Assessing Forest Cover Change and Fragmentation in Northeastern British Columbia Using Landsat Images and a Geospatial Approach

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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Forest Cover Change in the Ohangwena Region, Northern Namibia: a Case Study Based on Multitemporal Landsat Images and Aerial Photography

The Southern African Forestry Journal ◽

10.1080/10295925.1999.9631209 ◽

1999 ◽

Vol 184 (1) ◽

pp. 25-32 ◽

Cited By ~ 3

Author(s):

Antti Erkkilä ◽

Satu Löfman

Keyword(s):

Aerial Photography ◽

Forest Cover ◽

Forest Cover Change ◽

Landsat Images

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A satellite-derived database for stand-replacing windthrows in boreal forests of the European Russia in 1986–2017

10.5194/essd-2020-91 ◽

2020 ◽

Cited By ~ 1

Author(s):

Andrey N. Shikhov ◽

Alexander V. Chernokulsky ◽

Igor O. Azhigov ◽

Anastasia V. Semakina

Keyword(s):

Boreal Forests ◽

Forest Cover ◽

European Russia ◽

Storm Event ◽

Storm Events ◽

Forest Cover Change ◽

Forest Change ◽

Landsat Images ◽

Forest Zone ◽

Study Region

Abstract. Severe winds are among the main causes of natural disturbances in boreal and temperate forests. Here, we present a new GIS database of stand-replacing windthrows in the forest zone of the European Russia (ER) for the 1986–2017 period. Delineation of windthrows was based on the full archive of Landsat images and two Landsat-derived products on forest cover change, namely the Global Forest Change and the Eastern’ Europe Forest Cover Change datasets. Subsequent verification and analysis of each windthrow was carried out to determine a type of related storm event, its date or date range, and geometrical characteristics. The database contains 102 747 elementary areas of damaged forest that were combined into 700 windthrows caused by 486 convective or non-convective storm events. The database includes stand-replacing windthrows only, which an area > 5 ha and > 25 ha for events caused by tornadoes and other storms, respectively. Additional information contained weather station reports and event description from media sources is also provided. The total area of windthrows amounts to 2966 km2, that is 0.19 % of the forested area of the study region. Convective windstorms contribute 82.5 % to total wind-damaged area, while tornadoes and non-convective windstorms are responsible for 12.9 % and 4.6 % of this area, respectively. Most of windthrows in the ER happen in to summer that is in contrast to Western and Central Europe, where windthrows mainly occur in autumn and winter. The compiled database provides a valuable source of spatial and temporal information on windthrows in the ER and can be successfully used both in forest science and severe storm studies. The database is available at https://doi.org/10.6084/m9.figshare.12073278.v3 (Shikhov et al., 2020).

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Integration of Geospatial Tools and Multi-source Geospatial Data to Evaluate the Tropical Forest Cover Change in Central America and Its Methodological Replicability in Brazil and the DRC

Remote Sensing ◽

10.3390/rs12172705 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2705

Author(s):

Abner Jiménez ◽

Alexander J. Hernández ◽

Víctor M Rodríguez-Espinosa

Keyword(s):

