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

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.

Download Full-text

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.

Download Full-text

Mapping Mangrove Forest Change in Nijhum Dwip Island

Journal of Environmental Science and Natural Resources ◽

10.3329/jesnr.v11i1-2.43388 ◽

2019 ◽

Vol 11 (1-2) ◽

pp. 217-225

Author(s):

MM Rahman ◽

MAT Pramanik ◽

MI Islam ◽

S Razia

Keyword(s):

Mangrove Forest ◽

Forest Cover ◽

Storm Surges ◽

Forest Loss ◽

Forest Conversion ◽

Forest Cover Change ◽

Forest Change ◽

Change Analysis ◽

Coastal Belt ◽

Land Covers

Mangroves have been planting in the coastal belt of Bangladesh to protect the inhabitants of the coastal areas from cyclones and storm surges. Nijhum Dwip is located at the southern part of Hatiya Island. Most part of the island has been planted with the mangroves in the 1970s and 1980s; while parts of the mangroves have been deforested during the past few decades. The objectives of this research were to delineate and quantify the changes in the extent of mangroves in the island. The Landsat data of 1989, 2001, 2010 and 2018 have been utilized in the study. Three major land covers, namely forest, water and other land have been interpreted and delineated by using on-screen digitizing. The quantity of mangrove forest loss in the island is estimated as 1,024 ha, while 395 ha were afforested during 1989-2018. In the decadal change analysis, it was revealed that net forest cover change was higher in 2000s compared to other two decades and it was -425 ha. The result of the study is helpful to understand the extent and pattern of forest conversion in the island and to halt further forest loss and conserve the remaining forest. J. Environ. Sci. & Natural Resources, 11(1-2): 217-225 2018

Download Full-text

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.

Download Full-text

The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1913321117 ◽

2020 ◽

Vol 117 (6) ◽

pp. 3015-3025 ◽

Cited By ~ 15

Author(s):

Wayne S. Walker ◽

Seth R. Gorelik ◽

Alessandro Baccini ◽

Jose Luis Aragon-Osejo ◽

Carmen Josse ◽

...

Keyword(s):

Large Scale ◽

Amazon Basin ◽

Forest Cover ◽

Carbon Dynamics ◽

Forest Degradation ◽

Published Data ◽

Forest Conversion ◽

Carbon Density ◽

Aboveground Carbon ◽

Indigenous Territories

Maintaining the abundance of carbon stored aboveground in Amazon forests is central to any comprehensive climate stabilization strategy. Growing evidence points to indigenous peoples and local communities (IPLCs) as buffers against large-scale carbon emissions across a nine-nation network of indigenous territories (ITs) and protected natural areas (PNAs). Previous studies have demonstrated a link between indigenous land management and avoided deforestation, yet few have accounted for forest degradation and natural disturbances—processes that occur without forest clearing but are increasingly important drivers of biomass loss. Here we provide a comprehensive accounting of aboveground carbon dynamics inside and outside Amazon protected lands. Using published data on changes in aboveground carbon density and forest cover, we track gains and losses in carbon density from forest conversion and degradation/disturbance. We find that ITs and PNAs stored more than one-half (58%; 41,991 MtC) of the region’s carbon in 2016 but were responsible for just 10% (−130 MtC) of the net change (−1,290 MtC). Nevertheless, nearly one-half billion tons of carbon were lost from both ITs and PNAs (−434 MtC and −423 MtC, respectively), with degradation/disturbance accounting for >75% of the losses in 7 countries. With deforestation increasing, and degradation/disturbance a neglected but significant source of region-wide emissions (47%), our results suggest that sustained support for IPLC stewardship of Amazon forests is critical. IPLCs provide a global environmental service that merits increased political protection and financial support, particularly if Amazon Basin countries are to achieve their commitments under the Paris Climate Agreement.

Download Full-text

Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990–2005)

International Journal of Forestry Research ◽

10.1155/2012/729614 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 9

Author(s):

Peter Potapov ◽

Svetlana Turubanova ◽

Ilona Zhuravleva ◽

Matthew Hansen ◽

Alexey Yaroshenko ◽

...

Keyword(s):

Soviet Union ◽

Forest Cover ◽

Spatial Information ◽

Regional Scale ◽

Canopy Cover ◽

Tree Canopy ◽

Forest Cover Change ◽

European North ◽

Tree Canopy Cover ◽

Forest Cover Loss

Forest cover dynamics (defined as tree canopy cover change without regard to forest land use) within the Russian European North have been analyzed from 1990 to 2005 using a combination of results from two Landsat-based forest cover monitoring projects: 1990–2000 and 2000–2005. Results of the forest cover dynamics analysis highlighted several trends in forest cover change since the breakdown of the Soviet planned economy. While total logging area decreased from the 1990–2000 to the 2000–2005 interval, logging and other forms of anthropogenically-induced clearing increased within the Central and Western parts of the region. The most populated regions of European Russia featured the highest rates of net forest cover loss. Our results also revealed intensive gross forest cover loss due to forest felling close to the Russian-Finland border. The annual burned forest area almost doubled between the two time intervals. The 2000–2005 gross forest cover gain results suggest that tree encroachment on abandoned agriculture land is a wide-spread process over the region. The analysis demonstrates the value of regional-scale Landsat-based forest cover and change quantification. Our results supplemented official data by providing independently derived spatial information that could be used for assessing on-going trends and serve as a baseline for future forest cover monitoring.

