Applying Multi-Temporal Landsat Satellite Data and Markov-Cellular Automata to Predict Forest Cover Change and Forest Degradation of Sundarban Reserve Forest, Bangladesh

Overdependence on and exploitation of forest resources have significantly transformed the natural reserve forest of Sundarban, which shares the largest mangrove territory in the world, into a great degradation status. By observing these, a most pressing concern is how much degradation occurred in the past, and what will be the scenarios in the future if they continue? To confirm the degradation status in the past decades and reveal the future trend, we took Sundarban Reserve Forest (SRF) as an example, and used satellite Earth observation historical Landsat imagery between 1989 and 2019 as existing data and primary data. Moreover, a geographic information system model was considered to estimate land cover (LC) change and spatial health quality of the SRF from 1989 to 2029 based on the large and small tree categories. The maximum likelihood classifier (MLC) technique was employed to classify the historical images with five different LC types, which were further considered for future projection (2029) including trends based on 2019 simulation results from 1989 and 2019 LC maps using the Markov-cellular automata model. The overall accuracy achieved was 82.30%~90.49% with a kappa value of 0.75~0.87. The historical result showed forest degradation in the past (1989–2019) of 4773.02 ha yr−1, considered as great forest degradation (GFD) and showed a declining status when moving with the projection (2019–2029) of 1508.53 ha yr−1 and overall there was a decline of 3956.90 ha yr−1 in the 1989–2029 time period. Moreover, the study also observed that dense forest was gradually degraded (good to bad) but, conversely, light forest was enhanced, which will continue in the future even to 2029 if no effective management is carried out. Therefore, by observing the GFD, through spatial forest health quality and forest degradation mapping and assessment, the study suggests a few policies that require the immediate attention of forest policy-makers to implement them immediately and ensure sustainable development in the SRF.

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Value Chain of Charcoal Production and Implications for Forest Degradation: Case Study of Bié Province, Angola

Environments ◽

10.3390/environments5110113 ◽

2018 ◽

Vol 5 (11) ◽

pp. 113 ◽

Cited By ~ 6

Author(s):

Vasco Chiteculo ◽

Bohdan Lojka ◽

Peter Surový ◽

Vladimir Verner ◽

Dimitrios Panagiotidis ◽

...

Keyword(s):

Value Chain ◽

Forest Cover ◽

Forest Degradation ◽

Primary Data ◽

Natural Forests ◽

Forest Cover Change ◽

Charcoal Production ◽

Order Of Magnitude ◽

Alternative Sources ◽

Urban Consumption

Forest degradation and forest loss threaten the survival of many species and reduce the ability of forests to provide vital services. Clearing for agriculture in Angola is an important driver of forest degradation and deforestation. Charcoal production for urban consumption as a driver of forest degradation has had alarming impacts on natural forests, as well as on the social and economic livelihood of the rural population. The charcoal impact on forest cover change is in the same order of magnitude as deforestation caused by agricultural expansion. However, there is a need to monitor the linkage between charcoal production and forest degradation. The aim of this paper is to investigate the sequence of the charcoal value chain as a systematic key to identify policies to reduce forest degradation in the province of Bié. It is a detailed study of the charcoal value chain that does not stop on the production and the consumption side. The primary data of this study came from 330 respondents obtained through different methods (semi-structured questionnaire survey and market observation conducted in June to September 2013–2014). A logistic regression (logit) model in IBM SPSS Statistics 24 (IBM Corp, Armonk, NY, USA) was used to analyze the factors influencing the decision of the households to use charcoal for domestic purposes. The finding indicates that 21 to 27 thousand hectares were degraded due to charcoal production. By describing the chain of charcoal, it was possible to access the driving factors for charcoal production and to obtain the first-time overview flow of charcoal from producers to consumers in Bié province. The demand for charcoal in this province is more likely to remain strong if government policies do not aim to employ alternative sources of domestic energy.

