A Bayesian approach to multisource forest area estimation

Treesearch

Andrew O. Finley

2007-01-01

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, demand is increasing for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest and, most importantly, provide associated error estimates. This paper presents a model-based approach for...

A Comparison of Various Estimators for Updating Forest Area Coverage Using AVHRR and Forest Inventory Data

Treesearch

Francis A. Roesch; Paul C. van Deusen; Zhiliang Zhu

1995-01-01

Various methods of adjusting low-cost and possibly biased estimates of percent forest coverage from AVHRR data with a subsample of higher-cost estimates from the USDA Forest Service's Forest Inventory and Analysis plots were investigated. Two ratio and two regression estimators were evaluated. Previous work (Zhu and Teuber, 1991) finding that the estimates from...

Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

Treesearch

Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

2009-01-01

We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

[Estimation of Shenyang urban forest green biomass].

PubMed

Liu, Chang-fu; He, Xing-yuan; Chen, Wei; Zhao, Gui-ling; Xu, Wen-duo

2007-06-01

Based on ARC/GIS and by using the method of "planar biomass estimation", the green biomass (GB) of Shenyang urban forests was measured. The results demonstrated that the GB per unit area was the highest (3.86 m2.m(-2)) in landscape and relaxation forest, and the lowest (2.27 m2.m(-2)) in ecological and public welfare forest. The GB per unit area in urban forest distribution area was 2.99 m2.m(-2), and that of the whole Shenyang urban area was 0.25 m2.m(-2). The total GB of Shenyang urban forests was about 1.13 x 10(8) m2, among which, subordinated forest, ecological and public welfare forest, landscape and relaxation forest, road forest, and production and management forest accounted for 36.64% , 23.99% , 19.38% , 16.20% and 3.79%, with their GB being 4. 15 x 10(7), 2.72 x 10(7), 2.20 x 10(7), 1.84 x 10(7) and 0.43 x 10(7) m2, respectively. The precision of the method "planar biomass estimation" was 91.81% (alpha = 0.05) by credit test.

A comparison of small-area estimation techniques to estimate selected stand attributes using LiDAR-derived auxiliary variables

Treesearch

Michael E. Goerndt; Vicente J. Monleon; Hailemariam Temesgen

2011-01-01

One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and auxiliary information is available. Selected SAE methods were...

Modeling grain-size dependent bias in estimating forest area: a regional application

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

A better understanding of scaling-up effects on estimating important landscape characteristics (e.g. forest percentage) is critical for improving ecological applications over large areas. This study illustrated effects of changing grain sizes on regional forest estimates in Minnesota, Wisconsin, and Michigan of the USA using 30-m land-cover maps (1992 and 2001)...

Forest/non-forest mapping using inventory data and satellite imagery

Treesearch

Ronald E. McRoberts

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation

Treesearch

Goran Stahl; Svetlana Saarela; Sebastian Schnell; Soren Holm; Johannes Breidenbach; Sean P. Healey; Paul L. Patterson; Steen Magnussen; Erik Naesset; Ronald E. McRoberts; Timothy G. Gregoire

2016-01-01

This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where...

Evaluating Heterogeneous Conservation Effects of Forest Protection in Indonesia

PubMed Central

Shah, Payal; Baylis, Kathy

2015-01-01

Establishing legal protection for forest areas is the most common policy used to limit forest loss. This article evaluates the effectiveness of seven Indonesian forest protected areas introduced between 1999 and 2012. Specifically, we explore how the effectiveness of these parks varies over space. Protected areas have mixed success in preserving forest, and it is important for conservationists to understand where they work and where they do not. Observed differences in the estimated treatment effect of protection may be driven by several factors. Indonesia is particularly diverse, with the landscape, forest and forest threats varying greatly from region to region, and this diversity may drive differences in the effectiveness of protected areas in conserving forest. However, the observed variation may also be spurious and arise from differing degrees of bias in the estimated treatment effect over space. In this paper, we use a difference-in-differences approach comparing treated observations and matched controls to estimate the effect of each protected area. We then distinguish the true variation in protected area effectiveness from spurious variation driven by several sources of estimation bias. Based on our most flexible method that allows the data generating process to vary across space, we find that the national average effect of protection preserves an additional 1.1% of forest cover; however the effect of individual parks range from a decrease of 3.4% to an increase of 5.3% and the effect of most parks differ from the national average. Potential biases may affect estimates in two parks, but results consistently show Sebangau National Park is more effective while two parks are substantially less able to protect forest cover than the national average. PMID:26039754

Evaluating heterogeneous conservation effects of forest protection in Indonesia.

PubMed

Shah, Payal; Baylis, Kathy

2015-01-01

Establishing legal protection for forest areas is the most common policy used to limit forest loss. This article evaluates the effectiveness of seven Indonesian forest protected areas introduced between 1999 and 2012. Specifically, we explore how the effectiveness of these parks varies over space. Protected areas have mixed success in preserving forest, and it is important for conservationists to understand where they work and where they do not. Observed differences in the estimated treatment effect of protection may be driven by several factors. Indonesia is particularly diverse, with the landscape, forest and forest threats varying greatly from region to region, and this diversity may drive differences in the effectiveness of protected areas in conserving forest. However, the observed variation may also be spurious and arise from differing degrees of bias in the estimated treatment effect over space. In this paper, we use a difference-in-differences approach comparing treated observations and matched controls to estimate the effect of each protected area. We then distinguish the true variation in protected area effectiveness from spurious variation driven by several sources of estimation bias. Based on our most flexible method that allows the data generating process to vary across space, we find that the national average effect of protection preserves an additional 1.1% of forest cover; however the effect of individual parks range from a decrease of 3.4% to an increase of 5.3% and the effect of most parks differ from the national average. Potential biases may affect estimates in two parks, but results consistently show Sebangau National Park is more effective while two parks are substantially less able to protect forest cover than the national average.

Using Airborne LIDAR Data for Assessment of Forest Fire Fuel Load Potential

NASA Astrophysics Data System (ADS)

İnan, M.; Bilici, E.; Akay, A. E.

2017-11-01

Forest fire incidences are one of the most detrimental disasters that may cause long terms effects on forest ecosystems in many parts of the world. In order to minimize environmental damages of fires on forest ecosystems, the forested areas with high fire risk should be determined so that necessary precaution measurements can be implemented in those areas. Assessment of forest fire fuel load can be used to estimate forest fire risk. In order to estimate fuel load capacity, forestry parameters such as number of trees, tree height, tree diameter, crown diameter, and tree volume should be accurately measured. In recent years, with the advancements in remote sensing technology, it is possible to use airborne LIDAR for data estimation of forestry parameters. In this study, the capabilities of using LIDAR based point cloud data for assessment of the forest fuel load potential was investigated. The research area was chosen in the Istanbul Bentler series of Bahceköy Forest Enterprise Directorate that composed of mixed deciduous forest structure.

Minnesota's forest resources in 2005

Treesearch

Patrick D. Miles; Gary J. Brand

2007-01-01

Reports forest statistics for Minnesota based on five annual inventories from 2001 through 2005. Minnesota's total forest area is estimated at 16.3 million acres or 32 percent of the total land area of the State. The estmated total live-tree volume on forest land is 17.7 billion cubic feet or 1,085 cubic feet per acre. The estimated aboveground live-tree biomass...

COLE: A Web-based Tool for Interfacing with Forest Inventory Data

Treesearch

Patrick Proctor; Linda S. Heath; Paul C. Van Deusen; Jeffery H. Gove; James E. Smith

2005-01-01

We are developing an online computer program to provide forest carbon related estimates for the conterminous United States (COLE). Version 1.0 of the program features carbon estimates based on data from the USDA Forest Service Eastwide Forest Inventory database. The program allows the user to designate an area of interest, and currently provides area, growing-stock...

Historic Emissions from Deforestation and Forest Degradation in Mato Grosso, Brazil: 1. Source Data Uncertainties

NASA Technical Reports Server (NTRS)

Morton, Douglas C.; Sales, Marcio H.; Souza, Carlos M., Jr.; Griscom, Bronson

2011-01-01

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

An Illustration of Generalised Arma (garma) Time Series Modeling of Forest Area in Malaysia

NASA Astrophysics Data System (ADS)

Pillai, Thulasyammal Ramiah; Shitan, Mahendran

Forestry is the art and science of managing forests, tree plantations, and related natural resources. The main goal of forestry is to create and implement systems that allow forests to continue a sustainable provision of environmental supplies and services. Forest area is land under natural or planted stands of trees, whether productive or not. Forest area of Malaysia has been observed over the years and it can be modeled using time series models. A new class of GARMA models have been introduced in the time series literature to reveal some hidden features in time series data. For these models to be used widely in practice, we illustrate the fitting of GARMA (1, 1; 1, δ) model to the Annual Forest Area data of Malaysia which has been observed from 1987 to 2008. The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation.

Using small area estimation and Lidar-derived variables for multivariate prediction of forest attributes

Treesearch

F. Mauro; Vicente Monleon; H. Temesgen

2015-01-01

Small area estimation (SAE) techniques have been successfully applied in forest inventories to provide reliable estimates for domains where the sample size is small (i.e. small areas). Previous studies have explored the use of either Area Level or Unit Level Empirical Best Linear Unbiased Predictors (EBLUPs) in a univariate framework, modeling each variable of interest...

Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties

PubMed Central

2011-01-01

Background Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from credited mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results Deforestation estimates showed good agreement for multi-year periods of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by > 20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C ha-1, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions Estimates of source data uncertainties are essential for REDD+. Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions. PMID:22208947

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

Arkansas, 2009 forest inventory and analysis factsheet

Treesearch

James F. Rosson

2011-01-01

The summary includes estimates of forest land area (table 1), ownership (table 2), forest-type groups (table 3), volume (tables 4 and 5), biomass (tables 6 and 7), and pine plantation area (table 8) along with maps of Arkansas’ survey units (fig. 1), percent forest by county (fig. 2), and distribution of pine plantations (fig. 3). The estimates are presented by survey...

The effect of using complete and partial forested FIA plot data on biomass and forested area classifications from MODIS satellite data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2006-01-01

Authors’ objective was to determine at what level biomass and forest area obtained from partial and complete forested plot inventory data compares with forested area and biomass estimates from the national inventory data. A subset of 3819 inventory plots (100% forested, 100% non-forested, mixed-forest/non-forest) was used to classify the land cover and model the...

[Remote sensing estimation of urban forest carbon stocks based on QuickBird images].

PubMed

Xu, Li-Hua; Zhang, Jie-Cun; Huang, Bo; Wang, Huan-Huan; Yue, Wen-Ze

2014-10-01

Urban forest is one of the positive factors that increase urban carbon sequestration, which makes great contribution to the global carbon cycle. Based on the high spatial resolution imagery of QuickBird in the study area within the ring road in Yiwu, Zhejiang, the forests in the area were divided into four types, i. e., park-forest, shelter-forest, company-forest and others. With the carbon stock from sample plot as dependent variable, at the significance level of 0.01, the stepwise linear regression method was used to select independent variables from 50 factors such as band grayscale values, vegetation index, texture information and so on. Finally, the remote sensing based forest carbon stock estimation models for the four types of forest were established. The estimation accuracies for all the models were around 70%, with the total carbon reserve of each forest type in the area being estimated as 3623. 80, 5245.78, 5284.84, 5343.65 t, respectively. From the carbon density map, it was found that the carbon reserves were mainly in the range of 25-35 t · hm(-2). In the future, urban forest planners could further improve the ability of forest carbon sequestration through afforestation and interplanting of trees and low shrubs.

Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

USGS Publications Warehouse

Potapov, P.; Hansen, Matthew C.; Stehman, S.V.; Loveland, Thomas R.; Pittman, K.

2008-01-01

Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. These maps were used to assign all blocks (18.5 by 18.5 km) partitioning the boreal biome into strata of high, medium and low likelihood of forest cover loss. A stratified random sample of 118 blocks was interpreted for forest cover and forest cover loss using high spatial resolution Landsat imagery from 2000 and 2005. Area of forest cover gross loss from 2000 to 2005 within the boreal biome is estimated to be 1.63% (standard error 0.10%) of the total biome area, and represents a 4.02% reduction in year 2000 forest cover. The proportion of identified forest cover loss relative to regional forest area is much higher in North America than in Eurasia (5.63% to 3.00%). Of the total forest cover loss identified, 58.9% is attributable to wildfires. The MODIS pan-boreal change hotspot estimates reveal significant increases in forest cover loss due to wildfires in 2002 and 2003, with 2003 being the peak year of loss within the 5-year study period. Overall, the precision of the aggregate forest cover loss estimates derived from the Landsat data and the value of the MODIS-derived map displaying the spatial and temporal patterns of forest loss demonstrate the efficacy of this protocol for operational, cost-effective, and timely biome-wide monitoring of gross forest cover loss.

Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data.

PubMed

Hansen, Matthew C; Stehman, Stephen V; Potapov, Peter V; Loveland, Thomas R; Townshend, John R G; DeFries, Ruth S; Pittman, Kyle W; Arunarwati, Belinda; Stolle, Fred; Steininger, Marc K; Carroll, Mark; Dimiceli, Charlene

2008-07-08

Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy responses will be uninformed concerning the most basic facts of forest cover change. Results of a feasible and cost-effective monitoring strategy are presented that enable timely, precise, and internally consistent estimates of forest clearing within the humid tropics. A probability-based sampling approach that synergistically employs low and high spatial resolution satellite datasets was used to quantify humid tropical forest clearing from 2000 to 2005. Forest clearing is estimated to be 1.39% (SE 0.084%) of the total biome area. This translates to an estimated forest area cleared of 27.2 million hectares (SE 2.28 million hectares), and represents a 2.36% reduction in area of humid tropical forest. Fifty-five percent of total biome clearing occurs within only 6% of the biome area, emphasizing the presence of forest clearing "hotspots." Forest loss in Brazil accounts for 47.8% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 12.8%. Over three-fifths of clearing occurs in Latin America and over one-third in Asia. Africa contributes 5.4% to the estimated loss of humid tropical forest cover, reflecting the absence of current agro-industrial scale clearing in humid tropical Africa.

Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data

USGS Publications Warehouse

Hansen, Matthew C.; Stehman, S.V.; Potapov, Peter V.; Loveland, Thomas R.; Townshend, J.R.G.; DeFries, R.S.; Pittman, K.W.; Arunarwati, B.; Stolle, F.; Steininger, M.K.; Carroll, M.; DiMiceli, C.

2008-01-01

Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy responses will be uninformed concerning the most basic facts of forest cover change. Results of a feasible and cost-effective monitoring strategy are presented that enable timely, precise, and internally consistent estimates of forest clearing within the humid tropics. A probability-based sampling approach that synergistically employs low and high spatial resolution satellite datasets was used to quantify humid tropical forest clearing from 2000 to 2005. Forest clearing is estimated to be 1.39% (SE 0.084%) of the total biome area. This translates to an estimated forest area cleared of 27.2 million hectares (SE 2.28 million hectares), and represents a 2.36% reduction in area of humid tropical forest. Fifty-five percent of total biome clearing occurs within only 6% of the biome area, emphasizing the presence of forest clearing “hotspots.” Forest loss in Brazil accounts for 47.8% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 12.8%. Over three-fifths of clearing occurs in Latin America and over one-third in Asia. Africa contributes 5.4% to the estimated loss of humid tropical forest cover, reflecting the absence of current agro-industrial scale clearing in humid tropical Africa.

Improving carbon monitoring and reporting in forests using spatially-explicit information.

PubMed

Boisvenue, Céline; Smiley, Byron P; White, Joanne C; Kurz, Werner A; Wulder, Michael A

2016-12-01

Understanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere-specifically the process of C removal from the atmosphere, and how this process is changing-is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada. Our results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year -1 ) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha -1 . Comparisons between our estimates and estimates from Canada's National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates. Both estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences between these estimates. This study represents an important first step towards the integration of spatially-explicit information into Canada's NFCMARS.

Individual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon

NASA Astrophysics Data System (ADS)

Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.

2017-12-01

The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.

Extending large-scale forest inventories to assess urban forests.

PubMed

Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter

2012-03-01

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.

ForestCrowns: a transparency estimation tool for digital photographs of forest canopies

Treesearch

Matthew Winn; Jeff Palmer; S.-M. Lee; Philip Araman

2016-01-01

ForestCrowns is a Windows®-based computer program that calculates forest canopy transparency (light transmittance) using ground-based digital photographs taken with standard or hemispherical camera lenses. The software can be used by forest managers and researchers to monitor growth/decline of forest canopies; provide input for leaf area index estimation; measure light...

The effects of forest fragmentation on forest stand attributes

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and...

Minnesota's forest resources in 2004

Treesearch

Patrick D. Miles; Gary J. Brand; Manfred E. Mielke

2006-01-01

This report presents forest statistics based on the five annual inventory panels measured from 2000 through 2004. Forest area is estimated at 16.2 million acres or 32 percent of the total land area in the State. Important pests in Minnesota forests include the forest tent caterpillar and spruce budworm.

Identifying grain-size dependent errors on global forest area estimates and carbon studies

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our...

Using satellite imagery as ancillary data for increasing the precision of estimates for the Forest Inventory and Analysis program of the USDA Forest Service

Treesearch

Ronald E. McRoberts; Geoffrey R. Holden; Mark D. Nelson; Greg C. Liknes; Dale D. Gormanson

2006-01-01

Forest inventory programs report estimates of forest variables for areas of interest ranging in size from municipalities, to counties, to states or provinces. Because of numerous factors, sample sizes are often insufficient to estimate attributes as precisely as is desired, unless the estimation process is enhanced using ancillary data. Classified satellite imagery has...

Forests of Illinois, 2017

Treesearch

Susan J. Crocker

2018-01-01

This update provides an overview of forest resources in Illinois following an inventory by the USDA Forest Service, Forest Inventory and Analysis program, Northern Research Station. Estimates are derived from field data collected using an annualized sample design. Current variable estimates such as area and volume are based on 5,994 (1,046 forested) plots measured in...

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Treesearch

Ronald E. McRoberts

2010-01-01

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

Estimating erosion risks associated with logging and forest roads in northwestern California

Treesearch

Raymond M. Rice; Jack Lewis

1991-01-01

Abstract - Erosion resulting from logging and road building has long been a concern to forest managers and the general public. An objective methodology was developed to estimate erosion risk on forest roads and in harvest areas on private land in northwestern California. It was based on 260 plots sampled from the area harvested under 415 Timber Harvest Plans...

The national forest inventory of the United States of America

Treesearch

Ronald E. McRoberts

2008-01-01

The mission of the Forest Inventory and Analysis (FIA) program of the Forest Service, U.S. Department of Agriculture, is to conduct the national forest inventory of the United States of America for purposes of estimating the area of forest land; the volume, growth, and removal of forest resources; and the health of the forest. Users of FIA data, estimates, and related...

North Dakota's forest resources in 2004

Treesearch

David Haugen; Gary Brand; Michael Kangas

2006-01-01

Results of the combined 2001-2004 annual forest inventory panels for North Dakota show more than 733 thousand acres of forest land that contain an estimated 737 million cubic feet of all live tree volume or approximately 1,005 cubic feet per forest land acre. Timberland area in North Dakota was estimated at 547 thousand acres, with an estimated 358 million cubic feet...

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Treesearch

Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...

Measuring Forest Area Loss Over Time Using FIA Plots and Satellite Imagery

Treesearch

Michael L. Hoppus; Andrew J. Lister

2005-01-01

How accurately can FIA plots, scattered at 1 per 6,000 acres, identify often rare forest land loss, estimated at less than 1 percent per year in the Northeast? Here we explore this question mathematically, empirically, and by comparing FIA plot estimates of forest change with satellite image based maps of forest loss. The mathematical probability of exactly estimating...

North Dakota's forest resources in 2005

Treesearch

David E. Haugen; Gary J. Brand; Michael Kangas

2006-01-01

This report completes the first 5 years of the annual forest inventory in North Dakota and presents estimates of forest area, volume, and biomass for 2005. It is part of the national effort of annual forest inventory authorized by the 1998 Farm Bill. Sine the third forest inventory, in 1994, total forest land area has increased by 51,000 acres. Private forest land...

Estimating evapotranspiration change due to forest treatment and fire at the basin scale in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Roche, J. W.; Goulden, M.; Bales, R. C.

2017-12-01

Increased forest evapotranspiration (ET) coupled with snowpack decreases in a warming climate is likely to decrease runoff and increase forest drought stress. Field experiments and modeling suggest that forest thinning can reduce ET and thus increase potential runoff relative to untreated areas. We investigated the potential magnitude and duration of ET decreases resulting from forest-thinning treatments and fire using a robust empirical relation between Landsat-derived mean-annual normalized difference vegetation index (NDVI) and annual ET measured at flux towers. Among forest treatments, the minimum observed NDVI change required to produce a significant departure from control plots with NDVI of about 0.70 was -0.07 units, corresponding to a basal-area reduction of 3.1 m2 ha-1, and equivalent to an estimated ET reduction of -102 mm yr-1. Intensive thinning in highly productive forests that approached pre-fire-exclusion densities reduced basal area by 40-50%, generating estimated ET reductions of 152-216 mm yr-1 over five years following treatment. Between 1990 and 2008, fires in the American River basin generated more than twice the ET reduction per unit area than those in the Kings River basin, corresponding to greater water and energy limitations in the latter and greater fire severity in the former. A rough extrapolation of these results to the entire American River watershed, much of which would have burned naturally during this 19-year period, could result in ET reductions that approach 10% of full natural flows for drought years and 5% averaged over all years. This work demonstrates the potential utility to estimate forest ET change at the patch scale, which in turn may allow managers to estimate thinning benefits in areas lacking detailed hydrologic measurements.

Estimation of carbon emissions from wildfires in Alaskan boreal forests using AVHRR data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kasischke, E.S.; French, N.H.F.; Bourgeau-Chavez, L.L

1993-06-01

The objectives of this research study were to evaluate the utility of using AVHRR data for locating and measuring the areal extent of wildfires in the boreal forests of Alaska and to estimate the amount of carbon being released during these fires. Techniques were developed to using the normalized difference vegetation signature derived from AVHRR data to detect and measure the area of fires in Alaska. A model was developed to estimate the amount of biomass/carbon being stored in Alaskan boreal forests, and the amount of carbon released during fires. The AVHRR analysis resulted in detection of > 83% ofmore » all forest fires greater than 2,000 ha in size in the years 1990 and 1991. The areal estimate derived from AVHRR data were 75% of the area mapped by the Alaska Fire Service for these years. Using fire areas and locations for 1954 through 1992, it was determined that on average, 13.0 gm-C-m-2 of boreal forest area is released during fires every year. This estimate is two to six times greater than previous reported estimates. Our conclusions are that the analysis of AVHRR data represents a viable means for detecting and mapping fires in boreal regions on a global basis.« less

Forest Understory Fire in the Brazilian Amazon in ENSO and Non-ENSO Years: Area Burned and Committed Carbon Emissions

NASA Technical Reports Server (NTRS)

Alencar, A.; Nepstad, D.; Ver-Diaz, M. Del. C.

2004-01-01

"Understory fires" that burn the floor of standing forests are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Nino Southern Oscillation (ENSO) episodes. However, we are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. We calculated the area of forest understory fires for the Brazilian Amazon region during an El Nino (1998) and a non El Nino (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazon, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 millions of hectares) was 13 times greater than the area burned during the average rainfall year (0.2 million hectares), and twice the area of annual deforestation rate. Dense forest was, proportionally, the forest area most affected by understory fires during the El Nino year, while understory fires were concentrated in transitional forests during the year of average rainfall. Our estimate of aboveground tree biomass killed by fire ranged from 0.06 Pg to 0.38 Pg during the ENSO and from 0,004 Pg to 0,024 Pg during the non ENSO.

Assessing biomass and forest area classifications from modis satellite data while incrementing the number of FIA data panels

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2005-01-01

Our objective was to determine at what level biomass and forest area obtained from 2, 3, 4, or 5 panels of forest inventory data compares well with forested area and biomass estimates from the national inventory data. A subset of 2605 inventory plots (100% forested, 100% non-forested) was used to classify the land cover and model the biomass in South Carolina. Mixed...

Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurments of height and crown dimensions

Treesearch

Scott D. Roberts; Thomas J. Dean; David L. Evans; John W. McCombs; Richard L. Harrington; Partick A. Glass

2005-01-01

Accurate estimates of leaf area index (LAI) could provide useful information to forest managers, but due to difficulties in measurement, leaf area is rarely used in decision-making. A reliable approach to remotely estimating LA1 would greatly facilitate its use in forest management. This study investigated the potential for using small-footprint iDAR, a laser-based...

Missouri's forest resources, 2005

Treesearch

W. Keith Moser; Mark H. Hansen; Gary J. Brand; Thomas B. Treiman

2007-01-01

The U.S. Forest Service, Northern Research Station's Forest Inventory and Analysis program is continuing its annual inventory of Missouri's forest resources. This report presents estimates of area, volume, and biomass using data for 2005, and growth, removals, and mortality using data for the most recent remeasurement period. Estimates from this inventory...

A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

Treesearch

Donald Gagliasso; Susan Hummel; Hailemariam Temesgen

2014-01-01

Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

Forest resources of Prince William Sound and Afognak Island, Alaska: their character and ownership, 1978.

Treesearch

Wlllem W.S. van Hees

1989-01-01

The 1978 inventory of the forest resources of Prince William Sound and Afognak Island was designed to produce estimates of timberland area, volumes of timber, and growth and mortality of timber. Estimates of timber resource quantities were also categorized by owner. Nearly 56 percent of the available timberland area is under Forest Service management, and almost 40...

Four Decades of Forest Persistence, Clearance and Logging on Borneo

PubMed Central

Gaveau, David L. A.; Sloan, Sean; Molidena, Elis; Yaen, Husna; Sheil, Doug; Abram, Nicola K.; Ancrenaz, Marc; Nasi, Robert; Quinones, Marcela; Wielaard, Niels; Meijaard, Erik

2014-01-01

The native forests of Borneo have been impacted by selective logging, fire, and conversion to plantations at unprecedented scales since industrial-scale extractive industries began in the early 1970s. There is no island-wide documentation of forest clearance or logging since the 1970s. This creates an information gap for conservation planning, especially with regard to selectively logged forests that maintain high conservation potential. Analysing LANDSAT images, we estimate that 75.7% (558,060 km2) of Borneo's area (737,188 km2) was forested around 1973. Based upon a forest cover map for 2010 derived using ALOS-PALSAR and visually reviewing LANDSAT images, we estimate that the 1973 forest area had declined by 168,493 km2 (30.2%) in 2010. The highest losses were recorded in Sabah and Kalimantan with 39.5% and 30.7% of their total forest area in 1973 becoming non-forest in 2010, and the lowest in Brunei and Sarawak (8.4%, and 23.1%). We estimate that the combined area planted in industrial oil palm and timber plantations in 2010 was 75,480 km2, representing 10% of Borneo. We mapped 271,819 km of primary logging roads that were created between 1973 and 2010. The greatest density of logging roads was found in Sarawak, at 0.89 km km−2, and the lowest density in Brunei, at 0.18 km km−2. Analyzing MODIS-based tree cover maps, we estimate that logging operated within 700 m of primary logging roads. Using this distance, we estimate that 266,257 km2 of 1973 forest cover has been logged. With 389,566 km2 (52.8%) of the island remaining forested, of which 209,649 km2 remains intact. There is still hope for biodiversity conservation in Borneo. Protecting logged forests from fire and conversion to plantations is an urgent priority for reducing rates of deforestation in Borneo. PMID:25029192

Four decades of forest persistence, clearance and logging on Borneo.

PubMed

Gaveau, David L A; Sloan, Sean; Molidena, Elis; Yaen, Husna; Sheil, Doug; Abram, Nicola K; Ancrenaz, Marc; Nasi, Robert; Quinones, Marcela; Wielaard, Niels; Meijaard, Erik

2014-01-01

The native forests of Borneo have been impacted by selective logging, fire, and conversion to plantations at unprecedented scales since industrial-scale extractive industries began in the early 1970s. There is no island-wide documentation of forest clearance or logging since the 1970s. This creates an information gap for conservation planning, especially with regard to selectively logged forests that maintain high conservation potential. Analysing LANDSAT images, we estimate that 75.7% (558,060 km2) of Borneo's area (737,188 km2) was forested around 1973. Based upon a forest cover map for 2010 derived using ALOS-PALSAR and visually reviewing LANDSAT images, we estimate that the 1973 forest area had declined by 168,493 km2 (30.2%) in 2010. The highest losses were recorded in Sabah and Kalimantan with 39.5% and 30.7% of their total forest area in 1973 becoming non-forest in 2010, and the lowest in Brunei and Sarawak (8.4%, and 23.1%). We estimate that the combined area planted in industrial oil palm and timber plantations in 2010 was 75,480 km2, representing 10% of Borneo. We mapped 271,819 km of primary logging roads that were created between 1973 and 2010. The greatest density of logging roads was found in Sarawak, at 0.89 km km-2, and the lowest density in Brunei, at 0.18 km km-2. Analyzing MODIS-based tree cover maps, we estimate that logging operated within 700 m of primary logging roads. Using this distance, we estimate that 266,257 km2 of 1973 forest cover has been logged. With 389,566 km2 (52.8%) of the island remaining forested, of which 209,649 km2 remains intact. There is still hope for biodiversity conservation in Borneo. Protecting logged forests from fire and conversion to plantations is an urgent priority for reducing rates of deforestation in Borneo.

Estimating Unbiased Land Cover Change Areas In The Colombian Amazon Using Landsat Time Series And Statistical Inference Methods

NASA Astrophysics Data System (ADS)

Arevalo, P. A.; Olofsson, P.; Woodcock, C. E.

2017-12-01

Unbiased estimation of the areas of conversion between land categories ("activity data") and their uncertainty is crucial for providing more robust calculations of carbon emissions to the atmosphere, as well as their removals. This is particularly important for the REDD+ mechanism of UNFCCC where an economic compensation is tied to the magnitude and direction of such fluxes. Dense time series of Landsat data and statistical protocols are becoming an integral part of forest monitoring efforts, but there are relatively few studies in the tropics focused on using these methods to advance operational MRV systems (Monitoring, Reporting and Verification). We present the results of a prototype methodology for continuous monitoring and unbiased estimation of activity data that is compliant with the IPCC Approach 3 for representation of land. We used a break detection algorithm (Continuous Change Detection and Classification, CCDC) to fit pixel-level temporal segments to time series of Landsat data in the Colombian Amazon. The segments were classified using a Random Forest classifier to obtain annual maps of land categories between 2001 and 2016. Using these maps, a biannual stratified sampling approach was implemented and unbiased stratified estimators constructed to calculate area estimates with confidence intervals for each of the stable and change classes. Our results provide evidence of a decrease in primary forest as a result of conversion to pastures, as well as increase in secondary forest as pastures are abandoned and the forest allowed to regenerate. Estimating areas of other land transitions proved challenging because of their very small mapped areas compared to stable classes like forest, which corresponds to almost 90% of the study area. Implications on remote sensing data processing, sample allocation and uncertainty reduction are also discussed.

Effects of lidar pulse density and sample size on a model-assisted approach to estimate forest inventory variables

Treesearch

Jacob Strunk; Hailemariam Temesgen; Hans-Erik Andersen; James P. Flewelling; Lisa Madsen

2012-01-01

Using lidar in an area-based model-assisted approach to forest inventory has the potential to increase estimation precision for some forest inventory variables. This study documents the bias and precision of a model-assisted (regression estimation) approach to forest inventory with lidar-derived auxiliary variables relative to lidar pulse density and the number of...

Assessing the Effects of Forest Fragmentation Using Satellite Imagery and Forest Inventory Data

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2005-01-01

For a study area in the North Central region of the USA, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and forest attributes observed on...

Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data

NASA Astrophysics Data System (ADS)

Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

2018-03-01

In this paper, Bayesian inversion of a physically-based forest reflectance model is investigated to estimate of boreal forest canopy leaf area index (LAI) from EO-1 Hyperion hyperspectral data. The data consist of multiple forest stands with different species compositions and structures, imaged in three phases of the growing season. The Bayesian estimates of canopy LAI are compared to reference estimates based on a spectral vegetation index. The forest reflectance model contains also other unknown variables in addition to LAI, for example leaf single scattering albedo and understory reflectance. In the Bayesian approach, these variables are estimated simultaneously with LAI. The feasibility and seasonal variation of these estimates is also examined. Credible intervals for the estimates are also calculated and evaluated. The results show that the Bayesian inversion approach is significantly better than using a comparable spectral vegetation index regression.

Estimating forestland area change from inventory data

Treesearch

Paul Van Deusen; Francis Roesch; Thomas Wigley

2013-01-01

Simple methods for estimating the proportion of land changing from forest to nonforest are developed. Variance estimators are derived to facilitate significance tests. A power analysis indicates that 400 inventory plots are required to reliably detect small changes in net or gross forest loss. This is an important result because forest certification programs may...

Model-assisted estimation of forest resources with generalized additive models

Treesearch

Jean D. Opsomer; F. Jay Breidt; Gretchen G. Moisen; Goran Kauermann

2007-01-01

Multiphase surveys are often conducted in forest inventories, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from...

Annual forest inventory estimates based on the moving average

Treesearch

Francis A. Roesch; James R. Steinman; Michael T. Thompson

2002-01-01

Three interpretations of the simple moving average estimator, as applied to the USDA Forest Service's annual forest inventory design, are presented. A corresponding approach to composite estimation over arbitrarily defined land areas and time intervals is given for each interpretation, under the assumption that the investigator is armed with only the spatial/...

Forest descriptions and photographs of forested areas along the breaks of the Missouri River in eastern Montana, USA

Treesearch

Theresa B. Jain; Molly Juillerat; Jonathan Sandquist; Brad Sauer; Robert Mitchell; Scott McAvoy; Justin Hanley; John David

2007-01-01

This handbook presents information and photographs obtained from forest lands along the breaks of the Missouri River in eastern Montana. Forest characteristics summarized in tables with accompanying photographs can be used to provide quick estimates of species composition and densities within similar landscape features. These estimates may be useful to foresters,...

Small-area estimation of forest attributes within fire boundaries

Treesearch

T. Frescino; G. Moisen; K. Adachi; J. Breidt

2014-01-01

Wildfires are gaining more attention every year as they burn more frequently, more intensely, and across larger landscapes. Generating timely estimates of forest resources within fire perimeters is important for land managers to quickly determine the impact of fi res on U.S. forests. The U.S. Forest Service’s Forest Inventory and Analysis (FIA) program needs tools to...

Old growth in northwestern California national forests.

Treesearch

Debby Beardsley; Ralph. Warbington

1996-01-01

This report estimates old-growth forest area and summarizes stand characteristics of old growth in northwestern California National Forests by forest type. Old-growth definitions for each forest type are used.

Chicago's urban forest ecosystem: results of the Chicago Urban Forest Climate Project

Treesearch

Gregory E. McPherson; David J. Nowak; Rowan A. Rowntree

1994-01-01

Results of the 3-year Chicago Urban Forest Climate Project indicate that there are an estimated 50.8 million trees in the Chicago area of Cook and DuPage Counties; 66 percent of these trees rated in good or excellent condition. During 1991, trees in the Chicago area removed an estimated 6,145 tons of air pollutants, providing air cleansing valued at $9.2 million...

Beaufort scale of wind force as adapted for use on forested areas of the northern Rocky Mountains

Treesearch

George M. Jemison

1934-01-01

The Beaufort scale of wind force, internationally employed by weather agencies, was not designed for use on mountainous and forested areas like those of the Rocky Mountains of northern Idaho and western Montana. The United States Forest Service has used it to estimate wind velocities in this region, but has found that in too many cases the resulting estimates were...

Probability- and model-based approaches to inference for proportion forest using satellite imagery as ancillary data

Treesearch

Ronald E. McRoberts

2010-01-01

Estimates of forest area are among the most common and useful information provided by national forest inventories. The estimates are used for local and national purposes and for reporting to international agreements such as the Montréal Process, the Ministerial Conference on the Protection of Forests in Europe, and the Kyoto Protocol. The estimates are usually based on...

Leaf-on canopy closure in broadleaf deciduous forests predicted during winter

USGS Publications Warehouse

Twedt, Daniel J.; Ayala, Andrea J.; Shickel, Madeline R.

2015-01-01

Forest canopy influences light transmittance, which in turn affects tree regeneration and survival, thereby having an impact on forest composition and habitat conditions for wildlife. Because leaf area is the primary impediment to light penetration, quantitative estimates of canopy closure are normally made during summer. Studies of forest structure and wildlife habitat that occur during winter, when deciduous trees have shed their leaves, may inaccurately estimate canopy closure. We estimated percent canopy closure during both summer (leaf-on) and winter (leaf-off) in broadleaf deciduous forests in Mississippi and Louisiana using gap light analysis of hemispherical photographs that were obtained during repeat visits to the same locations within bottomland and mesic upland hardwood forests and hardwood plantation forests. We used mixed-model linear regression to predict leaf-on canopy closure from measurements of leaf-off canopy closure, basal area, stem density, and tree height. Competing predictive models all included leaf-off canopy closure (relative importance = 0.93), whereas basal area and stem density, more traditional predictors of canopy closure, had relative model importance of ≤ 0.51.

Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular

NASA Astrophysics Data System (ADS)

Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.

2015-12-01

The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had meaningful result with artificial and natural effect. It is expected to predict future forest fire risk with future climate variables as the climate changes.

Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data

NASA Astrophysics Data System (ADS)

Fang, Zhou; Cao, Chunxiang; Ji, Wei; Xu, Min; Chen, Wei

2012-10-01

The need exists to develop a systematic approach to inventory and monitor global forests, both for carbon stock evaluation and for land use change analysis. The use of freely available satellite-based data for carbon stock estimation mitigates both the cost and the spatial limitations of field-based techniques. Spaceborne lidar data have been demonstrated as useful for forest aboveground biomass (AGB) estimation over a wide range of biomass values and forest types. However, the application of these data is limited because of their spatially discrete nature. Spaceborne multispectral sensors have been used extensively to estimate AGB, but these methods have been demonstrated as inappropriate for forest structure characterization in high-biomass mature forests. This study uses an integration of ICESat Geospatial Laser Altimeter System (GLAS) lidar and HJ-1 satellites data to develop methods to estimate AGB in an area of Qilian Mountains, Northwest China. Considering the study area belongs to mountainous terrain, the difficulties of this article are how to extract canopy height from GLAS waveform metrics. Combining with HJ-1 data and ground survey data of the study area, we establish forest biomass estimation model for the GLAS data based on BP neural network model. In order to estimate AGB, the training sample data includes the canopy height extracted from GLAS, LAI, vegetation coverage and several kinds of vegetation indices from HJ-1 data. The results of forest aboveground biomass are very close to the fields measured results, and are consistent with land cover data in the spatial distribution.

Estimating two-way tables based on forest surveys

Treesearch

Charles T. Scott

2000-01-01

Forest survey analysts usually are interested in tables of values rather than single point estimates. A common error is to include only plots on which nonzero values of the attribute were observed when computing the variance of a mean. Similarly, analysts often exclude nonforest plots from the analysis. The development of the correct estimates of forest area, attribute...

New features added to EVALIDator: ratio estimation and county choropleth maps

Treesearch

Patrick D. Miles; Mark H. Hansen

2012-01-01

The EVALIDator Web application, developed in 2007, provides estimates and sampling errors for many user selected forest statistics from the Forest Inventory and Analysis Database (FIADB). Among the statistics estimated are forest area, number of trees, biomass, volume, growth, removals, and mortality. A new release of EVALIDator, developed in 2012, has an option to...

Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation

Treesearch

Ronald E. McRoberts; Greg C. Liknes; Grant M. Domke

2014-01-01

For most national forest inventories, the variables of primary interest to users are forest area and growing stock volume. The precision of estimates of parameters related to these variables can be increased using remotely sensed auxiliary variables, often in combination with stratified estimators. However, acquisition and processing of large amounts of remotely sensed...

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha-1) and a percent accuracy of 51%. TSI based PolInSAR inversion modeling showed the most accurate result for forest height estimation. The correlation between the field measured forest height and the estimated tree height using TSI technique is 62% with an average accuracy of 91.56% and RMSE of 2.28 m. The study suggested that PolInSAR coherence based modeling approach has significant potential for retrieval of forest biophysical parameters.

Uncertainty of large-area estimates of indicators of forest structural gamma diversity: A study based on national forest inventory data

Treesearch

Susanne Winter; Andreas Böck; Ronald E. McRoberts

2012-01-01

Tree diameter and height are commonly measured forest structural variables, and indicators based on them are candidates for assessing forest diversity. We conducted our study on the uncertainty of estimates for mostly large geographic scales for four indicators of forest structural gamma diversity: mean tree diameter, mean tree height, and standard deviations of tree...

Population trends and habitat occurrence of forest birds on southern national forests, 1992-2004

Treesearch

Frank A. La Sorte; Frank R., III Thompson; Margaret K. Trani; Timothy J. Mersmann

2007-01-01

We determined population trends and habitat occurrences for bird species in 14 national forests located in the Southern Region from 1992-2004. We estimated population trends for 144 species within: 14 national forests, 10 physiographic areas, and in the Southern Region as a whole. Habitat occurrences were estimated for 114 species based on 13 forest types and four...

Effects of LiDAR point density and landscape context on estimates of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

2015-03-01

Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.

Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees.

PubMed

Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E

2017-03-01

Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.

Modeling Mediterranean forest structure using airborne laser scanning data

NASA Astrophysics Data System (ADS)

Bottalico, Francesca; Chirici, Gherardo; Giannini, Raffaello; Mele, Salvatore; Mura, Matteo; Puxeddu, Michele; McRoberts, Ronald E.; Valbuena, Ruben; Travaglini, Davide

2017-05-01

The conservation of biological diversity is recognized as a fundamental component of sustainable development, and forests contribute greatly to its preservation. Structural complexity increases the potential biological diversity of a forest by creating multiple niches that can host a wide variety of species. To facilitate greater understanding of the contributions of forest structure to forest biological diversity, we modeled relationships between 14 forest structure variables and airborne laser scanning (ALS) data for two Italian study areas representing two common Mediterranean forests, conifer plantations and coppice oaks subjected to irregular intervals of unplanned and non-standard silvicultural interventions. The objectives were twofold: (i) to compare model prediction accuracies when using two types of ALS metrics, echo-based metrics and canopy height model (CHM)-based metrics, and (ii) to construct inferences in the form of confidence intervals for large area structural complexity parameters. Our results showed that the effects of the two study areas on accuracies were greater than the effects of the two types of ALS metrics. In particular, accuracies were less for the more complex study area in terms of species composition and forest structure. However, accuracies achieved using the echo-based metrics were only slightly greater than when using the CHM-based metrics, thus demonstrating that both options yield reliable and comparable results. Accuracies were greatest for dominant height (Hd) (R2 = 0.91; RMSE% = 8.2%) and mean height weighted by basal area (R2 = 0.83; RMSE% = 10.5%) when using the echo-based metrics, 99th percentile of the echo height distribution and interquantile distance. For the forested area, the generalized regression (GREG) estimate of mean Hd was similar to the simple random sampling (SRS) estimate, 15.5 m for GREG and 16.2 m SRS. Further, the GREG estimator with standard error of 0.10 m was considerable more precise than the SRS estimator with standard error of 0.69 m.

Missouri Forests 2013

Treesearch

Ronald J. Piva; Thomas B. Treiman; Brett J. Butler; Susan J. Crocker; Dale D. Gormanson; Douglas M. Griffith; Cassandra M. Kurtz; Tonya W. Lister; William G. Luppold; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Charles H. (Hobie) Perry; Rachel Riemann; James E. Smith; Brian F. Walters; Christopher W. Woodall

2016-01-01

The third full cycle of annual inventories (2009-2013) of Missouri's forests, completed in 2013, reports that there are an estimated 15.5 million acres of forest land in the State. An estimated 60 percent of the forest land area is in sawtimber size stands, 30 percent are pole timber size, and 10 percent are seedling/sapling size or nontstocked. The net volume of...

Mixed Estimation for a Forest Survey Sample Design

Treesearch

Francis A. Roesch

1999-01-01

Three methods of estimating the current state of forest attributes over small areas for the USDA Forest Service Southern Research Station's annual forest sampling design are compared. The three methods were (I) simple moving average, (II) single imputation of plot data that had been updated by externally developed models, and (III) local application of a global...

The forest-land owners of New Hampshire and Vermont

Treesearch

Neal P. Kingsley; Thomas W. Birch

1977-01-01

The recently completed forest surveys of New Hampshire and Vermont provided estimates of forest area and timber volume by broad owner categories (Kingsley 1976 and 1977). However, these reports did not provide estimates of the volume of timber or the acreage of commercial forest land that is currently available for harvesting. Nor did they provide descriptions of...

Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013

PubMed Central

Tyukavina, Alexandra; Hansen, Matthew C.; Potapov, Peter V.; Stehman, Stephen V.; Smith-Rodriguez, Kevin; Okpa, Chima; Aguilar, Ricardo

2017-01-01

Deforestation rates in primary humid tropical forests of the Brazilian Legal Amazon (BLA) have declined significantly since the early 2000s. Brazil’s national forest monitoring system provides extensive information for the BLA but lacks independent validation and systematic coverage outside of primary forests. We use a sample-based approach to consistently quantify 2000–2013 tree cover loss in all forest types of the region and characterize the types of forest disturbance. Our results provide unbiased forest loss area estimates, which confirm the reduction of primary forest clearing (deforestation) documented by official maps. By the end of the study period, nonprimary forest clearing, together with primary forest degradation within the BLA, became comparable in area to deforestation, accounting for an estimated 53% of gross tree cover loss area and 26 to 35% of gross aboveground carbon loss. The main type of tree cover loss in all forest types was agroindustrial clearing for pasture (63% of total loss area), followed by small-scale forest clearing (12%) and agroindustrial clearing for cropland (9%), with natural woodlands being directly converted into croplands more often than primary forests. Fire accounted for 9% of the 2000–2013 primary forest disturbance area, with peak disturbances corresponding to droughts in 2005, 2007, and 2010. The rate of selective logging exploitation remained constant throughout the study period, contributing to forest fire vulnerability and degradation pressures. As the forest land use transition advances within the BLA, comprehensive tracking of forest transitions beyond primary forest loss is required to achieve accurate carbon accounting and other monitoring objectives. PMID:28439536

Estimating Forest Recreation Demand Using Count Data Models

Treesearch

Jeffrey E. Englin; Thomas P. Holmes; Erin O. Sills

2003-01-01

Forests, along with related natural areas such as mountains, lakes, and rivers, provide opportunities for a wide variety of recreational activities. Although the recreational services supplied by forested areas produce value for the consumers of those services, the measurement of recreational value is complicated by the fact that access to most natural areas is non-...

Landsat for practical forest type mapping - A test case

NASA Technical Reports Server (NTRS)

Bryant, E.; Dodge, A. G., Jr.; Warren, S. D.

1980-01-01

Computer classified Landsat maps are compared with a recent conventional inventory of forest lands in northern Maine. Over the 196,000 hectare area mapped, estimates of the areas of softwood, mixed wood and hardwood forest obtained by a supervised classification of the Landsat data and a standard inventory based on aerial photointerpretation, probability proportional to prediction, field sampling and a standard forest measurement program are found to agree to within 5%. The cost of the Landsat maps is estimated to be $0.065/hectare. It is concluded that satellite techniques are worth developing for forest inventories, although they are not yet refined enough to be incorporated into current practical inventories.

SAFIS Area Estimation Techniques

Treesearch

Gregory A. Reams

2000-01-01

The Southern Annual Forest inventory System (SAFIS) is in various stages of implementation in 8 of the 13 southern states served by the Southern Research Station of the USDA Forest Service. Compared to periodic inventories, SAFIS requires more rapid generation of land use and land cover maps. The current photo system for phase one area estimation has changed little...

Wood fuel potential from harvested areas in the eastern United States.

Treesearch

Eugene M. Carpenter

1980-01-01

Estimates amount of wood fiber that could be available for fuel from forest residues on harvested areas in the eastern United States. Includes a key to resource data published by the USDA Forest Service and factors for estimating amounts of cull, bark, tops, and limbs from inventory and product output tabulations.

SAFIS area estimation techniques

Treesearch

Gregory A. Reams

2000-01-01

The Southern Annual Forest Inventory System (SAFIS) is in various stages of implementation in 8 of the 13 southern states served by the Southern Research Station of the USDA Forest Service. Compared to periodic inventories, SAFIS requires more rapid generation of land use and land cover maps. The current photo system for phase one area estimation has changed little...

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve, India using remote sensing and GIS.

PubMed

Saranya, K R L; Reddy, C Sudhakar; Rao, P V V Prasada; Jha, C S

2014-05-01

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.

Regional forest cover estimation via remote sensing: the calibration center concept

Treesearch

Louis R. Iverson; Elizabeth A. Cook; Robin L. Graham; Robin L. Graham

1994-01-01

A method for combining Landsat Thematic Mapper (TM), Advanced Very High Resolution Radiometer (AVHRR) imagery, and other biogeographic data to estimate forest cover over large regions is applied and evaluated at two locations. In this method, TM data are used to classify a small area (calibration center) into forest/nonforest; the resulting forest cover map is then...

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Kimes, Daniel S.; Kharuk, Vyetcheslav I.

2007-01-01

Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.

Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests

NASA Astrophysics Data System (ADS)

Benyon, Richard G.; Lane, Patrick N. J.; Jaskierniak, Dominik; Kuczera, George; Haydon, Shane R.

2015-07-01

Mean sapwood thickness, measured in fifteen 73 year old Eucalyptus regnans and E. delegatensis stands, correlated strongly with forest overstorey stocking density (R2 0.72). This curvilinear relationship was used with routine forest stocking density and basal area measurements to estimate sapwood area of the forest overstorey at various times in 15 research catchments in undisturbed and disturbed forests located in the Great Dividing Range, Victoria, Australia. Up to 45 years of annual precipitation and streamflow data available from the 15 catchments were used to examine relationships between mean annual loss (evapotranspiration estimated as mean annual precipitation minus mean annual streamflow), and sapwood area. Catchment mean sapwood area correlated strongly (R2 0.88) with catchment mean annual loss. Variation in sapwood area accounted for 68% more variation in mean annual streamflow than precipitation alone (R2 0.90 compared with R2 0.22). Changes in sapwood area accounted for 96% of the changes in mean annual loss observed after forest thinning or clear-cutting and regeneration. We conclude that forest inventory data can be used reliably to predict spatial and temporal variation in catchment annual losses and streamflow in response to natural and imposed disturbances in even-aged forests. Consequently, recent advances in mapping of sapwood area using airborne light detection and ranging will enable high resolution spatial and temporal mapping of mean annual loss and mean annual streamflow over large areas of forested catchment. This will be particularly beneficial in management of water resources from forested catchments subject to disturbance but lacking reliable long-term (years to decades) streamflow records.

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating forest characteristics using NAIP imagery and ArcObjects

Treesearch

John S Hogland; Nathaniel M. Anderson; Woodam Chung; Lucas Wells

2014-01-01

Detailed, accurate, efficient, and inexpensive methods of estimating basal area, trees, and aboveground biomass per acre across broad extents are needed to effectively manage forests. In this study we present such a methodology using readily available National Agriculture Imagery Program imagery, Forest Inventory Analysis samples, a two stage classification and...

The First Estimates of Marbled Cat Pardofelis marmorata Population Density from Bornean Primary and Selectively Logged Forest.

PubMed

Hearn, Andrew J; Ross, Joanna; Bernard, Henry; Bakar, Soffian Abu; Hunter, Luke T B; Macdonald, David W

2016-01-01

The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches.

The First Estimates of Marbled Cat Pardofelis marmorata Population Density from Bornean Primary and Selectively Logged Forest

PubMed Central

Hearn, Andrew J.; Ross, Joanna; Bernard, Henry; Bakar, Soffian Abu; Hunter, Luke T. B.; Macdonald, David W.

2016-01-01

The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches. PMID:27007219

A forester's look at the application of image manipulation techniques to multitemporal Landsat data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.; Leung, K. C.

1979-01-01

Registered, multitemporal Landsat data of a study area in central Pennsylvania were analyzed to detect and assess changes in the forest canopy resulting from insect defoliation. Images taken July 19, 1976, and June 27, 1977, were chosen specifically to represent forest canopy conditions before and after defoliation, respectively. Several image manipulation and data transformation techniques, developed primarily for estimating agricultural and rangeland standing green biomass, were applied to these data. The applicability of each technique for estimating the severity of forest canopy defoliation was then evaluated. All techniques tested had highly correlated results. In all cases, heavy defoliation was discriminated from healthy forest. Areas of moderate defoliation were confused with healthy forest on northwest (NW) aspects, but were distinct from healthy forest conditions on southeast (SE)-facing slopes.

The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

NASA Technical Reports Server (NTRS)

Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

2001-01-01

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

Comparison of direct and indirect methods for assessing leaf area index across a tropical rain forest landscape

Treesearch

Paulo C. Olivas; Steven F. Oberbauer; David B. Clark; Deborah A. Clark; Michael G. Ryan; Joseph J. O' Brien; Harlyn Ordonez

2013-01-01

Many functional properties of forests depend on the leaf area; however, measuring leaf area is not trivial in tall evergreen vegetation. As a result, leaf area is generally estimated indirectly by light absorption methods. These indirect methods are widely used, but have never been calibrated against direct measurements in tropical rain forests, either at point or...

Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis program, Landsat, and LANDFIRE

USGS Publications Warehouse

Chen, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.

2011-01-01

The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High Plateaus. We also estimated that 8054 Mg AFBC were released from 2.24 km2 burned forest area in the Longston fire. These results demonstrate that an AFBC spatial map and estimated biomass carbon consumption can readily be generated using existing database. The methodology provides a consistent, practical, and inexpensive way for estimating AFBC at 30-m resolution over large areas throughout the United States.

A general method for assessing the effects of uncertainty in individual-tree volume model predictions on large-area volume estimates with a subtropical forest illustration

Treesearch

Ronald E. McRoberts; Paolo Moser; Laio Zimermann Oliveira; Alexander C. Vibrans

2015-01-01

Forest inventory estimates of tree volume for large areas are typically calculated by adding the model predictions of volumes for individual trees at the plot level, calculating the mean over plots, and expressing the result on a per unit area basis. The uncertainty in the model predictions is generally ignored, with the result that the precision of the large-area...

Increasing the efficiency of airphoto forest surveys by better definition of classes

Treesearch

C. Allen Bickford

1953-01-01

Aerial photographs are now commonly used in forest-inventory work. In the forest-survey work of the Northeastern Forest Experiment Station we are interested most in using them to estimate total volume of a forested area.

Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

NASA Astrophysics Data System (ADS)

V V L, P. A.

2015-12-01

In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

Estimating national forest carbon stocks and dynamics: combining models and remotely sensed information

NASA Astrophysics Data System (ADS)

Smallman, Thomas Luke; Exbrayat, Jean-François; Bloom, Anthony; Williams, Mathew

2017-04-01

Forests are a critical component of the global carbon cycle, storing significant amounts of carbon, split between living biomass and dead organic matter. The carbon budget of forests is the most uncertain component of the global carbon cycle - it is currently impossible to quantify accurately the carbon source/sink strength of forest biomes due to their heterogeneity and complex dynamics. It has been a major challenge to generate robust carbon budgets across landscapes due to data scarcity. Models have been used for estimating carbon budgets, but outputs have lacked an assessment of uncertainty, making a robust assessment of their reliability and accuracy challenging. Here a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC) data assimilation framework has been used to combine remotely sensed leaf area index (MODIS), biomass (where available) and deforestation estimates, in addition to forest planting information from the UK's national forest inventory, an estimate of soil carbon from the Harmonized World Database (HWSD) and plant trait information with a process model (DALEC) to produce a constrained analysis with a robust estimate of uncertainty of the UK forestry carbon budget between 2000 and 2010. Our analysis estimates the mean annual UK forest carbon sink at -3.9 MgC ha-1 yr-1 with a 95 % confidence interval between -4.0 and -3.1 MgC ha-1yr-1. The UK national forest inventory (NFI) estimates the mean UK forest carbon sink to be between -1.4 and -5.5 MgC ha-1 yr-1. The analysis estimate for total forest biomass stock in 2010 is estimated at 229 (177/232) TgC, while the NFI an estimated total forest biomass carbon stock of 216 TgC. Leaf carbon area (LCA) is a key plant trait which we are able to estimate using our analysis. Comparison of median estimates for (LCA) retrieved from the analysis and a UK land cover map show higher and lower values for LCA are estimated areas dominated by needle leaf and broad leaf forests forest respectively, consistent with ecological expectations. Moreover, LCA is positively and negatively correlated with leaf-life span and allocation of photosynthate to foliage respectively, supported by field observations. This emergence of key plant traits and correlations between traits increases our confidence in the robustness of this analysis. Furthermore, this framework also allows us to search for additional emergent properties from the analysis such as spatial variation of retrieved drought tolerance. Finally our analysis is able to identify components of the carbon cycle with the largest uncertainty e.g. allocation of photosynthate to wood and wood residence times, providing targets for future observations (e.g. ESA's BIOMASS mission). Our Bayesian analysis system is ideally suited for assimilation of multiple biomass estimates and their associated uncertainties to reduce both the overall analysis uncertainty and bias in estimates biomass stocks.

Towards a sampling strategy for the assessment of forest condition at European level: combining country estimates.

PubMed

Travaglini, Davide; Fattorini, Lorenzo; Barbati, Anna; Bottalico, Francesca; Corona, Piermaria; Ferretti, Marco; Chirici, Gherardo

2013-04-01

A correct characterization of the status and trend of forest condition is essential to support reporting processes at national and international level. An international forest condition monitoring has been implemented in Europe since 1987 under the auspices of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The monitoring is based on harmonized methodologies, with individual countries being responsible for its implementation. Due to inconsistencies and problems in sampling design, however, the ICP Forests network is not able to produce reliable quantitative estimates of forest condition at European and sometimes at country level. This paper proposes (1) a set of requirements for status and change assessment and (2) a harmonized sampling strategy able to provide unbiased and consistent estimators of forest condition parameters and of their changes at both country and European level. Under the assumption that a common definition of forest holds among European countries, monitoring objectives, parameters of concern and accuracy indexes are stated. On the basis of fixed-area plot sampling performed independently in each country, an unbiased and consistent estimator of forest defoliation indexes is obtained at both country and European level, together with conservative estimators of their sampling variance and power in the detection of changes. The strategy adopts a probabilistic sampling scheme based on fixed-area plots selected by means of systematic or stratified schemes. Operative guidelines for its application are provided.

Investigation into calculating tree biomass and carbon in the FIADB using a biomass expansion factor approach

Treesearch

Linda S. Heath; Mark Hansen; James E. Smith; Patrick D. Miles

2009-01-01

The official U.S. forest carbon inventories (U.S. EPA 2008) have relied on tree biomass estimates that utilize diameter based prediction equations from Jenkins and others (2003), coupled with U.S. Forest Service, Forest Inventory and Analysis (FIA) sample tree measurements and forest area estimates. However, these biomass prediction equations are not the equations used...

Timber resource statistics for the upper Tanana block, Tanana inventory unit, Alaska, 1974.

Treesearch

Karl M. Hegg

1983-01-01

This report for the 3.6-million-acre Upper Tanana block is the third of four on the 14-million-acre Tanana Valley forest inventory unit. Descriptions of area, climate, forest, general resource use, and inventory methodology are presented. Area and volume tables are provided for commercial and operable noncommercial forest lands. Estimates for commercial forest land...

A Proposal for Phase 4 of the Forest Inventory and Analysis Program

Treesearch

Ronald E. McRoberts

2005-01-01

Maps of forest cover were constructed using observations from forest inventory plots, Landsat Thematic Mapper satellite imagery, and a logistic regression model. Estimates of mean proportion forest area and the variance of the mean were calculated for circular study areas with radii ranging from 1 km to 15 km. The spatial correlation among pixel predictions was...

The Finnish multisource national forest inventory: small-area estimation and map production

Treesearch

Erkki Tomppo

2009-01-01

A driving force motivating development of the multisource national forest inventory (MS-NFI) in connection with the Finnish national forest inventory (NFI) was the desire to obtain forest resource information for smaller areas than is possible using field data only without significantly increasing the cost of the inventory. A basic requirement for the method was that...

Mapping Forest Inventory and Analysis forest land use: timberland, reserved forest land, and other forest land

Treesearch

Mark D. Nelson; John Vissage

2007-01-01

The Forest Inventory and Analysis (FIA) program produces area estimates of forest land use within three subcategories: timberland, reserved forest land, and other forest land. Mapping these subcategories of forest land requires the ability to spatially distinguish productive from unproductive land, and reserved from nonreserved land. FIA field data were spatially...

Timber resource statistics for the Chatham area of the Tongass National Forest, Alaska, 1982.

Treesearch

George Rogers; Willern W.S. van Hees

1991-01-01

Statistics on forest area, total gross and net volumes, and annual net growth and mortality are presented from the 1980-82 timber inventory of the Chatham Area, Tongass National Forest, Alaska. Available timberland area is estimated at 1.4 million acres, net growing stock volume at 7.2 billion cubic feet, and annual net growth and mortality at 35.9 and 54.8 million...

Timber resource statistics for the Stikine area of the Tongass National Forest, Alaska, 1984.

Treesearch

George Rogers; Wlllem W.S. van Hees

1991-01-01

Statistics on forest area, total gross and net timber volumes, and annual net growth and mortality are presented from the 1983-84 timber inventory of the Stikine Area, Tongass National Forest, Alaska. Available timberland area is estimated at 1.2 million acres, net growing stock volume at 7.2 billion cubic feet, and annual net growth and mortality at 18.8 and 57.0...

Timber resource statistics for the Ketchikan area of the Tongass National Forest, Alaska, 1985.

Treesearch

George Rogers; Willem W.S. van Hees

1991-01-01

Statistics on forest area, total gross and net volumes, and annual net growth and mortality are presented from the 1984-85 timber inventory of the Ketchikan Area, Tongass National Forest, Alaska. Available timberland area is estimated at 1.5 million acres, net growing stock volume at 8.2 billion cubic feet, and annual net growth and mortality at 24.8 and 65.6 million...

Annual measurements of gain and loss in aboveground carbon density

NASA Astrophysics Data System (ADS)

Baccini, A.; Walker, W. S.; Carvalho, L.; Farina, M.; Sulla-menashe, D. J.; Houghton, R. A.

2017-12-01

Tropical forests hold large stores of carbon, but their net carbon balance is uncertain. Land use and land-cover change (LULCC) are believed to release between 0.81 and 1.14 PgC yr-1, while intact native forests are thought to be a net carbon sink of approximately the same magnitude. Reducing the uncertainty of these estimates is not only fundamental to the advancement of carbon cycle science but is also of increasing relevance to national and international policies designed to reduce emissions from deforestation and forest degradation (e.g., REDD+). Contemporary approaches to estimating the net carbon balance of tropical forests rely on changes in forest area between two periods, typically derived from satellite data, together with information on average biomass density. These approaches tend to capture losses in biomass due to deforestation (i.e., wholesale stand removals) but are limited in their sensitivity to forest degradation (e.g., selective logging or single-tree removals), which can account for additional biomass losses on the order of 47-75% of deforestation. Furthermore, while satellite-based estimates of forest area loss have been used successfully to estimate associated carbon losses, few such analyses have endeavored to determine the rate of carbon sequestration in growing forests. Here we use 12 years (2003-2014) of pantropical satellite data to quantify net annual changes in the aboveground carbon density of woody vegetation (MgC ha-1yr-1), providing direct, measurement-based evidence that the world's tropical forests are a net carbon source of 425.2 ± 92.0 Tg C yr-1. This net release of carbon consists of losses of 861.7 ± 80.2 Tg C yr-1 and gains of -436.5 ± 31.0 Tg C yr-1 . Gains result from forest growth; losses result from reductions in forest area due to deforestation and from reductions in biomass density within standing forests (degradation), with the latter accounting for 68.9% of overall losses. Our findings advance previous research by providing novel, annual measurements of carbon losses and gains, from forest loss, degradation, and growth, with reduced uncertainty that stems from an unconventional shift in emphasis away from classifications of land area change toward direct estimation of carbon density dynamics.

