Development of National Database on Long-term Deforestation in Sri Lanka

Reddy, C. Sudhakar; Manaswini, G.; Jha, C. S.; Diwakar, P. G.; Dadhwal, V. K.

doi:10.1007/s12524-016-0636-8

Cited by 14 publications

(7 citation statements)

References 19 publications

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“…Intensive, state-subsidized socio-economic development projects targeting rapid agrarian development in the DZ were observed both within and prior to our timeframe of interest is the likely primary cause of forest cover loss [56][57][58]. The political and socio-economic movements underlying these developmental schemes transformed the farming practices of the DZ from a subsistence economy founded on local markets into a competitive commercial enterprise centering the national market [59].…”

Section: Patterns Trends and Drivers Of Forest Cover Change In The mentioning

confidence: 92%

Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka

Ranagalage

Gunarathna

Surasinghe

et al. 2020

Forests

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Forest-cover change has become an important topic in global biodiversity conservation in recent decades because of the high rates of forest loss in different parts of the world, especially in the tropical region. While human interventions are the major cause, natural disasters also contribute to forest cover changes. During the past decades, several studies have been conducted to address different aspects of forest cover changes (e.g., drivers of deforestation, degradation, interventions) in different parts of the world. In Sri Lanka, increasing rates of forest loss have been recorded during the last 100 years on a regional basis, especially in the dry zone. However, Sri Lanka needs detailed studies that employ contemporary data and robust analytical tools to understand the patterns of forest cover changes and their drivers. The dry zone of Sri Lanka encompasses 59% of the total land area of the country, ergo, the most extensive forest cover. Our study analyzed forest cover dynamics and its drivers between 1992 and 2019. Our specific objectives included (i) producing a forest cover map for 2019, (ii) analyzing the spatiotemporal patterns of forest cover changes from 1992 to 2019, and (iii) determining the main driving forces. Landsat 8 images were used to develop forest-cover maps for 2019, and the rest of the forest cover maps (1992, 1999, and 2010) were obtained from the Forest Department of Sri Lanka. In this study, we found that the dry zone had undergone rapid forest loss (246,958.4 ha) during the past 27 years, which accounts for 8.0% of the net forest cover changes. From 2010 to 2019, the rates of forest loss were high, and this can be associated with the rapid infrastructure development of the country. The findings of this study can be used as a proxy to reform current forest policies and enhance the forest sustainability of the study area.

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Section: Patterns Trends and Drivers Of Forest Cover Change In The mentioning

confidence: 92%

Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka

Ranagalage

Gunarathna

Surasinghe

et al. 2020

Forests

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“…Similarly, the accuracy of mangrove forest mapping in Brazil from 1985 to 2018 was 87% [99], while another study reported the average accuracy and kappa coefficient of forest cover mapping in Ethiopia during 1991-2019 were 82.2% and 0.89 [2]. Another study also yielded an accuracy range from 86.6% to 89.80% for the long-term deforestation assessment in Sri Lanka between 1976 and 2005 [71]. Remarkably, it can be concluded that the classification performance was highly accurate and in line with previous studies [2,66,100].…”

Section: Accuracy Of Land Cover Maps and Significance Of Pbtc Mappingmentioning

confidence: 94%

“…From national statistics, the total forest cover in Sri Lanka reduced by 14.5% between 1956 and 2010, with forests covering 29.7% of the total land area in 2010 [23]. From 2005 to 2014, the annual rate of deforestation was 0.01%, while a high rate of deforestation was recorded between 1976 and 1994 [71]. The deforestation hotspots were discovered in Sri Lanka's southeast and northern regions [72].…”

Section: Trend In District Forest Covermentioning

confidence: 99%

Assessment of Forest Cover Changes in Vavuniya District, Sri Lanka: Implications for the Establishment of Subnational Forest Reference Emission Level

Vijitharan

Sasaki

Venkatappa

et al. 2022

Land

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Assessment of forest cover changes is required to establish the forest reference emission level (FREL) at any scale. Due to civil conflict, such assessments have not yet been undertaken in Sri Lanka, especially in the conflict zone. Here, we assessed the forest cover changes in Vavuniya District, Sri Lanka, from 2001 to 2020, using a combination of the Google Earth Engine (GEE) platform and the phenology-based threshold classification (PBTC) method. Landsat 5 TM data for 2001, 2006, and 2010, and Landsat 8 OLI data for 2016 and 2020 were used to classify forest cover by categories, and their related changes could be assessed by four categories, namely dry monsoon forest, open forest, other lands, and water bodies. With an overall average accuracy of 87% and an average kappa coefficient of 0.83, forest cover was estimated at 57.6% of the total land area in 2020. There was an increase of 0.46% per annum for the entire district between 2001 and 2010, but a drastic loss of 0.60% per year was observed between 2010 and 2020. Specifically, the dry monsoon forest lost 0.30%, but open forest gained 3.62% annually over the same period. Loss and gain of forest cover resulted in carbon emissions and removals of 165,306.6 MgCO2 and 24,064.5 MgCO2 annually, respectively, over the same period. Our findings could be used to set the baseline trend of deforestation, based on which, a subnational forest reference emission level can be established as an emission benchmark, against which comparisons of carbon emissions following the implementation of REDD+ activities can be made, and result-based payment can be claimed under the Paris Agreement.

