm Image ◽

Tm Image ◽

Dense Forest

This study analyzed the dynamics of changes of forest cover classes in the inner Terai District Dang, Nepal, based on Landsat Thematic Mapper (TM) images from two different years, viz., 1990 and 2011. Forest cover change analysis was performed through the analysis of a classified Landsat TM image using supervised classification. The overall classification accuracy for seven different land cover classes considered in this study were 80.37% and 80.56% for years 1990 and 2011, respectively. These classified images were further reclassified as forest and non-forest to analyze forest cover dynamics effectively using the post classification change detection. The results indicated that during 1990-2011, the total spatial areal coverage of forest land converted into other land cover was 20612 ha (shrub-land), 8571 ha (agriculture), and 2787 ha (others) non-forest classes. A significant portion of non-forest classes was also converted into forest (e.g., 11433 ha of shrubland, 5663 ha of agriculture, and 5581 ha of other non forest classes). Sand and water bodies remained more or less constant during this period. While forest cover was estimated to be disappearing at the rate of 0.2% per year, dense forest appears to be converting into a sparse forest at the rate of 0.1% per year. Future study to assess the causes and driving forces of forest cover change in Nepal should get guidance from this study on where to target interventions.

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Spatio–Temporal Changes of Forests in Northeast China: Insights from Landsat Images and Geospatial Analysis

Forests ◽

10.3390/f10110937 ◽

2019 ◽

Vol 10 (11) ◽

pp. 937 ◽

Cited By ~ 2

Author(s):

Chunying Ren ◽

Lin Chen ◽

Zongming Wang ◽

Bai Zhang ◽

Yanbiao Xi ◽

...

Keyword(s):

Northeast China ◽

Forest Cover ◽

Spatial Information ◽

Driving Forces ◽

Global Scale ◽

Geospatial Analysis ◽

Forest Loss ◽

Landsat Images ◽

Mountain Areas ◽

Spatio Temporal

Dramatic changes of forests have strong influence on regional and global carbon cycles, biodiversity, and ecosystem services. Understanding dynamics of forests from local to global scale is crucial for policymaking and sustainable development. In this study, we developed an updating and object-based image analysis method to map forests in Northeast China using Landsat images from 1990 to 2015. The spatio–temporal patterns of forests were quantified based on resultant maps and geospatial analysis. Results showed that the percentage of forested area occupying the entire northeast China was more than 40%, about 94% of initial forest cover remained unchanged (49.37 × 104 km2) over the course of 25 years. A small net forest loss (1051 km2) was observed during 1990–2015. High forest gain (10,315 km2) and forest loss (9923 km2) both occurred from 2010 to 2015. At the provincial level, Heilongjiang demonstrated the highest rate of deforestation, with a net loss of 1802 km2 (0.89%). Forest changes along elevation, slope, and distance from settlements and roads were also investigated. Over 90% of forest changes occurred in plains and low mountain areas within the elevation of 200–1000 m and slope under 15°. The most dramatic forest changes can be found within the distance of 2000 m from settlements and roads. The reclamation of sloping land, construction of settlements and roads, and possible smallholder clearing contributed more to forest loss, while ecological projects and related government policies play an important role on afforestation and reforestation. These results can provide useful spatial information for further research on the driving forces and consequences of forest changes, which have critical implications for scientific conservation and management of forests.

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