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Change assessment of forest cover in Ghodaghodi lake area in Kailali district of Nepal

Banko Janakari ◽

10.3126/banko.v19i2.2980 ◽

1970 ◽

Vol 19 (2) ◽

pp. 15-19 ◽

Cited By ~ 1

Author(s):

S Khanal

Keyword(s):

Forest Cover ◽

Landsat Imagery ◽

Forest Degradation ◽

Lake Area ◽

Forest Cover Change ◽

Comparison Approach ◽

Multi Temporal ◽

One Year

Ghodaghodi Lake in Far-West Nepal has been listed as a Ramsar Site due to its significance as a habitat for several endangered species of flora and fauna. The wetland and its surrounding area is facing deforestation, forest degradation and encroachment. In this case study, unsupervised and finally supervised classification of multi-temporal Landsat imagery covering the wetland area was applied. A post-classification comparison approach was used to derive forest cover change maps. The results depicted the loss of forest cover over a thirty- one year period, in three time slices. The highest rate of loss was observed in the 1990 to1999 time slice. Keywords: Change detection; forest cover; Ghodaghodi lake; Landsat DOI: 10.3126/banko.v19i2.2980 Banko Janakari, Vol. 19, No.2 2009 pp.15-19

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Opportunities for Reaping the Benefits of REDD+ in Sikkim Himalaya for Conservation and Enhancement of Carbon Stock

Indian Journal of Forestry ◽

10.54207/bsmps1000-2017-3q796x ◽

2017 ◽

Vol 40 (3) ◽

pp. 209-215

Author(s):

Mohommad Shahid ◽

◽

L.K. Rai ◽

Keyword(s):

Climate Change ◽

Forest Cover ◽

Carbon Sink ◽

Forest Degradation ◽

Forest Cover Change ◽

Change Analysis ◽

Carbon Sequestration Potential ◽

Sequestration Potential ◽

Article 5

Paris Agreement recognized the role of forests as carbon sink for mitigation of climate change, under Article 5 as REDD+, i.e., reducing emissions from deforestation and forest degradation and role of conservation, sustainable management of forests and enhancement of forest carbon stocks. Forest cover change analysis was done between two time periods 2005 and 2015 to assess the forest degradation. Carbon sequestration potential of the forests of Sikkim for mitigating climate change is also estimated. Benefits of implementing of REDD+ in Sikkim involving local communities as stakeholder to conserve and sustainably manage the forest is assessed. Gaps and challenges faced by the stakeholder in implementing REDD+ at project level are also highlighted.

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Appraisal of Deforestation and Forest Degradation in District Swat, Pakistan

International Journal of Economic and Environmental Geology ◽

10.46660/ijeeg.vol10.iss3.2019.301 ◽

2019 ◽

Vol 10 (3) ◽

pp. 7-15

Author(s):

Syed Muhammad Owais ◽

Saima Siddiqui

Keyword(s):

Forest Cover ◽

Forest Degradation ◽

Temporal Analysis ◽

Primary Data ◽

Landsat 8 ◽

Forest Reserves ◽

Deforestation Rate ◽

Geospatial Tools ◽

Analysis System ◽

The Right

14 September, 2019 Accepted: 07 October, 2019Abstract: Deforestation and forest degradation are not only a problem of north western mountainous region of Pakistanbut it is one of the main global environmental issues. To find out deforestation rate and its extent in Swat, KhyberPakhtunkhwa, Landsat 5 (October 2, 2011) and Landsat 8 OLI (October 15, 2016) data were processed in CarnegieLandsat Analysis System (CLASlite v3.3). Primary data related to deforestation in Swat were also obtained from localpeople through a structured questionnaire. Primary data were analyzed in Statistical Package for the Social Sciences(SPSS). Changes in land cover can be clearly identified during image analysis. The temporal analysis of forest coverbetween 2011 and 2016 showed a significant change in forest cover. About 11 km² area is converted from forest tobarren land, while approximately 9,985 km² area of forest cover was degraded. The perceived causes of deforestation inthe study area are unsustainable use and mismanagement of forest resources, population growth, plantation ofeucalyptus and lack of basic facilities and awareness. However, community ignorance is the main factor responsible fordeforestation and forest degradation. One of the major consequences of deforestation can be related to the totaldisappearance of Charchur waterfall in Talang Kota lower Swat in September 2016. Therefore, it is the right time tomove toward sustainable management, detection and monitoring of national forest reserves by using geospatial tools,and by the involvement of local communities to participate in decision making about the conservation of forestresources.

