Identifying Biases in Global Tree Cover Products: A Case Study in Costa Rica

Global tree cover products are widely used in analyses of deforestation, fragmentation, and connectivity, but are rarely critically assessed. Inaccuracies in these products could have consequences for future decision making, especially in data-poor regions like the tropics. In this study, potential biases in global and regional tree cover products were assessed across a diverse tropical country, Costa Rica. Two global tree cover products and one regional national forest cover map were evaluated along biophysical gradients in elevation, precipitation, and agricultural land cover. To quantify product accuracy and bias, freely available high-resolution imagery was used to validate tree and land cover across these gradients. Although the regional forest cover map was comparable in accuracy to a widely-used global forest map (the Global Forest Change of Hansen et al., also known as the GFC), another global forest map (derived from a cropland dataset) had the highest accuracy. Both global and regional forest cover products showed small to severe biases along biophysical gradients. Unlike the regional map, the global GFC map strongly underestimated tree cover (>10% difference) below 189 mm of precipitation and at elevations above 2000 m, with a larger bias for precipitation. All map products misclassified agricultural fields as forest, but the GFC product particularly misclassified row crops and perennial erect crops (banana, oil palm, and coffee), with maximum tree cover in agricultural fields of 89%–100% across all crops. Our analysis calls into further question the utility of the GFC product for global forest monitoring outside humid regions, indicating that, in tropical regions, the GFC product is most accurate in areas with high, aseasonal rainfall, low relief, and low cropland area. Given that forest product errors are spatially distributed along biophysical gradients, researchers should account for these spatial biases when attempting to analyze or generate forest map products.

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Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

Remote Sensing ◽

10.3390/rs12193226 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3226

Author(s):

Daniel Cunningham ◽

Paul Cunningham ◽

Matthew E. Fagan

Keyword(s):

Costa Rica ◽

Forest Cover ◽

Agricultural Land ◽

Forest Area ◽

Tree Cover ◽

Agricultural Crop ◽

Forest Change ◽

Alos Palsar ◽

Tropical Regions ◽

The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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Economic Issues Related to Asian Deforestation

Oxford Research Encyclopedia of Environmental Science ◽

10.1093/acrefore/9780199389414.013.575 ◽

2021 ◽

Author(s):

Stefanie Onder ◽

James T. Erbaugh ◽

Georgia Christina Kosmidou-Bradley

Keyword(s):

Supply Chains ◽

Multinational Corporations ◽

Forest Cover ◽

Local Population ◽

Economic Incentives ◽

Forest Monitoring ◽

Tree Cover ◽

Forest Governance ◽

Observation Data ◽

The Impact

The loss of Asian forests represents one of the most significant changes in contemporary land cover. Between 2000 and 2020 alone, an area twice the size of Malaysia has lost its tree cover as measured by Earth observation data. These trends have significant repercussions for greenhouse gas emissions, carbon storage, the conservation of biodiversity, and the wellbeing of Indigenous Peoples and local communities (IPLCs), making Asian deforestation a phenomenon of global concern. There are many immediate factors that drive deforestation across Asia, but the conversion to commodity agriculture is the leading cause. Most notably, the expansion of oil palm and rubber plantations by both multinational corporations and smallholders has led to dramatic conversion of forests. The production of timber as well as pulp and paper has further contributed to significant deforestation, with the evolution of each sector often driven by government policies, such as logging bans. However, it is the underlying drivers (i.e., distal and proximate causes) that determine where and when commodity production displaces forest cover. They are particularly challenging to tackle in a globalized world, where consumption patterns driven by local population and income growth lead to environmental and social change in distant producer countries, including in Asia. Certification programs and legality requirements have been put in place to address these externalities with varying success. Deforestation in Asia is also facilitated by weak governance and regulatory frameworks, where forest rights are often unclear, and financial, technological, and human resources for forest monitoring are limited. Several contemporary forest governance strategies seek to promote sustainable management of Asian forests. Financial mechanisms such as reducing emissions from deforestation and forest degradation (REDD+) and payments for ecosystem services (PES) schemes seek to provide economic incentives for forest conservation. Pledges and activities to remove deforestation from commodity supply chains seek to respond to consumer demand, promote corporate environmental and social responsibility, and reduce the extent to which commodity supply chains contribute to Asian deforestation. And multiple state-led initiatives across Asia to empower IPLCs aim to align forest management objectives between national governments, subnational administrations, and local people. Assessing the impact of interventions related to financial mechanisms, corporate responsibility, and local forest governance will be critical to shaping the future of Asian forest cover change.

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Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada

Remote Sensing ◽

10.3390/rs11192286 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2286

Author(s):

Libo Wang ◽

Paul Bartlett ◽

Darren Pouliot ◽

Ed Chan ◽

Céline Lamarche ◽

...

