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

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.

scholarly journals Assessing the Importance of Tree Cover Threshold for Forest Cover Mapping Derived from Global Forest Cover in Myanmar

Forests ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1062 ◽  
Author(s):  
Kay Khaing Lwin ◽  
Tetsuji Ota ◽  
Katsuto Shimizu ◽  
Nobuya Mizoue
Keyword(s):  
Large Scale ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Tree Cover ◽  
Tropical Rainforests ◽  
Forest Change ◽  
Tropical Regions ◽  
Ecological Zones ◽  
Optimal Tree ◽  
Forest Cover Mapping

Comprehensive forest cover mapping is essential for making policy and management decisions. However, creating a forest cover map from raw remote sensing data is a barrier for many users. Here, we investigated the effects of different tree cover thresholds on the accuracy of forest cover maps derived from the Global Forest Change Dataset (GFCD) across different ecological zones in a country-scale evaluation of Myanmar. To understand the effect of different thresholds on map accuracy, nine forest cover maps having thresholds ranging from 10% to 90% were created from the GFCD. The accuracy of the forest cover maps within each ecological zone and at the national scale was assessed. The overall accuracies of ecological zones other than tropical rainforest were highest when the threshold for tree cover was less than 50%. The appropriate threshold for tropical rainforests was 80%. Therefore, different optimal tree cover thresholds were required to achieve the highest overall accuracy depending on ecological zones. However, in the unique case of Myanmar, we were able to determine the threshold across the whole country. We concluded that the threshold for tree cover for creating a forest cover map should be determined according to the areal ratio of ecological zones determined from large-scale monitoring. Our results are applicable to tropical regions having similar ecological zones.

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

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 853 ◽  
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Land Cover ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Monitoring ◽  
Tree Cover ◽  
Agricultural Fields ◽  
Tropical Country ◽  
Row Crops ◽  
Regional Forest

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.

scholarly journals India’s Commitments to Increase Tree and Forest Cover: Consequences for Water Supply and Agriculture Production within the Central Indian Highlands

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 959
Author(s):  
Benjamin Clark ◽  
Ruth DeFries ◽  
Jagdish Krishnaswamy
Keyword(s):  
Groundwater Recharge ◽  
Forest Cover ◽  
Hydrological Modeling ◽  
Monsoon Season ◽  
Forest Policy ◽  
Central India ◽  
Field Measurements ◽  
Tree Cover ◽  
Policy Goals ◽  
The Impact

As part of its nationally determined contributions as well as national forest policy goals, India plans to boost tree cover to 33% of its land area. Land currently under other uses will require tree-plantations or reforestation to achieve this goal. This paper examines the effects of converting cropland to tree or forest cover in the Central India Highlands (CIH). The paper examines the impact of increased forest cover on groundwater infiltration and recharge, which are essential for sustainable Rabi (winter, non-monsoon) season irrigation and agricultural production. Field measurements of saturated hydraulic conductivity (Kfs) linked to hydrological modeling estimate increased forest cover impact on the CIH hydrology. Kfs tests in 118 sites demonstrate a significant land cover effect, with forest cover having a higher Kfs of 20.2 mm hr−1 than croplands (6.7mm hr−1). The spatial processes in hydrology (SPHY) model simulated forest cover from 2% to 75% and showed that each basin reacts differently, depending on the amount of agriculture under paddy. Paddy agriculture can compensate for low infiltration through increased depression storage, allowing for continuous infiltration and groundwater recharge. Expanding forest cover to 33% in the CIH would reduce groundwater recharge by 7.94 mm (−1%) when converting the average cropland and increase it by 15.38 mm (3%) if reforestation is conducted on non-paddy agriculture. Intermediate forest cover shows however shows potential for increase in net benefits.

scholarly journals The impact of forest regeneration on streamflow in 12 mesoscale humid tropical catchments