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Appraisal of Deforestation and Forest Degradation in District Swat, Pakistan

International Journal of Economic and Environmental Geology ◽

10.46660/ojs.v10i3.301 ◽

2019 ◽

Vol 10 (3) ◽

pp. 7-15

Author(s):

Syed Muhammad Owais ◽

Saima Siddiqui

Keyword(s):

Forest Cover ◽

Forest Degradation ◽

Temporal Analysis ◽

Primary Data ◽

Landsat 8 ◽

Forest Reserves ◽

Deforestation Rate ◽

Geospatial Tools ◽

Analysis System ◽

The Right

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The past, present and future of the Pite Saami language: Sociological factors and revitalization efforts

Nordic Journal of Linguistics ◽

10.1017/s0332586512000042 ◽

2011 ◽

Vol 34 (3) ◽

pp. 295-329

Author(s):

Riitta-Liisa Valijärvi ◽

Joshua Wilbur

Keyword(s):

Language Attitudes ◽

Primary Data ◽

Field Observations ◽

Future Prospects ◽

Sociological Factors ◽

The Past ◽

Future State ◽

The Future ◽

Vitality Scale

Our paper is a report on the past, current and future state of the endangered Pite Saami language (aka: Arjeplog Saami) spoken in Swedish Lapland. Our primary data come from interviews with Pite Saami individuals and our field observations. We estimate the vitality of Pite Saami based on the UNESCO Language Vitality Scale, taking into consideration factors such as the number of speakers, language attitudes and the quality of documentation. We also discuss the possible reasons for the decline of Pite Saami, report on the speakers’ views of other Saami languages and Swedish, consider whether there is a specific Pite Saami identity, describe revitalization efforts already taking place, and discuss the future prospects of the language.

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Forest Cover Change and the Effectiveness of Protected Areas in the Himalaya since 1998

Sustainability ◽

10.3390/su12156123 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6123

Author(s):

Changjun Gu ◽

Pei Zhao ◽

Qiong Chen ◽

Shicheng Li ◽

Lanhui Li ◽

...

Keyword(s):

Protected Areas ◽

Forest Cover ◽

Forest Degradation ◽

Google Earth ◽

Forest Cover Change ◽

Natural Conditions ◽

Positive Role ◽

Forest Cover Changes ◽

Matched Samples ◽

The Himalaya

Himalaya, a global biodiversity hotspot, has undergone considerable forest cover fluctuation in recent decades, and numerous protected areas (PAs) have been established to prohibit forest degradation there. However, the spatiotemporal characteristics of this forest cover change across the whole region are still unknown, as are the effectiveness of its PAs. Therefore, here, we first mapped the forest cover of Himalaya in 1998, 2008, and 2018 with high accuracy (>90%) using a random forest (RF) algorithm based on Google Earth Engine (GEE) platform. The propensity score matching (PSM) method was applied with eight control variables to balance the heterogeneity of land characteristics inside and outside PAs. The effectiveness of PAs in Himalaya was quantified based on matched samples. The results showed that the forest cover in Himalaya increased by 4983.65 km2 from 1998 to 2008, but decreased by 4732.71 km2 from 2008 to 2018. Further analysis revealed that deforestation and reforestation mainly occurred at the edge of forest tracts, with over 55% of forest fluctuation occurring below a 2000 m elevation. Forest cover changes in PAs of Himalaya were analyzed; these results indicated that about 56% of PAs had a decreasing trend from 1998 to 2018, including the Torsa (Ia PA), an area representative of the most natural conditions, which is strictly protected. Even so, as a whole, PAs in Himalaya played a positive role in halting deforestation.

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Use of Markov Processes in Predicting Dairy Farm Size Distribution Changes

Journal of the Northeastern Agricultural Economics Council ◽

10.1017/s0163548400004738 ◽

1979 ◽

Vol 8 (2) ◽

pp. 59-72

Author(s):

John W. Wysong ◽

Mahmood Y. Seyala

Keyword(s):

Dairy Farm ◽

Farm Size ◽

Primary Data ◽

The Past ◽

Farm Production ◽

The Future ◽

Short Run ◽

Long Term Trends ◽

Average Size

During the past several decades, a number of research publications have used Markov chain processes to predict changes in number of farm firms, the average size of farms and labor resource productivity in farm production (Conneman, Harris and Wilson, Judge and Swanson, Kottke, Seyala, Willett and Saupe, Wysong and Seyala). The Markov method assumes that the pattern of change exhibited in the past will continue into the future. This method provides information on historical changes by frequency distribution categories as well as for the whole cohort, and allows for projection of these changes into the future. Previous studies have used mainly short-run periods of up to 5 years as the primary data base. This study has considered the use of longer-run base periods of 10 to 20 years combined with periodic updating of sample data in projecting long-term trends in numbers and sizes of dairy farms and revising such projections through time.

