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

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 Â 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 Â were insignificant (p &geq; 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.

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The impact of forest regeneration on streamflow in 12 meso-scale humid tropical catchments

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-3045-2013 ◽

2013 ◽

Vol 10 (3) ◽

pp. 3045-3102 ◽

Cited By ~ 6

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 Area ◽

Apparent Lack ◽

Macro Scale ◽

Annual Time Series ◽

The Impact ◽

Annual Time ◽

Meso Scale

Abstract. Although regenerating forests make up an increasingly large portion of humid tropical landscapes, comparatively 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 forest regeneration on several Q metrics for 12 meso-scale catchments (23–346 km2; mean precipitation 1720–3422 mm yr−1) with long (33–51 yr) and simultaneous records for Q, precipitation (P), potential evapotranspiration (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 metrics 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 metric. From this the total cumulative change Â was calculated, representing the change in each metric after controlling for climate variability and water storage carry-over effects between years. Negative values of Â were found for most catchments and Q metrics, suggesting enhanced actual evapotranspiration overall following forest regeneration. However, correlations between changes in urban or forest area and values of Â were insignificant (p &geq; 0.389) for all Q metrics. This suggests there is no convincing evidence that changes in the chosen Q metrics 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 apparent 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 meso scale.

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Land Cover Classification Using Features Generated From Annual Time-Series Landsat Data

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2018.2805715 ◽

2018 ◽

Vol 15 (5) ◽

pp. 739-743 ◽

Cited By ~ 5

Author(s):

Jingge Xiao ◽

Honggan Wu ◽

Chengbo Wang ◽

Hao Xia

Keyword(s):

Time Series ◽

Land Cover ◽

Land Cover Classification ◽

Landsat Data ◽

Annual Time Series ◽

Annual Time

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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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Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

Remote Sensing ◽

10.3390/rs71215833 ◽

2015 ◽

Vol 7 (12) ◽

pp. 16274-16292 ◽

Cited By ~ 15

Author(s):

Jesús Anaya ◽

René Colditz ◽

Germán Valencia

Keyword(s):

Time Series ◽

Land Cover ◽

Tropical Region ◽

Land Cover Mapping ◽

Annual Time Series ◽

Annual Time

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Impact of Fiscal Deficit on Inflation in Sri Lanka: An Econometric Time Series Analysis

International Letters of Social and Humanistic Sciences ◽

10.18052/www.scipress.com/ilshs.70.8 ◽

2016 ◽

Vol 70 ◽

pp. 8-13

Author(s):

A.L.M. Aslam ◽

S.M. Ahamed Lebbe

Keyword(s):

Time Series ◽

Sri Lanka ◽

Price Index ◽

Time Series Data ◽

Consumer Price Index ◽

Series Data ◽

Fiscal Deficit ◽

Annual Time Series ◽

The Impact ◽

Annual Time

There is a relationship between the fiscal deficit and inflation, which was confirmed empirically in several studies conducted in many countries. Sri Lanka has been encountering the problem of inflation for the recent years. But in Sri Lanka, this proposition has not yet been studied scientifically. Therefore, this study was going to fill this gap. The objective of this study was to test the impact of fiscal deficit on inflation in Sri Lanka. For this study, the annual time series data were used during the period of 1959 to 2013. The fiscal deficit, exchange rate, government expenditures and import outflow were used as independent variables while the Colombo consumer price index was considered as dependent variable. In addition, the multiple regressions model was used to test the impact of fiscal deficit on inflation. Based on the regression results, the fiscal deficit preserved the positive relationship with inflation in Sri Lanka at one percent significant level. Therefore, this study confirmed that the fiscal deficit accelerates the inflation in Sri Lanka.

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Assessment of Annual Composite Images Obtained by Google Earth Engine for Urban Areas Mapping Using Random Forest

Remote Sensing ◽

10.3390/rs13040748 ◽

2021 ◽

Vol 13 (4) ◽

pp. 748

Author(s):

Zhaoming Zhang ◽

Mingyue Wei ◽

Dongchuan Pu ◽

Guojin He ◽

Guizhou Wang ◽

...

Keyword(s):

Time Series ◽

Random Forest ◽

Urban Areas ◽

Google Earth ◽

Landsat 8 ◽

Annual Time Series ◽

Google Earth Engine ◽

Time Series Images ◽

The Impact ◽

Annual Time

Urban areas represent the primary source region of greenhouse gas emissions. Mapping urban areas is essential for understanding land cover change, carbon cycles, and climate change (urban areas also refer to impervious surfaces, i.e., artificial cover and structures). Remote sensing has greatly advanced urban areas mapping over the last several decades. At present, we have entered the era of big data. Long time series of satellite data such as Landsat and high-performance computing platforms such as Google Earth Engine (GEE) offer new opportunities to map urban areas. The objective of this research was to determine how annual time series images from Landsat 8 Operational Land Imager (OLI) can effectively be composed to map urban areas in three cities in China in support of GEE. Three reducer functions, ee.Reducer.min(), ee.Reducer.median(), and ee.Reducer.max() provided by GEE, were selected to construct four schemes to synthesize the annual intensive time series Landsat 8 OLI data for three cities in China. Then, urban areas were mapped based on the random forest algorithm and the accuracy was evaluated in detail. The results show that (1) the quality of annual composite images was improved significantly, particularly in reducing the impact of cloud and cloud shadows, and (2) the annual composite images obtained by the combination of multiple reducer functions had better performance than that obtained by a single reducer function. Further, the overall accuracy of urban areas mapping with the combination of multiple reducer functions exceeded 90% in all three cities in China. In summary, a suitable combination of reducer functions for synthesizing annual time series images can enhance data quality and ensure differences between characteristics and higher precision for urban areas mapping.

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

Jurnal Sylva Lestari ◽

10.23960/jsl3435-46 ◽

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

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

Glasnik Sumarskog fakulteta ◽

10.2298/gsf1206183r ◽

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.

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