2013 ◽  
Vol 17 (7) ◽  
pp. 2613-2635 ◽  
Author(s):  
H. E. Beck ◽  
L. A. Bruijnzeel ◽  
A. I. J. M. van Dijk ◽  
T. R. McVicar ◽  
F. N. Scatena ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Forest Regeneration ◽  
Forest Cover ◽  
Impact Analysis ◽  
Forest Area ◽  
Macro Scale ◽  
Annual Time Series ◽  
The Impact ◽  
Annual Time

Abstract. Although regenerating forests make up an increasingly large portion of humid tropical landscapes, little is known of their water use and effects on streamflow (Q). Since the 1950s the island of Puerto Rico has experienced widespread abandonment of pastures and agricultural lands, followed by forest regeneration. This paper examines the possible impacts of these secondary forests on several Q characteristics for 12 mesoscale catchments (23–346 km2; mean precipitation 1720–3422 mm yr−1) with long (33–51 yr) and simultaneous records for Q, precipitation (P), potential evaporation (PET), and land cover. A simple spatially-lumped, conceptual rainfall–runoff model that uses daily P and PET time series as inputs (HBV-light) was used to simulate Q for each catchment. Annual time series of observed and simulated values of four Q characteristics were calculated. A least-squares trend was fitted through annual time series of the residual difference between observed and simulated time series of each Q characteristic. From this the total cumulative change (Â) was calculated, representing the change in each Q characteristic after controlling for climate variability and water storage carry-over effects between years. Negative values of  were found for most catchments and Q characteristics, suggesting enhanced actual evaporation overall following forest regeneration. However, correlations between changes in urban or forest area and values of  were insignificant (p ≥ 0.389) for all Q characteristics. This suggests there is no convincing evidence that changes in the chosen Q characteristics in these Puerto Rican catchments can be ascribed to changes in urban or forest area. The present results are in line with previous studies of meso- and macro-scale (sub-)tropical catchments, which generally found no significant change in Q that can be attributed to changes in forest cover. Possible explanations for the lack of a clear signal may include errors in the land cover, climate, Q, and/or catchment boundary data; changes in forest area occurring mainly in the less rainy lowlands; and heterogeneity in catchment response. Different results were obtained for different catchments, and using a smaller subset of catchments could have led to very different conclusions. This highlights the importance of including multiple catchments in land-cover impact analysis at the mesoscale.

scholarly journals Perubahan Penggunaan Lahan Di Provinsi Lampung Dan Pengaruhnya Terhadap Insidensi Demam Berdarah Dengue (DBD)

2016 ◽  
Vol 4 (3) ◽  
pp. 35
Author(s):  
Agustin Arisandi Mustika ◽  
Samsul Bakri ◽  
Dyah Wulan S. R. Wardani
Keyword(s):  
Land Use ◽  
Forest Cover ◽  
Land Use Changes ◽  
Hemorrhagic Fever ◽  
Forest Area ◽  
Primary Data ◽  
Forest Conversion ◽  
Housing Conditions ◽  
Poverty Level ◽  
The Impact

The conversion of forest area into non-forest area generally can causing the ecology and micro climate change especially rainfall.   The impact of these changes in other side can increasing the probability in occurrence of vector-born disease such as Aedes aegypti mosquito couse of Dengue Hemorrhagic Fever (DHF).   Besides of environmental factors, poverty level, rainfall, and housing conditions the suspected also affect the incidence of dengue.  This research aimed to determine of changes in forest cover and land, poverty level, and housing conditions as well as the impact to the incidence of dengue fever in Lampung. Data collected included primary data of land use changes of Lampung Province and the secondary  data  such  as  the  data  of  precipitation  rapid,  poverty  level,  healthy  house proportion and Incidence Rate of dengue.  The dynamic of changes in forest cover and landper distric/city identified through by Landsat image interpretation 5, 7 and 8  in 2002, 2009 and 2014.   While the impact on DHF analyzed using multiple linear models.   The results showed that there was a significant relationship between the changes of the people forest cover   -1,2634   (p=0,001),   intensive   agricultural   0,5315   (p=0,016),   the   number   of precipitation rapid 0,06869 (p=0,087) and the poverty level -0,2213 (p=0,038) and urbanism region in the towns and villages 28,75 (p=0,010) toward the incidence of dengue in Lampung from the year 2003 to 2014.  Based on the reseacrh result that the goverment should be able to increase the percentage of forest area cause able to decrease the incidence DHF. Keyword: forest conversion, incidence DHF, land use changes

scholarly journals Trends of forest area and population and the impact of population on forest area per hectare in Serbia without APS