Depauperate Avifauna in Plantations Compared to Forests and Exurban Areas

PubMed Central

Haskell, David G.; Evans, Jonathan P.; Pelkey, Neil W.

2006-01-01

Native forests are shrinking worldwide, causing a loss of biological diversity. Our ability to prioritize forest conservation actions is hampered by a lack of information about the relative impacts of different types of forest loss on biodiversity. In particular, we lack rigorous comparisons of the effects of clearing forests for tree plantations and for human settlements, two leading causes of deforestation worldwide. We compared avian diversity in forests, plantations and exurban areas on the Cumberland Plateau, USA, an area of global importance for biodiversity. By combining field surveys with digital habitat databases, and then analyzing diversity at multiple scales, we found that plantations had lower diversity and fewer conservation priority species than did other habitats. Exurban areas had higher diversity than did native forests, but native forests outscored exurban areas for some measures of conservation priority. Overall therefore, pine plantations had impoverished avian communities relative to both native forests and to exurban areas. Thus, reports on the status of forests give misleading signals about biological diversity when they include plantations in their estimates of forest cover but exclude forested areas in which humans live. Likewise, forest conservation programs should downgrade incentives for plantations and should include settled areas within their purview. PMID:17183694

Louisiana’s forests, 2005

Treesearch

Sonja N. Oswalt; James W. Bentley

2013-01-01

This bulletin describes forest resources of the State of Louisiana at the time of the 2005 forest inventory. It is based on sampling conducted by the U.S. Department of Agriculture Forest Service, Southern Research Station, Forest Inventory and Analysis. This bulletin addresses forest area estimates; timber growth, removals, and mortality; invasive species; and timber...

Midsouth forest area trends

Treesearch

Richard A. Birdsey; William H. McWilliams

1986-01-01

The forest inventory and analysis unit of the southern forest experiment stations (Forest Survey) conducts periodic inventories at approximately 10-year intervals of the forest resources of the Midsouth States (fig. 1). This report contains a summary of forest acreage estimates made between 1950 and 1985. The statistics are based on published forest survey reports and...

Nebraska's forests, 2005

Treesearch

Dacia M. Meneguzzo; Brett J. Butler; Susan J. Crocker; David E. Haugen; W. Keith Moser; Charles H. Perry; Barry T. Wilson; Christopher W. Woodall

2008-01-01

Results of the first annual inventory of Nebraska's forests (2001-05) show an estimated 1.24 million acres of forest land; 1.17 million acres meet the definition of timberland. Softwood forest types account for one-third of all forest land area, with ponderosa pine being the most prevalent type. Hardwood forest types comprise 58 percent of Nebraska's forest...

Multistage variable probability forest volume inventory. [Defiance Unit of the Navajo Nation in Arizona and Colorado

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1979-01-01

The net board foot volume (Scribner log rule) of the standing Ponderosa pine timber on the Defiance Unit of the Navajo Nation's forested land was estimated using a multistage forest volume inventory scheme with variable sample selection probabilities. The inventory designed to accomplish this task required that both LANDSAT MSS digital data and aircraft acquired data be used to locate one acre ground splits, which were subsequently visited by ground teams conducting detailed tree measurements using an optical dendrometer. The dendrometer measurements were then punched on computer input cards and were entered in a computer program developed by the U.S. Forest Service. The resulting individual tree volume estimates were then expanded through the use of a statistically defined equation to produce the volume estimate for the entire area which includes 192,026 acres and is approximately a 44% the total forested area of the Navajo Nation.

Inventory of forest resources (including water) by multi-level sampling. [nine northern Virginia coastal plain counties

NASA Technical Reports Server (NTRS)

Aldrich, R. C.; Dana, R. W.; Roberts, E. H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A stratified random sample using LANDSAT band 5 and 7 panchromatic prints resulted in estimates of water in counties with sampling errors less than + or - 9% (67% probability level). A forest inventory using a four band LANDSAT color composite resulted in estimates of forest area by counties that were within + or - 6.7% and + or - 3.7% respectively (67% probability level). Estimates of forest area for counties by computer assisted techniques were within + or - 21% of operational forest survey figures and for all counties the difference was only one percent. Correlations of airborne terrain reflectance measurements with LANDSAT radiance verified a linear atmospheric model with an additive (path radiance) term and multiplicative (transmittance) term. Coefficients of determination for 28 of the 32 modeling attempts, not adverseley affected by rain shower occurring between the times of LANDSAT passage and aircraft overflights, exceeded 0.83.

Reconciling forest conservation and logging in Indonesian Borneo.

PubMed

Gaveau, David L A; Kshatriya, Mrigesh; Sheil, Douglas; Sloan, Sean; Molidena, Elis; Wijaya, Arief; Wich, Serge; Ancrenaz, Marc; Hansen, Matthew; Broich, Mark; Guariguata, Manuel R; Pacheco, Pablo; Potapov, Peter; Turubanova, Svetlana; Meijaard, Erik

2013-01-01

Combining protected areas with natural forest timber concessions may sustain larger forest landscapes than is possible via protected areas alone. However, the role of timber concessions in maintaining natural forest remains poorly characterized. An estimated 57% (303,525 km²) of Kalimantan's land area (532,100 km²) was covered by natural forest in 2000. About 14,212 km² (4.7%) had been cleared by 2010. Forests in oil palm concessions had been reduced by 5,600 km² (14.1%), while the figures for timber concessions are 1,336 km² (1.5%), and for protected forests are 1,122 km² (1.2%). These deforestation rates explain little about the relative performance of the different land use categories under equivalent conversion risks due to the confounding effects of location. An estimated 25% of lands allocated for timber harvesting in 2000 had their status changed to industrial plantation concessions in 2010. Based on a sample of 3,391 forest plots (1×1 km; 100 ha), and matching statistical analyses, 2000-2010 deforestation was on average 17.6 ha lower (95% C.I.: -22.3 ha- -12.9 ha) in timber concession plots than in oil palm concession plots. When location effects were accounted for, deforestation rates in timber concessions and protected areas were not significantly different (Mean difference: 0.35 ha; 95% C.I.: -0.002 ha-0.7 ha). Natural forest timber concessions in Kalimantan had similar ability as protected areas to maintain forest cover during 2000-2010, provided the former were not reclassified to industrial plantation concessions. Our study indicates the desirability of the Government of Indonesia designating its natural forest timber concessions as protected areas under the IUCN Protected Area Category VI to protect them from reclassification.

Reconciling Forest Conservation and Logging in Indonesian Borneo

PubMed Central

Gaveau, David L. A.; Kshatriya, Mrigesh; Sheil, Douglas; Sloan, Sean; Molidena, Elis; Wijaya, Arief; Wich, Serge; Ancrenaz, Marc; Hansen, Matthew; Broich, Mark; Guariguata, Manuel R.; Pacheco, Pablo; Potapov, Peter; Turubanova, Svetlana; Meijaard, Erik

2013-01-01

Combining protected areas with natural forest timber concessions may sustain larger forest landscapes than is possible via protected areas alone. However, the role of timber concessions in maintaining natural forest remains poorly characterized. An estimated 57% (303,525 km2) of Kalimantan's land area (532,100 km2) was covered by natural forest in 2000. About 14,212 km2 (4.7%) had been cleared by 2010. Forests in oil palm concessions had been reduced by 5,600 km2 (14.1%), while the figures for timber concessions are 1,336 km2 (1.5%), and for protected forests are 1,122 km2 (1.2%). These deforestation rates explain little about the relative performance of the different land use categories under equivalent conversion risks due to the confounding effects of location. An estimated 25% of lands allocated for timber harvesting in 2000 had their status changed to industrial plantation concessions in 2010. Based on a sample of 3,391 forest plots (1×1 km; 100 ha), and matching statistical analyses, 2000–2010 deforestation was on average 17.6 ha lower (95% C.I.: −22.3 ha–−12.9 ha) in timber concession plots than in oil palm concession plots. When location effects were accounted for, deforestation rates in timber concessions and protected areas were not significantly different (Mean difference: 0.35 ha; 95% C.I.: −0.002 ha–0.7 ha). Natural forest timber concessions in Kalimantan had similar ability as protected areas to maintain forest cover during 2000–2010, provided the former were not reclassified to industrial plantation concessions. Our study indicates the desirability of the Government of Indonesia designating its natural forest timber concessions as protected areas under the IUCN Protected Area Category VI to protect them from reclassification. PMID:23967062

Estimating national forest carbon stocks and dynamics: combining models and remotely sensed information

NASA Astrophysics Data System (ADS)

Smallman, Luke; Williams, Mathew

2016-04-01

Forests are a critical component of the global carbon cycle, storing significant amounts of carbon, split between living biomass and dead organic matter. The carbon budget of forests is the most uncertain component of the global carbon cycle - it is currently impossible to quantify accurately the carbon source/sink strength of forest biomes due to their heterogeneity and complex dynamics. It has been a major challenge to generate robust carbon budgets across landscapes due to data scarcity. Models have been used but outputs have lacked an assessment of uncertainty, making a robust assessment of their reliability and accuracy challenging. Here a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC) data assimilation framework has been used to combine remotely sensed leaf area index (MODIS), biomass (where available) and deforestation estimates, in addition to forest planting and clear-felling information from the UK's national forest inventory, an estimate of soil carbon from the Harmonized World Database (HWSD) and plant trait information with a process model (DALEC) to produce a constrained analysis with a robust estimate of uncertainty of the UK forestry carbon budget between 2000 and 2010. Our analysis estimates the mean annual UK forest carbon sink at -3.9 MgC ha-1yr-1 with a 95 % confidence interval between -4.0 and -3.1 MgC ha-1 yr-1. The UK national forest inventory (NFI) estimates the mean UK forest carbon sink to be between -1.4 and -5.5 MgC ha-1 yr-1. The analysis estimate for total forest biomass stock in 2010 is estimated at 229 (177/232) TgC, while the NFI an estimated total forest biomass carbon stock of 216 TgC. Leaf carbon area (LCA) is a key plant trait which we are able to estimate using our analysis. Comparison of median estimates for LCA retrieved from the analysis and a UK land cover map show higher and lower values for LCA are estimated areas dominated by needle leaf and broad leaf forests forest respectively, consistent with ecological expectations. Moreover, the retrieved LCA is positively correlated with leaf-life span and negatively correlated with allocation of photosynthate to foliage, supported by field observations. This emergence of key plant traits and correlations between traits increases our confidence in the robustness of this analysis. Furthermore, this framework also allows us to search for additional emergent properties from the analysis such as spatial variation of retrieved drought tolerance. Finally our analysis is able to identify components of the carbon cycle with the largest uncertainty providing targets for future observations (e.g. remotely sensed biomass). Our Bayesian analysis system is ideally suited for assimilation of multiple biomass estimates and their associated uncertainties to reduce both uncertainty in the state of the system but also process parameters (e.g. wood residence time).

Estimating total forest biomass in Maine, 1995

Treesearch

Eric H. Wharton; Douglas M. Griffith; Douglas M. Griffith

1998-01-01

Presents methods for synthesizing information from existing biomass literature for estimating biomass over extensive forest areas with specific applications to Maine. Tables of appropriate regression equations and the tree and shrub species to which these equations can be applied are presented as well as biomass estimates at the county and state level.

Forest wildlife habitat statistics for Maine - 1982

Treesearch

Robert T. Brooks; Thomas S. Frieswyk; Arthur Ritter

1986-01-01

A statistical report on the first forest wildlife habitat survey of Maine (1982). Eighty-five tables show estimates of forest area and several attributes of forest land wildlife habitat. Data are presented at two levels: state and geographic sampling unit.

Structural Dynamics of Tropical Moist Forest Gaps

PubMed Central

Hunter, Maria O.; Keller, Michael; Morton, Douglas; Cook, Bruce; Lefsky, Michael; Ducey, Mark; Saleska, Scott; de Oliveira, Raimundo Cosme; Schietti, Juliana

2015-01-01

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest structure (top down) differ from traditional field measurements (bottom up), and necessitate clear-cut definitions unencumbered by the wisdom of a field observer. We offer a new definition of a forest gap that is driven by forest dynamics and consistent with precise ranging measurements from airborne lidar data and tall, multi-layered tropical forest structure. We used 1000 ha of multi-temporal lidar data (2008, 2012) at two sites, the Tapajos National Forest and Ducke Reserve, to study gap dynamics in the Brazilian Amazon. Here, we identified dynamic gaps as contiguous areas of significant growth, that correspond to areas > 10 m2, with height <10 m. Applying the dynamic definition at both sites, we found over twice as much area in gap at Tapajos National Forest (4.8 %) as compared to Ducke Reserve (2.0 %). On average, gaps were smaller at Ducke Reserve and closed slightly more rapidly, with estimated height gains of 1.2 m y-1 versus 1.1 m y-1 at Tapajos. At the Tapajos site, height growth in gap centers was greater than the average height gain in gaps (1.3 m y-1 versus 1.1 m y-1). Rates of height growth between lidar acquisitions reflect the interplay between gap edge mortality, horizontal ingrowth and gap size at the two sites. We estimated that approximately 10 % of gap area closed via horizontal ingrowth at Ducke Reserve as opposed to 6 % at Tapajos National Forest. Height loss (interpreted as repeat damage and/or mortality) and horizontal ingrowth accounted for similar proportions of gap area at Ducke Reserve (13 % and 10 %, respectively). At Tapajos, height loss had a much stronger signal (23 % versus 6 %) within gaps. Both sites demonstrate limited gap contagiousness defined by an increase in the likelihood of mortality in the immediate vicinity (~6 m) of existing gaps. PMID:26168242

Structural Dynamics of Tropical Moist Forest Gaps.

PubMed

Hunter, Maria O; Keller, Michael; Morton, Douglas; Cook, Bruce; Lefsky, Michael; Ducey, Mark; Saleska, Scott; de Oliveira, Raimundo Cosme; Schietti, Juliana

2015-01-01

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest structure (top down) differ from traditional field measurements (bottom up), and necessitate clear-cut definitions unencumbered by the wisdom of a field observer. We offer a new definition of a forest gap that is driven by forest dynamics and consistent with precise ranging measurements from airborne lidar data and tall, multi-layered tropical forest structure. We used 1000 ha of multi-temporal lidar data (2008, 2012) at two sites, the Tapajos National Forest and Ducke Reserve, to study gap dynamics in the Brazilian Amazon. Here, we identified dynamic gaps as contiguous areas of significant growth, that correspond to areas > 10 m2, with height <10 m. Applying the dynamic definition at both sites, we found over twice as much area in gap at Tapajos National Forest (4.8%) as compared to Ducke Reserve (2.0%). On average, gaps were smaller at Ducke Reserve and closed slightly more rapidly, with estimated height gains of 1.2 m y-1 versus 1.1 m y-1 at Tapajos. At the Tapajos site, height growth in gap centers was greater than the average height gain in gaps (1.3 m y-1 versus 1.1 m y-1). Rates of height growth between lidar acquisitions reflect the interplay between gap edge mortality, horizontal ingrowth and gap size at the two sites. We estimated that approximately 10% of gap area closed via horizontal ingrowth at Ducke Reserve as opposed to 6% at Tapajos National Forest. Height loss (interpreted as repeat damage and/or mortality) and horizontal ingrowth accounted for similar proportions of gap area at Ducke Reserve (13% and 10%, respectively). At Tapajos, height loss had a much stronger signal (23% versus 6%) within gaps. Both sites demonstrate limited gap contagiousness defined by an increase in the likelihood of mortality in the immediate vicinity (~6 m) of existing gaps.

Black-backed woodpecker habitat suitability mapping using conifer snag basal area estimated from airborne laser scanning

NASA Astrophysics Data System (ADS)

Casas Planes, Á.; Garcia, M.; Siegel, R.; Koltunov, A.; Ramirez, C.; Ustin, S.

2015-12-01

Occupancy and habitat suitability models for snag-dependent wildlife species are commonly defined as a function of snag basal area. Although critical for predicting or assessing habitat suitability, spatially distributed estimates of snag basal area are not generally available across landscapes at spatial scales relevant for conservation planning. This study evaluates the use of airborne laser scanning (ALS) to 1) identify individual conifer snags and map their basal area across a recently burned forest, and 2) map habitat suitability for a wildlife species known to be dependent on snag basal area, specifically the black-backed woodpecker (Picoides arcticus). This study focuses on the Rim Fire, a megafire that took place in 2013 in the Sierra Nevada Mountains of California, creating large patches of medium- and high-severity burned forest. We use forest inventory plots, single-tree ALS-derived metrics and Gaussian processes classification and regression to identify conifer snags and estimate their stem diameter and basal area. Then, we use the results to map habitat suitability for the black-backed woodpecker using thresholds for conifer basal area from a previously published habitat suitability model. Local maxima detection and watershed segmentation algorithms resulted in 75% detection of trees with stem diameter larger than 30 cm. Snags are identified with an overall accuracy of 91.8 % and conifer snags are identified with an overall accuracy of 84.8 %. Finally, Gaussian process regression reliably estimated stem diameter (R2 = 0.8) using height and crown area. This work provides a fast and efficient methodology to characterize the extent of a burned forest at the tree level and a critical tool for early wildlife assessment in post-fire forest management and biodiversity conservation.

Determination of tropical deforestation rates and related carbon losses from 1990 to 2010

PubMed Central

Achard, Frédéric; Beuchle, René; Mayaux, Philippe; Stibig, Hans-Jürgen; Bodart, Catherine; Brink, Andreas; Carboni, Silvia; Desclée, Baudouin; Donnay, François; Eva, Hugh D; Lupi, Andrea; Raši, Rastislav; Seliger, Roman; Simonetti, Dario

2014-01-01

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990–2000 and 2000–2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr−1 in the 1990s and 7.6 million ha yr−1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr−1 (range: 646–1238) and 880 MtC yr−1 (range: 602–1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000–2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr−1 (range: 61–168) and 97 MtC yr−1 (53–141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates. PMID:24753029

Determination of tropical deforestation rates and related carbon losses from 1990 to 2010.

PubMed

Achard, Frédéric; Beuchle, René; Mayaux, Philippe; Stibig, Hans-Jürgen; Bodart, Catherine; Brink, Andreas; Carboni, Silvia; Desclée, Baudouin; Donnay, François; Eva, Hugh D; Lupi, Andrea; Raši, Rastislav; Seliger, Roman; Simonetti, Dario

2014-08-01

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990-2000 and 2000-2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr(-1) in the 1990s and 7.6 million ha yr(-1) in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr(-1) (range: 646-1238) and 880 MtC yr(-1) (range: 602-1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000-2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr(-1) (range: 61-168) and 97 MtC yr(-1) (53-141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates. © The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Estimating mangrove in Florida: trials monitoring rare ecosystems

Treesearch

Mark J. Brown

2015-01-01

Mangrove species are keystone components in coastal ecosystems and are the interface between forest land and sea. Yet, estimates of their area have varied widely. Forest Inventory and Analysis (FIA) data from ground-based sample plots provide one estimate of the resource. Initial FIA estimates of the mangrove resource in Florida varied dramatically from those compiled...

Screenometer: a device for sampling vegetative screening in forested areas

Treesearch

Victor A. Rudis

1985-01-01

A-device for estimating the degree to which vegetation and other obstructions screen forested areas has been adapted to an extensive sampling design for forest surveys. Procedures are recommended to assure that uniform measurements can be made. Examination of sources of sampling variation (observers, points within sampled locations, series of observations within points...

Area change reporting using the desktop FIADB

Treesearch

Patrick D. Miles; Mark H. Hansen

2012-01-01

The estimation of area change between two FIA inventories is complicated by the "mapping" of subplots. Subplots can be subdivided or mapped into forest and nonforest conditions, and forest conditions can be further mapped based on distinct changes in reserved status, owner group, forest type, stand-size class, regeneration status, and stand density. The...

A preview of Delaware's timber resource

Treesearch

Joseph E. Barnard; Teresa M. Bowers

1973-01-01

The recently completed forest survey of Delaware indicated little change in the total forest area since the 1957 estimate. Softwood volume and the acreage of softwood types decreased considerably. Hardwoods now comprise two-thirds of the volume and three-fourths of the forest area. Total average annual growth exceeded removals, but softwood removals exceeded average...

Implications of allometric model selection for county-level biomass mapping

Treesearch

Laura Duncanson; Wenli Huang; Kristofer Johnson; Anu Swatantran; Ronald E. McRoberts; Ralph Dubayah

2017-01-01

Background: Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend...

Estimating Canopy Structure in an Amazon Forest from Laser Range Finder and IKONOS Satellite Observations

Treesearch

Gregory P. Asner; Michael Palace; Michael Keller; Rodrigo Pereira Jr.; Jose N. M. Silva; Johan C. Zweede

2002-01-01

Canopy structural data can be used for biomass estimation and studies of carbon cycling, disturbance, energy balance, and hydrological processes in tropical forest ecosystems. Scarce information on canopy dimensions reflects the difficulties associated with measuring crown height, width, depth, and area in tall, humid tropical forests. New field and spaceborne...

Illinois' forest resources, 2005

Treesearch

Susan J. Crocker; Gary J. Brand; Dick C. Little

2007-01-01

Results of the completed 2005 Illinois annual inventory show an estimated 4.5 million acres of forest land that supports 7.6 billion cubic feet (ft3) of total net live-tree volume. Since 1948, timberland area has steadily increased and now represents 96 percent of total forest land. Growing-stock volume on timberland has risen to an estimated 6.8...

A methodological framework to assess the carbon balance of tropical managed forests.

PubMed

Piponiot, Camille; Cabon, Antoine; Descroix, Laurent; Dourdain, Aurélie; Mazzei, Lucas; Ouliac, Benjamin; Rutishauser, Ervan; Sist, Plinio; Hérault, Bruno

2016-12-01

Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions.

GIS-based estimation of the winter storm damage probability in forests: a case study from Baden-Wuerttemberg (Southwest Germany).

PubMed

Schindler, Dirk; Grebhan, Karin; Albrecht, Axel; Schönborn, Jochen; Kohnle, Ulrich

2012-01-01

Data on storm damage attributed to the two high-impact winter storms 'Wiebke' (28 February 1990) and 'Lothar' (26 December 1999) were used for GIS-based estimation and mapping (in a 50 × 50 m resolution grid) of the winter storm damage probability (P(DAM)) for the forests of the German federal state of Baden-Wuerttemberg (Southwest Germany). The P(DAM)-calculation was based on weights of evidence (WofE) methodology. A combination of information on forest type, geology, soil type, soil moisture regime, and topographic exposure, as well as maximum gust wind speed field was used to compute P(DAM) across the entire study area. Given the condition that maximum gust wind speed during the two storm events exceeded 35 m s(-1), the highest P(DAM) values computed were primarily where coniferous forest grows in severely exposed areas on temporarily moist soils on bunter sandstone formations. Such areas are found mainly in the mountainous ranges of the northern Black Forest, the eastern Forest of Odes, in the Virngrund area, and in the southwestern Alpine Foothills.

Using airborne lidar as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska

Treesearch

Hans-Erik Andersen; Jacob Strunk; Hailemariam Temesgen

2011-01-01

Airborne laser scanning, collected in a sampling mode, has the potential to be a valuable tool for estimating the biomass resources available to support bioenergy production in rural communities of interior Alaska. In this study, we present a methodology for estimating forest biomass over a 201,226-ha area (of which 163,913 ha are forested) in the upper Tanana valley...

Geospatial monitoring and prioritization of forest fire incidences in Andhra Pradesh, India.

PubMed

Manaswini, G; Sudhakar Reddy, C

2015-10-01

Forest fire has been identified as one of the key environmental issue for long-term conservation of biodiversity and has impact on global climate. Spatially multiple observations are necessary for monitoring of forest fires in tropics for understanding conservation efficacy and sustaining biodiversity in protected areas. The present work was carried out to estimate the spatial extent of forest burnt areas and fire frequency using Resourcesat Advanced Wide Field Sensor (AWiFS) data (2009, 2010, 2012, 2013 and 2014) in Andhra Pradesh, India. The spatio-temporal analysis shows that an area of 7514.10 km(2) (29.22% of total forest cover) has been affected by forest fires. Six major forest types are distributed in Andhra Pradesh, i.e. semi-evergreen, moist deciduous, dry deciduous, dry evergreen, thorn and mangroves. Of the total forest burnt area, dry deciduous forests account for >75%. District-wise analysis shows that Kurnool, Prakasam and Cuddapah have shown >100 km(2) of burnt area every year. The total forest burnt area estimate covering protected areas ranges between 6.9 and 22.3% during the study period. Spatial burnt area analysis for protected areas in 2014 indicates 37.2% of fire incidences in the Nagarjunasagar Srisailam Tiger Reserve followed by 20.2 % in the Sri Lankamalleswara Wildlife Sanctuary, 20.1% in the Sri Venkateswara Wildlife Sanctuary and 17.4% in the Gundla Brahmeswaram Wildlife Sanctuary. The analysis of cumulative fire occurrences from 2009 to 2014 has helped in delineation of conservation priority hotspots using a spatial grid cell approach. Conservation priority hotspots I and II are distributed in major parts of study area including protected areas of the Nagarjunasagar Srisailam Tiger Reserve and Gundla Brahmeswaram Wildlife Sanctuary. The spatial database generated will be useful in studies related to influence of fires on species adaptability, ecological damage assessment and conservation planning.

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Kimes, Daniel; Sun, Guoqing; Kharuk, Viatcheslav; Hyde, Peter; Nelson, Ross

2007-01-01

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Monitoring of fire incidences in vegetation types and Protected Areas of India: Implications on carbon emissions

NASA Astrophysics Data System (ADS)

Reddy, C. Sudhakar; Padma Alekhya, V. V. L.; Saranya, K. R. L.; Athira, K.; Jha, C. S.; Diwakar, P. G.; Dadhwal, V. K.

2017-02-01

Carbon emissions released from forest fires have been identified as an environmental issue in the context of global warming. This study provides data on spatial and temporal patterns of fire incidences, burnt area and carbon emissions covering natural vegetation types (forest, scrub and grassland) and Protected Areas of India. The total area affected by fire in the forest, scrub and grasslands have been estimated as 48765.45, 6540.97 and 1821.33 km 2, respectively, in 2014 using Resourcesat-2 AWiFS data. The total CO 2 emissions from fires of these vegetation types in India were estimated to be 98.11 Tg during 2014. The highest emissions were caused by dry deciduous forests, followed by moist deciduous forests. The fire season typically occurs in February, March, April and May in different parts of India. Monthly CO 2 emissions from fires for different vegetation types have been calculated for February, March, April and May and estimated as 2.26, 33.53, 32.15 and 30.17 Tg, respectively. Protected Areas represent 11.46% of the total natural vegetation cover of India. Analysis of fire occurrences over a 10-year period with two types of sensor data, i.e., AWiFS and MODIS, have found fires in 281 (out of 614) Protected Areas of India. About 16.78 Tg of CO 2 emissions were estimated in Protected Areas in 2014. The natural vegetation types of Protected Areas have contributed for burnt area of 17.3% and CO 2 emissions of 17.1% as compared to total natural vegetation burnt area and emissions in India in 2014. 9.4% of the total vegetation in the Protected Areas was burnt in 2014. Our results suggest that Protected Areas have to be considered for strict fire management as an effective strategy for mitigating climate change and biodiversity conservation.

The status of North Carolina's national forests, 2002

Treesearch

Sonja N. Oswalt; Tony G. Johnson

2007-01-01

This bulletin describes forest resources of the Pisgah/Cherokee, Nantahala, Croatan, and Uwharrie National Forests in the State of North Carolina. It is based on sampling conducted by the U.S. Department of Agriculture Forest Service, Southern Research Station, Forest Inventory and Analysis Research Work Unit. This bulletin addresses forest area estimates; timber...

Structural dynamics of tropical moist forest gaps

Treesearch

Maria O. Hunter; Michael Keller; Douglas Morton; Bruce Cook; Michael Lefsky; Mark Ducey; Scott Saleska; Raimundo Cosme de Oliveira; Juliana Schietti

2015-01-01

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest...

Assessment of Burned Area and Atmospheric Gases from Multi- temporal MODIS Images (2000- 2017) in Nainital District, Uttarakhand

NASA Astrophysics Data System (ADS)

Aggarwal, R.; K V, S. B.; Dhakate, P. M.

2017-12-01

Recent times have observed a significant rate of deforestation and forest degradation. One of the major causes of forest degradation is forest fires. Forest fires though have shaped the current forest ecosystem but also have continued to degrade the system by causing loss of flora and fauna. In addition to that, forest fire leads to emission of carbon and other trace gases which contributes to global warming. The hill states in India, particularly Uttarakhand witnesses annual forest fires; which are primarily anthropogenic caused, occurring from March to June. Nainital one of the thirteen districts in Uttarakhand, has been selected as the study site. The region has diverse endemic species of vegetation, ranging from Alpine in North to moist deciduous in South. The increasing forest fire incidents in the region and limited studies on the subject, calls for landscape assessment of the complex Human Environment System (HES). It is in this context, that a greater need for monitoring forest fire incidents has been felt. Remote Sensing and GIS which are robust tool, provides continuous information of an area at various spatial and temporal resolutions. The goal of this study is to map burned area, burned severity and estimate atmospheric gas emissions in forested areas of Nainital by utilizing cloud free MODIS images from 2000- 2017. Multiple spectral indices were generated from pre and post burn dataset of MODIS to conclude the most sensitive band combination. Inter- comparison of results obtained from different spectral indices and the global MODIS MCD45A1 was carried out using linear regression analysis. Additionally, burned area estimation from satellite was compared to figures reported by forest department. There were considerable differences amongst the two which could be primarily due to differences in spatial resolution, and timings of forest fire occurrence and image acquisition. Further, estimation of various atmospheric gases was carried out based on the IPCC guidelines. Such an analysis is critically important for designing of relevant forest fire mitigation strategies. The study signifies that long term MODIS data and the rationing method is an effective technique to map and monitor the burned area, burned severity and atmospheric gas emission in the forested regions of Himalayan.

Accuracy assessment of biomass and forested area classification from modis, landstat-tm satellite imagery and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2007-01-01

The objective of this study was to determine how well forestfnon-forest and biomass classifications obtained from Landsat-TM and MODIS satellite data modeled with FIA plots, compare to each other and with forested area and biomass estimates from the national inventory data, as well as whether there is an increase in overall accuracy when pixel size (spatial resolution...

Combining satellite imagery with forest inventory data to assess damage severity following a major blowdown event in northern Minnesota, USA

Treesearch

Mark D. Nelson; Sean P. Healey; W. Keith Moser; Mark H. Hansen

2009-01-01

Effects of a catastrophic blowdown event in northern Minnesota, USA were assessed using field inventory data, aerial sketch maps and satellite image data processed through the North American Forest Dynamics programme. Estimates were produced for forest area and net volume per unit area of live trees pre- and post-disturbance, and for changes in volume per unit area and...

Estimating total forest biomass in New York, 1993

Treesearch

Eric Wharton; Carol Alerich; David A. Drake; David A. Drake

1997-01-01

Presents methods for synthesizing information from existing biomass literature for estimating biomass over extensive forest areas with specific applications to New York. Tables of appropriate regression equations and the tree and shrub species to which these equations can be applied are presented well as biomass estimates at the county, geographic unit, and state level...

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information.

PubMed

Mauro, Francisco; Monleon, Vicente J; Temesgen, Hailemariam; Ford, Kevin R

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey's height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates.

