scholarly journals Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan

2018 ◽  
Vol 50 (2) ◽  
pp. 222 ◽  
Author(s):  
Sanjiwana Arjasakusuma ◽  
Uji Astrono Pribadi ◽  
Gilang Aria Seta
Keyword(s):  
Spatial Pattern ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Accurate Information ◽  
Forest Cover Change ◽  
Forest Change ◽  
Consistency Analysis ◽  
Error Matrix ◽  
Central Kalimantan ◽  
The Road

The accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simple manner. We measured the accuracy by constructing area-proportion error matrix from 388 random sample points and assessed the consistency analysis by looking at the spatial pattern of deforestation and regrowth from built-up area, roads, and rivers from 2010 – 2015 in Katingan district, Central Kalimantan. Accuracy assessment showed that those 3 datasets indicate low to medium accuracy level in which the highest accuracy was achieved by Claslite who produced 71 % ± 5 % of overall accuracy. The consistency analysis provides a similar spatial pattern of deforestation and regrowth measured from the road, river, and built-up area though their distance sensitivity are different one to another. 

scholarly journals SPATIOTEMPORAL CHANGE DETECTION IN FOREST COVER DYNAMICS ALONG LANDSLIDE SUSCEPTIBLE REGION OF KARAKORAM HIGHWAY, PAKISTAN

2018 ◽  
Vol IV-3 ◽  
pp. 177-184
Author(s):  
Barira Rashid ◽  
Javed Iqbal
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Forest Degradation ◽  
Native Forest ◽  
Landsat 8 ◽  
Forest Cover Change ◽  
Forest Change ◽  
Karakoram Highway

Forest Cover dynamics and its understanding is essential for a country’s social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it’s a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

scholarly journals Mapping Mangrove Forest Change in Nijhum Dwip Island

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

scholarly journals Change in tropical forest cover of Southeast Asia from 1990 to 2010

2013 ◽  
Vol 10 (8) ◽  
pp. 12625-12653 ◽  
Author(s):  
H.-J. Stibig ◽  
F. Achard ◽  
S. Carboni ◽  
R. Raši ◽  
J. Miettinen
Keyword(s):  
Southeast Asia ◽  
Satellite Imagery ◽  
Forest Cover ◽  
Satellite Image ◽  
Image Interpretation ◽  
Selective Logging ◽  
Automated Classification ◽  
Forest Cover Change ◽  
Forest Change ◽  
The One

Abstract. The study assesses the extent and trends of forest cover in Southeast Asia for the period 1990–2000–2010 and provides an overview on the main drivers of forest cover change. A systematic sample of 418 sites (10 km × 10 km size) located at the one-degree geographical confluence points and covered with satellite imagery of 30 m resolution is used for the assessment. Techniques of image segmentation and automated classification are combined with visual satellite image interpretation and quality control, involving forestry experts from Southeast Asian countries. The accuracy of our results is assessed through an independent consistency assessment, performed from a subsample of 1572 mapping units and resulting in an overall agreement of > 85% for the general differentiation of forest cover vs. non-forest cover. The total forest cover of Southeast Asia is estimated at 268 Mha in 1990, dropping to 236 Mha in 2010, with annual change rates of 1.75 Mha (~0.67% and 1.45 Mha (~0.59%) for the periods 1990–2000 and 2000–2010, respectively. The vast majority of forest cover loss (~2/3 for 2000–2010) occurred in insular Southeast Asia. Combining the change patterns visible from satellite imagery with the output of an expert consultation on the main drivers of forest change highlights the high pressure on the region's remaining forests. The conversion of forest cover to cash crop plantations (e.g. oil palm) is ranked as the dominant driver of forest change in Southeast Asia, followed by selective logging and the establishment of tree plantations.

scholarly journals Global economic and diet transitions drove Latin American and Caribbean forest change during the first decade of the century.