Keyword(s):

Land Cover ◽

Spatial Resolution ◽

Land Surface ◽

Forest Cover ◽

Reference Sample ◽

Tree Cover ◽

Initial Surface ◽

Forest Cover Change ◽

Global Land Cover ◽

Global Land

Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the Climate Change Initiative (CCI) LC product for use in the Canadian Land Surface Scheme (CLASS) through comparison with finer resolution datasets over Canada, assisted with reference sample data and a vegetation continuous field tree cover fraction dataset. The results show that in comparison with the finer resolution maps over Canada, the 300 m CCI product provides much improved LC distribution over that from the 1 km GLC2000 dataset currently used to provide initial surface conditions in CLASS. However, the CCI dataset appears to overestimate needleleaf forest cover especially in the taiga-tundra transition zone of northwestern Canada. This may have partly resulted from limited availability of clear sky MEdium Resolution Imaging Spectrometer (MERIS) images used to generate the CCI classification maps due to the long snow cover season in Canada. In addition, changes based on the CCI time series are not always consistent with those from the MODIS or a Landsat-based forest cover change dataset, especially prior to 2003 when only coarse spatial resolution satellite data were available for change detection in the CCI product. It will be helpful for application in global simulations to determine whether these results also apply to other regions with similar landscapes, such as Eurasia. Nevertheless, the detailed LC classes and finer spatial resolution in the CCI dataset provide an improved reference map for use in land surface models in Canada. The results also suggest that uncertainties in the current cross-walking tables are a major source of the often large differences in the plant functional types (PFT) maps, and should be an area of focus in future work.

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Evaluation of Land Use and Land Cover Change and Its Drivers in Battambang Province, Cambodia from 1998 to 2018

Sustainability ◽

10.3390/su132011170 ◽

2021 ◽

Vol 13 (20) ◽

pp. 11170

Author(s):

Taingaun Sourn ◽

Sophak Pok ◽

Phanith Chou ◽

Nareth Nut ◽

Dyna Theng ◽

...

Keyword(s):

Economic Growth ◽

Land Use ◽

Land Cover ◽

Forest Cover ◽

Agricultural Land ◽

Development Economic ◽

Infrastructure Development ◽

Lulc Change ◽

Barren Land ◽

Land Prices

The main objective of this research was to evaluate land use and land cover (LULC) change in Battambang province of Cambodia over the last two decades. The LULC maps for 1998, 2003, 2008, 2013 and 2018 were produced from Landsat satellite imagery using the supervised classification technique with the maximum likelihood algorithm. Each map consisted of seven LULC classes: built-up area, water feature, grassland, shrubland, agricultural land, barren land and forest cover. The overall accuracies of the LULC maps were 93%, 82%, 94%, 93% and 83% for 1998, 2003, 2008, 2013 and 2018, respectively. The LULC change results showed a significant increase in agricultural land, and a large decrease in forest cover. Most of the changes in both LULC types occurred during 2003–2008. Overall, agricultural land, shrubland, water features, built-up areas and barren land increased by 287,600 hectares, 58,600 hectares, 8300 hectares, 4600 hectares and 1300 hectares, respectively, while forest cover and grassland decreased by 284,500 hectares and 76,000 hectares respectively. The rate of LULC changes in the upland areas were higher than those in the lowland areas of the province. The main drivers of LULC change identified over the period of study were policy, legal framework and projects to improve economy, population growth, infrastructure development, economic growth, rising land prices, and climate and environmental change. Landmine clearance projects and land concessions resulted in a transition from forest cover and shrubland to agricultural land. Population and economic growth not only resulted in an increase of built-up area, but also led to increasing demand for agricultural land and rising land prices, which triggered the changes of other LULC types. This research provides a long-term and detailed analysis of LULC change together with its drivers, which is useful for decision-makers to make and implement better policies for sustainable land management.

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Analysis of Forest Deforestation and its Driving Factors in Myanmar from 1988 to 2017

Sustainability ◽

10.3390/su11113047 ◽

2019 ◽

Vol 11 (11) ◽

pp. 3047 ◽

Cited By ~ 7

Author(s):

Rongfeng Yang ◽

Yi Luo ◽

Kun Yang ◽

Liang Hong ◽

Xiaolu Zhou

Keyword(s):

Land Cover ◽

Large Scale ◽

Forest Cover ◽

Agricultural Land ◽

Temporal Evolution ◽

Driving Factors ◽

Deforestation Rate ◽

Land Cover Data ◽

Spatio Temporal ◽

Landsat Satellite

Myanmar, abundant in natural resources, is one of the countries with high forest cover in Southeast Asia. Along with its rapid socio-economic development, however, the construction of large-scale infrastructure, expansion of agricultural land, and an increasing demand for timber products have posed serious threats to the forests and significantly affected regional sustainable development. However, the geographical environment in Myanmar is complex, resulting in the lack of long-term sequence of land cover data products. Based on 30 years’ Landsat satellite remote sensing imagery data and the land cover data extracted by a mixed classification method, this paper examined the spatial and temporal evolution characteristics of forest cover in Myanmar and investigated driving factors of the spatio-temporal evolution. Results show that the forest cover has decreased by 110,621 km2 in the past 30 years with the annual deforestation rate of 0.87%. Cropland expansion is the main reason for the deforestation throughout the study period. The study can provide basic information of the forest cover data to the Myanmar government for ecological environment protection. At the same time, it can provide important support to the “Belt and Road” initiative to invest in the region’s economy.