Download Full-text

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

Forests ◽

10.3390/f11091016 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1016

Author(s):

Mohammad Emran Hasan ◽

Biswajit Nath ◽

A.H.M. Raihan Sarker ◽

Zhihua Wang ◽

Li Zhang ◽

...

Keyword(s):

Cellular Automata ◽

Forest Cover ◽

Landsat Imagery ◽

Forest Degradation ◽

Primary Data ◽

Forest Cover Change ◽

The Past ◽

The Future ◽

Reserve Forest ◽

Health Quality

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.

Download Full-text

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.

Download Full-text

Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-557-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 557-562 ◽

Cited By ~ 9

Author(s):

A. Wijaya ◽

R. A. Sugardiman Budiharto ◽

A. Tosiani ◽

D. Murdiyarso ◽

L.V. Verchot

Keyword(s):

Land Cover ◽

Large Scale ◽

Forest Cover ◽

Spatial Information ◽

Brazilian Amazon ◽

Congo Basin ◽

Reliable Estimate ◽

Forest Conversion ◽

Forest Cover Change ◽

Forest Change

Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.

Download Full-text

Tangible economic value of non-timber forest products from peat swamp forest in Kampar, Indonesia

Biodiversitas Journal of Biological Diversity ◽

10.13057/biodiv/d211260 ◽

2020 ◽

Vol 21 (12) ◽

Author(s):

Bintang Charles Hamonangan Simangunsong ◽

Elisa Ganda Togu Manurung ◽

Elias Elias ◽

Manuntun Parulian Hutagaol ◽

Jusupta Tarigan ◽

...

Keyword(s):

Forest Ecosystem ◽

Forest Cover ◽

Economic Value ◽

Forest Products ◽

Forest Conversion ◽

Swamp Forest ◽

Peat Swamp Forest ◽

Peat Swamp ◽

Non Timber Forest Products ◽

The Government

Abstract. Simangunsong BCH, Manurung EGT, Elias, Hutagaol MP, Tarigan J, Prabawa SB. 2020. Tangible economic value of non-timber forest products from peat swamp forest in Kampar, Indonesia. Biodiversitas 21: 5954-5960. Development of alternative economy based on non-timber forest products usage is an important means to prevent forest conversion and preserve the quality of a forest ecosystem. The main objectives of this study were to identify and calculate the economic value from tangible/marketable perspective of the non-timber forest products (NTFPs) provided by peat swamp forest in Kampar, Sumatra, Indonesia. This is one of the largest remaining peat swamp forest ecosystems in the country. Seven villages located around that forest ecosystem with total forest cover area of 201,224 ha were chosen as samples. A conversion return approach was used to estimate the economic value of non-timber forest products. The results showed 18 kinds of non-timber forest products were identified, but only seven were used commercially by community. They are jungle rubber (Hevea brasiliensis), sago (Metroxylon sp.), swiftlet nest (Aerodramus fuciphagus), honey, betel nut (Areca catechu L), Agathis resin (Agathis dammara), and pandan (Pandanus amaryllifolius Roxb.) The obtained economic value of NTFPs was very low, which was about Rp 9,367.4 (or US$0.68 ha-1 yr-1). Market development of non-timber forest products is then crucial, and the government should play an important role in promoting it in collaboration with private companies. Non-marketed non-timber forest products and various environmental services should also be taken into account to measure that peat swamp forest ecosystem value. Otherwise, concerns about the sustainability of that forest ecosystem in Indonesia due to undervaluation of forest resources will continue.

Download Full-text

30-year changes of natural forests under human activities in the Indochina peninsula - case studies in Cambodia, Laos and Vietnam

Vietnam Journal of Earth Sciences ◽

10.15625/2615-9783/16196 ◽

2021 ◽

Vol 43 (3) ◽

Author(s):

Duong Nguyen Dinh ◽

Cam Lai Vinh

Keyword(s):

Forest Cover ◽

Hydrological Cycle ◽

Regional Scale ◽

Google Earth ◽

Natural Forest ◽

Infrastructure Development ◽

Natural Forests ◽

Forest Cover Change ◽

Remotely Sensed Data ◽

Automated Method

Natural forests are a basic component of the earth's ecology. It is essential for biodiversity, hydrological cycle regulation, and environmental protection. Natural forests are gradually degraded and reduced due to timber logging, conversion to cropland, production forests, commodity trees, and infrastructure development. Decreasing natural forests results in loss of valuable habitats, land degradation, soil erosion, and imbalance of water cycle on the regional scale. Thus, operational monitoring of natural forest cover change has been in the interest of scientists for a long time. Current forest mapping methods using remotely sensed data provide limited capability to separate natural forests and planted forests. Natural forest statistics are often generated using official forestry national reports that have different bias levels due to different methodologies applied in different countries in forest inventory. Over the last couple of decades, natural forests have been over-exploited for various reasons. This led to forest cover degradation and water regulation capability, which results in extreme floods and drought of a watershed in general. This situation demands an urgent need to develop a fast, reliable, and automated method for mapping natural forests. In this study, by applying a new method for mapping natural forests by Landsat time series, the authors succeeded in mapping changes of natural forests of Cambodia, Laos, and Vietnam from 1989 to 2018. As a focused study area, three provinces: Ratanakiri of Cambodia, Attapeu of Laos, and Kon Tum of Vietnam were selected. The study reveals that after 30 years, 51.3% of natural forests in Ratanakiri, 27.8% of natural forests in Attapeu, and 50% of natural forests in Kon Tum were lost. Classification results were validated using high spatial resolution imagery of Google Earth. The overall accuracy of 99.3% for the year 2018 was achieved.

Download Full-text