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information

PubMed Central

Monleon, Vicente J.; Temesgen, Hailemariam; Ford, Kevin R.

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey’s height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates. PMID:29216290

Sample-based estimation of tree species richness in a wet tropical forest compartment

Treesearch

Steen Magnussen; Raphael Pelissier

2007-01-01

Petersen's capture-recapture ratio estimator and the well-known bootstrap estimator are compared across a range of simulated low-intensity simple random sampling with fixed-area plots of 100 m? in a rich wet tropical forest compartment with 93 tree species in the Western Ghats of India. Petersen's ratio estimator was uniformly superior to the bootstrap...

Plot intensity and cycle-length effects on growth and removals estimates from forest inventories

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2015-01-01

Continuous forest inventory planners can allocate the budget to more plots per acre or a shorter remeasurement cycle. A higher plot intensity benefits small area estimation and allows for more precision in current status estimates. Shorter cycles may provide better estimates of growth, removals and mortality. On a fixed budget, the planner can't have both greater...

Estimating variation in a landscape simulation of forest structure.

Treesearch

S. Hummel; P. Cunningham

2006-01-01

Modern technology makes it easy to show how forested landscapes might change with time but it remains difficult to estimate how sampling error affects landscape simulation results. To address this problem we used two methods to project the area in late-sera1 forest (LSF) structure for the same 6070 hectare (ha) study site over 30 years. The site was stratified into...

Illinois' forest resources in 2004

Treesearch

Susan J. Crocker; Earl C. Leatherberry; Gary J. Brand; Dick C. Little

2006-01-01

Results of the 2004 annual inventory of Illinois show an estimated 4.4 million acres of forest land that supports 7.7 billion cubic feet of total net volume of all live trees. Since 1948, timberland area has steadily increased and now represents 96 percent of total forest land. Growing-stock volume on timberland has risen to an estimated 6.7 billion cubic feet. All...

Bridging the gap between strategic and management forest inventories

Treesearch

Ronald E. McRoberts

2009-01-01

Strategic forest inventory programs collect information for a large number of variables on a relatively sparse array of field plots. Data from these inventories are used to produce estimates for large areas such as states and provinces, regions, or countries. The purpose of management forest inventories is to guide management decisions for small areas such as stands....

Using airborne light detection and ranging as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska

Treesearch

Hans-Erik Andersen; Jacob Strunk; Hailemariam Temesgen

2011-01-01

Airborne laser scanning, collected in a sampling mode, has the potential to be a valuable tool for estimating the biomass resources available to support bioenergy production in rural communities of interior Alaska. In this study, we present a methodology for estimating forest biomass over a 201,226-ha area (of which 163,913 ha are forested) in the upper Tanana valley...

Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000

PubMed Central

Bodart, Catherine; Brink, Andreas B; Donnay, François; Lupi, Andrea; Mayaux, Philippe; Achard, Frédéric

2013-01-01

Aim This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium-resolution satellite imagery which was processed consistently across the continent. Location The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi-arid regions. This area covers the Sudanian and Zambezian ecoregions. Methods A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts. Results Land cover and land-cover changes were estimated at continental and ecoregion scales and compared with existing pan-continental, regional and local studies. The overall accuracy of our land-cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area. Main conclusions Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies. PMID:23935237

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

PubMed

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Dinh Duong, Nguyen; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity. PMID:24465714

Carbon changes in conterminous US forests associated with growth and major disturbances: 1992-2001

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2011-01-01

We estimated forest area and carbon changes in the conterminous United States using a remote sensing based land cover change map, forest fire data from the Monitoring Trends in Burn Severity program, and forest growth and harvest data from the USDA Forest Service, Forest Inventory and Analysis Program. Natural and human-associated disturbances reduced the forest...

Improved estimation of forest area in tropical Africa through ALOS/PALSAR 50-m orthorectified mosaic images

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.; Li, L.; Tenku, S. N.; Zhang, G.; Biradar, C. M.

2013-12-01

Tropical and moist Africa has one of the largest rainforests in the world. However, our knowledge about its forest area and spatial extent is still very limited. Forest area datasets from the Food and Agriculture Organization (FAO) Forest Resource Assessment (FRA) and the analyses of optical images (e.g., MODIS and MERIS) had a significant discrepancy, and they cannot meet the requirements to support the studies of forest carbon cycle and biodiversity, as well as the implementation of reducing emissions from deforestation and forest degradation (REDD+). The reasons for the large data discrepancy are complex and may attribute to the frequent cloud cover, coarse spatial resolution of images (MODIS, MERIS), diverse forest definition and classification approaches. In this study we generated a forest cover map in central Africa at 50-m resolution through the use of the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) 50-m orthorectified mosaic imagery in 2009. The resultant forest map was evaluated by the ground-reference data collected from the Geo-referenced Field Photo Library and Google Earth, and it has a reasonably high accuracy (producer's accuracy 83% and user's accuracy 94%). We also compared the PALSAR-based forest map with other three forest cover products (MCD12Q1 2009, GlobCover 2009 and VCF tree cover 2009) at the scales of (1) entire study domain and (2) selected sample regions. This new PALSAR-based 50-m forest cover map is likely to help reduce the uncertainty in forest area estimation, and better quantify and track deforestation, REDD+ implementation, and biodiversity conservation in central Africa.

Impact of anthropogenic climate change on wildfire across western US forests.

PubMed

Abatzoglou, John T; Williams, A Park

2016-10-18

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Park Williams, A.

2016-10-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ˜55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Deforestation and Forest Fires in Roraima and Their Relationship with Phytoclimatic Regions in the Northern Brazilian Amazon

NASA Astrophysics Data System (ADS)

Barni, Paulo Eduardo; Pereira, Vaneza Barreto; Manzi, Antonio Ocimar; Barbosa, Reinaldo Imbrozio

2015-05-01

Deforestation and forest fires in the Brazilian Amazon are a regional-scale anthropogenic process related to biomass burning, which has a direct impact on global warming due to greenhouse gas emissions. Containment of this process requires characterizing its spatial distribution and that of the environmental factors related to its occurrence. The aim of this study is to investigate the spatial and temporal distribution of deforested areas and forest fires in the State of Roraima from 2000 to 2010. We mapped deforested areas and forest fires using Landsat images and associated their occurrence with two phytoclimatic zones: zone with savanna influence (ZIS), and zone without savanna influence (ZOS). Total deforested area during the interval was estimated at 3.06 × 103 km2 (ZIS = 55 %; ZOS = 45 %) while total area affected by forest fires was estimated at 3.02 × 103 km2 (ZIS = 97.7 %; ZOS = 2.3 %). Magnitude of deforestation in Roraima was not related to the phytoclimatic zones, but small deforested areas (≤17.9 ha) predominated in ZOS while larger deforestation classes (>17.9 ha) predominated in ZIS, which is an area with a longer history of human activities. The largest occurrence of forest fires was observed in the ZIS in years with El Niño events. Our analysis indicates that the areas most affected by forest fires in Roraima during 2000-2010 were associated with strong climatic events and the occurrence these fires was amplified in ZIS, a sensitive phytoclimatic zone with a higher risk of anthropogenic fires given its drier climate and open forest structure.

The extent of forest in dryland biomes.

PubMed

Bastin, Jean-François; Berrahmouni, Nora; Grainger, Alan; Maniatis, Danae; Mollicone, Danilo; Moore, Rebecca; Patriarca, Chiara; Picard, Nicolas; Sparrow, Ben; Abraham, Elena Maria; Aloui, Kamel; Atesoglu, Ayhan; Attore, Fabio; Bassüllü, Çağlar; Bey, Adia; Garzuglia, Monica; García-Montero, Luis G; Groot, Nikée; Guerin, Greg; Laestadius, Lars; Lowe, Andrew J; Mamane, Bako; Marchi, Giulio; Patterson, Paul; Rezende, Marcelo; Ricci, Stefano; Salcedo, Ignacio; Diaz, Alfonso Sanchez-Paus; Stolle, Fred; Surappaeva, Venera; Castro, Rene

2017-05-12

Dryland biomes cover two-fifths of Earth's land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%. Copyright © 2017, American Association for the Advancement of Science.

Gross changes in forest area shape the future carbon balance of tropical forests

NASA Astrophysics Data System (ADS)

Li, Wei; Ciais, Philippe; Yue, Chao; Gasser, Thomas; Peng, Shushi; Bastos, Ana

2018-01-01

Bookkeeping models are used to estimate land-use and land-cover change (LULCC) carbon fluxes (ELULCC). The uncertainty of bookkeeping models partly arises from data used to define response curves (usually from local data) and their representativeness for application to large regions. Here, we compare biomass recovery curves derived from a recent synthesis of secondary forest plots in Latin America by Poorter et al. (2016) with the curves used previously in bookkeeping models from Houghton (1999) and Hansis et al. (2015). We find that the two latter models overestimate the long-term (100 years) vegetation carbon density of secondary forest by about 25 %. We also use idealized LULCC scenarios combined with these three different response curves to demonstrate the importance of considering gross forest area changes instead of net forest area changes for estimating regional ELULCC. In the illustrative case of a net gain in forest area composed of a large gross loss and a large gross gain occurring during a single year, the initial gross loss has an important legacy effect on ELULCC so that the system can be a net source of CO2 to the atmosphere long after the initial forest area change. We show the existence of critical values of the ratio of gross area change over net area change (γAnetAgross), above which cumulative ELULCC is a net CO2 source rather than a sink for a given time horizon after the initial perturbation. These theoretical critical ratio values derived from simulations of a bookkeeping model are compared with observations from the 30 m resolution Landsat Thematic Mapper data of gross and net forest area change in the Amazon. This allows us to diagnose areas in which current forest gains with a large land turnover will still result in LULCC carbon emissions in 20, 50 and 100 years.

Light Diffusion in the Tropical Dry Forest of Costa Rica

NASA Astrophysics Data System (ADS)

Calvo-Rodriguez, S.; Sanchez-Azofeifa, G. A.

2016-06-01

Leaf Area Index (LAI) has been defined as the total leaf area (one-sided) in relation to the ground. LAI has an impact on tree growth and recruitment through the interception of light, which in turn affects primary productivity. Even though many instruments exist for estimating LAI from ground, they are often laborious and costly to run continuously. Measurements of LAI from the field using traditional sensors (e.g., LAI-2000) require multiple visits to the field under very specific sky conditions, making them unsuitable to operate in inaccessible areas and forests with dense vegetation, as well as areas where persistent sunny conditions are the norm like tropical dry forests. With this context, we proposed a methodology to characterize light diffusion based on NDVI and LAI measurements taken from the field in two successional stages in the tropical dry forest of Santa Rosa National Park in Costa Rica. We estimate a "K" coefficient to characterize light diffusion by the canopy, based on field NDVI measurements derived from optical phenology instruments and MODIS NDVI. From the coefficients determined, we estimated LAI values and compared them with ground measurements of LAI. In both successional stages ground measurements of LAI had no significant difference to the tower-derived LAI and the estimated LAI from MODIS NDVI.

Forest resources of the United States, 1992

Treesearch

Douglas S. Powell; Joanne L. Faulkner; David R. Darr; Zhiliang Zhu; Douglas W. MacCleery

1993-01-01

The 1987 Resources Planning Act (RPA) Assessment forest resources statistics are updated to 1992, to provide current information on the Nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output. Resource data are analyzed, and trends since 1987 are noted. A forest type map produced from...

Forest Resources of the United States, 1997, METRIC UNITS.

Treesearch

W. Brad Smith; John S. Vissage; Davie R. Darr; Raymond M. Sheffield

2002-01-01

Forest resource statistics from the 1987 Forest Resources Planning Act (RPA) Asessment were updated to 1997 to provide current information on the Nation's forests. Resource tables present estimates in metric measure of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State.

Implementing a land cover stratification on-the-fly

Treesearch

Ronald E. McRoberts; Daniel G. Wendt

2002-01-01

Stratified estimation is used by the Forest Inventory and Analysis program of the USDA Forest Service to increase the precision of county-level inventory estimates. Stratified estimation requires that plots be assigned to strata and that proportions of land area in each strata be determined. Classified satellite imagery has been found to be an efficient and effective...

Analysis And Assessment Of Forest Cover Change For The State Of Wisconsin

NASA Astrophysics Data System (ADS)

Perry, C. H.; Nelson, M. D.; Stueve, K.; Gormanson, D.

2010-12-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service is charged with documenting the status and trends of forest resources of the United States. Since the 1930s, FIA has implemented an intensive field campaign that collects measurements on plots distributed across all ownerships, historically completing analyses which include estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Originally a periodic inventory, FIA has been measuring plots on an annual basis since the passage of the Agriculture Research, Extension and Education Reform Act of 1998 (Farm Bill). The resulting change in sampling design and intensity presents challenges to establishing baseline and measuring changes in forest area and biomass. A project jointly sponsored by the Forest Service and the National Aeronautics and Space Agency (NASA) titled “Integrating Landscape-scale Forest Measurements with Remote Sensing and Ecosystem Models to Improve Carbon Management Decisions” seeks to improve estimates of landscape- and continental-scale carbon dynamics and causes of change for North American forest land, and to use this information to support land management decisions. Specifically, we are developing and applying methods to scale up intensive biomass and carbon measurements from the field campaign to larger land management areas while simultaneously estimating change in the above-ground forest carbon stocks; the State of Wisconsin is being used as the testbed for this large-scale integration remote sensing with field measurements. Once defined, the temporal and spatial patterns of forest resources by watershed for Lake Superior and Lake Michigan outputs are being integrated into water quality assessments for the Great Lakes.

An estimate of the amount of road in the staggered-setting system of clearcutting.

Treesearch

Roy R. Silen; H.J. Gratkowski

1953-01-01

One question frequently asked by foresters in the Douglas-fir region is: "How much land is taken out of forest production by logging roads and landings?" The final answer is not known, but a rough estimate recently prepared for a sizable portion of the H. J. Andrews Experimental Forest may be useful as a tentative figure. The experimental area is located...

Analysis of forest structure using thematic mapper simulator data

NASA Technical Reports Server (NTRS)

Peterson, D. L.; Westman, W. E.; Brass, J. A.; Stephenson, N. J.; Ambrosia, V. G.; Spanner, M. A.

1986-01-01

The potential of Thematic Mapper Simulator (TMS) data for sensing forest structure information has been explored by principal components and feature selection techniques. In a survey of forest structural properties conducted for 123 field sites of the Sequoia National Park, the canopy closure could be well estimated (r = 0.62 to 0.69) by a variety of channel bands and band ratios, without reference to the forest type. Estimation of the basal area was less successful (r = 0.51 or less) on the average, but could be improved for certain forest types when data were stratified by floristic composition. To achieve such a stratification, individual sites were ordinated by a detrended correspondence analysis based on the canopy of dominant species. The analysis of forest structure in the Sequoia data suggests that total basal area can be best predicted in stands of lower density, and in younger even-aged managed stands.

Assessing change in large-scale forest area by visually interpreting Landsat images

Treesearch

Jerry D. Greer; Frederick P. Weber; Raymond L. Czaplewski

2000-01-01

As part of the Forest Resources Assessment 1990, the Food and Agriculture Organization of the United Nations visually interpreted a stratified random sample of 117 Landsat scenes to estimate global status and change in tropical forest area. Images from 1980 and 1990 were interpreted by a group of widely experienced technical people in many different tropical countries...

Planted forests and plantations

Treesearch

Ray Sheffield

2009-01-01

Forest resource statistics from the 2000 Resources Planning Act (RPA) Assessment were updated to provide current information on the Nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Currrent resources data and trends...

Capturing spiral radial growth of conifers using the superellipse to model tree-ring geometric shape

PubMed Central

Shi, Pei-Jian; Huang, Jian-Guo; Hui, Cang; Grissino-Mayer, Henri D.; Tardif, Jacques C.; Zhai, Li-Hong; Wang, Fu-Sheng; Li, Bai-Lian

2015-01-01

Tree-rings are often assumed to approximate a circular shape when estimating forest productivity and carbon dynamics. However, tree rings are rarely, if ever, circular, thereby possibly resulting in under- or over-estimation in forest productivity and carbon sequestration. Given the crucial role played by tree ring data in assessing forest productivity and carbon storage within a context of global change, it is particularly important that mathematical models adequately render cross-sectional area increment derived from tree rings. We modeled the geometric shape of tree rings using the superellipse equation and checked its validation based on the theoretical simulation and six actual cross sections collected from three conifers. We found that the superellipse better describes the geometric shape of tree rings than the circle commonly used. We showed that a spiral growth trend exists on the radial section over time, which might be closely related to spiral grain along the longitudinal axis. The superellipse generally had higher accuracy than the circle in predicting the basal area increment, resulting in an improved estimate for the basal area. The superellipse may allow better assessing forest productivity and carbon storage in terrestrial forest ecosystems. PMID:26528316

Capturing spiral radial growth of conifers using the superellipse to model tree-ring geometric shape.

PubMed

Shi, Pei-Jian; Huang, Jian-Guo; Hui, Cang; Grissino-Mayer, Henri D; Tardif, Jacques C; Zhai, Li-Hong; Wang, Fu-Sheng; Li, Bai-Lian

2015-01-01

Tree-rings are often assumed to approximate a circular shape when estimating forest productivity and carbon dynamics. However, tree rings are rarely, if ever, circular, thereby possibly resulting in under- or over-estimation in forest productivity and carbon sequestration. Given the crucial role played by tree ring data in assessing forest productivity and carbon storage within a context of global change, it is particularly important that mathematical models adequately render cross-sectional area increment derived from tree rings. We modeled the geometric shape of tree rings using the superellipse equation and checked its validation based on the theoretical simulation and six actual cross sections collected from three conifers. We found that the superellipse better describes the geometric shape of tree rings than the circle commonly used. We showed that a spiral growth trend exists on the radial section over time, which might be closely related to spiral grain along the longitudinal axis. The superellipse generally had higher accuracy than the circle in predicting the basal area increment, resulting in an improved estimate for the basal area. The superellipse may allow better assessing forest productivity and carbon storage in terrestrial forest ecosystems.

The Polarization Orientation Shift Estimation and Compensation of PolSAR Data in Forest Area

NASA Astrophysics Data System (ADS)

Zhao, Lei; Chen, Erxue; Li, Zengyuan; Li, Lan; Gu, Xinzhi

2016-08-01

Polarization orientation angle (POA) is a major parameter of electromagnetic wave. This angle will be shift due to azimuth slopes, which will affect the radiometric quality of PolSAR data. Under the assumption of reflection symmetrical medium, the shift value of polarization orientation angle (POAs) can be estimated by Circular Polarization Method (CPM). Then, the shift angle can be used to compensate PolSAR data or extract DEM information. However, it is less effective when using high-frequency SAR (L-, C-band) in the forest area. The main reason is that the polarization orientation angle shift of forest area not only influenced by topography, but also affected by the forest canopy. Among them, the influence of the former belongs to the interference information should be removed, but the impact of the latter belongs to the polarization feature information needs to be retained. The ALOS2 PALSAR2 L-band full polarimetric SAR data was used in this study. Base on the Circular Polarization and DEM-based method, we analyzed the variation of shift value of polarization orientation angle and developed the polarization orientation shift estimation and compensation of PolSAR data in forest.

A Measure of the Forest Protected Areas Benefits for the Surrounding Population: A Case Study of the Bouaflé Protected Forest (CÔTE D'IVOIRE)

NASA Astrophysics Data System (ADS)

Kouame, B. N. P.

2015-12-01

Côte d'Ivoire located in West Africa, registers high level of biodiversity which occurs mainly in forest land. The country has suffered severe deforestation. However, deforestation and forest degradation release Greenhouse Gases into the atmosphere which contributes to Climate Change. In order to address the deforestation, many actions are taken, one of which is the implementation of protected areas within countries. These measures put restrictions on the access of local communities to forest services. However, local communities supplement their daily livelihood from forests, especially from timber and non-timber forest products. What are the effects of forests conservation in protected areas on surrounding population? This study focuses on the Bouaflé protected forest (foret classée de Bouaflé) in the western part of Côte d'Ivoire. The forest is 20350 ha and was made a protected forest in 1974. It is one of the most deforested protected areas in the country. Firstly, we described the perception of forest benefits by the population. Secondly, we estimated the benefits of forest conservation using a contingent valuation approach, particularly the Willingness to Pay (WTP) methodology. From our sample size of 156 households, it appears that most of the individuals are aware of the importance of the forest (94 % against 6%). According to the estimate of the benefits, it results on average, people are willing to pay 1658.491F CFA (2.53 Euros). The median WTP is 1000 FCFA. This study will be helpful by adding to the scientific literature and for inducing local people implication in conservation.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals

NASA Astrophysics Data System (ADS)

Chen, Youhua; Peng, Shushi

2017-03-01

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals.

PubMed

Chen, Youhua; Peng, Shushi

2017-03-16

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Structural and compositional controls on transpiration in 40- and 450-year-old riparian forests in western Oregon, USA.

PubMed

Moore, Georgianne W; Bond, Barbara J; Jones, Julia A; Phillips, Nathan; Meinzer, Federick C

2004-05-01

Large areas of forests in the Pacific Northwest are being transformed to younger forests, yet little is known about the impact this may have on hydrological cycles. Previous work suggests that old trees use less water per unit leaf area or sapwood area than young mature trees of the same species in similar environments. Do old forests, therefore, use less water than young mature forests in similar environments, or are there other structural or compositional components in the forests that compensate for tree-level differences? We investigated the impacts of tree age, species composition and sapwood basal area on stand-level transpiration in adjacent watersheds at the H.J. Andrews Forest in the western Cascades of Oregon, one containing a young, mature (about 40 years since disturbance) conifer forest and the other an old growth (about 450 years since disturbance) forest. Sap flow measurements were used to evaluate the degree to which differences in age and species composition affect water use. Stand sapwood basal area was evaluated based on a vegetation survey for species, basal area and sapwood basal area in the riparian area of two watersheds. A simple scaling exercise derived from estimated differences in water use as a result of differences in age, species composition and stand sapwood area was used to estimate transpiration from late June through October within the entire riparian area of these watersheds. Transpiration was higher in the young stand because of greater sap flux density (sap flow per unit sapwood area) by age class and species, and greater total stand sapwood area. During the measurement period, mean daily sap flux density was 2.30 times higher in young compared with old Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) trees. Sap flux density was 1.41 times higher in young red alder (Alnus rubra Bong.) compared with young P. menziesii trees, and was 1.45 times higher in old P. menziesii compared with old western hemlock (Tsuga heterophylla (Raf.) Sarg.) trees. Overall, sapwood basal area was 21% higher in the young stand than in the old stand. In the old forest, T. heterophylla is an important co-dominant, accounting for 58% of total sapwood basal area, whereas P. menziesii is the only dominant conifer in the young stand. Angiosperms accounted for 36% of total sapwood basal area in the young stand, but only 7% in the old stand. For all factors combined, we estimated 3.27 times more water use by vegetation in the riparian area of the young stand over the measurement period. Tree age had the greatest effect on stand differences in water use, followed by differences in sapwood basal area, and finally species composition. The large differences in transpiration provide further evidence that forest management alters site water balance via elevated transpiration in vigorous young stands.

Measuring global canopy reduction: A forest degradation proxy for FRA2015

Treesearch

Kenneth MacDicken; Erik Lidquist

2013-01-01

Global interest in forest degradation is widespread – but is fraught with widely differing views. Forest degradation by one definition may be sustainable forest management by another. The Global Forest Resources Assessment, conducted by FAO every five years, is working to find an approach to a global estimation of forest area that can address these differing...

Estimating rainforest biomass stocks and carbon loss from deforestation and degradation in Papua New Guinea 1972-2002: Best estimates, uncertainties and research needs.

PubMed

Bryan, Jane; Shearman, Phil; Ash, Julian; Kirkpatrick, J B

2010-01-01

Reduction of carbon emissions from tropical deforestation and forest degradation is being considered a cost-effective way of mitigating the impacts of global warming. If such reductions are to be implemented, accurate and repeatable measurements of forest cover change and biomass will be required. In Papua New Guinea (PNG), which has one of the world's largest remaining areas of tropical forest, we used the best available data to estimate rainforest carbon stocks, and emissions from deforestation and degradation. We collated all available PNG field measurements which could be used to estimate carbon stocks in logged and unlogged forest. We extrapolated these plot-level estimates across the forested landscape using high-resolution forest mapping. We found the best estimate of forest carbon stocks contained in logged and unlogged forest in 2002 to be 4770 Mt (+/-13%). Our best estimate of gross forest carbon released through deforestation and degradation between 1972 and 2002 was 1178 Mt (+/-18%). By applying a long-term forest change model, we estimated that the carbon loss resulting from deforestation and degradation in 2001 was 53 Mt (+/-18%), rising from 24 Mt (+/-15%) in 1972. Forty-one percent of 2001 emissions resulted from logging, rising from 21% in 1972. Reducing emissions from logging is therefore a priority for PNG. The large uncertainty in our estimates of carbon stocks and fluxes is primarily due to the dearth of field measurements in both logged and unlogged forest, and the lack of PNG logging damage studies. Research priorities for PNG to increase the accuracy of forest carbon stock assessments are the collection of field measurements in unlogged forest and more spatially explicit logging damage studies. Copyright 2009 Elsevier Ltd. All rights reserved.

Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets

USGS Publications Warehouse

Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark

2009-01-01

Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.

Washington's public and private forests.

Treesearch

Charles L. Bolsinger; Neil McKay; Donald FL Gedney; Carol Alerich

1997-01-01

This report summarizes and analyzes 1988-91 timber inventories of western and eastern Washington. These inventories were conducted on all private and public lands except National Forests. Timber resource statistics from National Forest inventories also are presented. Detailed tables provide estimates of forest area, timber volume, growth, mortality, and harvest. Data...

Old-growth forests in the Sierra Nevada: by type in 1945 and 1993 and ownership in 1993.

Treesearch

Debby Beardsley; Charles Bolsinger; Ralph. Warbington

1999-01-01

This report presents estimates of old-growth forest area in the Sierra Nevada by forest type in 1993 and 1945 and by old-growth stand characteristics as they existed in 1993. Ecological old-growth definitions for each forest type are used.

Predictions of Tropical Forest Biomass and Biomass Growth Based on Stand Height or Canopy Area Are Improved by Landsat-Scale Phenology across Puerto Rico and the U.S. Virgin Islands

Treesearch

David Gwenzi; Eileen Helmer; Xiaolin Zhu; Michael Lefsky; Humfredo Marcano-Vega

2017-01-01

Remotely-sensed estimates of forest biomass are usually based on various measurements of canopy height, area, volume or texture, as derived from LiDAR, radar or fine spatial resolution imagery. These measurements are then calibrated to estimates of stand biomass that are primarily based on tree stem diameters. Although humid tropical...

Tropical forest plantation biomass estimation using RADARSAT-SAR and TM data of south china

NASA Astrophysics Data System (ADS)

Wang, Chenli; Niu, Zheng; Gu, Xiaoping; Guo, Zhixing; Cong, Pifu

2005-10-01

Forest biomass is one of the most important parameters for global carbon stock model yet can only be estimated with great uncertainties. Remote sensing, especially SAR data can offers the possibility of providing relatively accurate forest biomass estimations at a lower cost than inventory in study tropical forest. The goal of this research was to compare the sensitivity of forest biomass to Landsat TM and RADARSAT-SAR data and to assess the efficiency of NDVI, EVI and other vegetation indices in study forest biomass based on the field survey date and GIS in south china. Based on vegetation indices and factor analysis, multiple regression and neural networks were developed for biomass estimation for each species of the plantation. For each species, the better relationships between the biomass predicted and that measured from field survey was obtained with a neural network developed for the species. The relationship between predicted and measured biomass derived from vegetation indices differed between species. This study concludes that single band and many vegetation indices are weakly correlated with selected forest biomass. RADARSAT-SAR Backscatter coefficient has a relatively good logarithmic correlation with forest biomass, but neither TM spectral bands nor vegetation indices alone are sufficient to establish an efficient model for biomass estimation due to the saturation of bands and vegetation indices, multiple regression models that consist of spectral and environment variables improve biomass estimation performance. Comparing with TM, a relatively well estimation result can be achieved by RADARSAT-SAR, but all had limitations in tropical forest biomass estimation. The estimation results obtained are not accurate enough for forest management purposes at the forest stand level. However, the approximate volume estimates derived by the method can be useful in areas where no other forest information is available. Therefore, this paper provides a better understanding of relationships of remote sensing data and forest stand parameters used in forest parameter estimation models.

Nebraska's Forest Resources in 2005

Treesearch

Dacia M. Meneguzzo; Gary J. Brand; William R. Lovett

2007-01-01

Results of the 2005 annual inventory of Nebraska show an estimated 1.24 million acres of forest land. Softwoods comprise one-third of this forested area, with ponderosa pine being the primary component by acreage and volume. Hardwoods comprise more than half (58 percent) of all forested acreage. Overall, the elm/ash/cottonwood type is the predominant forest-type group...

Minimum cost strategies for sequestering carbon in forests.

Treesearch

Darius M. Adams; Ralph J. Alig; Bruce A. McCarl; John M. Callaway; Steven M. Winnett

1999-01-01

This paper examines the costs of meeting explicit targets for increments of carbon sequestered in forests when both forest management decisions and the area of forests can be varied. Costs are estimated as welfare losses in markets for forest and agricultural products. Results show greatest change in management actions when targets require large near-term flux...

Iowa's forest resources, 2005

Treesearch

Susan J. Crocker; Gary J. Brand; Aron Flickinger

2007-01-01

Report presents Iowa's annual inventory results for 2005. Estimates show that Iowa has more than 2.8 million acres of forest land. Total live-tree volume on forest land is 4.0 billion cubic feet. Ninety-eight percent of forest land is classified as timberland. Oak/hickory is the predominant forest-type group, representing 54 percent of timberland area. Growing-...

Tennessee's Forests, 2004

Treesearch

Christopher M. Oswalt; Sonja N. Oswalt; Tony G. Johnson; James L. Chamberlain; KaDonna C. Randolph; John W. Coulston

2009-01-01

Forest land area in Tennessee amounted to 13.78 million acres. About 125 different species, mostly hardwood, account for an estimated 22.6 billion cubic feet of all growing-stock volume on timberland in the State. Hardwood forest types occupy the vast majority of the State's forest land, and oak-hickory is the dominant forest-type group, accounting for about 10.1...

Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Treesearch

Michael J. Falkowski; Jeffrey S. Evans; Sebastian Martinuzzi; Paul E. Gessler; Andrew T. Hudak

2009-01-01

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest...

The use of remote sensing for updating extensive forest inventories

Treesearch

John F. Kelly

1990-01-01

The Forest Inventory and Analysis unit of the USDA Forest Service Southern Forest Experiment Station (SO-FIA) has the research task of devising an inventory updating system that can be used to provide reliable estimates of forest area, volume, growth, and removals at the State level. These updated inventories must be accomplished within current budgetary restraints....

Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data

NASA Technical Reports Server (NTRS)

Nelson, Ross; Horning, Ned; Stone, Thomas A.

1987-01-01

AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV

NASA Astrophysics Data System (ADS)

Chianucci, Francesco; Disperati, Leonardo; Guzzi, Donatella; Bianchini, Daniele; Nardino, Vanni; Lastri, Cinzia; Rindinella, Andrea; Corona, Piermaria

2016-05-01

Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L*a*b* colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications.

Deforestation and forest fires in Roraima and their relationship with phytoclimatic regions in the northern Brazilian Amazon.