2012 ◽  
pp. 183-196
Author(s):  
Nenad Rankovic
Keyword(s):  
Population Density ◽  
Population Growth ◽  
Forest Cover ◽  
Forest Policy ◽  
Forest Area ◽  
Economic Changes ◽  
Policy Measures ◽  
Per Capita ◽  
The Impact

Socio-economic changes throughout history have shaped the attitude towards the forest and most significant ones are changes in terms of population. Over the centuries population and population density have had a significant impact on deforestation and the reduction of forest areas. Therefore, it is important to check what kind of trends are concerned and how population growth affects forest areas, forest cover and forest area per capita. These elements are important for assessing the direction, intensity of activity and the degree of success in the implementation of all forest policy measures in Serbia.

CHANGES IN LAND USE: ILLUSTRATION OF THE IMPACT OF REGIONAL PROGRAM SUPPORT IN INCREASING THE FORESTED AREA IN PODLASKIE VOIVODSHIP

2017 ◽  
Vol XIX (5) ◽  
pp. 106-112
Author(s):  
Anna Maria Klepacka ◽  
Wojciech Florkowski ◽  
Monika Bagińska
Keyword(s):  
Forest Cover ◽  
Agricultural Land ◽  
Pearson Correlation ◽  
Strong Association ◽  
Road Construction ◽  
Entrepreneurial Activity ◽  
Regional Migration ◽  
Program Support ◽  
The Impact ◽  
The Eu

Achieving goals of the national reforestation program for 2020 is threatened by its slow implementation despite financial support provided through the EU rural development programs. This study attempts to examine association between the increase in the forest cover and they are of agricultural land in Poland between 2010 and 2015 and the indirect association between the forest cover and regional migration, and residents seeking employment outside agriculture by registering microenterprises focusing only on Podlaskie Voivodship. The description of the observed developments has been supplemented by calculations of the Pearson correlation coefficient between the key indicators considered in this study. The calculated correlations coefficients suggest strong association between the EU funding and the reforested area in three districts surrounding the major cities in the region. Strong correlations were found between regional migration and the entrepreneurial activity reflected in the number of registered micro-enterprises in the case of Białystok and Łomża districts, but somewhat weaker associations in the case of Suwałki district. The transfer of land away from agriculture to reforestation is affected by the local technical infrastructure expansion, e.g., road construction, and influences the obtained correlation coefficients.

Global analysis of mountain forest distribution and change during 2000 to 2018

2020 ◽  
Author(s):  
Xinyue He ◽  
Dominick Spracklen ◽  
Joseph Holden ◽  
Zhenzhong Zeng
Keyword(s):  
Forest Cover ◽  
River Flow ◽  
Global Analysis ◽  
Tree Cover ◽  
Mountain Forest ◽  
Mountain Forests ◽  
Forest Change ◽  
Elevation Data ◽  
Forest Distribution ◽  
Hydrological Cycles

<p>Mountain forests cover a small fraction of the Earth’s surface, but may exert important influence on the hydrological cycles of river basins (e.g., evapotranspiration, river flow). Many montane ecosystems are currently experiencing forest loss or gain, due to direct land-use change and due to changes in climate. Previous studies revealed most deforestation and afforestation occur in the lowlands, while how forest cover changes at different altitudes in the mountains has not been fully understood. Here we present a study that aims to better understand the distribution of mountain forest change. We use a high-resolution global map of forest change during 2000-2018 combined with elevation data to complete a global analysis of the relationship of elevation with tree cover and tree cover loss and gain. We also assess which climate variables (temperature, rainfall, wind speed) might explain observed variations in tree cover. Our analysis provides new information on how and why mountain forests are changing.</p>

scholarly journals Effect of oil palm sustainability certification on deforestation and fire in Indonesia