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The Influence of Rainfall and Land Use/Land Cover Changes on River Discharge Variability in the Mountainous Catchment of the Bagmati River

Water ◽

10.3390/w11122444 ◽

2019 ◽

Vol 11 (12) ◽

pp. 2444 ◽

Cited By ~ 3

Author(s):

Dinesh Tuladhar ◽

Ashraf Dewan ◽

Michael Kuhn ◽

Robert J. Corner

Keyword(s):

Land Use ◽

Land Cover ◽

River Discharge ◽

Forest Cover ◽

Agricultural Land ◽

Strong Association ◽

Land Use Land Cover ◽

Discharge Data ◽

Bagmati River

Changes in rainfall and land use/land cover (LULC) can influence river discharge from a catchment in many ways. Homogenized river discharge data from three stations and average rainfall records, interpolated from 13 stations, were examined for long-term trends and decadal variations (1970–2017) in the headwater, upper and middle catchments of the Bagmati River. LULC changes over five decades were quantified using multitemporal Landsat images. Mann–Kendall tests on annual time series showed a significant decrease in river discharge (0.61% per year) from the entire Bagmati catchment, although the decrease in rainfall was statistically insignificant. However, declines in river discharge and rainfall were both significant in upper catchment. Decadal departures from long-term means support these trend results. Over tenfold growth in urban area and a decrease in agricultural land were observed in the upper catchment, while forest cover slightly increased in the entire catchment between 1975 and 2015. Correlation analysis showed a strong association between surface runoff, estimated using the curve number method, observed river discharge and rainfall in the upper catchment, while the relationship was weaker in the headwater catchment. These results were also supported by multiple regression analysis, suggesting that human activities together with climate change have contributed to river discharge changes in the Bagmati catchment.

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China's fight to halt tree cover loss

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2016.2559 ◽

2017 ◽

Vol 284 (1854) ◽

pp. 20162559 ◽

Cited By ~ 34

Author(s):

Antje Ahrends ◽

Peter M. Hollingsworth ◽

Philip Beckschäfer ◽

Huafang Chen ◽

Robert J. Zomer ◽

...

Keyword(s):

Forest Cover ◽

Forest Tree ◽

Forest Monitoring ◽

Tree Cover ◽

Environmental Modelling ◽

The Past ◽

Environmental Suitability ◽

Crown Cover ◽

Order Of Magnitude ◽

Definition Of

China is investing immense resources for planting trees, totalling more than US$ 100 billion in the past decade alone. Every year, China reports more afforestation than the rest of the world combined. Here, we show that China's forest cover gains are highly definition-dependent. If the definition of ‘forest’ follows FAO criteria (including immature and temporarily unstocked areas), China has gained 434 000 km 2 between 2000 and 2010. However, remotely detectable gains of vegetation that non-specialists would view as forest (tree cover higher than 5 m and minimum 50% crown cover) are an order of magnitude less (33 000 km 2 ). Using high-resolution maps and environmental modelling, we estimate that approximately 50% of the world's forest with minimum 50% crown cover has been lost in the past approximately 10 000 years. China historically lost 1.9–2.7 million km 2 (59–67%), and substantial losses continue. At the same time, most of China's afforestation investment targets environments that our model classes as unsuitable for trees. Here, gains detectable via satellite imagery are limited. Conversely, the regions where modest gains are detected are environmentally suitable but have received little afforestation investment due to conflicting land-use demands for agriculture and urbanization. This highlights the need for refined forest monitoring, and greater consideration of environmental suitability in afforestation programmes.

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Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements

Forestry An International Journal of Forest Research ◽

10.1093/forestry/cpaa006 ◽

2020 ◽

Vol 93 (3) ◽

pp. 331-343 ◽

Cited By ~ 2

Author(s):

Michael A Wulder ◽

Txomin Hermosilla ◽

Graham Stinson ◽

François A Gougeon ◽

Joanne C White ◽

...