PubMed

Barni, Paulo Eduardo; Pereira, Vaneza Barreto; Manzi, Antonio Ocimar; Barbosa, Reinaldo Imbrozio

2015-05-01

Deforestation and forest fires in the Brazilian Amazon are a regional-scale anthropogenic process related to biomass burning, which has a direct impact on global warming due to greenhouse gas emissions. Containment of this process requires characterizing its spatial distribution and that of the environmental factors related to its occurrence. The aim of this study is to investigate the spatial and temporal distribution of deforested areas and forest fires in the State of Roraima from 2000 to 2010. We mapped deforested areas and forest fires using Landsat images and associated their occurrence with two phytoclimatic zones: zone with savanna influence (ZIS), and zone without savanna influence (ZOS). Total deforested area during the interval was estimated at 3.06 × 10(3) km(2) (ZIS = 55 %; ZOS = 45 %) while total area affected by forest fires was estimated at 3.02 × 10(3) km(2) (ZIS = 97.7 %; ZOS = 2.3 %). Magnitude of deforestation in Roraima was not related to the phytoclimatic zones, but small deforested areas (≤17.9 ha) predominated in ZOS while larger deforestation classes (>17.9 ha) predominated in ZIS, which is an area with a longer history of human activities. The largest occurrence of forest fires was observed in the ZIS in years with El Niño events. Our analysis indicates that the areas most affected by forest fires in Roraima during 2000-2010 were associated with strong climatic events and the occurrence these fires was amplified in ZIS, a sensitive phytoclimatic zone with a higher risk of anthropogenic fires given its drier climate and open forest structure.

Estimating actual evapotranspiration for forested sites: modifications to the Thornthwaite Model

Treesearch

Randall K. Kolka; Ann T. Wolf

1998-01-01

A previously coded version of the Thornthwaite water balance model was used to estimate annual actual evapotranspiration (AET) for 29 forested sites between 1900 and 1993 in the Upper Great Lakes area. Approximately 8 percent of the data sets calculated AET in error. Errors were detected in months when estimated AET was greater than potential evapotranspiration. Annual...

Protected Areas' Impacts on Brazilian Amazon Deforestation: Examining Conservation-Development Interactions to Inform Planning.

PubMed

Pfaff, Alexander; Robalino, Juan; Herrera, Diego; Sandoval, Catalina

2015-01-01

Protected areas are the leading forest conservation policy for species and ecoservices goals and they may feature in climate policy if countries with tropical forest rely on familiar tools. For Brazil's Legal Amazon, we estimate the average impact of protection upon deforestation and show how protected areas' forest impacts vary significantly with development pressure. We use matching, i.e., comparisons that are apples-to-apples in observed land characteristics, to address the fact that protected areas (PAs) tend to be located on lands facing less pressure. Correcting for that location bias lowers our estimates of PAs' forest impacts by roughly half. Further, it reveals significant variation in PA impacts along development-related dimensions: for example, the PAs that are closer to roads and the PAs closer to cities have higher impact. Planners have multiple conservation and development goals, and are constrained by cost, yet still conservation planning should reflect what our results imply about future impacts of PAs.

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our ability to map forest structure, species gradient and growth rate occur in residential neighborhoods and along forest edges. Maps generated from this dissertation provide estimates of broad-scale spatial variations in forest structure, species distributions and growth to the city forest managers. The associated maps of uncertainty help managers understand the limitations of the maps and identify locations where the maps are more reliable and where more data are needed.

Allocating Fire Mitigation Funds on the Basis of the Predicted Probabilities of Forest Wildfire

Treesearch

Ronald E. McRoberts; Greg C. Liknes; Mark D. Nelson; Krista M. Gebert; R. James Barbour; Susan L. Odell; Steven C. Yaddof

2005-01-01

A logistic regression model was used with map-based information to predict the probability of forest fire for forested areas of the United States. Model parameters were estimated using a digital layer depicting the locations of wildfires and satellite imagery depicting thermal hotspots. The area of the United States in the upper 50th percentile with respect to...

Impact of anthropogenic climate change on wildfire across western US forests

PubMed Central

Williams, A. Park

2016-01-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting. PMID:27791053

U.S. Virgin Islands’ Forests, 2009

Treesearch

Thomas J. Brandeis; Jeffery A. Turner

2013-01-01

Forest area on the U.S. Virgin Islands held steady, or decreased slightly, from 2004 (46,564 acres) to 2009 (45,163 acres). There were 26,179 acres of forest on St. Croix (49.6 percent forested), 10,343 acres of forest on St. John (85.5 percent forested) and 8,641 acres of forest on St. Thomas (50.1 percent forested). We estimate there to be 85.1 million trees in the U...

Monitoring forest/non-forest land use conversion rates with annual inventory data

Treesearch

Francis A. Roesch; Paul C. Van Deusen

2012-01-01

The transitioning of land from forest to other uses is of increasing interest as urban areas expand and the world’s population continues to grow. Also of interest, but less recognized, is the transitioning of land from other uses into forest. In this paper, we show how rates of conversion from forest to non-forest and non-forest to forest can be estimated in the US...

A Model-Based Approach to Inventory Stratification

Treesearch

Ronald E. McRoberts

2006-01-01

Forest inventory programs report estimates of forest variables for areas of interest ranging in size from municipalities to counties to States and Provinces. Classified satellite imagery has been shown to be an effective source of ancillary data that, when used with stratified estimation techniques, contributes to increased precision with little corresponding increase...

Forest statistics for New Jersey--1987

Treesearch

Dawn M. DiGiovanni; Charles T. Scott; Charles T. Scott

1990-01-01

A statistical report on the third forest survey of New Jersey (1987). Findings are displayed in 66 tables containing estimates of forest area, numbers of trees, timber volume, tree biomass, and timber products output. Data are presented at two levels: state and county.

Forest statistics for Vermont: 1983 and 1997

Treesearch

Thomas S. Frieswyk; Richard H. Widmann; Richard H. Widmann

2000-01-01

A statistical report on the fifth forest inventory of Vermont 1996-1998. Findings are displayed in 86 tables containing estimates of forest area numbers of trees timber volume growth change and biomass. Data are presented at three levels: state, county, and region.

Forest Statistics for Maine, 1995

Treesearch

Douglas M. Griffith; Carol L. Alerich; Carol L. Alerich

1996-01-01

A statistical report on the fourth forest inventory of Maine conducted in 1994-96. Findings are displayed in 117 tables containing estimates of forest area numbers of trees, timber volume, and growth. Data are presented at three levels: state, geographic unit, and county.

Forest Statistics for New Jersey: 1987 and 1999

Treesearch

Douglas M. Griffith; Richard H. Widmann; Richard H. Widmann

2001-01-01

A statistical report on the fourth forest inventory of New Jersey 1999. Findings are displayed in 49 tables containing estimates of forest area numbers of trees timber volume growth change and biomass. Data are presented at two levels state and county.

Forest Statistics for Connecticut--1972 and 1985

Treesearch

David R. Dickson; Carol L. McAfee; Carol L. McAfee

1988-01-01

A statistical report on the third forest survey of Connecticut (1984). Findings are displayed in 77 tables containing estimates of forest area, numbers of trees, timber volume, tree biomass, and timber products output. Data are presented at two levels: state and county.

Forest statistics for Delaware-1972 and 1986

Treesearch

Thomas S. Frieswyk; Dawn M. DiGiovanni; Dawn M. DiGiovanni

1989-01-01

A statistical report on the third forest survey of Delaware (1986). Findings are displayed in 65 tables containing estimates of forest area, number of trees, timber volume, tree biomass, and timber products output. Data are presented at two levels: state and county.

Forest Statistics for Massachusetts--1972 and 1985

Treesearch

David R. Dickson; Carol L. McAfee; Carol L. McAfee

1988-01-01

A statistical report on the third forest survey of Massachusetts (1984). Findings are displayed in 76 tables containing estimates of forest area, numbers of trees, timber volume, tree biomass, and timber products output. Data are presented at two levels: state and county.

A Simulation Algorithm to Approximate the Area of Mapped Forest Inventory Plots

Treesearch

William A. Bechtold; Naser E. Heravi; Matthew E. Kinkenon

2003-01-01

Calculating the area of polygons associated with mapped forest inventory plots can be mathematically cumbersome, especially when computing change between inventories. We developed a simulation technique that utilizes a computer-generated dot grid and geometry to estimate the area of mapped polygons within any size circle. The technique also yields a matrix of change in...

Carbon emissions from deforestation and forest fragmentation in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Numata, Izaya; Cochrane, Mark A.; Souza, Carlos M., Jr.; Sales, Marcio H.

2011-10-01

Forest-fragmentation-related edge effects are one of the major causes of forest degradation in Amazonia and their spatio-temporal dynamics are highly influenced by annual deforestation patterns. Rapid biomass collapse due to edge effects in forest fragments has been reported in the Brazilian Amazon; however the collective impacts of this process on Amazonian carbon fluxes are poorly understood. We estimated biomass loss and carbon emissions from deforestation and forest fragmentation related to edge effects on the basis of the INPE (Brazilian National Space Research Institute) PRODES deforestation data and forest biomass volume data. The areas and ages of edge forests were calculated annually and the corresponding biomass loss and carbon emissions from these forest edges were estimated using published rates of biomass decay and decomposition corresponding to the areas and ages of edge forests. Our analysis estimated carbon fluxes from deforestation (4195 Tg C) and edge forest (126-221 Tg C) for 2001-10 in the Brazilian Amazon. The impacts of varying rates of deforestation on regional forest fragmentation and carbon fluxes were also investigated, with the focus on two periods: 2001-5 (high deforestation rates) and 2006-10 (low deforestation rates). Edge-released carbon accounted for 2.6-4.5% of deforestation-related carbon emissions. However, the relative importance of carbon emissions from forest fragmentation increased from 1.7-3.0% to 3.3-5.6% of the respective deforestation emissions between the two contrasting deforestation rates. Edge-related carbon fluxes are of increasing importance for basin-wide carbon accounting, especially as regards ongoing reducing emissions from deforestation and forest degradation (REDD) efforts in Brazilian Amazonia.

Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest

PubMed Central

Michaelian, Michael; Hogg, Edward H; Hall, Ronald J; Arsenault, Eric

2011-01-01

Drought-induced, regional-scale dieback of forests has emerged as a global concern that is expected to escalate under model projections of climate change. Since 2000, drought of unusual severity, extent, and duration has affected large areas of western North America, leading to regional-scale dieback of forests in the southwestern US. We report on drought impacts on forests in a region farther north, encompassing the transition between boreal forest and prairie in western Canada. A central question is the significance of drought as an agent of large-scale tree mortality and its potential future impact on carbon cycling in this cold region. We used a combination of plot-based, meteorological, and remote sensing measures to map and quantify aboveground, dead biomass of trembling aspen (Populus tremuloides Michx.) across an 11.5 Mha survey area where drought was exceptionally severe during 2001–2002. Within this area, a satellite-based land cover map showed that aspen-dominated broadleaf forests occupied 2.3 Mha. Aerial surveys revealed extensive patches of severe mortality (>55%) resembling the impacts of fire. Dead aboveground biomass was estimated at 45 Mt, representing 20% of the total aboveground biomass, based on a spatial interpolation of plot-based measurements. Spatial variation in percentage dead biomass showed a moderately strong correlation with drought severity. In the prairie-like, southern half of the study area where the drought was most severe, 35% of aspen biomass was dead, compared with an estimated 7% dead biomass in the absence of drought. Drought led to an estimated 29 Mt increase in dead biomass across the survey area, corresponding to 14 Mt of potential future carbon emissions following decomposition. Many recent, comparable episodes of drought-induced forest dieback have been reported from around the world, which points to an emerging need for multiscale monitoring approaches to quantify drought effects on woody biomass and carbon cycling across large areas.

Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

PubMed Central

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J.; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

Estimates of forest biomass carbon storage inLiaoning Province of Northeast China: a review and assessment.

PubMed

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha(-1) in 1980 to 31.0 Mg ha(-1) in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations.

Guam's forest resources, 2002.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Walter Grabowiecki; Bruce A. Hiserote; David. Limtiaco

2004-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 46 forested plots on the island of Guam. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide a summary of Guam...

Forest statistics for Arkansas counties - 1979

Treesearch

Renewable Resources Evaluation Research Work Unit

1979-01-01

This report tabulates information from a new forest survey of Arkansas completed in 1979 by the Renewable Resources Evaluation Research Unit of the Southern Forest Experiment Station. Forest area was estimated from aerial photos with an adjustment for ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid...

Estimates of the occurrence of dwarf mistletoe on the Deschutes National Forest.

Treesearch

Donald J. DeMars

1980-01-01

The proportion of forest area infested and of trees infected were calculated for the Deschutes National Forest by using 10-point plot inventory data. The proportion of commercial forest acres infested with dwarf mistletoe is 0.476, and the proportion of trees infected on these acres is 0.308.

Forest Resources of the United States, 1997

Treesearch

W. Brad Smith; John S. Vissage; David R. Darr; Raymond M. Sheffield

2001-01-01

Forest resource statistics from the 1987 Resources Planning Act (RPA) Assessment were updated to 1997 to provide current information on the Nation`s forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Current resource data are analyzed and...

Palau's forest resources, 2003.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Brent J. Stroud; Bruce A. Hiserote; Kashgar. Rengulbai

2007-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 54 forested plots on the islands in the Republic of Palau. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide...

Forest Resources of the United States, 2007

Treesearch

W. Brad, tech. coord. Smith; Patrick D., data coord. Miles; Charles H., map coord. Perry; Scott A., Data CD coord. Pugh

2009-01-01

Forest resource statistics from the 2000 Resources Planning Act (RPA) Assessment were updated to provide current information on the Nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Current resource data and trends are analyzed...

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

NASA Technical Reports Server (NTRS)

Fatoyinbo, Temilola E.

2010-01-01

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots

Treesearch

Karin Riley; Isaac C. Grenfell; Mark A. Finney

2016-01-01

Maps of the number, size, and species of trees in forests across the western United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical...

Can a Forest/Nonforest Change Map Improve the Precision of Forest Area, Volume, Growth, Removals, and Mortality Estimates?

Treesearch

Dale D. Gormanson; Mark H. Hansen; Ronald E. McRoberts

2005-01-01

In an extensive forest inventory, stratifications that use dual-date forest/nonforest classifications of Landsat Thematic Mapper data approximately 10 years apart are tested against similar classifications that use data from only one date. Alternative stratifications that further define edge strata as pixels adjacent to a forest/nonforest boundary are included in the...

Forest resources of Puerto Rico, 1990. Forest Service Resource Bulletin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franco, P.A.; Weaver, P.L.; Eggen-McIntosh, S.

1997-10-01

The prinicipal findings of the second forest survey of Puerto Rico (1990) and changes that have occurred since the survey was established in 1980 are presented. The forest inventory estimates describe the timber resource found within the potential commercial region designated in the first survey. The timber resource addressed consists primarily of regrown areas on abandoned pastures and cropland, including coffee production areas. The status and trends of the timber resource are presented for the two Life Zones occurring in the commercial region, as well as for various forest classes, which are based on stand history and origin. Topics dicussedmore » include forest area, timberland area, basal area, species composition, timber volume, growing-stock volume, and sawtimber volume. results of the 1990 survey are promising, showing inceases in numbers of trees across all diamater classes and substantial increases in volume. These trends offer evidence that Puerto Rico`s forests are continuing to recover following a dramatic decline of the late 19th and early 20th centuries.« less

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

PubMed

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1-98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

PubMed Central

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

The impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Williams, P.; Abatzoglou, J. T.

2016-12-01

Increased forest fire activity across the western United States (US) in recent decades has contributed to widespread forest mortality, carbon emissions, periods of degraded air quality, and substantial fire suppression expenditures. The increase in forest fire activity has likely been enabled by a number of factors including the legacy of fire suppression and human settlement, changes in suppression policies, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western US. Anthropogenic increases in temperature and vapor pressure deficit have significantly enhanced fuel aridity across western US forests over the past several decades. Comparing observational climate records to records recalculated after removal of modeled anthropogenic trends, we find that anthropogenic climate change accounted for approximately 55% of observed increases in the eight-metric mean fuel aridity during 1979-2015 across western US forests. This implicates anthropogenic climate change as an important driver of observed increases in fuel aridity, and also highlights the importance of natural multi-decadal climate variability in influencing trends in forest fire potential on the timescales of human lives. Based on a very strong (R2 = 0.76) and mechanistically reasonable relationship between interannual variability in the eight-metric mean fuel aridity and forest-fire area in the western US, we estimate that anthropogenic increases in fuel aridity contributed to an additional 4.2 million ha (95% confidence range: 2.7-6.5 million ha) of forest fire area during 1984-2015, nearly doubling the total forest fire area expected in the absence of anthropogenic climate change. The relationship between annual forest fire area and fuel aridity is exponential and the proportion of total forest area burned in a given year has grown rapidly over the past 32 years. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a chronic driver of increased forest fire activity and should continue to do so where fuels are not limiting.

Forest statistics for Rhode Island--1972 and 1985

Treesearch

David R. Dickson; Carol L. McAfee; Carol L. McAfee

1988-01-01

A statistical report on the third forest survey of Rhode Island (1984). Findings are displayed in 77 tables containing estimates of forest area, numbers of trees, timber volume, tree biomass, and timber products output. Data are presented at two levels: state and county.

Forest statistics for New Hampshire; 1983 and 1997

Treesearch

Thomas S. Frieswyk; Richard H. Widmann; Richard H. Widmann

2000-01-01

A statistical report on the fifth forest inventory of New Hampshire 1996-1998. Findings are displayed in 86 tables containing estimates of forest area numbers of trees timber volume growth change and biomass. Data are presented at three levels; state, county, and region.

Forest statistics for Massachusetts: 1985 and 1998

Treesearch

Carol L. Alerich; Carol L. Alerich

2000-01-01

A statistical report on the fourth forest inventory of Massachusetts (1997-1998.) Findings are dispayed in 67 tables containing estimates of forest area numbers of trees, wildlife habitat, timber volume, growth, change, and biomass. Data are presented at two levels: state and county.

Forest Statistics for Kentucky - 1975 and 1988

Treesearch

Carol L. Alerich

1990-01-01

A statistical report on the fourth forest survey of Kentucky (1988). Findings are displayed in 204 tables containing estimates of forest area, number of trees, timber volume, tree biomass, and timber products output. Data are presented at three levels: state, geographic unit, and county.

Forest statistics for Connecticut: 1985 and 1998

Treesearch

Carol L. Alerich; Carol L. Alerich

2000-01-01

A statistical report on the fourth forest inventory of Connecticut 1997-1998. Findings are displayed in 67 tables containing estimates of forest area numbers of trees wildlife habitat timber volume growth change and biomass Data are presented at two levels: state and county.

Forest statistics for Maryland--1976 and 1986

Treesearch

Thomas S. Frieswyk; Dawn M. DiGiovanni; Dawn M. DiGiovanni

1988-01-01

A statistical report on the fourth forest survey of Maryland (1986). Findings are displayed in 115 tables containing estimates of forest area, numbers of trees, timber volume, tree biomass, and timber products output. Data are presented at three levels: state, geographic unit, and county.

The effect of land cover change to the biomass value in the forest region of West Java province

NASA Astrophysics Data System (ADS)

Rahayu, M. I.; Waryono, T.; Rokhmatullah; Shidiq, I. P. A.

2018-05-01

Due to the issue of climate change as a public concern, information of carbon stock availability play an important role to describe the condition of forest ecosystems in the context of sustainable forest management. This study has the objective to identify land cover change during 2 decades (1996 – 2016) in the forest region and estimate the value of forest carbon stocks in west Java Province using remote sensing imagery. The land cover change information was obtained by visually interpreting the Landsat image, while the estimation of the carbon stock value was performed using the transformation of the NDVI (Normalized Difference Vegetation Index) which extracted from Landsat image. Biomass value is calculated by existing allometric equations. The results of this study shows that the forest area in the forest region of West Java Province have decreased from year to year, and the estimation value of forest carbon stock in the forest region of West Java Province also decreased from year to year.

Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

NASA Technical Reports Server (NTRS)

Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

1995-01-01

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR images in synoptic modes are used to generate the parameter maps. The maps are then combined to generate mosaic maps over the BOREAS modeling grid.

A strategic assessment of forest biomass and fuel reduction treatments in western states

Treesearch

Bob Rummer; Jeff Prestemon; Dennis May; Pat Miles; John Vissage; Ron McRoberts; Greg Liknes; Wayne D. Shepperd; Dennis Ferguson; William Elliot; Sue Miller; Steve Reutebuch; Jamie Barbour; Jeremy Fried; Bryce Stokes; Edward Bilek; Ken Skog

2003-01-01

In the 15 western states there are at least 28 million acres of forest that could benefit from some type of mechanical treatment to reduce hazardous fuel loading. It is estimated that about 60 percent of this area could be operationally accessible for treatment with a total biomass treatment volume of 345 million bone dry tons (bdt). Two-thirds of this forest area is...

Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions

Treesearch

Barry Tyler Wilson

2015-01-01

This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...

Accelerated deforestation in the humid tropics from the 1990s to the 2000s

NASA Astrophysics Data System (ADS)

Kim, Do-Hyung; Sexton, Joseph O.; Townshend, John R.

2015-05-01

Using a consistent, 20 year series of high- (30 m) resolution, satellite-based maps of forest cover, we estimate forest area and its changes from 1990 to 2010 in 34 tropical countries that account for the majority of the global area of humid tropical forests. Our estimates indicate a 62% acceleration in net deforestation in the humid tropics from the 1990s to the 2000s, contradicting a 25% reduction reported by the United Nations Food and Agriculture Organization Forest Resource Assessment. Net loss of forest cover peaked from 2000 to 2005. Gross gains accelerated slowly and uniformly between 1990-2000, 2000-2005, and 2005-2010. However, the gains were overwhelmed by gross losses, which peaked from 2000 to 2005 and decelerated afterward. The acceleration of humid tropical deforestation we report contradicts the assertion that losses decelerated from the 1990s to the 2000s.

Gis-Based Multi-Criteria Decision Analysis for Forest Fire Risk Mapping

NASA Astrophysics Data System (ADS)

Akay, A. E.; Erdoğan, A.

2017-11-01

The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81 % of the area was of extreme risk, while 25.81 % was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.

QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee Spangler; Lee A. Vierling; Eva K. Stand

2012-04-01

Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 acrossmore » {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density between the 2003 and 2009 did not affect the biomass estimates. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of our study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.« less

LEAF AREA INDEX (LAI) CHANGE DETECTION ON LOBLOLLY PINE FOREST STANDS WITH COMPLETE UNDERSTORY REMOVAL

EPA Science Inventory

The confounding effect of understory vegetation contributions to satellite derived
estimates of leaf area index (LAI) was investigated on two loblolly pine (Pinus taeda) forest stands located in the southeastern United States. Previous studies have shown that understory can a...

LEAF AREA INDEX (LAI) CHANGE DETECTION ON LOBLOLLY PINE FOREST STANDS WITH COMPLETE UNDERSTORY REMOVAL

EPA Science Inventory

The confounding effect of understory vegetation contributions to satellite derived estimates of leaf area index (LAI) was investigated on two loblolly pine forest stands located in the southeastern United States. Previous studies have shown that understory can account from 0-40%...

Using Landsat to Diagnose Trends in Disturbance Magnitude Across the National Forest System

NASA Astrophysics Data System (ADS)

Hernandez, A. J.; Healey, S. P.; Stehman, S. V.; Ramsey, R. D.

2014-12-01

The Landsat archive is increasingly being used to detect trends in the occurrence of forest disturbance. Beyond information about the amount of area affected, forest managers need to know if and how disturbance severity is changing. For example, the United States National Forest System (NFS) has developed a comprehensive plan for carbon monitoring, which requires a detailed temporal mapping of forest disturbance magnitudes across 75 million hectares. To meet this need, we have prepared multitemporal models of percent canopy cover that were calibrated with extensive field data from the USFS Forest Inventory and Analysis Program (FIA). By applying these models to pre- and post-event Landsat images at the site of known disturbances, we develop maps showing first-order estimates of disturbance magnitude on the basis of cover removal. However, validation activities consistently show that these initial estimates under-estimate disturbance magnitude. We have developed an approach, which quantifies this under-prediction at the landscape level and uses empirical validation data to adjust change magnitude estimates derived from initial disturbance maps. In an assessment of adjusted magnitude trends of NFS' Northern Region from 1990 to the present, we observed significant declines since 1990 (p < .01) in harvest magnitude, likely related to known reduction of clearcutting practices in the region. Fire, conversely, did not show strongly significant trends in magnitude, despite an increase in the overall area affected. As Landsat is used to provide increasingly precise maps of the timing and location of historical forest disturbance, a logical next step is to use the archive to generate widely interpretable and objective estimates of disturbance magnitude.

Multi-stage approach to estimate forest biomass in degraded area by fire and selective logging

NASA Astrophysics Data System (ADS)

Santos, E. G.; Shimabukuro, Y. E.; Arai, E.; Duarte, V.; Jorge, A.; Gasparini, K.

2017-12-01

The Amazon forest has been the target of several threats throughout the years. Anthropogenic disturbances in the region can significantly alter this environment, affecting directly the dynamics and structure of tropical forests. Monitoring these threats of forest degradation across the Amazon is of paramount to understand the impacts of disturbances in the tropics. With the advance of new technologies such as Light Detection and Ranging (LiDAR) the quantification and development of methodologies to monitor forest degradation in the Amazon is possible and may bring considerable contributions to this topic. The objective of this study was to use remote sensing data to assess and estimate the aboveground biomass (AGB) across different levels of degradation (fire and selective logging) using multi-stage approach between airborne LiDAR and orbital image. The study area is in the northern part of the state of Mato Grosso, Brazil. It is predominantly characterized by agricultural land and remnants of the Amazon Forest intact and degraded by either anthropic or natural reasons (selective logging and/or fire). More specifically, the study area corresponds to path/row 226/69 of OLI/Landsat 8 image. With a forest mask generated from the multi-resolution segmentation, agriculture and forest areas, forest biomass was calculated from LiDAR data and correlated with texture images, vegetation indices and fraction images by Linear Spectral Unmixing of OLI/Landsat 8 image and extrapolated to the entire scene 226/69 and validated with field inventories. The results showed that there is a moderate to strong correlation between forest biomass and texture data, vegetation indices and fraction images. With that, it is possible to extract biomass information and create maps using optical data, specifically by combining vegetation indices, which contain forest greening information with texture data that contains forest structure information. Then it was possible to extrapolate the biomass to the entire scene (226/69) from the optical data and to obtain an overview of the biomass distribution throughout the area.

Timberland resources of the Kenai Peninsula, Alaska, 1987.

Treesearch

Willem W.S. van Hees; Frederic R. Larson

1991-01-01

The 1987 inventory of the forest resources of the Kenai Peninsula was designed to assess the impact of the spruce beetle (Dendroctonus rufipennis (Kirby)) on the timberland component of the forest resource. Estimates of timberland area, volumes of timber, and growth and mortality of timber were developed. These estimates of timber resource...

Mapping Forest Height in Gabon Using UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Lidar Fusion

NASA Astrophysics Data System (ADS)

Simard, M.; Denbina, M. W.

2017-12-01

Using data collected by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Land, Vegetation, and Ice Sensor (LVIS) lidar, we have estimated forest canopy height for a number of study areas in the country of Gabon using a new machine learning data fusion approach. Using multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data collected by UAVSAR, forest heights can be estimated using the random volume over ground model. In the case of multi-baseline UAVSAR data consisting of many repeat passes with spatially separated flight tracks, we can estimate different forest height values for each different image pair, or baseline. In order to choose the best forest height estimate for each pixel, the baselines must be selected or ranked, taking care to avoid baselines with unsuitable spatial separation, or severe temporal decorrelation effects. The current baseline selection algorithms in the literature use basic quality metrics derived from the PolInSAR data which are not necessarily indicative of the true height accuracy in all cases. We have developed a new data fusion technique which treats PolInSAR baseline selection as a supervised classification problem, where the classifier is trained using a sparse sampling of lidar data within the PolInSAR coverage area. The classifier uses a large variety of PolInSAR-derived features as input, including radar backscatter as well as features based on the PolInSAR coherence region shape and the PolInSAR complex coherences. The resulting data fusion method produces forest height estimates which are more accurate than a purely radar-based approach, while having a larger coverage area than the input lidar training data, combining some of the strengths of each sensor. The technique demonstrates the strong potential for forest canopy height and above-ground biomass mapping using fusion of PolInSAR with data from future spaceborne lidar missions such as the upcoming Global Ecosystems Dynamics Investigation (GEDI) lidar.

Forest statistics for Rhode Island: 1985 and 1998

Treesearch

Carol L. Alerich; Carol L. Alerich

2000-01-01

A statistical report on the fourth forest inventory of Rhode Island (1997-1998.) Findings are displayed in 67 tables containing estimates of forest area numbers of trees, wildlife habitat, timber, volume, growth, change and biomass. Data are presented at two levels: state and county.

Forest statistics for Maryland: 1986 and 1999

Treesearch

Thomas S. Frieswyk

2001-01-01

A statistical report on the fifth forest inventory of Maryland (1998-1999). Findings are displayed in 109 tables containing estimates of forest area, numbers of trees, wildlife habitat, timber volume, growth, change, and biomass. Data are presented at three levels: state, geographic unit and county.

Forest statistics for Ohio, 1991

Treesearch

Douglas M. Griffith; Dawn M. DiGiovanni; Teresa L. Witzel; Eric H. Wharton

1993-01-01

A statistical report on the fourth forest inventory of Ohio conducted in 1988-90. Findings are displayed in tables containing estimates of forest area, number of trees, sawtimber volume, growing-stock volume, biomass, growth, and removals. Data are presented at three levels: state, geographic unit, and county.

Forest statistics for West Virginia--1975 and 1989

Treesearch

Dawn M. Di Giovanni; Dawn M. Di Giovanni

1990-01-01

A statistical report on the fourth forest survey of West Virginia (1989). Findings are displayed in 119 tables containing estimates of forest area, number of trees, timber volume, tree biomass, and timber products output. Data are presented at three levels: state, geographic unit, and county.

The affection of boreal forest changes on imbalance of Nature (Invited)

NASA Astrophysics Data System (ADS)

Tana, G.; Tateishi, R.

2013-12-01

Abstract: The balance of nature does not exist, and, perhaps, never has existed [1]. In other words, the Mother Nature is imbalanced at all. The Mother Nature is changing every moment and never returns to previous condition. Because of the imbalance of nature, global climate has been changing gradually. To reveal the imbalance of nature, there is a need to monitor the dynamic changes of the Earth surface. Forest cover and forest cover change have been grown in importance as basic variables for modelling of global biogeochemical cycles as well as climate [2]. The boreal area contains 1/3 of the earth's trees. These trees play a large part in limiting harmful greenhouse gases by aborbing much of the earth's carbon dioxide (CO2) [3]. The boreal area mainly consists of needleleaf evergreen forest and needleleaf deciduous forest. Both of the needleleaf evergreen forest and needleleaf deciduous forest play the important roles on the uptake of CO2. However, because of the dormant period of needleleaf evergreen forest are shorter than that of needleleaf deciduous forest, needleleaf evergreen forest makes a greater contribution to the absorbtion of CO2. Satellite sensor because of its ability to observe the Earth continuously, can provide the opportunity to monitor the dynamic changes of the Earth. In this study, we used the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data to monitor the dynamic change of boreal forest area which are mainly consist from needleleaf evergreen forest and needleleaf deciduous forest during 2003-2012. Three years MODIS data from the year 2003, 2008 and 2012 were used to detect the forest changed area. A hybrid change detection method which combines the threshold method and unsupervised classification method was used to detect the changes of forest area. In the first step, the difference of Normalized Difference Vegetation Index (NDVI) of the three years were calculated and were used to extract the changed areas by the threshold method. In the second step, the unsupervised classification method was used to classify and analyze detected change areas derived from the first step. Finally, the changed area were validated using the traning data collected for the three years. The validation result revealed that the forest in the study area has undergone the area and type changes during 2003-2012. The detailed procedure will be presented in the meeting. References: [1] Elton, C.S. (1930). Animal Ecology and Evolution. New York, Oxford University Press. [2] Potapov, P., Hansen, M. C., Stehman, S. V., Loveland, T. R., Pittman, K. (2008). Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss, Remote Sensing of Environment, 112, 3708-3719. [3] Houghton, R. A. (2003). Why are estimates of the terrestrial carbon balance so different? Global Change Biology, 9, 500-509.