2021 ◽  
Author(s):  
David Lopez-Carr ◽  
Sadie Jane Ryan ◽  
Matthew Clark
Keyword(s):  
Latin American ◽  
Forest Cover ◽  
Multiple Scales ◽  
Migrant Worker ◽  
National Level ◽  
Environmental Drivers ◽  
Forest Cover Change ◽  
Forest Change ◽  
Forest Regrowth ◽  
Economic Transitions

Latin America and the Caribbean (LAC) contain more tropical high-biodiversity forest than the remaining areas of the planet combined, yet experienced more than a third of global deforestation during the first decade of the 21st century. While drivers of forest change occur at multiple scales, we examined forest change at the municipal and national scales integrated with global processes such as capital, commodity, and labor flows. We modeled multi-scale socioeconomic, demographic, and environmental drivers of local forest cover change. Consistent with LAC’s global leadership in soy and beef exports, primarily to China, Russia, the US, and the EU, national-level beef and soy production were the primary land use drivers of decreased forest cover. National level GDPs, migrant worker remittances, and foreign investment, along with municipal-level temperature and area, were also significantly related to reduced forest cover. This challenges forest transition frameworks, which theorize that rising GDP and intensified agricultural production should be increasingly associated with forest regrowth. Instead, LAC forest change was linked to local, national, and global demographic, dietary and economic transitions, resulting in massive net forest cover loss. This suggests an urgent need to reconcile forest conservation with mounting global demand for animal protein.

scholarly journals Object-Based Classification of Forest Disturbance Types in the Conterminous United States

2019 ◽  
Vol 11 (5) ◽  
pp. 477 ◽  
Author(s):  
Lian-Zhi Huo ◽  
Luigi Boschetti ◽  
Aaron Sparks
Keyword(s):  
United States ◽  
Forest Cover ◽  
Forest Disturbance ◽  
Global Scale ◽  
Management Policy ◽  
Forest Loss ◽  
Forest Cover Change ◽  
Forest Change ◽  
Goods And Services ◽  
Moderate Resolution Imaging Spectroradiometer

Forest ecosystems provide critical ecosystem goods and services, and any disturbance-induced changes can have cascading impacts on natural processes and human socioeconomic systems. Forest disturbance frequency, intensity, and spatial and temporal scale can be altered by changes in climate and human activity, but without baseline forest disturbance data, it is impossible to quantify the magnitude and extent of these changes. Methodologies for quantifying forest cover change have been developed at the regional-to-global scale via several approaches that utilize data from high (e.g., IKONOS, Quickbird), moderate (e.g., Landsat) and coarse (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) spatial resolution satellite imagery. While detection and quantification of forest cover change is an important first step, attribution of disturbance type is critical missing information for establishing baseline data and effective land management policy. The objective here was to prototype and test a semi-automated methodology for characterizing high-magnitude (>50% forest cover loss) forest disturbance agents (stress, fire, stem removal) across the conterminous United States (CONUS) from 2003–2011 using the existing University of Maryland Landsat-based Global Forest Change Product and Web-Enabled Landsat Data (WELD). The Forest Cover Change maps were segmented into objects based on temporal and spatial adjacency, and object-level spectral metrics were calculated based on WELD reflectance time series. A training set of objects with known disturbance type was developed via high-resolution imagery and expert interpretation, ingested into a Random Forest classifier, which was then used to attribute disturbance type to all 15,179,430 forest loss objects across CONUS. Accuracy assessments of the resulting classification was conducted with an independent dataset consisting of 4156 forest loss objects. Overall accuracy was 88.1%, with the highest omission and commission errors observed for fire (32.8%) and stress (31.9%) disturbances, respectively. Of the total 172,686 km2 of forest loss, 83.75% was attributed to stem removal, 10.92% to fire and 5.33% to stress. The semi-automated approach described in this paper provides a promising framework for the systematic characterization and monitoring of forest disturbance regimes.

scholarly journals Change in tropical forest cover of Southeast Asia from 1990 to 2010

