scholarly journals Assessing the tropical forest cover change in northern parts of Sonitpur and Udalguri district of Assam, India

2021 ◽  
Author(s):  
Ranjit Mahato ◽  
Gibji Nimasow ◽  
Oyi Dai Nimasow ◽  
Dhoni Bushi
Keyword(s):  
Protected Areas ◽  
National Park ◽  
Large Scale ◽  
Forest Cover ◽  
Ground Truth ◽  
Forest Cover Change ◽  
Wildlife Sanctuary ◽  
Remotely Sensed Data ◽  
Ground Truth Data ◽  
Increasing Trends

Abstract Sonitpur and Udalguri district of Assam possess rich tropical forests with equally important faunal species. The Nameri National Park, Sonai-Rupai Wildlife Sanctuary, and other Reserved Forests are areas of attraction for the tourists and wildlife lovers. However, these protected areas are reportedly facing the problem of encroachment and large-scale deforestation. So, this study attempts to estimate the forest cover change in the area through integrating the remotely sensed data of 1990, 2000, 2010, and 2020 with Geographic Information System. The Maximum Likelihood algorithm based supervised classification shows acceptable agreement between the classified image and the ground truth data with an overall accuracy of about 96% and a Kappa coefficient of 0.95. The results reveal a forest cover loss of 7.47% from 1990 to 2000 and 7.11% from 2000 to 2010. However, there was a slight gain of 2.34% in forest cover from 2010 to 2020. The net change of forest to non-forest was 195.17 km2 in the last forty years. The forest transition map shows a declining trend of forest remains forest till 2010 and a slight increase after that. There was a considerable decline in the forest to non-forest (11.94% to 3.50%) from 2000-2010 to 2010-2020. Further, a perceptible gain was also observed in the non-forest to the forest during the last four decades. The overlay analysis of forest cover maps show an area of 460.76 km2 (28.89%) as forest (unchanged), 764.21 km2 (47.91%) as non-forest (unchanged), 282.67 km2 (17.72%) as deforestation and 87.50 km2 (5.48%) as afforestation. The study found hotspots of deforestation in the closest areas of National Park, Wildlife Sanctuary, and Reserved Forests due to encroachments for human habitation, agriculture, and timber/fuelwood extractions. Therefore, the study suggests an early declaration of these protected areas as Eco-Sensitive Zone to control the increasing trends of deforestation.

scholarly journals Assessing the tropical forest cover change in northern parts of Sonitpur and Udalguri District of Assam, India

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ranjit Mahato ◽  
Gibji Nimasow ◽  
Oyi Dai Nimasow ◽  
Dhoni Bushi
Keyword(s):  
Protected Areas ◽  
National Park ◽  
Large Scale ◽  
Forest Cover ◽  
Ground Truth ◽  
Forest Cover Change ◽  
Wildlife Sanctuary ◽  
Remotely Sensed Data ◽  
Ground Truth Data ◽  
Increasing Trends

AbstractSonitpur and Udalguri district of Assam possess rich tropical forests with equally important faunal species. The Nameri National Park, Sonai-Rupai Wildlife Sanctuary, and other Reserved Forests are areas of attraction for tourists and wildlife lovers. However, these protected areas are reportedly facing the problem of encroachment and large-scale deforestation. Therefore, this study attempts to estimate the forest cover change in the area through integrating the remotely sensed data of 1990, 2000, 2010, and 2020 with the Geographic Information System. The Maximum Likelihood algorithm-based supervised classification shows acceptable agreement between the classified image and the ground truth data with an overall accuracy of about 96% and a Kappa coefficient of 0.95. The results reveal a forest cover loss of 7.47% from 1990 to 2000 and 7.11% from 2000 to 2010. However, there was a slight gain of 2.34% in forest cover from 2010 to 2020. The net change of forest to non-forest was 195.17 km2 in the last forty years. The forest transition map shows a declining trend of forest remained forest till 2010 and a slight increase after that. There was a considerable decline in the forest to non-forest (11.94% to 3.50%) from 2000–2010 to 2010–2020. Further, a perceptible gain was also observed in the non-forest to the forest during the last four decades. The overlay analysis of forest cover maps show an area of 460.76 km2 (28.89%) as forest (unchanged), 764.21 km2 (47.91%) as non-forest (unchanged), 282.67 km2 (17.72%) as deforestation and 87.50 km2 (5.48%) as afforestation. The study found hotspots of deforestation in the closest areas of National Park, Wildlife Sanctuary, and Reserved Forests due to encroachments for human habitation, agriculture, and timber/fuelwood extractions. Therefore, the study suggests an early declaration of these protected areas as Eco-Sensitive Zone to control the increasing trends of deforestation.

scholarly journals Synthesizing published knowledge of boreal forest cover change for large-scale landscape dynamics modelling