Analyzing riparian forest cover changes along the Firniz River in the Mediterranean City of Kahramanmaras in Turkey.

PubMed

Akay, Abdullah E; Sivrikaya, Fatih; Gulci, Sercan

2014-05-01

Riparian forests adjacent to surface water are important transitional zones which maintain and enrich biodiversity and ensure the sustainability in a forest ecosystem. Also, riparian forests maintain water quality, reduce sediment delivery, enhance habitat areas for aquatic life and wildlife, and provide ecological corridors between the upland and the downstream. However, the riparian ecosystems have been degraded mainly due to human development, forest operations, and agricultural activities. In order to evaluate the impacts of these factors on riparian forests, it is necessary to estimate trends in forest cover changes. This study aims to analyze riparian forest cover changes along the Firniz River located in Mediterranean city of Kahramanmaras in Turkey. Changes in riparian forest cover from 1989 to 2010 have been determined by implementing supervised classification method on a series of Landsat TM imagery of the study area. The results indicated that the classification process applied on 1989 and 2010 images provided overall accuracy of 80.08 and 75 %, respectively. It was found that the most common land use class within the riparian zone was productive forest, followed by degraded forest, agricultural areas, and other land use classes. The results also indicated that the areas of degraded forest and forest openings increased, while productive forest and agricultural areas decreased between the years of 1989 and 2010. The amount of agricultural areas decreased due to the reduction in the population of rural people. According to these results, it can be concluded that special forest management and operation techniques should be implemented to restore the forest ecosystem in riparian areas.

Predicting future forestland area: a comparison of econometric approaches.

Treesearch

SoEun Ahn; Andrew J. Plantinga; Ralph J. Alig

2000-01-01

Predictions of future forestland area are an important component of forest policy analyses. In this article, we test the ability of econometric land use models to accurately forecast forest area. We construct a panel data set for Alabama consisting of county and time-series observation for the period 1964 to 1992. We estimate models using restricted data sets-namely,...

Modeling long-term suspended-sediment export from an undisturbed forest catchment

NASA Astrophysics Data System (ADS)

Zimmermann, Alexander; Francke, Till; Elsenbeer, Helmut

2013-04-01

Most estimates of suspended sediment yields from humid, undisturbed, and geologically stable forest environments fall within a range of 5 - 30 t km-2 a-1. These low natural erosion rates in small headwater catchments (≤ 1 km2) support the common impression that a well-developed forest cover prevents surface erosion. Interestingly, those estimates originate exclusively from areas with prevailing vertical hydrological flow paths. Forest environments dominated by (near-) surface flow paths (overland flow, pipe flow, and return flow) and a fast response to rainfall, however, are not an exceptional phenomenon, yet only very few sediment yields have been estimated for these areas. Not surprisingly, even fewer long-term (≥ 10 years) records exist. In this contribution we present our latest research which aims at quantifying long-term suspended-sediment export from an undisturbed rainforest catchment prone to frequent overland flow. A key aspect of our approach is the application of machine-learning techniques (Random Forest, Quantile Regression Forest) which allows not only the handling of non-Gaussian data, non-linear relations between predictors and response, and correlations between predictors, but also the assessment of prediction uncertainty. For the current study we provided the machine-learning algorithms exclusively with information from a high-resolution rainfall time series to reconstruct discharge and suspended sediment dynamics for a 21-year period. The significance of our results is threefold. First, our estimates clearly show that forest cover does not necessarily prevent erosion if wet antecedent conditions and large rainfalls coincide. During these situations, overland flow is widespread and sediment fluxes increase in a non-linear fashion due to the mobilization of new sediment sources. Second, our estimates indicate that annual suspended sediment yields of the undisturbed forest catchment show large fluctuations. Depending on the frequency of large events, annual suspended-sediment yield varies between 74 - 416 t km-2 a-1. Third, the estimated sediment yields exceed former benchmark values by an order of magnitude and provide evidence that the erosion footprint of undisturbed, forested catchments can be undistinguishable from that of sustainably managed, but hydrologically less responsive areas. Because of the susceptibility to soil loss we argue that any land use should be avoided in natural erosion hotspots.

Estimation of the Forest Fire Risk in Indonesia based on Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Suzuki, H.; Takahashi, Y.; Hashimoto, A.; Akita, M.; Hasegawa, Y.; Ogino, Y.; Naruse, N.; Takahashi, Y.

2016-12-01

To minimize forest fires in tropical area is extremely important, because the fire has a large impact on global warming, biodiversity, and human society. In the previous study, Shimada and Ishibashi monitored the ground-water lever from the value of Normalized Difference Vegetation Index (NDVI) obtained in Kalimantan Island to predict where the forest fires will happen. We have developed a method to map the forest fire risk by calculating the value of Modified Soil Adjusted Vegetation Index 2 (MSAVI2). Moreover, we investigated the relation between the distance from a road as an artificial factor and the occurrence of the fire.First, calculating the MSAVI2 from Landsat 7 and 8 images of August, 2015 around Martapura in South Sumatra, Indonesia, we mapped the area where the plants were stressed. Next, we checked the degrees of matching between the area of low MSAVI2 and the forest fire points.As a result, half of the fires happened in the area having the MSAVI2 values of 0.20 to 0.35. When we focused on only the area which is over 5 kilometers far from a road, the degrees of matching became higher; it rose up to 62 percent.Those results indicate that the fire risks relate to the dry area calculated as low MSAVI2 in the case with less human activities. We need to consider an effect of artificial factors to estimate the whole risk of forest fire.In conclusion, the map of forest fire risk by calculating the value of MSAVI2 is applicable to an area with less artificial factor, while we have to take the effect of artificial fire factor into the consideration.

An assessment of forest cover trends in South and North Korea, from 1980 to 2010.

PubMed

Engler, Robin; Teplyakov, Victor; Adams, Jonathan M

2014-01-01

It is generally believed that forest cover in North Korea has undergone a substantial decrease since 1980, while in South Korea, forest cover has remained relatively static during that same period of time. The United Nations Food and Agriculture Organization (FAO) Forest Resources Assessments--based on the reported forest inventories from North and South Korea--suggest a major forest cover decrease in North Korea, but only a slight decrease in South Korea during the last 30 years. In this study, we seek to check and validate those assessments by comparing them to independently derived forest cover maps compiled for three time intervals between 1990 and 2010, as well as to provide a spatially explicit view of forest cover change in the Korean Peninsula since the 1990s. We extracted tree cover data for the Korean Peninsula from existing global datasets derived from satellite imagery. Our estimates, while qualitatively supporting the FAO results, show that North Korea has lost a large number of densely forested areas, and thus in this sense has suffered heavier forest loss than the FAO assessment suggests. Given the limited time interval studied in our assessment, the overall forest loss from North Korea during the whole span of time since 1980 may have been even heavier than in our estimate. For South Korea, our results indicate that the forest cover has remained relatively stable at the national level, but that important variability in forest cover evolution exists at the regional level: While the northern and western provinces show an overall decrease in forested areas, large areas in the southeastern part of the country have increased their forest cover.

Remote estimation of crown size and tree density in snowy areas

NASA Astrophysics Data System (ADS)

Kishi, R.; Ito, A.; Kamada, K.; Fukita, T.; Lahrita, L.; Kawase, Y.; Murahashi, K.; Kawamata, H.; Naruse, N.; Takahashi, Y.

2017-12-01

Precise estimation of tree density in the forest leads us to understand the amount of carbon dioxide fixed by plants. Aerial photographs have been used to measure the number of trees. Campaign using aircraft, however, is expensive ( $50,000/1 campaign flight) and the research area is limited in drone. In addition, previous studies estimating the density of trees from aerial photographs have been performed in the summer, so there was a gap of 15% in the estimation due to the overlapping of the leaves. Here, we have proposed a method to accurately estimate the number of forest trees from the satellite images of snow-covered deciduous forest area, using the ratio of branches to snow. The advantages of our method are as follows; 1) snow area could be excluded easily due to the high reflectance, 2) tree branches are small overlapping compared to leaves. Although our method can use only in the snowfall region, the area covered with snow in the world becomes more than 12,800,000 km2. Our proposition should play an important role in discussing global warming. As a test area, we have chosen the forest near Mt. Amano in Iwate prefecture in Japan. First, we made a new index of (Band1-Band5)/(Band1+Band5), which will be suitable to distinguish between the snow and the tree trunk using the corresponding spectral reflection data. Next, the index values of changing the ratio in 1% increments were listed. From the satellite image analysis at 4 points, the ratio of snow to tree trunk showed the following values, I:61%, II:65%, III:66% and IV:65%. To confirm the estimation, we used the aerial photograph from Google earth; the rate was I:42.05%, II:48.89%, III:50.64%, IV:49.05%, respectively. There is a correlation between the numerical values of both, but there are differences. We will discuss in detail at this point, focusing on the effect of shadows.

Forest Resources of the United States, 2012: a technical document supporting the Forest Service 2010 update of the RPA Assessment

Treesearch

Sonja N. Oswalt; W. Brad Smith; Patrick D. Miles; Scott A. Pugh

2014-01-01

Forest resource statistics from the 2010 Resources Planning Act (RPA) Assessment were updated to provide current information on the Nation's forests as a baseline for the 2015 national assessment. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State...

Minnesota's forest resources in 2002

Treesearch

Patrick D. Miles; Gary J. Brand; Manfred E. Mielke

2003-01-01

Results of the combined 1999, 2000, 2001, and 2002 annual forest inventories of Minesota show that 16.3 million acres or 32 percent of the total land area is forested. The estimate of total all live tree volume on forest land is 17.6 billion cubic feet or approximately 1,080 cubic feet per acre. Just over 15.0 million acres of forest land in Minnesota is classified...

Minnesota's forest resources in 2001

Treesearch

Patrick D. Miles; Manfred E. Mielke; Gary J. Brand

2003-01-01

Results of the combined 1999, 2000, and 2001 annual forest inventories of Minnesota show that 16.3 million acres or 32 percent of the total land area is forested. The estimate of total all live tree volume on forest land is 17.4 billion cubic feet or approximately 1,068 cubic feet per acre. Nearly 15.0 million acres of forest land in Minnesota are classified as...

Federated States of Micronesia's forest resources, 2006

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 73 forested field plots on the islands of Kosrae, Chuuk, Pohnpei, and Yap in the Federated States of Micronesia (FSM). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden

2005-01-01

Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...

How to estimate forest carbon for large areas from inventory data

Treesearch

James E. Smith; Linda S. Heath; Peter B. Woodbury

2004-01-01

Carbon sequestration through forest growth provides a low-cost approach for meeting state and national goals to reduce net accumulations of atmospheric carbon dioxide. Total forest ecosystem carbon stocks include "pools" in live trees, standing dead trees, understory vegetation, down dead wood, forest floor, and soil. Determining the level of carbon stocks in...

Kentucky's forests, 2004

Treesearch

Jeffery A. Turner; Christopher M. Oswalt; James L. Chamberlain; Roger C. Conner; Tony G. Johnson; Sonja N. Oswalt; KaDonna C. Randolph

2008-01-01

Forest land area in the Commonwealth of Kentucky amounted to 11.97 million acres, including 11.6 million acres of timberland. Over 110 different species, mostly hardwoods, account for an estimated 21.2 billion cubic feet of all live tree volume. Hardwood forest types occupy 85 percent of Kentucky’s timberland, and oak-hickory is the dominant forest-type group...

Batch reporting of forest inventory statistics using the EVALIDator

Treesearch

Patrick D. Miles

2015-01-01

The EVALIDator Web application, developed in 2007, provides estimates and sampling errors of forest statistics (e.g., forest area, number of trees, tree biomass) from data stored in the Forest Inventory and Analysis database. In response to user demand, new features have been added to the EVALIDator. The most recent additions are 1) the ability to generate multiple...

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Seasonal LAI in slash pine estimated with LANDSAT TM

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.; Gholz, Henry L.

1990-01-01

The leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LAI seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values derived using LANDSAT Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on 3 dates. Linear relationships existed between NDVI and LAI with R(sup 2) values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March, 1989, respectively. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass. Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6 percent of the mean LAI. This demonstrates the potential use of LANDSAT TM data for studying seasonal dynamics in forest canopies.

Application of Forest Inventory and Analysis (FIA) data to estimate the amount of old growth forest and snag density in the Northern Region of the National Forest System

Treesearch

Raymond L. Czaplewski

2004-01-01

This report discusses valid use of data produced by the Forest Service?s Forest Inventory and Analysis (FIA) program and used by the Northern Region of the National Forest System to analyze the compliance of individual National Forests with their Standards and Guidelines. It emphasizes use of FIA data on snag density and the percentage of forest area that meets the...

Height and Biomass of Mangroves in Africa from ICEsat/GLAS and SRTM

NASA Technical Reports Server (NTRS)

Fatoyinbo, Temilola E.; Simard, Marc

2012-01-01

The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and SRTM data is well suited for vegetation 3-D mapping on a continental scale.

Research on Inversion Models for Forest Height Estimation Using Polarimetric SAR Interferometry

NASA Astrophysics Data System (ADS)

Zhang, L.; Duan, B.; Zou, B.

2017-09-01

The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can't estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.

Accuracy and equivalence testing of crown ratio models and assessment of their impact on diameter growth and basal area increment predictions of two variants of the Forest Vegetation Simulator

Treesearch

Laura P. Leites; Andrew P. Robinson; Nicholas L. Crookston

2009-01-01

Diameter growth (DG) equations in many existing forest growth and yield models use tree crown ratio (CR) as a predictor variable. Where CR is not measured, it is estimated from other measured variables. We evaluated CR estimation accuracy for the models in two Forest Vegetation Simulator variants: the exponential and the logistic CR models used in the North...

Dry Season Rainfall Anomalies due to Deforestation in Northern Mesoamerica: Implications for Forest Sustainability

NASA Astrophysics Data System (ADS)

Welch, R. M.; Ray, D. K.; Lawton, R. O.; Nair, U.

2005-12-01

In the region stretching between Mexico and Panama, the proposed Mesoamerican Biological Corridor (MBC) is an ambitious effort to stem and turn back the erosion of biodiversity in one of the world's biologically richest regions by connecting large existing parks and reserves with new protected areas by means of an extensive network of biological corridors. The success of this effort will depend in part on the ability of the connecting corridors to provide adequate habitats permitting the sustainability of some populations and the migratory movements of others. Ideally these connecting corridors would contain the biological communities which were originally present. Currently, however, many of these connecting corridors do not contain their original forest, but are instead occupied by agricultural landscapes containing croplands, grasslands and degraded woodlands. The forest types in northern Mesoamerica generally are those that require dry season rainfall for their survival, and it is not clear whether current environmental and climatological conditions are sufficient to maintain existing forests and regenerate the pristine forests in the deforested patches. Hourly climatological rainfall rates have been averaged for the time period of 1961 to 1997 at 266 stations in Guatemala and adjacent areas. These climatological rainfall rates have been segregated for forested and deforested regions of each of the major Holdridge life zones. Dry season cloud frequency of occurrences derived from GOES satellite imagery then are. correlated with the March climalogical data in order to generate regression estimates of current local rainfall. Differences between estimated current rainfall and historical values define regions under increased dry season water stress. In general dry season rainfall in March is markedly lower in deforested areas than in forested areas of the same life zone for most of the Holdridge life zones. In some deforested areas within the Holdridge wet forest life zones, estimated March rainfall deficits are >25 mm. Dry season deforested habitats tend to have higher daytime temperatures, are less cloudy, have lower estimated soil moisture and lower values of Normalized Difference Vegetation Index (NDVI) than do forested habitats in the same life zone. The result is hotter and drier air over deforested regions, with lower values of cloud formation and precipitation. The data suggest that deforestation is locally intensifying the dry season and increasing the risk of fire, especially for the long corridor connecting regions. In addition, forest regeneration in some parts of the MBC may not result in second-growth forest that is characteristic of that life zone but rather in forest regeneration more typical of drier conditions. The extent to which this would influence the conservation utility of any given corridor depends upon the ecological requirements of the organisms concerned.

36 CFR 223.229 - Contents of prospectus.

Code of Federal Regulations, 2011 CFR

2011-07-01

....229 Section 223.229 Parks, Forests, and Public Property FOREST SERVICE, DEPARTMENT OF AGRICULTURE SALE... sale of special forest products shall include the following: (a) The minimum acceptable value or unit... downpayment; (d) The location and area of the sale, including acreage; (e) The estimated volumes, quality...

Forest Statistics for New York 1980 and 1993

Treesearch

Carol L. Alerich; David A. Drake; David A. Drake

1995-01-01

A statistical report on the fourth forest inventory of New York 1991- 1994. Findings are displayed in 155 tables containing estimates of forest area numbers of trees wildlife habitat timber volume growth change and biomass. Data are presented at three levels; state, geographic unit, and county.

Distribution and Source Apportionment of Polycyclic Aromatic Hydrocarbons (PAHs) in Forest Soils from Urban to Rural Areas in the Pearl River Delta of Southern China

PubMed Central

Xiao, Yihua; Tong, Fuchun; Kuang, Yuanwen; Chen, Bufeng

2014-01-01

The upper layer of forest soils (0–20 cm depth) were collected from urban, suburban, and rural areas in the Pearl River Delta of Southern China to estimate the distribution and the possible sources of polycyclic aromatic hydrocarbons (PAHs). Total concentrations of PAHs in the forest soils decreased significantly along the urban–suburban–rural gradient, indicating the influence of anthropogenic emissions on the PAH distribution in forest soils. High and low molecular weight PAHs dominated in the urban and rural forest soils, respectively, implying the difference in emission sources between the areas. The values of PAH isomeric diagnostic ratios indicated that forest soil PAHs were mainly originated from traffic emissions, mixed sources and coal/wood combustion in the urban, suburban and rural areas, respectively. Principal component analysis revealed that traffic emissions, coal burning and residential biomass combustion were the three primary contributors to forest soil PAHs in the Pearl River Delta. Long range transportation of PAHs via atmosphere from urban area might also impact the PAHs distribution in the forest soils of rural area. PMID:24599040

An application of remote sensing data in mapping landscape-level forest biomass for monitoring the effectiveness of forest policies in northeastern China.

PubMed

Wang, Xinchuang; Shao, Guofan; Chen, Hua; Lewis, Bernard J; Qi, Guang; Yu, Dapao; Zhou, Li; Dai, Limin

2013-09-01

Monitoring the dynamics of forest biomass at various spatial scales is important for better understanding the terrestrial carbon cycle as well as improving the effectiveness of forest policies and forest management activities. In this article, field data and Landsat image data acquired in 1999 and 2007 were utilized to quantify spatiotemporal changes of forest biomass for Dongsheng Forestry Farm in Changbai Mountain region of northeastern China. We found that Landsat TM band 4 and Difference Vegetation Index with a 3 × 3 window size were the best predictors associated with forest biomass estimations in the study area. The inverse regression model with Landsat TM band 4 predictor was found to be the best model. The total forest biomass in the study area decreased slightly from 2.77 × 10(6) Mg in 1999 to 2.73 × 10(6) Mg in 2007, which agreed closely with field-based model estimates. The area of forested land increased from 17.9 × 10(3) ha in 1999 to 18.1 × 10(3) ha in 2007. The stabilization of forest biomass and the slight increase of forested land occurred in the period following implementations of national forest policies in China in 1999. The pattern of changes in both forest biomass and biomass density was altered due to different management regimes adopted in light of those policies. This study reveals the usefulness of the remote sensing-based approach for detecting and monitoring quantitative changes in forest biomass at a landscape scale.

Forest above ground biomass estimation and forest/non-forest classification for Odisha, India, using L-band Synthetic Aperture Radar (SAR) data

NASA Astrophysics Data System (ADS)

Suresh, M.; Kiran Chand, T. R.; Fararoda, R.; Jha, C. S.; Dadhwal, V. K.

2014-11-01

Tropical forests contribute to approximately 40 % of the total carbon found in terrestrial biomass. In this context, forest/non-forest classification and estimation of forest above ground biomass over tropical regions are very important and relevant in understanding the contribution of tropical forests in global biogeochemical cycles, especially in terms of carbon pools and fluxes. Information on the spatio-temporal biomass distribution acts as a key input to Reducing Emissions from Deforestation and forest Degradation Plus (REDD+) action plans. This necessitates precise and reliable methods to estimate forest biomass and to reduce uncertainties in existing biomass quantification scenarios. The use of backscatter information from a host of allweather capable Synthetic Aperture Radar (SAR) systems during the recent past has demonstrated the potential of SAR data in forest above ground biomass estimation and forest / nonforest classification. In the present study, Advanced Land Observing Satellite (ALOS) / Phased Array L-band Synthetic Aperture Radar (PALSAR) data along with field inventory data have been used in forest above ground biomass estimation and forest / non-forest classification over Odisha state, India. The ALOSPALSAR 50 m spatial resolution orthorectified and radiometrically corrected HH/HV dual polarization data (digital numbers) for the year 2010 were converted to backscattering coefficient images (Schimada et al., 2009). The tree level measurements collected during field inventory (2009-'10) on Girth at Breast Height (GBH at 1.3 m above ground) and height of all individual trees at plot (plot size 0.1 ha) level were converted to biomass density using species specific allometric equations and wood densities. The field inventory based biomass estimations were empirically integrated with ALOS-PALSAR backscatter coefficients to derive spatial forest above ground biomass estimates for the study area. Further, The Support Vector Machines (SVM) based Radial Basis Function classification technique was employed to carry out binary (forest-non forest) classification using ALOSPALSAR HH and HV backscatter coefficient images and field inventory data. The textural Haralick's Grey Level Cooccurrence Matrix (GLCM) texture measures are determined on HV backscatter image for Odisha, for the year 2010. PALSAR HH, HV backscatter coefficient images, their difference (HHHV) and HV backscatter coefficient based eight textural parameters (Mean, Variance, Dissimilarity, Contrast, Angular second moment, Homogeneity, Correlation and Contrast) are used as input parameters for Support Vector Machines (SVM) tool. Ground based inputs for forest / non-forest were taken from field inventory data and high resolution Google maps. Results suggested significant relationship between HV backscatter coefficient and field based biomass (R2 = 0.508, p = 0.55) compared to HH with biomass values ranging from 5 to 365 t/ha. The spatial variability of biomass with reference to different forest types is in good agreement. The forest / nonforest classified map suggested a total forest cover of 50214 km2 with an overall accuracy of 92.54 %. The forest / non-forest information derived from the present study showed a good spatial agreement with the standard forest cover map of Forest Survey of India (FSI) and corresponding published area of 50575 km2. Results are discussed in the paper.

Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests

NASA Astrophysics Data System (ADS)

Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo

2016-10-01

Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.

Earth observation data for assessment of nationwide land cover and long-term deforestation in Afghanistan

NASA Astrophysics Data System (ADS)

Sudhakar Reddy, C.; Saranya, K. R. L.

2017-08-01

This study has generated a national level spatial database of land cover and changes in forest cover of Afghanistan for the 1975-1990, 1990-2005 and 2005-2014 periods. Using these results we have analysed the annual deforestation rates, spatial changes in forests, forest types and fragmentation classes over a period of 1975 to 2014 in Afghanistan. The land cover map of 2014 provides distribution of forest (dry evergreen, moist temperate, dry temperate, pine, sub alpine) and non-forest (grassland, scrub, agriculture, wetlands, barren land, snow and settlements) in Afghanistan. The largest land cover, barren land, contributes to 56% of geographical area of country. Forest is distributed mostly in eastern Afghanistan and constitutes an area of 1.02% of geographical area in 2014. The annual deforestation rate in Afghanistan's forests for the period from 1975 to 1990 estimated as 0.06% which was declined significantly from 2005 to 2014. The predominant forest type in Afghanistan is moist temperate which shows loss of 80 km2 of area during the last four decades of the study period. At national level, the percentage of large core forest area was calculated as 52.20% in 2014.

[Estimation of forest canopy chlorophyll content based on PROSPECT and SAIL models].

PubMed

Yang, Xi-guang; Fan, Wen-yi; Yu, Ying

2010-11-01

The forest canopy chlorophyll content directly reflects the health and stress of forest. The accurate estimation of the forest canopy chlorophyll content is a significant foundation for researching forest ecosystem cycle models. In the present paper, the inversion of the forest canopy chlorophyll content was based on PROSPECT and SAIL models from the physical mechanism angle. First, leaf spectrum and canopy spectrum were simulated by PROSPECT and SAIL models respectively. And leaf chlorophyll content look-up-table was established for leaf chlorophyll content retrieval. Then leaf chlorophyll content was converted into canopy chlorophyll content by Leaf Area Index (LAD). Finally, canopy chlorophyll content was estimated from Hyperion image. The results indicated that the main effect bands of chlorophyll content were 400-900 nm, the simulation of leaf and canopy spectrum by PROSPECT and SAIL models fit better with the measured spectrum with 7.06% and 16.49% relative error respectively, the RMSE of LAI inversion was 0. 542 6 and the forest canopy chlorophyll content was estimated better by PROSPECT and SAIL models with precision = 77.02%.

Effects of increasing forest plantation area and management practices on carbon storage and water use in the United States

NASA Astrophysics Data System (ADS)

Chen, G.; Hayes, D. J.; Tian, H.

2013-12-01

Planted forest area in the United States gradually increased during the last half century, and by 2007 accounted for about 20% of the total forest area in the southern United States and about 13% in the entire country. Intensive plantation management activities - such as slash burning, thinning, weed control, fertilization and the use of genetically improved seedlings - are routinely applied during the forest rotation. However, no comprehensive assessments have been made to examine the impacts of this increased forest plantation area and associated management practices on ecosystem function. In this study, we integrated field measurement data and process-based modeling to quantitatively estimate the changes in carbon storage, nitrogen cycling and water use as influenced by forest plantations in the United States from 1925 to 2007. The results indicated that forest plantations and management practices greatly increased forest productivity, vegetation carbon, and wood product carbon storage in the United States, but slightly reduce soil carbon storage at some areas; however, the carbon sink induced by forest plantations was at the expense of more water use as represented by higher evapotranspiration. Stronger nitrogen and water limitations were found for forest plantations as compared to natural or naturally-regenerated forests.

Estimating leaf area and above-ground biomass of forest regeneration areas using a corrected normalized difference vegetation index

Treesearch

Tommy L. Coleman; James H. Miller; Bruce R. Zutter

1992-01-01

The objective of this study was to investigate the regression relations between vegetation indices derived from remotely-sensed data of single and mixed forest regeneration plots. Loblolly pine (Pinus taeda L.) seedlings, sweelgum (Liquidambar styraciflua L.) seedlings and broomsedge (Andropogon virginicus L.)...

[Quantitative estimation of evapotranspiration from Tahe forest ecosystem, Northeast China].

PubMed

Qu, Di; Fan, Wen-Yi; Yang, Jin-Ming; Wang, Xu-Peng

2014-06-01

Evapotranspiration (ET) is an important parameter of agriculture, meteorology and hydrology research, and also an important part of the global hydrological cycle. This paper applied the improved DHSVM distributed hydrological model to estimate daily ET of Tahe area in 2007 using leaf area index and other surface data extracted TM remote sensing data, and slope, aspect and other topographic indices obtained by using the digital elevation model. The relationship between daily ET and daily watershed outlet flow was built by the BP neural network, and a water balance equation was established for the studied watershed, together to test the accuracy of the estimation. The results showed that the model could be applied in the study area. The annual total ET of Tahe watershed was 234.01 mm. ET had a significant seasonal variation. The ET had the highest value in summer and the average daily ET value was 1.56 mm. The average daily ET in autumn and spring were 0.30, 0.29 mm, respectively, and winter had the lowest ET value. Land cover type had a great effect on ET value, and the broadleaf forest had a higher ET ability than the mixed forest, followed by the needle leaf forest.

An evaluation of satellite data for estimating the area of small forestland in the southern lower peninsula of Michigan. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Karteris, M. A. (Principal Investigator)

1980-01-01

A winter black and white band 5, a winter color, a fall color, and a diazo color composite of the fall scene were used to assess the use and potential of LANDSAT images for mapping and estimating acreage of small scattered forest tracts in Barry County, Michigan. Forests as small as 2.5 acres were mapped from each LANDSAT data source. The maps for each image were compared with an available forest-type map. Mapping errors detected were categorized as boundary and identification errors. The most frequently misclassified areas were agriculture lands, treed-bogs, brushlands and lowland and mixed hardwood stands. Stocking level affected interpretation more than stand size. The overall level of the interpretation performance was expressed through the estimation of classification, interpretation, and mapping accuracies. These accuracies ranged from 74 between 74% and 98%. Considering errors, accuracy, and cost, winter color imagery is the best LANDSAT alternative for mapping small forest tracts. However, since the availability of cloud-free winter images of the study area is significantly lower than images for other seasons, a diazo enhanced image of a fall scene is recommended as the best next best alternative.

Rapid assessment of U.S. forest and soil organic carbon storage and forest biomass carbon-sequestration capacity

USGS Publications Warehouse

Sundquist, Eric T.; Ackerman, Katherine V.; Bliss, Norman B.; Kellndorfer, Josef M.; Reeves, Matt C.; Rollins, Matthew G.

2009-01-01

This report provides results of a rapid assessment of biological carbon stocks and forest biomass carbon sequestration capacity in the conterminous United States. Maps available from the U.S. Department of Agriculture are used to calculate estimates of current organic carbon storage in soils (73 petagrams of carbon, or PgC) and forest biomass (17 PgC). Of these totals, 3.5 PgC of soil organic carbon and 0.8 PgC of forest biomass carbon occur on lands managed by the U.S. Department of the Interior (DOI). Maps of potential vegetation are used to estimate hypothetical forest biomass carbon sequestration capacities that are 3–7 PgC higher than current forest biomass carbon storage in the conterminous United States. Most of the estimated hypothetical additional forest biomass carbon sequestration capacity is accrued in areas currently occupied by agriculture and development. Hypothetical forest biomass carbon sequestration capacities calculated for existing forests and woodlands are within ±1 PgC of estimated current forest biomass carbon storage. Hypothetical forest biomass sequestration capacities on lands managed by the DOI in the conterminous United States are 0–0.4 PgC higher than existing forest biomass carbon storage. Implications for forest and other land management practices are not considered in this report. Uncertainties in the values reported here are large and difficult to quantify, particularly for hypothetical carbon sequestration capacities. Nevertheless, this rapid assessment helps to frame policy and management discussion by providing estimates that can be compared to amounts necessary to reduce predicted future atmospheric carbon dioxide levels.

Ancient human disturbances may be skewing our understanding of Amazonian forests.

PubMed

McMichael, Crystal N H; Matthews-Bird, Frazer; Farfan-Rios, William; Feeley, Kenneth J

2017-01-17

Although the Amazon rainforest houses much of Earth's biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests.

Quantifying edge effect extent and its impacts on carbon stocks across a degraded landscape in the Amazon using airborne lidar.

NASA Astrophysics Data System (ADS)

dos-Santos, M. N.; Keller, M.; Morton, D. C.; Longo, M.; Scaranello, M. A., Sr.; Pinagé, E. R.; Correa Pabon, R.