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“…Land cover and land use information are primary indicators utilized to assess environmental processes quantitatively (Sudhakar Reddy, Manaswini, Jha, Diwakar, & Dadhwal, 2017) . The low spectral resolution of satellite data restricts the application of automated classification techniques (Hu et al, 2015) .…”

Section: Landscape Classificationmentioning

confidence: 99%

“…To quantify landscape patterns and analyze landscape dynamics, in the first step, we reviewed 21 related articles (Cai, Li, Ye, & Zhang, 2016), (Sudhakar Reddy, Manaswini, Jha, Diwakar, & Dadhwal, 2017), (Mahamane, Hochschild, Schultz, & Kuma, 2015), (Feng et al, 2018), (Tran & Fischer, 2017), (Dong & Wang, 2010), (Vaz, 2014) , (Manson, Loneragan, & Phinn, 2003), (Singh et al, 2017), (Ju, Arnaldo, Gomes, Fontes, & Mcmanus, 2017), (Sinha, Kumar, & Reid, 2016), (Alphan, 2017), (Gbanie, Griffin, & Thornton, 2018) , (Deng, Wang, Hong, & Qi, 2009), (Basin, 2018), (Chen, Jia, Hutjes, & Menenti, 2015), (Araya & Cabral, 2010), (Zhao et al, 2010), (Botequilha-Leitao & Diaz-Varela, 2018), (Narumalani, Mishra, & Rothwell, 2004) , (Xu & Min, 2013) and found 8 landscape metrics were more emphasized. In the second step, indicated landscape metrics were calculated at the landscape and class levels by FRAGSTATS 3.3 (Feng et al, 2018;Wu et al, 2017) .…”

Section: Landscape Metrics Analysismentioning

confidence: 99%

Landscape Analysis Over 30 Years to Assess the Impact of River Damming On Natural Ecosystem

Petrosians

Danehkar

Samani

et al. 2020

Preprint

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Although there are considerable profits in dam projects, they contribute to significant environmental changes. Landscape patterns are influenced by human pressure and are altered continuously. This study investigated the changes in the landscape pattern of Jask's coastal area in Iran due to the Jagin River dam's construction. A proposed methodology employed satellite images from 1987 to 2018 and classified them by multiple approaches to make LULC maps. Eight information categories were evaluated after classification. The accuracy of the classification was determined using the error matrix and kappa index. FRAGSTATS software was applied to calculate several landscape metrics such as edge density (ED), largest patch index (LPI) and Shannon's diversity index (SHDI). The study reported that water right especially in the recent years, because of excessive use of reserve water, decreased and downstream of Jagin River was dried. The landscapes were continuously characterized by anthropogenic pattern features (agriculture land, aquaculture land, built-up land and residential land) after the dam's construction. Rangeland cover and riparian vegetation decreased, and agriculture land increased with in filling pattern. The sand dune area has been spread to the residential area and roots of mangrove forests, because of this reason some parts of mangrove forest dried and roads are covered by sand dune. Their temporal comparison allowed us to localize the change in landscape patterns under the study time. The results can help decision-makers to evaluate the net benefits acquired as a result of the dam projects. Introduction:Land cover generally has a close correlation with human activities and the physical environment. Its interaction with physical, ecological, geomorphic and anthropogenic processes is significant and they can change it drastically. Between all the mentioned factors, anthropogenic is a critical factor that causes some changes in land cover and land-use (Singh et al., 2017). Detection of LULC change of the Earth's surface is extremely important for any kind of sustainable development program and helps to provide a solution for social, economic and environmental problem (El-kawy, Rød, Ismail, & Suliman, 2011) The spatial structure and form of landscape components are considered as Landscape patterns. Land-cover and land-use change (LCLUC) alters landscape patterns and affects regional ecosystems (Zhang, Kung, & Johnson, 2017).Landscape patterns concept have been reflected in several different subjects such as land-use change, urban planning, environmental protection, ecological construction and policy making continuously. Over the past three decades, the study of the spatiotemporal patterns of landscape has been one of the most critical hotspot research subjects (Gustafson, 2019 ; Feng et al., 2018). Landscape ecologists might be unable to detect landscape pattern attributes such as habitat provision or soil degradation if pattern measurement limits to a few points within a land-cover sequence ( Feng et al., 2...

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Development of National Database on Long-term Deforestation in Sri Lanka

Cited by 14 publications

References 19 publications

Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka

Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka

Assessment of Forest Cover Changes in Vavuniya District, Sri Lanka: Implications for the Establishment of Subnational Forest Reference Emission Level

Landscape Analysis Over 30 Years to Assess the Impact of River Damming On Natural Ecosystem

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