2003 ◽  
Vol 79 (1) ◽  
pp. 132-146 ◽  
Author(s):  
Dennis Yemshanov ◽  
Ajith H Perera
Keyword(s):  
Boreal Forest ◽  
Large Scale ◽  
Forest Canopy ◽  
Forest Cover ◽  
Forest Succession ◽  
Simulation Models ◽  
Limiting Factors ◽  
Sources Of Information ◽  
Forest Cover Change ◽  
Discrete State

We reviewed the published knowledge on forest succession in the North American boreal biome for its applicability in modelling forest cover change over large extents. At broader scales, forest succession can be viewed as forest cover change over time. Quantitative case studies of forest succession in peer-reviewed literature are reliable sources of information about changes in forest canopy composition. We reviewed the following aspects of forest succession in literature: disturbances; pathways of post-disturbance forest cover change; timing of successional steps; probabilities of post-disturbance forest cover change, and effects of geographic location and ecological site conditions on forest cover change. The results from studies in the literature, which were mostly based on sample plot observations, appeared to be sufficient to describe boreal forest cover change as a generalized discrete-state transition process, with the discrete states denoted by tree species dominance. In this paper, we outline an approach for incorporating published knowledge on forest succession into stochastic simulation models of boreal forest cover change in a standardized manner. We found that the lack of details in the literature on long-term forest succession, particularly on the influence of pre-disturbance forest cover composition, may be limiting factors in parameterizing simulation models. We suggest that the simulation models based on published information can provide a good foundation as null models, which can be further calibrated as detailed quantitative information on forest cover change becomes available. Key words: probabilistic model, transition matrix, boreal biome, landscape ecology

scholarly journals Effectiveness of Protected Areas in the Pan-Tropics and International Aid for Conservation

Geomatics ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 335-346
Author(s):  
Do-Hyung Kim ◽  
Anupam Anand
Keyword(s):  
Protected Areas ◽  
Forest Conservation ◽  
Forest Cover ◽  
International Aid ◽  
Asian Countries ◽  
Forest Cover Change ◽  
Average Effect ◽  
Tropical Countries ◽  
Conservation Policies ◽  
The Tropics

Evaluation of the effectiveness of protected areas is critical for forest conservation policies and priorities. We used 30 m resolution forest cover change data from 1990 to 2010 for ~4000 protected areas to evaluate their effectiveness. Our results show that protected areas in the tropics avoided 83,500 ± 21,200 km2 of deforestation during the 2000s. Brazil’s protected areas have the largest amount of avoided deforestation at 50,000 km2. We also show the amount of international aid received by tropical countries compared to the effectiveness of protected areas. Thirty-four tropical countries received USD 42 billion during the 1990s and USD 62 billion during the 2000s in international aid for biodiversity conservation. The effectiveness of international aid was highest in Latin America, with 4.3 m2/USD, led by Brazil, while tropical Asian countries showed the lowest average effect of international aid, reaching only 0.17 m2/USD.

scholarly journals Spatial and Temporal Trends of Burnt Area in Angola: Implications for Natural Vegetation and Protected Area Management

Diversity ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 307
Author(s):  
Silvia Catarino ◽  
Maria Manuel Romeiras ◽  
Rui Figueira ◽  
Valentine Aubard ◽  
João M. N. Silva ◽  
...  
Keyword(s):  
Land Cover ◽  
Protected Areas ◽  
Forest Cover ◽  
Temporal Trends ◽  
Sub Saharan Africa ◽  
Conservation Priorities ◽  
Negative Consequences ◽  
Burnt Area ◽  
Increasing Trends ◽  
Spatial And Temporal Trends

Fire is a key driver of natural ecosystems in Africa. However, human activity and climate change have altered fire frequency and severity, with negative consequences for biodiversity conservation. Angola ranks among the countries with the highest fire activity in sub-Saharan Africa. In this study, we investigated the spatial and temporal trends of the annual burnt area in Angola, from 2001 to 2019, and their association with terrestrial ecoregions, land cover, and protected areas. Based on satellite imagery, we analyzed the presence of significant trends in burnt area, applying the contextual Mann–Kendall test and the Theil–Sen slope estimator. Data on burnt areas were obtained from the moderate-resolution imaging spectroradiometer (MODIS) burnt area product and the analyses were processed in TerrSet. Our results showed that ca. 30% of the country’s area burned every year. The highest percentage of annual burnt area was found in northeast and southeast Angola, which showed large clusters of decreasing trends of burnt area. The clusters of increasing trends were found mainly in central Angola, associated with savannas and grasslands of Angolan Miombo woodlands. The protected areas of Cameia, Luengue-Luiana, and Mavinga exhibited large areas of decreasing trends of burnt area. Conversely, 23% of the Bicuar National Park was included in clusters of increasing trends. Distinct patterns of land cover were found in areas of significant trends, where the clusters of increasing trends showed a higher fraction of forest cover (80%) than the clusters of decreasing trends (55%). The documentation of burnt area trends was very important in tropical regions, since it helped define conservation priorities and management strategies, allowing more effective management of forests and fires in countries with few human and financial resources.

scholarly journals Effects of Protected Areas on Forest Cover Change and Local Communities: Evidence from the Peruvian Amazon