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TEMPORAL VEGETATION DYNAMICS IN PEAT SWAMP AREA USING MODIS TIME-SERIES IMAGERY: A MONITORING APPROACH OF HIGH-SENSITIVE ECOSYSTEM IN REGIONAL SCALE

Geoplanning Journal of Geomatics and Planning ◽

10.14710/geoplanning.3.2.137-146 ◽

2016 ◽

Vol 3 (2) ◽

pp. 137

Author(s):

Yudi Setiawan ◽

Hidayat Pawitan ◽

Lilik Budi Prasetyo ◽

May Parlindungan ◽

Prita Ayu Permatasari

Keyword(s):

Vegetation Dynamics ◽

Management Practices ◽

Forest Cover ◽

Environmental Changes ◽

Regional Scale ◽

Forest Degradation ◽

Forest Conversion ◽

Forest Cover Change ◽

Peat Swamp ◽

Significant Patterns

Peat swamp area is an essential ecosystem due to high vulnerability of functions and services. As the change of forest cover in peat swamp area has increased considerably, many studies on peat swamp have focused on forest conversion or forest degradation. Meanwhile, in the context of changes in the forestlands are the sum of several processes such as deforestation, reforestation/afforestation, regeneration of previously deforested areas, and the changing spatial location of the forest boundary. Remote sensing technology seems to be a powerful tool to provide information required following that concerns. A comparison imagery taken at the different dates over the same locations for assessing those changes tends to be limited by the vegetation phenology and land-management practices. Consequently, the simultaneous analysis seems to be a way to deal with the issues above, as a means for better understanding of the dynamics changes in peat swamp area. In this study, we examined the feasibility of using MODIS images during the last 14 years for detecting and monitoring the changes in peat swamp area. We identified several significant patterns that have been assigned as the specific peat swamp ecosystem. The results indicate that a different type of ecosystem and its response to the environmental changes can be portrayed well by the significant patterns. In understanding the complex situations of each pattern, several vegetation dynamics patterns were characterized by physical land characteristics, such as peat depth, land use, concessions and others. Characterizing the pathways of dynamics change in peat swamp area will allow further identification for the range of proximate and underlying factors of the forest cover change that can help to develop useful policy interventions in peatland management.

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Using Geospatial Analysis to Map Forest Change in New Hampshire: 1996–Present

Journal of Forestry ◽

10.1093/jofore/fvaa039 ◽

2020 ◽

Vol 118 (6) ◽

pp. 598-612

Author(s):

Heather Grybas ◽

Russell G Congalton ◽

Andrew F Howard

Keyword(s):

Land Cover ◽

New Hampshire ◽

Forest Cover ◽

Landsat Imagery ◽

The State ◽

Forest Cover Change ◽

Forest Change ◽

Change Analysis ◽

Land Cover Map ◽

Forest Use

Abstract New Hampshire’s forests are vitally important to the state’s economy; however, there are indications that the state is experiencing a continuous loss in forest cover. We sought to investigate forest cover trends in New Hampshire. A baseline trend in forest cover between 1996 and 2010 was established using National Oceanic and Atmospheric Administration Coastal Change Analysis Program land cover data. A land cover map was then generated from Landsat imagery to extend the baseline trend to 2018. Results show that the state has experienced a continual decline in forest cover with the annual net loss steadily increasing from 0.14% between 1996 and 2001 to 0.27% between 2010 and 2018. Additionally, the more urbanized counties in southern New Hampshire are experiencing some of the greatest rates of net forest loss, most likely because of urbanization and agricultural expansion. This study demonstrated an effective methodology for tracking forest cover change and will hopefully inform future forest use policies.

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