2017-12-01

Ongoing tropical forest degradation and forest fragmentation increases forest edge area. Forest edges experience hotter, drier, and windier conditions and greater exposure to fires compared to interior areas, which elevate rates of tree mortality. Previous studies have suggested that forests within 100 m from the edge may lose 36% of biomass during the first two decades following fragmentation, although such estimates are based on a limited number of experimental plots. Degraded forests behave differently from intact forests and quantifying edge effect extension in a degraded forest landscape is more challenging compared to experimental studies. To overcome these limitations, we used airborne lidar data to quantify changes in forest structure near 91 edges in a heavily degraded tropical forest in Paragominas Municipality, eastern Brazilian Amazon. Paragominas was a center of timber production in the 1990s. Today, the landscape is a mosaic of different agricultural uses, degraded, secondary and unmanaged forests. A total of 3000 ha of high density (mean density of 17.9 points/m2) lidar data were acquired in August/September 2013 and June/July 2014 over 30 transects (200 x 5000m), systematically distributed over the study area, using the Optech Orion M-200 laser scanning system. We adopted lidar-measured forest heights as the edge effect criteria and found that mean extent of edge effect was highly variable across degraded forests (150 ± 354m) and secondary forest fragments (265 ± 365m). We related the extent of forest edges to the historical disturbances identified in Landsat imagery since 1984. Contrary to previous studies, we found that carbon stocks along forest edges were not significantly lower than forest core biomass when edges were defined by previously estimated range of 100 and 300m. In frontier forests, ecological edge effect may be masked by the cumulative impact of historic forest degradation - an anthropogenic edge effect that extends beyond the scale of changes in forest microclimate from fragmentation.

Estimating historical snag density in dry forests east of the Cascade Range

Treesearch

Richy J. Harrod; William L. Gaines; William E. Hartl; Ann. Camp

1998-01-01

Estimating snag densities in pre-European settlement landscapes (i.e., historical conditions) provides land managers with baseline information for comparing current snag densities. We propose a method for determining historical snag densities in the dry forests east of the Cascade Range. Basal area increase was calculated from tree ring measurements of old ponderosa...

Sensitivity Analysis of Down Woody Material Data Processing Routines

Treesearch

Christopher W. Woodall; Duncan C. Lutes

2005-01-01

Weight per unit area (load) estimates of Down Woody Material (DWM) are the most common requests by users of the USDA Forest Service's Forest Inventory and Analysis (FIA) program's DWM inventory. Estimating of DWM loads requires the uniform compilation of DWM transect data for the entire United States. DWM weights may vary by species, level of decay, woody...

Biomass statistics for Maryland--1986

Treesearch

Thomas S. Frieswyk; Dawn M. DiGiovanni; Dawn M. DiGiovanni

1990-01-01

A statistical report on the fourth forest survey of Maryland (1986). Findings are displayed in 97 tables containing estimates of forest area, tree biomass, and timber volume. Data are presented by state and county level.

American Samoa's forest resources, 2001.

Treesearch

Joseph A. Donnegan; Sheri S. Mann; Sarah L. Butler; Bruce A. Hiserote

2004-01-01

The Forest Inventory and Analysis Program of the Pacific Northwest Research Station collected, analyzed, and summarized data from field plots, and mapped land cover on four islands in American Samoa. This statistical sample provides estimates of forest area, stem volume, biomass, numbers of trees, damages to trees, and tree size distribution. The summary provides...

7 CFR 625.6 - Establishing priority for enrollment in HFRP.

Code of Federal Regulations, 2012 CFR

2012-01-01

... contribution of non-Federal funds; (6) Significance of forest ecosystem functions and values; (7) Estimated... place higher priority on certain forest ecosystems based regions of the State or multi-State area where... is essential to the successful restoration of the forest ecosystem and those adjacent landowners are...

7 CFR 625.6 - Establishing priority for enrollment in HFRP.

Code of Federal Regulations, 2013 CFR

2013-01-01

... contribution of non-Federal funds; (6) Significance of forest ecosystem functions and values; (7) Estimated... place higher priority on certain forest ecosystems based regions of the State or multi-State area where... is essential to the successful restoration of the forest ecosystem and those adjacent landowners are...

7 CFR 625.6 - Establishing priority for enrollment in HFRP.

Code of Federal Regulations, 2014 CFR

2014-01-01

... contribution of non-Federal funds; (6) Significance of forest ecosystem functions and values; (7) Estimated... place higher priority on certain forest ecosystems based regions of the State or multi-State area where... is essential to the successful restoration of the forest ecosystem and those adjacent landowners are...

7 CFR 625.6 - Establishing priority for enrollment in HFRP.

Code of Federal Regulations, 2011 CFR

2011-01-01

... contribution of non-Federal funds; (6) Significance of forest ecosystem functions and values; (7) Estimated... place higher priority on certain forest ecosystems based regions of the State or multi-State area where... is essential to the successful restoration of the forest ecosystem and those adjacent landowners are...

Forest statistics for Pennsylvania--1978 and 1989

Treesearch

Carol L. Alerich; Carol L. Alerich

1993-01-01

A statistical report on the fourth forest survey of Pennsylvania (1988-90). Findings are displayed in 157 tables containing estimates of forest area, numbers of trees, wildlife habitat, tree biomass, timber volume, timber products outp~qg, rowth, and change. Data are presented at three levels: state, geographic unit, and county.

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling

PubMed Central

2011-01-01

Background A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Results Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Conclusions Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. PMID:21835025

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.

PubMed

Potter, Christopher; Klooster, Steven; Crabtree, Robert; Huang, Shengli; Gross, Peggy; Genovese, Vanessa

2011-08-11

A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.

Evaporation from cultivated and semi-wild Sudanian Savanna in west Africa

NASA Astrophysics Data System (ADS)

Ceperley, Natalie C.; Mande, Theophile; van de Giesen, Nick; Tyler, Scott; Yacouba, Hamma; Parlange, Marc B.

2017-08-01

Rain-fed farming is the primary livelihood of semi-arid west Africa. Changes in land cover have the potential to affect precipitation, the critical resource for production. Turbulent flux measurements from two eddy-covariance towers and additional observations from a dense network of small, wireless meteorological stations combine to relate land cover (savanna forest and agriculture) to evaporation in a small (3.5 km2) catchment in Burkina Faso, west Africa. We observe larger sensible and latent heat fluxes over the savanna forest in the headwater area relative to the agricultural section of the watershed all year. Higher fluxes above the savanna forest are attributed to the greater number of exposed rocks and trees and the higher productivity of the forest compared to rain-fed, hand-farmed agricultural fields. Vegetation cover and soil moisture are found to be primary controls of the evaporative fraction. Satellite-derived vegetation index (NDVI) and soil moisture are determined to be good predictors of evaporative fraction, as indicators of the physical basis of evaporation. Our measurements provide an estimator that can be used to derive evaporative fraction when only NDVI is available. Such large-scale estimates of evaporative fraction from remotely sensed data are valuable where ground-based measurements are lacking, which is the case across the African continent and many other semi-arid areas. Evaporative fraction estimates can be combined, for example, with sensible heat from measurements of temperature variance, to provide an estimate of evaporation when only minimal meteorological measurements are available in remote regions of the world. These findings reinforce local cultural beliefs of the importance of forest fragments for climate regulation and may provide support to local decision makers and rural farmers in the maintenance of the forest areas.

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

Estimation of Aboveground Biomass Change for Tropical Deciduous Forest in Bago Yoma, Myanmar between year 2000 and 2014 using Landsat Images and Ground Measurements

NASA Astrophysics Data System (ADS)

Kim, H. S.; Wynn, K. Z.; Ryu, Y.

2015-12-01

Even with recently increased awareness of the environmental conservation, the degradation of tropical forests are still one of the major sources of global carbon emission. Especially in Myanmar, the pressure to develop natural forest is growing rapidly after the change from socialism to capitalism in 2010. As the initial step of the forest conservation, the aboveground biomass(AGB) of South Zarmani Reserved Forest in Bago Yoma region were estimated using Landsat 8 OLI after the evaluation with 100 sample plot measurements. Multiple linear regression (MLR) model of band values and their principal component analysis (PCA) model were developed to estimate the AGB using the spectral reflectance from Landsat images and elevation as the input variables. The MLR model had r2 = 0.43, RMSE = 60.2 tons/ha, relative RMSE = 70.1%, Bias = -9.1 tons/ha, Bias (%) = -10.6%, and p < 0.0001, while the PCA model showed r2 = 0.45, RMSE = 55.1 tons/ha, relative RMSE = 64.1%, Bias = -8.3 tons/ha, Bias (%) = -9.7%, and p < 0.0001. The AGB maps of the study area were generated based on both MLR and PCA models. The estimated mean AGB values were 74.74±22.3 tons/ha and 73.04±17.6 tons/ha and the total AGB of the study area are about 5.7 and 5.6 million tons from MLR and PCA, respectively. Then, Landsat 7 ETM+ image acquired on 2000 was also used to compare the changing of AGB between year 2000 and 2014. The estimated mean AGB value generated from the Landsat 7 ETM+ image was 78.9±16.9 tons/ha, which is substantially decreased about 7.5% compared to year 2014. The reduction of AGB increased with closeness to village, however AGB in distant areas showed steady increases. In conclusion, we were able to generate solid regression models from Landsat 8 OLI image after ground truth and two regression models gave us very similar AGB estimation (less than 2%) of the study area. We were also able to estimate the changing of AGB from year 2000 to 2014 of South Zarmani Reserved Forest, Bago Yoma, Myanmar.

Effects of different definitions on forest area estimation in national forest inventories in Europe

Treesearch

Berthold Traub; Michael Kohl; Risto Paivinen; Olaf Kugler

2000-01-01

International forest statistics such as those provided by the UN/ECE-FAO Temperate and Boreal Forest Resource Assessment (TBFRA) are typically compiled from national surveys. However, the national systems of nomenclature as well as the definition of the attributes often vary considerably. The European Commission, DG VI, initiated a study to investigate the potential of...

VARIABILITY IN NET PRIMARY PRODUCTION AND CARBON STORAGE IN BIOMASS ACROSS OREGON FORESTS - AN ASSESSMENT INTEGRATING DATA FROM FOREST INVENTORIES, INTENSIVE SITES, AND REMOTE SENSING. (R828309)

EPA Science Inventory

We used a combination of data from USDA Forest Service inventories, intensive
chronosequences, extensive sites, and satellite remote sensing, to estimate biomass
and net primary production (NPP) for the forested region of western Oregon. The
study area was divided int...

Temporal transferability of LiDAR-based imputation of forest structure attributes

Treesearch

Patrick A. Fekety; Michael J. Falkowski; Andrew T. Hudak

2015-01-01

Forest inventory and planning decisions are frequently informed by LiDAR data. Repeated LiDAR acquisitions offer an opportunity to update forest inventories and potentially improve forest inventory estimates through time. We leveraged repeated LiDAR and ground measures for a study area in northern Idaho, U.S.A., to predict (via imputation) - across both space and time-...

Statistical strategies for global monitoring of tropical forests

Treesearch

Raymond L. Czaplewski

1991-01-01

The Food and Agricultural Organization (FAO) of the United Nations is conducting a global assessment of tropical forest resources, which will be accomplished by mid-1992. This assessment requires, in part, estimates of the total area of tropical forest cover in 1990, and the rate of change in forest cover between 1980 and 1990. This paper describes: (1) the strategic...

Strategies for global monitoring of tropical forests

Treesearch

Raymond L. Czaplewski

1994-01-01

The Food and Agricultural Organization (FAO) of the United Nations is conducting a global assessment of tropical forest resources, which will be accomplished by mid-1992. This assessment requires, in part, estimates of the total area of tropical forest cover in 1990 and the rate of change in forest cover between 1980 and 1990. The following are described here: (1) the...

Fire emissions in central Siberia

Treesearch

Douglas J. McRae; Steve P. Baker; Yuri N. Samsonov; Galina A. Ivanova

2009-01-01

Wildfires in the Russian boreal forest zone are estimated to typically burn 12-14 million hectares (ha) annually [Cahoon et al. 1994; Conard and Ivanova 1997; Conard et al. 2002; Dixon and Krankina 1993; Kasischke et al. 1999]. Boreal forests contain about 21 percent of global forest area and 28 percent of global forest carbon [Dixon et al. 1994], yet data on the...

Application of mapped plots for single-owner forest surveys

Treesearch

Paul C. Van Deusen; Francis Roesch

2009-01-01

Mapped plots are used for the nation forest inventory conducted by the U.S. Forest Service. Mapped plots are also useful foro single ownership inventoires. Mapped plots can handle boundary overlap and can aprovide less variable estimates for specified forest conditions. Mapping is a good fit for fixed plot inventories where the fixed area plot is used for both mapping...

Assessing forest degradation in Guyana with GeoEye, Quickbird and Landsat

Treesearch

Bobby Braswell; Steve Hagen; William Salas; Michael Palace; Sandra Brown; Felipe Casarim; Nancy Harris

2013-01-01

Forest degradation is defined as a change in forest quality and condition (e.g. reduction in biomass), while deforestation is a change in forest area. This pilot study evaluated several image processing approaches to map degradation and estimate carbon removals from logging. From the Joint Concept Note on REDD+ cooperation between Guyana and Norway carbon loss as...

Indirect and direct recharges in a tropical forested watershed: Mule Hole, India

NASA Astrophysics Data System (ADS)

Maréchal, Jean-Christophe; Varma, Murari R. R.; Riotte, Jean; Vouillamoz, Jean-Michel; Kumar, M. S. Mohan; Ruiz, Laurent; Sekhar, M.; Braun, Jean-Jacques

2009-01-01

SummaryIt is commonly accepted that forest plays role to modify the water cycle at the watershed scale. However, the impact of forest on aquifer recharge is still discussed: some studies indicate that infiltration is facilitated under forest while other studies suggest a decrease of recharge. This paper presents an estimate of recharge rates to groundwater in a humid forested watershed of India. Recharge estimates are based on the joint use of several methods: chloride mass balance, water table fluctuation, geophysics, groundwater chemistry and flow analysis. Two components of the recharge (direct and indirect) are estimated over 3 years of monitoring (2003-2006). The direct and localized recharges resulting from rainfall over the entire watershed surface area is estimated to 45 mm/yr while the indirect recharge occurring from the stream during flood events is estimated to 30 mm/yr for a 2 km-long stream. Calculated recharge rates, rainfall and runoff measurements are then combined in a water budget to estimate yearly evapotranspiration which ranges from 80% to 90% of the rainfall, i.e. 1050 mm/y as an average. This unexpected high value for a deciduous forest is nevertheless in agreement with the forest worldwide relationship between rainfall and evapotranspiration. The large evapotranspiration from the forest cover contributes to decrease the recharge rate which leads to a lowering of the water table. This is the reason why the stream is highly ephemeral.

Use of map analysis to elucidate flooding in an Australian Riparian River Red Gum Forest

NASA Astrophysics Data System (ADS)

Bren, L. J.; O'Neill, I. C.; Gibbs, N. L.

1988-07-01

Red gum (Eucalyptus camaldulensis) forests occur on extensive floodplains along the river Murray in Australia. This type of forest is unusual because of its high quality in a semiarid area, the absence of woody species other than red gum, and its survival on a deep, intractable, swelling clay soil of depths exceeding 20 m. This soil probably acts as an aquiclude. The forests require flooding to thrive and regenerate. For many years there has been speculation that irrigation regulation of the river was reducing forest flooding. A grid cell analysis of flood maps of areas flooded over a period of 22 years showed that vegetation communities and forest site quality were statistically related to the flood frequencies of sites. The percentage of forest inundated was dependent on the peak daily flow during the period of inundation. A historical analysis of the estimated percentage of forest inundated showed a substantial influence of river regulation on both timing and extent of inundation. Estimates of historical floodings showed that the environment is one that changes rapidly from wetland to dry land. Although not without limitations, the analysis produced information not available from other sources.

Difficulties in tracking the long-term global trend in tropical forest area.

PubMed

Grainger, Alan

2008-01-15

The long-term trend in tropical forest area receives less scrutiny than the tropical deforestation rate. We show that constructing a reliable trend is difficult and evidence for decline is unclear, within the limits of errors involved in making global estimates. A time series for all tropical forest area, using data from Forest Resources Assessments (FRAs) of the United Nations Food and Agriculture Organization, is dominated by three successively corrected declining trends. Inconsistencies between these trends raise questions about their reliability, especially because differences seem to result as much from errors as from changes in statistical design and use of new data. A second time series for tropical moist forest area shows no apparent decline. The latter may be masked by the errors involved, but a "forest return" effect may also be operating, in which forest regeneration in some areas offsets deforestation (but not biodiversity loss) elsewhere. A better monitoring program is needed to give a more reliable trend. Scientists who use FRA data should check how the accuracy of their findings depends on errors in the data.

Three Different Methods of Estimating LAI in a Small Watershed

NASA Astrophysics Data System (ADS)

Speckman, H. N.; Ewers, B. E.; Beverly, D.

2015-12-01

Leaf area index (LAI) is a critical input of models that improve predictive understanding of ecology, hydrology, and climate change. Multiple techniques exist to quantify LAI, most of which are labor intensive, and all often fail to converge on similar estimates. . Recent large-scale bark beetle induced mortality greatly altered LAI, which is now dominated by younger and more metabolically active trees compared to the pre-beetle forest. Tree mortality increases error in optical LAI estimates due to the lack of differentiation between live and dead branches in dense canopy. Our study aims to quantify LAI using three different LAI methods, and then to compare the techniques to each other and topographic drivers to develop an effective predictive model of LAI. This study focuses on quantifying LAI within a small (~120 ha) beetle infested watershed in Wyoming's Snowy Range Mountains. The first technique estimated LAI using in-situ hemispherical canopy photographs that were then analyzed with Hemisfer software. The second LAI estimation technique was use of the Kaufmann 1982 allometrerics from forest inventories conducted throughout the watershed, accounting for stand basal area, species composition, and the extent of bark beetle driven mortality. The final technique used airborne light detection and ranging (LIDAR) first DMS returns, which were used to estimating canopy heights and crown area. LIDAR final returns provided topographical information and were then ground-truthed during forest inventories. Once data was collected, a fractural analysis was conducted comparing the three methods. Species composition was driven by slope position and elevation Ultimately the three different techniques provided very different estimations of LAI, but each had their advantage: estimates from hemisphere photos were well correlated with SWE and snow depth measurements, forest inventories provided insight into stand health and composition, and LIDAR were able to quickly and efficiently cover a very large area.

Targeted habitat restoration can reduce extinction rates in fragmented forests.

PubMed

Newmark, William D; Jenkins, Clinton N; Pimm, Stuart L; McNeally, Phoebe B; Halley, John M

2017-09-05

The Eastern Arc Mountains of Tanzania and the Atlantic Forest of Brazil are two of the most fragmented biodiversity hotspots. Species-area relationships predict that their habitat fragments will experience a substantial loss of species. Most of these extinctions will occur over an extended time, and therefore, reconnecting fragments could prevent species losses and allow locally extinct species to recolonize former habitats. An empirical relaxation half-life vs. area relationship for tropical bird communities estimates the time that it takes to lose one-half of all species that will be eventually lost. We use it to estimate the increase in species persistence by regenerating a forest connection 1 km in width among the largest and closest fragments at 11 locations. In the Eastern Arc Mountains, regenerating 8,134 ha of forest would create >316,000 ha in total of restored contiguous forest. More importantly, it would increase the persistence time for species by a factor of 6.8 per location or ∼2,272 years, on average, relative to individual fragments. In the Atlantic Forest, regenerating 6,452 ha of forest would create >251,000 ha in total of restored contiguous forest and enhance species persistence by a factor of 13.0 per location or ∼5,102 years, on average, relative to individual fragments. Rapidly regenerating forest among fragments is important, because mean time to the first determined extinction across all fragments is 7 years. We estimate the cost of forest regeneration at $21-$49 million dollars. It could provide one of the highest returns on investment for biodiversity conservation worldwide.

Targeted habitat restoration can reduce extinction rates in fragmented forests

PubMed Central

Newmark, William D.; Pimm, Stuart L.; McNeally, Phoebe B.; Halley, John M.

2017-01-01

The Eastern Arc Mountains of Tanzania and the Atlantic Forest of Brazil are two of the most fragmented biodiversity hotspots. Species–area relationships predict that their habitat fragments will experience a substantial loss of species. Most of these extinctions will occur over an extended time, and therefore, reconnecting fragments could prevent species losses and allow locally extinct species to recolonize former habitats. An empirical relaxation half-life vs. area relationship for tropical bird communities estimates the time that it takes to lose one-half of all species that will be eventually lost. We use it to estimate the increase in species persistence by regenerating a forest connection 1 km in width among the largest and closest fragments at 11 locations. In the Eastern Arc Mountains, regenerating 8,134 ha of forest would create >316,000 ha in total of restored contiguous forest. More importantly, it would increase the persistence time for species by a factor of 6.8 per location or ∼2,272 years, on average, relative to individual fragments. In the Atlantic Forest, regenerating 6,452 ha of forest would create >251,000 ha in total of restored contiguous forest and enhance species persistence by a factor of 13.0 per location or ∼5,102 years, on average, relative to individual fragments. Rapidly regenerating forest among fragments is important, because mean time to the first determined extinction across all fragments is 7 years. We estimate the cost of forest regeneration at $21–$49 million dollars. It could provide one of the highest returns on investment for biodiversity conservation worldwide. PMID:28827340

A national scale estimation of soil carbon stocks of Pinus densiflora forests in Korea: a modelling approach

NASA Astrophysics Data System (ADS)

Yi, K.; Park, C.; Ryu, S.; Lee, K.; Yi, M.; Kim, C.; Park, G.; Kim, R.; Son, Y.

2011-12-01

Soil carbon (C) stocks of Pinus densiflora forests in Korea were estimated using a generic forest soil C dynamics model based on the process of dead organic matter input and decomposition. Annual input of dead organic matter to the soil was determined by stand biomass and turnover rates of tree components (stem, branch, twig, foliage, coarse root, and fine root). The model was designed to have a simplified structure consisting of three dead organic matter C (DOC) pools (aboveground woody debris (AWD), belowground woody debris (BWD), and litter (LTR) pool) and one soil organic C (SOC) pool. C flows in the model were regulated by six turnover rates of stem, branch, twig, foliage, coarse root, and fine root, and four decay rates of AWD, BWD, LTR, and SOC. To simulate the soil C stocks of P. densiflora forests, statistical data of forest land area (1,339,791 ha) and growing stock (191,896,089 m3) sorted by region (nine provinces and seven metropolitan cities) and stand age class (11 to 20- (II), 21 to 30- (III), 31 to 40- (IV), 41 to 50- (V), and 51 to 60-year-old (VI)) were used. The growing stock of each stand age class was calculated for every region and representable site index was also determined by consulting the yield table. Other model parameters related to the stand biomass, annual input of dead organic matter and decomposition were estimated from previous studies conducted on P. densiflora forests in Korea, which were also applied for model validation. As a result of simulation, total soil C stock of P. densiflora forests were estimated as 53.9 MtC and soil C stocks per unit area ranged from 28.71 to 47.81 tC ha-1 within the soil depth of 30 cm. Also, soil C stocks in the P. densiflora forests of age class II, III, IV, V, and VI were 16,780,818, 21,450,812, 12,677,872, 2,366,939, and 578,623 tC, respectively, and highly related to the distribution of age classes. Soil C stocks per unit area initially decreased with stand age class and started to increase after the stand age class of V. Regional soil C stocks ranged from 9,805 to 15,595,802 tC, and were generally proportional to the forest land area. Our results suggest an approach to estimate soil C stock on a national scale by using a computer model and manipulating the existing statistical data.

Estimation of biogeochemical climate regulation services in Chinese forest ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, S.

2016-12-01

As the global climate is changing, the climate regulation service of terrestrial ecosystem has been widely studied. Forests, as one of the most important terrestrial ecosystem types, is the biggest carbon pool or sink on land and can regulate climate through both biophysical and biogeochemical means. China is a country with vast forested areas and a variety of forest ecosystems types. Although current studies have related the climate regulation service of forest in China with biophysical or biogeochemical mechanism, there is still a lack of quantitative estimation of climate regulation services, especially for the biogeochemical climate regulation service. The GHGV (greenhouse gas value) is an indicator that can quantify the biochemical climate regulation service using ecosystems' stored organic matter, annual greenhouse gas flux, and potential greenhouse gas exchange rates during disturbances over a multiple year time frame. Therefore, we used GHGV to estimate the contribution of China's ten main forest types to biogeochemical climate regulation and generate the pattern of biochemical climate regulation service in Chinese forest ecosystems.

Estimating forest productivity with Thematic Mapper and biogeographical data

NASA Technical Reports Server (NTRS)

Cook, Elizabeth A.; Iverson, Louis R.; Graham, Robin L.

1989-01-01

Spectral data from the Landsat Thematic Mapper (TM) on three forest exosystems (the southern Illinois, the Great Smoky Mountains regions in Tennessee and North Carolina, and the central Adirondack Mountains in New York) were used in conjunction with ground-collected measures of forest productivity and such information as the area's slope, aspect, elevation, and soil and vegetation types, to develop models of regional forest productivity. It is shown that the models developed may be used to estimate the productivity of a region with a high degree of confidence, but that the reliability of single-pixel estimates is poor. The characteristics of a given ecosystem determine which spectral values are most closely related to forest productivity. Thus, mid-IR, NIR, and visible bands are most significant in Illinois and New York, while the thermal band is relatively more important in the Smokies.

Automated Burned Area Delineation Using IRS AWiFS satellite data

NASA Astrophysics Data System (ADS)

Singhal, J.; Kiranchand, T. R.; Rajashekar, G.; Jha, C. S.

2014-12-01

India is endowed with a rich forest cover. Over 21% of country's area is covered by forest of varied composition and structure. Out of 67.5 million ha of Indian forests, about 55% of the forest cover is being subjected to fires each year, causing an economic loss of over 440 crores of rupees apart from other ecological effects. Studies carried out by Forest Survey of India reveals that on an average 53% forest cover of the country is prone to fires and 6.17% of the forests are prone to severe fire damage. Forest Survey of India in a countrywide study in 1995 estimated that about 1.45 million hectares of forest are affected by fire annually. According to Forest Protection Division of the Ministry of Environment and Forest (GOI), 3.73 million ha of forests are affected by fire annually in India. Karnataka is one of the southern states of India extending in between latitude 110 30' and 180 25' and longitudes 740 10' and 780 35'. As per Forest Survey of India's State of Forest Report (SFR) 2009, of the total geographic area of 191791sq.km, the state harbors 38284 sq.km of recorded forest area. Major forest types occurring in the study area are tropical evergreen and semi-evergreen, tropical moist and dry deciduous forests along with tropical scrub and dry grasslands. Typical forest fire season in the study area is from February-May with a peak during March-April every year, though sporadic fire episodes occur in other parts of the year sq.km, the state harbors 38284 sq.km of recorded forest area. Major forest types occurring in the study area are tropical evergreen and semi-evergreen, tropical moist and dry deciduous forests along with tropical scrub and dry grasslands. Significant area of the deciduous forests, scrub and grasslands is prone to recurrent forest fires every year. In this study we evaluate the feasibility of burned area mapping over a large area (Karnataka state, India) using a semi-automated detection algorithm applied to medium resolution multi spectral data from the IRS AWiFS sensor. The method is intended to be used by non-specialist users for diagnostic rapid burnt area mapping.

Root mass, net primary production and turnover in aspen, jack pine and black spruce forests in Saskatchewan and Manitoba, Canada.

PubMed

Steele, Sarah J.; Gower, Stith T.; Vogel, Jason G.; Norman, John M.

1997-01-01

Root biomass, net primary production and turnover were studied in aspen, jack pine and black spruce forests in two contrasting climates. The climate of the Southern Study Area (SSA) near Prince Albert, Saskatchewan is warmer and drier in the summer and milder in the winter than the Northern Study Area (NSA) near Thompson, Manitoba, Canada. Ingrowth soil cores and minirhizotrons were used to quantify fine root net primary production (NPPFR). Average daily fine root growth (m m(-2) day(-1)) was positively correlated with soil temperature at 10-cm depth (r(2) = 0.83-0.93) for all three species, with black spruce showing the strongest temperature effect. At both study areas, fine root biomass (measured from soil cores) and fine root length (measured from minirhizotrons) were less for jack pine than for the other two species. Except for the aspen stands, estimates of NPPFR from minirhizotrons were significantly greater than estimates from ingrowth cores. The core method underestimated NPPFR because it does not account for simultaneous fine root growth and mortality. Minirhizotron NPPFR estimates ranged from 59 g m(-2) year(-1) for aspen stands at SSA to 235 g m(-2) year(-1) for black spruce at NSA. The ratio of NPPFR to total detritus production (aboveground litterfall + NPPFR) was greater for evergreen forests than for deciduous forests, suggesting that carbon allocation patterns differ between boreal evergreen and deciduous forests. In all stands, NPPFR consistently exceeded annual fine root turnover and the differences were larger for stands in the NSA than for stands in the SSA, whereas the difference between study areas was only significant for black spruce. The imbalance between NPPFR and fine root turnover is sufficient to explain the net accumulation of carbon in boreal forest soils.

High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle

NASA Astrophysics Data System (ADS)

Brinck, Katharina; Fischer, Rico; Groeneveld, Jürgen; Lehmann, Sebastian; Dantas de Paula, Mateus; Pütz, Sandro; Sexton, Joseph O.; Song, Danxia; Huth, Andreas

2017-03-01

Deforestation in the tropics is not only responsible for direct carbon emissions but also extends the forest edge wherein trees suffer increased mortality. Here we combine high-resolution (30 m) satellite maps of forest cover with estimates of the edge effect and show that 19% of the remaining area of tropical forests lies within 100 m of a forest edge. The tropics house around 50 million forest fragments and the length of the world's tropical forest edges sums to nearly 50 million km. Edge effects in tropical forests have caused an additional 10.3 Gt (2.1-14.4 Gt) of carbon emissions, which translates into 0.34 Gt per year and represents 31% of the currently estimated annual carbon releases due to tropical deforestation. Fragmentation substantially augments carbon emissions from tropical forests and must be taken into account when analysing the role of vegetation in the global carbon cycle.

Remote Sensing Precision Requirements For FIA Estimation

Treesearch

Mark H. Hansen

2001-01-01

In this study the National Land Cover Data (NLCD) available from the Multi-Resolution Land Characteristics Consortium (MRLC) is used for stratification in the estimation of forest area, timberland area, and growing-stock volume from the first year (1999) of annual FIA data collected in Indiana, Iowa, Minnesota, and Missouri. These estimates show that with improvements...

Land use, forest density, soil mapping, erosion, drainage, salinity limitations

NASA Technical Reports Server (NTRS)

Yassoglou, N. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The results of analyses show that it is possible to obtain information of practical significance as follows: (1) A quick and accurate estimate of the proper use of the valuable land can be made on the basis of temporal and spectral characteristics of the land features. (2) A rather accurate delineation of the major forest formations in the test areas was achieved on the basis of spatial and spectral characteristics of the studied areas. The forest stands were separated into two density classes; dense forest, and broken forest. On the basis of ERTS-1 data and the existing ground truth information a rather accurate mapping of the major vegetational forms of the mountain ranges can be made. (3) Major soil formations are mapable from ERTS-1 data: recent alluvial soils; soil on quarternary deposits; severely eroded soil and lithosol; and wet soils. (4) An estimation of cost benefits cannot be made accurately at this stage of the investigation. However, a rough estimate of the ratio of the cost for obtaining the same amount information from ERTS-1 data and from conventional operations would be approximately 1:6 to 1:10, in favor of the ERTS-1.

Identifying Priority Areas for Conservation: A Global Assessment for Forest-Dependent Birds

PubMed Central

Buchanan, Graeme M.; Donald, Paul F.; Butchart, Stuart H. M.