2014 ◽  
Author(s):  
Juan Jose Miranda ◽  
Leonardo Corral ◽  
Allen Blackman ◽  
Gregory Asner ◽  
Eirivelthon Lima
Keyword(s):  
Protected Areas ◽  
Forest Cover ◽  
Local Communities ◽  
Peruvian Amazon ◽  
Forest Cover Change

scholarly journals A Product Feature Inference Model for Mining Implicit Customer Preferences Within Large Scale Social Media Networks

2015 ◽  
Author(s):  
Suppawong Tuarob ◽  
Conrad S. Tucker
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Ground Truth ◽  
Inference Model ◽  
Underlying Assumption ◽  
Ground Truth Data ◽  
Social Media Networks ◽  
Customer Preferences ◽  
Product Features ◽  
Online Sources

The acquisition and mining of product feature data from online sources such as customer review websites and large scale social media networks is an emerging area of research. In many existing design methodologies that acquire product feature preferences form online sources, the underlying assumption is that product features expressed by customers are explicitly stated and readily observable to be mined using product feature extraction tools. In many scenarios however, product feature preferences expressed by customers are implicit in nature and do not directly map to engineering design targets. For example, a customer may implicitly state “wow I have to squint to read this on the screen”, when the explicit product feature may be a larger screen. The authors of this work propose an inference model that automatically assigns the most probable explicit product feature desired by a customer, given an implicit preference expressed. The algorithm iteratively refines its inference model by presenting a hypothesis and using ground truth data, determining its statistical validity. A case study involving smartphone product features expressed through Twitter networks is presented to demonstrate the effectiveness of the proposed methodology.

Economic crisis, small-scale agriculture, and forest cover change in southern Cameroon

2000 ◽  
Vol 27 (3) ◽  
pp. 284-290 ◽  
Author(s):  
W.D. SUNDERLIN ◽  
O. NDOYE ◽  
H. BIKIÉ ◽  
N. LAPORTE ◽  
B. MERTENS ◽  
...  
Keyword(s):  
Population Growth ◽  
Economic Crisis ◽  
Rural Population ◽  
Structural Adjustment ◽  
Large Scale ◽  
Forest Cover ◽  
Small Scale ◽  
Forest Cover Change ◽  
Macroeconomic Shocks ◽  
Adjustment Policies

The rate of forest cover loss in the humid tropics of Cameroon is one of the highest in Central Africa. The aim of the large-scale, two-year research project described here was to understand the effect of the country's economic crisis and policy change on small-scale agricultural systems and land-clearing practices. Hypotheses were tested through surveys of more than 5000 households in 125 villages, and through time-series remote sensing analysis at two sites. The principal findings are that: (1) the rate of deforestation increased significantly in the decade after the 1986 onset of the crisis, as compared to the decade prior to the crisis; (2) the main proximate causes of this change were sudden rural population growth and a shift from production of cocoa and coffee to plantain and other food crops; and (3) the main underlying causes were macroeconomic shocks and structural adjustment policies that led to rural population growth and farming system changes. The implication of this study is that it is necessary to understand and anticipate the undesirable consequences of macroeconomic shocks and adjustment policies for forest cover. Such policies, even though they are often not formulated with natural resource consequences in mind, are often of greater relevance to the fate of forests than forest policy.

scholarly journals Understanding 34 Years of Forest Cover Dynamics across the Paraguayan Chaco: Characterizing Annual Changes and Forest Fragmentation Levels between 1987 and 2020

Forests ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 25
Author(s):  
Emmanuel Da Da Ponte ◽  
Monserrat García-Calabrese ◽  
Jennifer Kriese ◽  
Nestor Cabral ◽  
Lidia Perez de Perez de Molas ◽  
...  
Keyword(s):  
Protected Areas ◽  
Forest Cover ◽  
Natural Habitat ◽  
Remote Sensing Data ◽  
Rapid Expansion ◽  
Forest Cover Change ◽  
Landsat Images ◽  
Forest Clearing ◽  
Deforestation Rates ◽  
Degree Of Fragmentation

Over the past 40 years, Paraguay has lost the majority of its natural forest cover, thus becoming one of the countries with the highest deforestation rates in the world. The rapid expansion of the agricultural frontier, cattle ranching, and illegal logging between 1987 and 2012 resulted in the loss of 27% of original forest cover, equivalent to almost 44,000 km2. Within this context, the present research provides the first yearly analysis of forest cover change in the Paraguayan Chaco between the years 1987 and 2020. Remote sensing data obtained from Landsat images were applied to derive annual forest cover masks and deforestation rates over 34 years. Part of this study is a comprehensive assessment of the effectiveness of protected areas, as well as an analysis of the degree of fragmentation of the forest. All classification results obtained accuracies above 80% and revealed a total forest cover loss of approximately 64,700 km2. Forest clearing within protected areas was not frequent; however, some natural reserves presented losses of up to 25% of their forest cover. Through the consideration of several landscape metrics, this study reveals an onward fragmentation of forest cover, which endangers the natural habitat of numerous species.

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