Keyword(s):

Time Series ◽

Land Cover ◽

Forest Cover ◽

Landsat Imagery ◽

Forest Area ◽

Tree Cover ◽

Minimum Size ◽

Spatially Explicit ◽

Reference Source ◽

International Reporting

Abstract Forests are dynamic ecosystems, subject to both natural and anthropogenic agents of change. Wildfire, harvesting and other human activities alter the tree-covered area present in forests. From national and international reporting perspectives, forests include areas currently treed, as well as those disturbed forest areas that are not currently treed but will be, given time for regeneration and the advancement of natural successional processes. As a consequence, forest area can be depicted at a particular point in time, informed by a retrospective temporal context. Using time series of Landsat imagery, annual land cover maps can be generated that are informed by knowledge of past disturbance history (such as wildfire and harvesting). In this research, we use over three decades of annual land cover data generated from Landsat time series to generate a spatially explicit estimate of the forest area of Canada in 2010. We demonstrate how land cover and disturbance information can be combined to map the area of ‘forest’, as defined by the Food and Agricultural Organization of the United Nations (FAO), within Canada’s 650 Mha of forested ecozones. Following this approach, we estimated Canada’s total forest area in 2010 to be 354.5 Mha. This estimate includes 324.5 Mha of current forest cover in 2010, plus an additional 33.2 Mha (or 9.4 per cent) of temporally informed forest area where tree cover had been temporarily lost due to fire or harvest, less 3.3 Mha that were removed to meet a definitional minimum size (0.5 ha) for contiguous forest area. Using Canada’s National Forest Inventory (NFI) as an independent reference source, the spatial agreement between the two estimates of forest area was ~84 per cent overall. Aspatially, the total area of the Landsat-derived estimate of 2010 forest area and the NFI baseline estimates differed by only 3 per cent, with notable regional differences in the wetland-dominated Hudson Plains Ecozone. Satellite-derived time series land cover and change information enable spatially explicit depictions of forest area (distinct from representations of forest cover) in a robust and transparent fashion, producing information of value to science, management and reporting information needs.

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Forest Cover Assessment in Tuv province of Mongolia Using MODIS and Landsat-7 ETM+

Proceedings of the Mongolian Academy of Sciences ◽

10.5564/pmas.v0i4.40 ◽

2011 ◽

pp. 51-60

Author(s):

R Tsolmon ◽

K Yanagida ◽

M Erdenetuya ◽

L Ochirhuyag

Keyword(s):

High Resolution ◽

Land Cover ◽

Forest Cover ◽

Agricultural Fields ◽

Forest Cover Change ◽

Vegetation Monitoring ◽

Mixed Pixel ◽

Modis Data ◽

Landsat 7 ◽

Academy Of Sciences

The study aimed at determining the relative proportions of forest cover and other components in a mixed pixel. For this purpose a linear mixing model was used for the derivation of a land cover classification map in two study areas of Tuv province, Mongolia. Main types of forest cover change are forests to burn scars and agricultural fields in the study areas. In this paper, two reflective channels 3 and 4 of LANDSAT ETM+ and reflective channels land 2 of MODIS data was used to map five and four land components respectively. Clouds proportion was derived using MODIS data. A synergy between high-resolution MODIS and Landsat ETM+ data may greatly enhance the operational success of satellite based vegetation monitoring, in providing multi-spectral data on parameters of the environment.DOI: http://dx.doi.org/10.5564/pmas.v0i4.40Proceedings of the Mongolian Academy of Sciences 2007 No 4 pp.50-59

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Land use/land cover change assessment of Mohana watershed (Far-Western Nepal) using GIS and remote sensing

Archives of Agriculture and Environmental Science ◽

10.26832/24566632.2021.060309 ◽

2021 ◽

Vol 6 (3) ◽

pp. 320-328

Author(s):

Suraj Prasad Bist ◽

Rabindra Adhikari ◽

Raju Raj Regmi ◽

Rajan Subedi

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Forest Cover ◽

Agricultural Land ◽

Water Bodies ◽

Land Use Land Cover ◽

Landsat Images ◽

Barren Land ◽

Gis And Remote Sensing

The present study was conducted in the Mohana watershed of Far-western Nepal to assess land use land cover change. The study has used ArcGIS and three Landsat images - Landsat TM (1999), Landsat ETM+ (2009), and Landsat OLI (2019) – to analyze land use the land cover change of the watershed. The change matrix technique was used for change detection analysis. The study area was classified into five classes; forest, agriculture, built-up, water bodies, and barren lands. The study has found that among the five identified classes forest and build-up increased positively from 45.40 % to 51.51 % - forest cover and 11.26 % to 19. 85 % - build-up respectively. Similarly, agricultural land and water bodies initially increased but after 2009 both land cover areas decreased to 23.79 % and 0.73 % from 31.38 % and 0.97 % in 2009 respectively. Barren land decreased from 15.37% to 4.12% over the last 20 years. This study might support land-use planners and policymakers to adopt the best suitable land use management option for the Mohana watershed.

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