2017 ◽  
Vol 115 (1) ◽  
pp. 121-126 ◽  
Author(s):  
Kimberly M. Carlson ◽  
Robert Heilmayr ◽  
Holly K. Gibbs ◽  
Praveen Noojipady ◽  
David N. Burns ◽  
...  
Keyword(s):  
Palm Oil ◽  
Oil Palm ◽  
Forest Cover ◽  
Fire Detection ◽  
Tree Cover ◽  
Forest Loss ◽  
Detection Rates ◽  
Active Fire ◽  
Routine Monitoring ◽  
The Impact

Many major corporations and countries have made commitments to purchase or produce only “sustainable” palm oil, a commodity responsible for substantial tropical forest loss. Sustainability certification is the tool most used to fulfill these procurement policies, and around 20% of global palm oil production was certified by the Roundtable on Sustainable Palm Oil (RSPO) in 2017. However, the effect of certification on deforestation in oil palm plantations remains unclear. Here, we use a comprehensive dataset of RSPO-certified and noncertified oil palm plantations (∼188,000 km2) in Indonesia, the leading producer of palm oil, as well as annual remotely sensed metrics of tree cover loss and fire occurrence, to evaluate the impact of certification on deforestation and fire from 2001 to 2015. While forest loss and fire continued after RSPO certification, certified palm oil was associated with reduced deforestation. Certification lowered deforestation by 33% from a counterfactual of 9.8 to 6.6% y−1. Nevertheless, most plantations contained little residual forest when they received certification. As a result, by 2015, certified areas held less than 1% of forests remaining within Indonesian oil palm plantations. Moreover, certification had no causal impact on forest loss in peatlands or active fire detection rates. Broader adoption of certification in forested regions, strict requirements to avoid all peat, and routine monitoring of clearly defined forest cover loss in certified and RSPO member-held plantations appear necessary if the RSPO is to yield conservation and climate benefits from reductions in tropical deforestation.

scholarly journals Assessing the Impact of land-use types on the groundwater quality: a case study of Mid River Njoro Catchment, Kenya

2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Halake Guyo Rendilicha ◽  
Patrick Home ◽  
James M. Raude ◽  
Charles M. M’Erimba ◽  
Stellamaris Muthoka
Keyword(s):  
Land Use ◽  
Groundwater Quality ◽  
Forest Cover ◽  
Agricultural Land ◽  
Settlement Area ◽  
Mixed Area ◽  
Land Use Types ◽  
The Mean ◽  
The Impact

The study assessed the impact of land-use types on the groundwater quality of the mid River Njoro catchment, Kenya. Groundwater samples were collected from eight boreholes between the period of October 2017 to February 2018 and analyzed for pH, temperature, electrical conductivity, dissolved oxygen, nitrate, ammonium, and total phosphorus. These parameters were used to calculate the Groundwater Quality Index (GQI) value of the study area. The concentration maps (“primary maps I”) were constructed using Kriging interpolation of ArcGIS software from the seven groundwater quality parameters. The “primary maps I” were standardized with the KEBS and WHO standards to the “primary maps II” for ease of integration into a GIS environment. The “primary maps II” were then rated and weighted using a polynomial function to generate “rank maps” before calculating the GQI using spatial analyst tools of ArcGIS software. The land use map was prepared from a high-resolution Google earth satellite imagery of 2015. The mean GQI values for the different land use polygons were calculated and compared using GIS techniques. The GQI ranged from 68.38 to 70.92, indicating a high groundwater quality of mid River Njoro catchment. The major land-use types identified include settlement area, forest cover, agricultural land and mixed area. The agricultural land dominated the study area, followed by settlement area, forest cover and finally mixed area. The mean GQI value in each land use type varied minimally and this could be because of the diffuse nature of the land use types of the study area. Settlement area had low GQI, followed by agricultural land, mixed area and the forest cover had the highest mean GQI value, which corresponds to good quality of groundwater. Even though the variation is insignificant in this particular study, it somehow indicates the adverse effects of different land use on the quality of groundwater.

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