2014 ◽  
Vol 11 (2) ◽  
pp. 247-258 ◽  
Author(s):  
H.-J. Stibig ◽  
F. Achard ◽  
S. Carboni ◽  
R. Raši ◽  
J. Miettinen
Keyword(s):  
Southeast Asia ◽  
Satellite Imagery ◽  
Forest Cover ◽  
Satellite Image ◽  
Image Interpretation ◽  
Important Change ◽  
Automated Classification ◽  
Natural Forests ◽  
Forest Cover Change ◽  
Forest Change

Abstract. The study assesses the extent and trends of forest cover in Southeast Asia for the periods 1990–2000 and 2000–2010 and provides an overview on the main causes of forest cover change. A systematic sample of 418 sites (10 km × 10 km size) located at the one-degree geographical confluence points and covered with satellite imagery of 30 m resolution is used for the assessment. Techniques of image segmentation and automated classification are combined with visual satellite image interpretation and quality control, involving forestry experts from Southeast Asian countries. The accuracy of our results is assessed through an independent consistency assessment, performed from a subsample of 1572 mapping units and resulting in an overall agreement of >85% for the general differentiation of forest cover versus non-forest cover. The total forest cover of Southeast Asia is estimated at 268 Mha in 1990, dropping to 236 Mha in 2010, with annual change rates of 1.75 Mha (∼0.67%) and 1.45 Mha (∼0.59%) for the periods 1990–2000 and 2000–2010, respectively. The vast majority of forest cover loss (∼2 / 3 for 2000–2010) occurred in insular Southeast Asia. Complementing our quantitative results by indicative information on patterns and on processes of forest change, obtained from the screening of satellite imagery and through expert consultation, respectively, confirms the conversion of forest to cash crops plantations (including oil palm) as the main cause of forest loss in Southeast Asia. Logging and the replacement of natural forests by forest plantations are two further important change processes in the region.

scholarly journals Models and spatial patterns of deforestation in the Jeneberang watershed

2021 ◽  
Vol 886 (1) ◽  
pp. 012082
Author(s):  
Syamsu Rijal ◽  
Tirza Tirsyayu ◽  
A Chairil ◽  
Munajat Nursaputra ◽  
Andi Nurul Mukhlisa
Keyword(s):  
Spatial Pattern ◽  
Road Network ◽  
Forest Cover ◽  
Binary Logistic Regression ◽  
Analysis Model ◽  
Large Area ◽  
River Population ◽  
Deforestation Rate ◽  
The Road ◽  
Logistic Regression Method

Abstract Deforestation is an event of permanent land cover change from forest cover to non-forest cover. Deforestation events are very influential on the condition of a watershed area. One of the watersheds on the island of Sulawesi that has become a concern is the Jeneberang watershed because of its influence on the city of Makassar and is a priority watershed in Indonesia. This study aims to analyze the model and spatial pattern of deforestation in the Jeneberang watershed. The deforestation analysis model uses the binary logistic regression method by including factors such as a river, population density, road, count, and slope. Analysis of the spatial pattern of deforestation using Fragstat software based on three indices to describe the spatial pattern, namely the Clumpiness Index, Contiguity Mean Index, and Patch Density. The model of deforestation in the Jeneberang watershed shows the road network factor that has the most influence on the occurrence of deforestation. The road network is quite high in all areas in the Jeneberang watershed including the upstream part as a protection zone. The road network serves as community access between villages and sub-districts in Gowa Regency and connects other regencies such as Sinjai, Takalar, and Jeneponto. The spatial pattern of deforestation in the Jeneberang watershed is grouping, the level of connectivity is high, and it is not fragmented. This pattern shows that deforestation occurs in groups, is interconnected with previously deforested areas, and has a fairly large area. This pattern occurs at a relatively low rate and remains the same when the deforestation rate increases or decreases.

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

2020 ◽  
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).

scholarly journals TIPOLOGI PERUBAHAN TUTUPAN HUTAN DI KABUPATEN KUBU RAYA KALIMANTAN BARAT

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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