Central America ◽

Forest Cover ◽

Satellite Image ◽

National Level ◽

The State ◽

Satellite Monitoring ◽

Forest Cover Change ◽

Landsat Images ◽

Secondary Sources ◽

Geospatial Tools

Satellite monitoring of forests plays a relevant role in the agendas of tropical countries, mainly in the framework of international negotiations to implement a mechanism that ensures a reduction in global CO2 emissions from deforestation. An efficient way to approach this monitoring is to avoid duplication of efforts, generating products in a regional context that are subsequently adopted at the national level. In this effort, you should take advantage of the different data sources available by integrating geospatial tools and satellite image classification algorithms. In this research, a methodological framework was developed to generate cost-efficient national maps of forest cover and its dynamics for the countries of Central America, and its scalability and replicability was explored in the Democratic Republic of the Congo (DRC) and the State of Pará in Brazil. The maps were generated from Landsat images from the years 2000, 2012, and 2017. New geoprocessing elements have been incorporated into the digital classification procedures for satellite images, such as the automated extraction of training samples from secondary sources, the use of official national reference maps that respond to nationally adopted forest definitions, and automation of post-classification adjustments incorporating expert criteria. The applied regional approach offers advantages in terms of reducing costs and time, as well as improving the consistency and coherence of reports at different territorial levels (regional and national), reducing duplication of efforts and optimizing technical and financial resources. In Central America, the percentage of forest area decreased from 44% in 2000 to 38% in 2017. Average deforestation in the 2000–2012 period was 197,443 ha/year and that of 2012–2017 was 332,243 ha/year. Average deforestation for the complete period 2000–2017 was 264,843 ha/year. The tropical forests in both the State of Pará, Brazil, and the DRC have decreased over time.

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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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Forest Cover Change Pattern after the Intervention of Community Forestry Management System in the Mid-Hill of Nepal: A Case Study

Remote Sensing ◽

10.3390/rs12172756 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2756

Author(s):

Shankar Tripathi ◽

Rajan Subedi ◽

Hari Adhikari

Keyword(s):

Management System ◽

Forest Cover ◽

Community Forestry ◽

Community Forest Management ◽

Community Perception ◽

Forest Cover Change ◽

Landsat Images ◽

Community Forests ◽

The Government ◽

Forest Users

An account of widespread degradation and deforestation in Nepal has been noticed in various literature sources. Although the contribution of community forests (CF) on the improvement of forest cover and condition in the Mid-hill of Nepal is positive, detailed study to understand the current situation seems important. The study area (Tanahun District) lies in the Gandaki Province of western Nepal. The objective of this study was to estimate the forest cover change over the specified period and to identify factors influencing the change. We used Landsat images from the years 1976, 1991, and 2015 to classify land use and land cover. We considered community perception in addition to the forest cover map to understand the different causes of forest cover change. Forest cover decreased from 1976 to 1991 annually at a rate of 0.96%. After 1991, the forest increased annually at a rate of 0.63%. The overall forest cover in the district regained its original status. Factors related to increasing forest cover were emigration, occupation shift, agroforestry practices, as well as particularly by plantation on barren lands, awareness among forest users, and conservation activities conducted by local inhabitants after the government forest was handed over to community members as a community forest management system.

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

Remote Sensing ◽

10.3390/rs13204093 ◽

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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Mangrove Forest Cover Change Detection Along the Coastline of Trincomalee District, Sri Lanka Using GIS and Remote Sensing Techniques

Journal of Marine Science Research and Oceanography ◽

10.33140/jmsro.02.01.04 ◽

2019 ◽

Vol 2 (1) ◽

Keyword(s):

Forest Cover ◽

Forest Cover Change ◽

Landsat Images ◽

Gis And Remote Sensing ◽

Medium Resolution ◽

Data Gaps ◽

Rate Of Decline ◽

Remote Sensing Techniques ◽

Landsat Satellite ◽

Alteration Pattern

Mangroves provide valuable services to the coastal community in Trincomalee District despite they distributed in the small area. The objectives of this research are to map out the distribution of the mangroves and to detect the change in mangroves in Trincomalee District during the last 20 years. According to this study the reduction in the extent of mangroves caused by clearance for alternative land use including aquaculture, tourism. The total extent of mangroves in Trincomalee district was estimated using Landsat satellite imageries 1997 and 2017. The medium resolution of Landsat imageries may lead to underestimating relatively small, linear mangroves in coastal line of Trincomalee district. The occurrence of clouds in the coastal area can cause data gaps during analysis. This study estimated total mangroves in Trincomalee district was 20.26km2 and 15.07 km2 in 1997 and 2017 respectively and representing a loss of 5.19 km2 in the 20 years (1997-2017). Mangroves loss in the study area varied both spatially and temporally due to differences in habitat alteration pattern. However, Landsat images adequately aided to detect changes in mangroves in Trincomalee district which shows the rate of decline in mangroves.

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