2011-01-01

Limited resources are available to address the world's growing environmental problems, requiring conservationists to identify priority sites for action. Using new distribution maps for all of the world's forest-dependent birds (60.6% of all bird species), we quantify the contribution of remaining forest to conserving global avian biodiversity. For each of the world's partly or wholly forested 5-km cells, we estimated an impact score of its contribution to the distribution of all the forest bird species estimated to occur within it, and so is proportional to the impact on the conservation status of the world's forest-dependent birds were the forest it contains lost. The distribution of scores was highly skewed, a very small proportion of cells having scores several orders of magnitude above the global mean. Ecoregions containing the highest values of this score included relatively species-poor islands such as Hawaii and Palau, the relatively species-rich islands of Indonesia and the Philippines, and the megadiverse Atlantic Forests and northern Andes of South America. Ecoregions with high impact scores and high deforestation rates (2000–2005) included montane forests in Cameroon and the Eastern Arc of Tanzania, although deforestation data were not available for all ecoregions. Ecoregions with high impact scores, high rates of recent deforestation and low coverage by the protected area network included Indonesia's Seram rain forests and the moist forests of Trinidad and Tobago. Key sites in these ecoregions represent some of the most urgent priorities for expansion of the global protected areas network to meet Convention on Biological Diversity targets to increase the proportion of land formally protected to 17% by 2020. Areas with high impact scores, rapid deforestation, low protection and high carbon storage values may represent significant opportunities for both biodiversity conservation and climate change mitigation, for example through Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives. PMID:22205998

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

Mascaro, Joseph; Asner, Gregory P.; Knapp, David E.; Kennedy-Bowdoin, Ty; Martin, Roberta E.; Anderson, Christopher; Higgins, Mark; Chadwick, K. Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. PMID:24489686

Estimating erosion in a riverine watershed: Bayou Liberty-Tchefuncta River in Louisiana.

PubMed

Martin, August; Gunter, James T; Regens, James L

2003-01-01

GOAL, SCOPE, BACKGROUND: Sheet erosion from agricultural, forest and urban lands may increase stream sediment loads as well as transport other pollutants that adversely affect water quality, reduce agricultural and forest production, and increase infrastructure maintenance costs. This study uses spatial analysis techniques and a numerical modeling approach to predict areas with the greatest sheet erosion potential given different soils disturbance scenarios. A Geographic Information System (GIS) and the Universal Soil Loss Equation (USLE) were used to estimate sheet erosion from 0.64 ha parcels of land within the watershed. The Soil Survey of St. Tammany Parish, Louisiana was digitized, required soil attributes entered into the GIS database, and slope factors determined for each 80 x 80 meter parcel in the watershed. The GIS/USLE model used series-specific erosion K factors, a rainfall factor of 89, and a GIS database of scenario-driven cropping and erosion control practice factors to estimate potential soil loss due to sheet erosion. A general trend of increased potential sheet erosion occurred for all land use categories (urban, agriculture/grasslands, forests) as soil disturbance increases from cropping, logging and construction activities. Modeling indicated that rapidly growing urban areas have the greatest potential for sheet erosion. Evergreen and mixed forests (production forest) had lower sheet erosion potentials; with deciduous forests (mostly riparian) having the least sheet erosion potential. Erosion estimates from construction activities may be overestimated because of the value chosen for the erosion control practice factor. This study illustrates the ease with which GIS can be integrated with the Universal Soil Loss Equation to identify areas with high sheet erosion potential for large scale management and policy decision making. The GIS/USLE modeling approach used in this study offers a quick and inexpensive tool for estimating sheet erosion within watersheds using publicly available information. This method can quickly identify discrete locations with relatively precise spatial boundaries (approximately 80 meter resolution) that have a high sheet erosion potential as well as areas where management interventions might be appropriate to prevent or ameliorate erosion.

Comparing Minnesota land cover/use area estimates using NRI and FIA data

Treesearch

Veronica C. Lessard; Mark H. Hansen; Mark D. Nelson

2002-01-01

Areas for land cover/use categories on non-Federal land in Minnesota were estimated from Forest Inventory and Analysis (FIA) data and National Resources Inventory (NRI) data. Six common land cover/use categories were defined, and the NRI and FIA land cover/use categories were assigned to them. Area estimates for these categories were calculated from the FIA and NRI...

Discrete return lidar-based prediction of leaf area index in two conifer forests

Treesearch

Jennifer L. R. Jensen; Karen S. Humes; Lee A. Vierling; Andrew T. Hudak

2008-01-01

Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical...

Urban surface energy fluxes based on remotely-sensed data and micrometeorological measurements over the Kansai area, Japan

NASA Astrophysics Data System (ADS)

Sukeyasu, T.; Ueyama, M.; Ando, T.; Kosugi, Y.; Kominami, Y.

2017-12-01

The urban heat island is associated with land cover changes and increases in anthropogenic heat fluxes. Clear understanding of the surface energy budget at urban area is the most important for evaluating the urban heat island. In this study, we develop a model based on remotely-sensed data for the Kansai area in Japan and clarify temporal transitions and spatial distributions of the surface energy flux from 2000 to 2016. The model calculated the surface energy fluxes based on various satellite and GIS products. The model used land surface temperature, surface emissivity, air temperature, albedo, downward shortwave radiation and land cover/use type from the moderate resolution imaging spectroradiometer (MODIS) under cloud free skies from 2000 to 2016 over the Kansai area in Japan (34 to 35 ° N, 135 to 136 ° E). Net radiation was estimated by a radiation budget of upward/downward shortwave and longwave radiation. Sensible heat flux was estimated by a bulk aerodynamic method. Anthropogenic heat flux was estimated by the inventory data. Latent heat flux was examined with residues of the energy budget and parameterization of bulk transfer coefficients. We validated the model using observed fluxes from five eddy-covariance measurement sites: three urban sites and two forested sites. The estimated net radiation roughly agreed with the observations, but the sensible heat flux were underestimated. Based on the modeled spatial distributions of the fluxes, the daytime net radiation in the forested area was larger than those in the urban area, owing to higher albedo and land surface temperatures in the urban area than the forested area. The estimated anthropogenic heat flux was high in the summer and winter periods due to increases in energy-requirements.

Carbon pool densities and a first estimate of the total carbon pool in the Mongolian forest-steppe.

PubMed

Dulamsuren, Choimaa; Klinge, Michael; Degener, Jan; Khishigjargal, Mookhor; Chenlemuge, Tselmeg; Bat-Enerel, Banzragch; Yeruult, Yolk; Saindovdon, Davaadorj; Ganbaatar, Kherlenchimeg; Tsogtbaatar, Jamsran; Leuschner, Christoph; Hauck, Markus

2016-02-01

The boreal forest biome represents one of the most important terrestrial carbon stores, which gave reason to intensive research on carbon stock densities. However, such an analysis does not yet exist for the southernmost Eurosiberian boreal forests in Inner Asia. Most of these forests are located in the Mongolian forest-steppe, which is largely dominated by Larix sibirica. We quantified the carbon stock density and total carbon pool of Mongolia's boreal forests and adjacent grasslands and draw conclusions on possible future change. Mean aboveground carbon stock density in the interior of L. sibirica forests was 66 Mg C ha(-1) , which is in the upper range of values reported from boreal forests and probably due to the comparably long growing season. The density of soil organic carbon (SOC, 108 Mg C ha(-1) ) and total belowground carbon density (149 Mg C ha(-1) ) are at the lower end of the range known from boreal forests, which might be the result of higher soil temperatures and a thinner permafrost layer than in the central and northern boreal forest belt. Land use effects are especially relevant at forest edges, where mean carbon stock density was 188 Mg C ha(-1) , compared with 215 Mg C ha(-1) in the forest interior. Carbon stock density in grasslands was 144 Mg C ha(-1) . Analysis of satellite imagery of the highly fragmented forest area in the forest-steppe zone showed that Mongolia's total boreal forest area is currently 73 818 km(2) , and 22% of this area refers to forest edges (defined as the first 30 m from the edge). The total forest carbon pool of Mongolia was estimated at ~ 1.5-1.7 Pg C, a value which is likely to decrease in future with increasing deforestation and fire frequency, and global warming. © 2015 John Wiley & Sons Ltd.

Synthesizing Global and Local Datasets to Estimate Jurisdictional Forest Carbon Fluxes in Berau, Indonesia.

PubMed

Griscom, Bronson W; Ellis, Peter W; Baccini, Alessandro; Marthinus, Delon; Evans, Jeffrey S; Ruslandi

2016-01-01

Forest conservation efforts are increasingly being implemented at the scale of sub-national jurisdictions in order to mitigate global climate change and provide other ecosystem services. We see an urgent need for robust estimates of historic forest carbon emissions at this scale, as the basis for credible measures of climate and other benefits achieved. Despite the arrival of a new generation of global datasets on forest area change and biomass, confusion remains about how to produce credible jurisdictional estimates of forest emissions. We demonstrate a method for estimating the relevant historic forest carbon fluxes within the Regency of Berau in eastern Borneo, Indonesia. Our method integrates best available global and local datasets, and includes a comprehensive analysis of uncertainty at the regency scale. We find that Berau generated 8.91 ± 1.99 million tonnes of net CO2 emissions per year during 2000-2010. Berau is an early frontier landscape where gross emissions are 12 times higher than gross sequestration. Yet most (85%) of Berau's original forests are still standing. The majority of net emissions were due to conversion of native forests to unspecified agriculture (43% of total), oil palm (28%), and fiber plantations (9%). Most of the remainder was due to legal commercial selective logging (17%). Our overall uncertainty estimate offers an independent basis for assessing three other estimates for Berau. Two other estimates were above the upper end of our uncertainty range. We emphasize the importance of including an uncertainty range for all parameters of the emissions equation to generate a comprehensive uncertainty estimate-which has not been done before. We believe comprehensive estimates of carbon flux uncertainty are increasingly important as national and international institutions are challenged with comparing alternative estimates and identifying a credible range of historic emissions values.

A simple tool for estimating throughfall nitrogen deposition in forests of western North America using lichens

Treesearch

Heather T. Root; Linda H. Geiser; Mark E. Fenn; Sarah Jovan; Martin A. Hutten; Suraj Ahuja; Karen Dillman; David Schirokauer; Shanti Berryman; Jill A. McMurray

2013-01-01

Anthropogenic nitrogen (N) deposition has had substantial impacts on forests of North America. Managers seek to monitor deposition to identify areas of concern and establish critical loads, which define the amount of deposition that can be tolerated by ecosystems without causing substantial harm. We present a new monitoring approach that estimates throughfall inorganic...

Handbook for predicting residue weights of Pacific Northwest conifers.

Treesearch

J.A. Kendall Snell; James K. Brown

1980-01-01

Procedures are given forest estimating weights of potential residue from Douglas- fir and western hemlock created by forest management activities west of the summit of the Cascade Range. Preliminary estimates are given for six other species. The weight tables are in pounds per tree and pounds per square foot of basal area for a 6- or 8- inch unmerchantable tip. The...

Implications of allometric model selection for county-level biomass mapping.

PubMed

Duncanson, Laura; Huang, Wenli; Johnson, Kristofer; Swatantran, Anu; McRoberts, Ronald E; Dubayah, Ralph

2017-10-18

Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend on the application of allometric models, which often have unknown and unreported uncertainties outside of the size class or environment in which they were developed. Here, we test three popular allometric approaches to field biomass estimation, and explore the implications of allometric model selection for county-level biomass mapping in Sonoma County, California. We test three allometric models: Jenkins et al. (For Sci 49(1): 12-35, 2003), Chojnacky et al. (Forestry 87(1): 129-151, 2014) and the US Forest Service's Component Ratio Method (CRM). We found that Jenkins and Chojnacky models perform comparably, but that at both a field plot level and a total county level there was a ~ 20% difference between these estimates and the CRM estimates. Further, we show that discrepancies are greater in high biomass areas with high canopy covers and relatively moderate heights (25-45 m). The CRM models, although on average ~ 20% lower than Jenkins and Chojnacky, produce higher estimates in the tallest forests samples (> 60 m), while Jenkins generally produces higher estimates of biomass in forests < 50 m tall. Discrepancies do not continually increase with increasing forest height, suggesting that inclusion of height in allometric models is not primarily driving discrepancies. Models developed using all three allometric models underestimate high biomass and overestimate low biomass, as expected with random forest biomass modeling. However, these deviations were generally larger using the Jenkins and Chojnacky allometries, suggesting that the CRM approach may be more appropriate for biomass mapping with lidar. These results confirm that allometric model selection considerably impacts biomass maps and estimates, and that allometric model errors remain poorly understood. Our findings that allometric model discrepancies are not explained by lidar heights suggests that allometric model form does not drive these discrepancies. A better understanding of the sources of allometric model errors, particularly in high biomass systems, is essential for improved forest biomass mapping.

Timber resource statistics for eastern Washington, 1995.

Treesearch

Neil McKay; Patricia M. Bassett; Colin D. MacLean

1995-01-01

This report summarizes a 1990-91 timber resource inventory of Washington east of the crest of the Cascade Range. The inventory was conducted on all private and public lands except National Forests. Timber resource statistics from National Forest inventories also are presented. Detailed tables provide estimates of forest area, timber volume, growth, mortality, and...

Kansas' forest resources, 2005

Treesearch

W. Keith Moser; Gary J. Brand; Melissa Powers

2007-01-01

The USDA Forest Service, Northern Research Station, Forest Inventory and Analysis (NRS-FIA) program is changing to a Web-based, dynamically linked reporting system. As part of the process, this year NRS-FIA is producing this abbreviated summary of 2005 data. This resource bulletin reports on area, volume, and biomass using data from 2001 through 2005. Estimates from...

Forest resources of Puerto Rico

Treesearch

Peter A. Franco; Peter L. Weaver; Susan Eggen-McIntosh

1997-01-01

The principal findings of the second forest survey of Puerto Rico (1990) and changes that have occurred since the survey was established in 1980 are presented. The forest inventory estimates describe the timber resource found within the potential commercial region designated in the first survey. The timber resource addressed consists primarily of regrown areas on...

Forest statistics for the Piedmont of South Carolina, 1993

Treesearch

Mark J. Brown

1993-01-01

This report summarizes results from a 1993 inventory of the forest resources of the Piedmont of South Carolina. Current estimates of forest area, associated characteristics, and timber volumes are highlighted and compared with the 1986 and earlier inventory findings. Average annual rates of growth, removals, and mortality since the previous inventory are reported....

Mapping urban forest structure and function using hyperspectral imagery and lidar data

Treesearch

Michael Alonzo; Joseph P. McFadden; David J. Nowak; Dar A. Roberts

2016-01-01

Cities measure the structure and function of their urban forest resource to optimize forest managementand the provision of ecosystem services. Measurements made using plot sampling methods yield useful results including citywide or land-use level estimates of species counts, leaf area, biomass, and air pollution reduction. However, these quantities are statistical...

Forest statistics of the United States, 1992 metric units.

Treesearch

W. Brad Smith; Joanne L. Faulkner; Douglas S. Powell

1994-01-01

The 1987 Resources Planning Act (RPA) Assessment was conducted to provide current information on the nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or state. Statistics are provided in a metric format for international use.

Annual Dynamics of Forest Areas in South America during 2007-2010 at 50-m Spatial Resolution

NASA Astrophysics Data System (ADS)

Qin, Y.; Xiao, X.; Dong, J.; Zhou, Y.; Wang, J.; Doughty, R.; Chen, Y.; Zou, Z.; Moore, B., III

2017-12-01

The user community has an urgent need for high accuracy tropical forest distribution and spatio-temporal changes since tropical forests are facing defragmentation and persistent clouds. In this study, we selected South America as a hotspot and presented a robust approach to map annual forests during 2007-2010 based on the coupled greenness-relevant MOD13Q1 NDVI and structure/biomass-relevant ALOS PALSAR time series data. We analyzed the consistency and uncertainty among eight major forest maps at continental, country, and pixel scales. The 50-m PALSAR/MODIS forest area in South America was about 8.63×106 km2 in 2010. Large differences in total forest area (8.2×106 km2-12.7×106 km2) existed among these forest products. Forest products generated under a similar forest definition had similar or even larger variation than those generated under differing forest definitions. One needs to consider leaf area index as an adjusting factor and use much higher threshold values in the VCF datasets to estimate forest cover. Analyses of PALSAR/MODIS forest maps showed a relatively small and equivalent rate of loss (3.2×104 km2 year-1) in net forest cover to that of FAO FRA (3.3×104 km2 year-1). PALSAR/MODIS forest maps showed that more and more deforestation occurred in the intact forest areas. The rate of forest loss (1.95×105 km2 year-1) was higher than that of Global Forest Watch (0.81×105 km2 year-1). Caution should be used when using the different forest maps to analyze forest loss and make policies regarding forest ecosystem services and biodiversity conservation.

Effectiveness of Protected Areas in the Pan-Tropics and International Aid for Conservation

NASA Astrophysics Data System (ADS)

Kim, D. H.

2015-12-01

Protected areas are crucial for tropical forest conservation efforts. Estimation of the effectiveness of protected areas is thus important for evaluating the efficacy of forest conservation policies and priorities. However, comprehensive evaluation of the long-term effects of Protected Areas and international aid is lacking. However, with the recent availability of long-term, large-scale forest cover change data at 30-m resolution, it has become possible to address some of the issues surrounding the effectiveness of protected areas. To evaluate the effectiveness of Protected Areas in the pan-tropics and international aid for conservation, we use the 30m resolution data along with econometrics 1) to estimate avoided deforestation by PAs in the tropics during the 2000s, 2) estimate effects of international aid on avoided deforestation by PAs and 3) analyze the relationships between the socio-economic variables and increases in deforestation, avoided deforestation by PAs and effects of international aid. Our results show that protected areas avoided 83,500 ± 21,200 km2 of deforestation during the 2000s. Brazil showed the highest estimates of effects of international aid on the avoided deforestation of 22 m2/USD, which is about 50 times higher compared to Indonesia (0.5 m2/USD). The regression analysis between avoided deforestation, effects of international aid and socio-economic factors demonstrates that PAs have been relatively more effective in the countries where the deforestation pressures were increasing and that governance and forest change monitoring capacity may be important factors enhancing the efficacy of international aid. Our study presents the first pan-tropical analysis of the long-term evaluation of the effectiveness of protected areas, international aid and their regulating factors using spatially explicit fine resolution data. Our findings allow us to pinpoint where conservation initiatives and resource management are effectively practiced and to discover the link with socio-economic factors and their significance and underlying implications for the effectiveness of PAs.

Mapping wetland and forest landscapes in Siberia with Landsat data

NASA Astrophysics Data System (ADS)

Maksyutov, Shamil; Kleptsova, Irina; Glagolev, Mikhail; Sedykh, Vladimir; Kuzmenko, Ekaterina; Silaev, Anton; Frolov, Alexander; Nikolaeva, Svetlana; Fedorov, Alexander

2014-05-01

Landsat data availability provides opportunity for improving the knowledge of the Siberian ecosystems necessary for quantifying the response of the regional carbon cycle to the climate change. We developed a new wetland map based on Landsat data for whole West Siberia aiming at scaling up the methane emission observations. Mid-summer Landsat scenes were used in supervised classification method, based on ground truth data obtained during multiple field surveys. The method allows distinguishing following wetland types: pine-dwarf shrubs-sphagnum bogs or ryams, ridge-hollows complexes, shallow-water complexes, sedge-sphagnum poor fens, herbaceous-sphagnum poor fens, sedge-(moss) poor fens and fens, wooded swamps or sogra, palsa complexes. In our estimates wetlands cover 36% of the taiga area. Total methane emission from WS taiga mires is estimated as 3.6 TgC/yr,which is 77% larger as compared to the earlier estimate based on partial Landsat mapping combined with low resolution map due to higher fraction of fen area. We make an attempt to develop a forest typology system useful for a dynamic vegetation modeling and apply it to the analysis of the forest type distribution for several test areas in West and East Siberia, aiming at capability of mapping whole Siberian forests based on Landsat data. Test region locations are: two in West Siberian middle taiga (Laryegan and Nyagan), and one in East Siberia near Yakutsk. The ground truth data are based on analysis of the field survey, forest inventory data from the point of view of the successional forest type classification. Supervised classification was applied to the areas where ample ground truth and inventory data are available, using several limited area maps and vegetation survey. In Laryegan basin the upland forest areas are dominated (as climax forest species) by Scots pine on sandy soils and Siberian pine with presence of fir and spruce on the others. Those types are separable using Landsat spectral data alone. In the permafrost area around Yakutsk the most widespread succession type is birch to larch succession. Three stages of the birch to larch succession are detectable from Landsat image. When Landsat data is used in both West and East Siberia, distinction between deciduous broad-leaved species (birch, aspen, and willow) is difficult due to similarity in spectral signatures. Same problem exists for distinguishing between dark coniferous species (Siberian pine, fir and spruce). Forest classification can be improved by applying landscape type analysis, such as separation into floodplain, terrace, sloping hills.

New Projections of Global Forest Carbon and Ecosystems at Risk for Increased Greenhouse Gas Emissions From Disturbance and Forest Degradation

NASA Astrophysics Data System (ADS)

Klooster, S.; Potter, C. S.; Genovese, V. B.; Gross, P. M.; Kumar, V.; Boriah, S.; Mithal, V.; Castilla-Rubio, J.

2009-12-01

Widely cited forest carbon values from look-up tables and statistical correlations with aboveground biomass have proven to be inadequate to discern details of national carbon stocks in forest pools. Similarly, global estimates based on biome-average (tropical, temperate, boreal, etc.) carbon measurements are generally insufficient to support REDD incentives (Reductions in Emission from Deforestation in Developing countries). The NASA-CASA (Carnegie-Ames-Stanford Approach) ecosystem model published by Potter et al. (1999 and 2003) offers several unique advantages for carbon accounting that cannot be provided by conventional inventory techniques. First, CASA uses continuous satellite observations to map land cover status and changes in vegetation on a monthly time interval over the past 25 years. NASA satellites observe areas that are too remote or rugged for conventional inventory-based techniques to measure. Second, CASA estimates both aboveground and belowground pools of carbon in all ecosystems (forests, shrublands, croplands, and rangelands). Carbon storage estimates for forests globally are currently being estimated for the Cisco Planetary Skin open collaborative platform (www.planetaryskin.org ) in a new series of CASA model runs using the latest input data from the NASA MODIS satellites, from 2000 to the present. We have also developed an approach for detection of large-scale ecosystem disturbance (LSED) events based on sustained declines in the same satellite greenness data used for CASA modeling. This approach is global in scope, covers more than a decade of observations, and encompasses all potential categories of major ecosystem disturbance - physical, biogenic, and anthropogenic, using advanced methods of data mining and analysis. In addition to quantifying forest areas at various levels of risk for loss of carbon storage capacity, our data mining approaches for LSED events can be adapted to detect and map biophysically unsuitable areas for deforestation worldwide and to develop carbon risk scoring algorithms that can enable large scale finance for conservation and reforestation efforts globally.

Carbon stocks on forestland of the United States, with emphasis on USDA Forest Service ownership

Treesearch

Linda S. Heath; James E. Smith; Christopher W. Woodall; David L. Azuma; Karen L. Waddell

2011-01-01

The U.S. Department of Agriculture Forest Service (USFS) manages one-fifth of the area of forestland in the United States. The Forest Service Roadmap for responding to climate change identified assessing and managing carbon stocks and change as a major element of its plan. This study presents methods and results of estimating current forest carbon stocks and change in...

Carbon stocks on forestland of the United States, with emphaisis on USDA Forest Service ownership

Treesearch

Linda S. Heath; James E. Smith; Christopher W. Woodall; Dave Azuma; Karen L. Waddell

2011-01-01

The U.S. Department of Agriculture Forest Service (USFS) manages one-fifth of the area of forestland in the United States. The Forest Service Roadmap for responding to climate change identified assessing and managing carbon stocks and change as a major element of its plan. This study presents methods and results of estimating current forest carbon stocks and change in...

Predicting live and dead tree basal area of bark beetle affected forests from discrete-return lidar

Treesearch

Benjamin C. Bright; Andrew T. Hudak; Robert McGaughey; Hans-Erik Andersen; Jose Negron

2013-01-01

Bark beetle outbreaks have killed large numbers of trees across North America in recent years. Lidar remote sensing can be used to effectively estimate forest biomass, but prediction of both live and dead standing biomass in beetle-affected forests using lidar alone has not been demonstrated. We developed Random Forest (RF) models predicting total, live, dead, and...

Microscale photo interpretation of forest and nonforest land classes

NASA Technical Reports Server (NTRS)

Aldrich, R. C.; Greentree, W. J.

1972-01-01

Remote sensing of forest and nonforest land classes are discussed, using microscale photointerpretation. Results include: (1.) Microscale IR color photography can be interpreted within reasonable limits of error to estimate forest area. (2.) Forest interpretation is best on winter photography with 97 percent or better accuracy. (3.) Broad forest types can be classified on microscale photography. (4.) Active agricultural land is classified most accurately on early summer photography. (5.) Six percent of all nonforest observations were misclassified as forest.

Carbon stock loss from deforestation through 2013 in Brazilian Amazonia.

PubMed

Nogueira, Euler Melo; Yanai, Aurora M; Fonseca, Frederico O R; Fearnside, Philip Martin

2015-03-01

The largest carbon stock in tropical vegetation is in Brazilian Amazonia. In this ~5 million km(2) area, over 750,000 km(2) of forest and ~240,000 km(2) of nonforest vegetation types had been cleared through 2013. We estimate current carbon stocks and cumulative gross carbon loss from clearing of premodern vegetation in Brazil's 'Legal Amazonia' and 'Amazonia biome' regions. Biomass of 'premodern' vegetation (prior to major increases in disturbance beginning in the 1970s) was estimated by matching vegetation classes mapped at a scale of 1 : 250,000 and 29 biomass means from 41 published studies for vegetation types classified as forest (2317 1-ha plots) and as either nonforest or contact zones (1830 plots and subplots of varied size). Total biomass (above and below-ground, dry weight) underwent a gross reduction of 18.3% in Legal Amazonia (13.1 Pg C) and 16.7% in the Amazonia biome (11.2 Pg C) through 2013, excluding carbon loss from the effects of fragmentation, selective logging, fires, mortality induced by recent droughts and clearing of forest regrowth. In spite of the loss of carbon from clearing, large amounts of carbon were stored in stands of remaining vegetation in 2013, equivalent to 149 Mg C ha(-1) when weighted by the total area covered by each vegetation type in Legal Amazonia. Native vegetation in Legal Amazonia in 2013 originally contained 58.6 Pg C, while that in the Amazonia biome contained 56 Pg C. Emissions per unit area from clearing could potentially be larger in the future because previously cleared areas were mainly covered by vegetation with lower mean biomass than the remaining vegetation. Estimates of original biomass are essential for estimating losses to forest degradation. This study offers estimates of cumulative biomass loss, as well as estimates of premodern carbon stocks that have not been represented in recent estimates of deforestation impacts. © 2014 John Wiley & Sons Ltd.

Sources of variation in nitrous oxide flux from Amazonian ecosystems

NASA Technical Reports Server (NTRS)

Matson, P. A.; Vitousek, P. M.; Livingston, G. P.; Swanberg, N. A.

1990-01-01

Nitrous oxide flux and soil nutrient characteristics were measured in three undisturbed tropical ecosystem types, in cleared and burned areas, and in areas of forest converted to pasture near Manaus, Brazil. Nitrogen mineralization, nitrification, and soil nitrogen pools were high in upland forests on clay soils (terra firme) and low in the sand-type and floodplain (varzea) soils. Nitrous oxide flux followed the same pattern, with an average flux of 1.9 ng/sq cm per hr in terra firme, 0.3 in sand types, and 0.1 in varzea. Flux from recently cleared and burned areas did not differ from terra firme forest, but pastures had significantly elevated fluxes (10.3 ng/sq cm per hr). These data were combined with satellite data-based areal estimates of land cover classes to estimate total N2O-N flux from the intensive study area used by the Amazon Boundary Layer Experiment. Total N2O-N flux from the area was 22.9 kg/h; pastures covered 11 percent of the area but accounted for over 40 percent of the flux.

Brazilian environmental legislation and scenarios for carbon balance in Areas of Permanent Preservation (APP) in dairy livestock regions

NASA Astrophysics Data System (ADS)

Hott, M. C.; Fonseca, L. D.; Andrade, R. G.

2011-12-01

The present study aimed at mapping some categories of Areas of Permanent Preservation (APP) for natural regeneration of semideciduous forests in the regions of Zona da Mata and Campo das Vertentes, Minas Gerais State (Figure 1), and from this to establish what impact the deployment of APP over area of pastures and subsequently milk production and carbon sequestration, considering areas of pasture as one of major factors for the dairy farming in the regions concerned. From the altimetric information from MDE, it was possible to extract morphological and morphometrical data to estimate the areas of APP. We used imagery of MODIS/Terra for extraction of the pastures areas from the vegetation index data NDVI to intersect with the estimated area of APP. In a linear or deterministic scenario of deployment of APPs over in the pasture areas considering that wich are proportionately responsible for sizing the herd, and thus for the milk production in extensive livestock, despite the existence of numerous other factors, there would be an impact 12% in the production of Campo das Vertentes region and 21.5% for the Zona da Mata. In this scenario, according to the carbon balance of forests and livestock, there would be a positive balance with the deployment of areas of permanent preservation and, subsequent promotion of natural regeneration. Considering the current grazing area of the Zona da Mata and Campo das Vertentes, 1.6 million hectares, with the carbon balance estimated at 1 ton/hectare/year, 300,000 hectares would have a balance of 5 ton/hectare/year in whole cycle of 40 years, totaling 200 tons carbon by hectare, or additional 48 million tons fixed, considering 4 tons more than pastures in the case of semideciduous forest. At the end of the cycle or forest climax, there would still be positive carbon balance, estimated as a balance of 2 ton/hectare/year. However, despite the higher carbon balance for the semideciduous forest, compared to livestock, it is important to maintain a balance between conservation of natural resources, land suitability and demand for food, especially for milk in these regions, which provide inputs for the dairy industry. The brazilian environmental legislation faces a turbulent period of change, but certainly it can contribute to increase carbon sequestration.

Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

NASA Astrophysics Data System (ADS)

Jaskierniak, D.; Kuczera, G.; Benyon, R.

2016-04-01

A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

Use of non-invasive genetics to generate core-area population estimates of a threatened predator in the Superior National Forest, USA

USGS Publications Warehouse

Barber-Meyer, Shannon; Ryan, Daniel; Grosshuesch, David; Catton, Timothy; Malick-Wahls, Sarah

2018-01-01

core areas and averaged 52.3 (SD=8.3, range=43-59) during 2015-2017 in the larger core areas. We found no evidence for a decrease or increase in abundance during either period. Lynx density estimates were approximately 7-10 times lower than densities of lynx in northern populations at the low of the snowshoe hare (Lepus americanus) population cycle. To our knowledge, our results are the first attempt to estimate abundance, trend and density of lynx in Minnesota using non-invasive genetic capture-mark-recapture. Estimates such as ours provide useful benchmarks for future comparisons by providing a context with which to assess 1) potential changes in forest management that may affect lynx recovery and conservation, and 2) possible effects of climate change on the depth, density, and duration of annual snow cover and correspondingly, potential effects on snowshoe hares as well.

Satellite Analysis of the Severe 1987 Forest Fires in Northern China and Southeastern Siberia

NASA Technical Reports Server (NTRS)

Cahoon, Donald R., Jr.; Stocks, Brian J.; Levine, Joel S.; Cofer, Wesley R., III; Pierson, Joseph M.

1994-01-01

Meteorological conditions, extremely conducive to fire development and spread in the spring of 1987, resulted in forest fires burning over extremely large areas in the boreal forest zone in northeastern China and the southeastern region of Siberia. The great China fire, one of the largest and most destructive forest fires in recent history, occurred during this period in the Heilongjiang Province of China. Satellite imagery is used to examine the development and areal distribution of 1987 forest fires in this region. Overall trace gas emissions to the atmosphere from these fires are determined using a satellite-derived estimate of area burned in combination with fuel consumption figures and carbon emission ratios for boreal forest fires.

Satellite analysis of the severe 1987 forest fires in northern China and southeastern Siberia

NASA Technical Reports Server (NTRS)

Cahoon, Donald R, Jr.; Stocks, Brian J.; Levine, Joel S.; Cofer, Wesley R., III; Pierson, Joseph M.

1994-01-01

Meteorological conditions, extremely conducive to fire development and spread in the spring of 1987, resulted in forest fires burning over extremely large areas in the boreal forest zone in northeastern China and the southeastern region of Siberia. The great China fire, one of the largest and most destructive forest fires in recent history, occurred during this period in the Heilongjiang Province of China. Satellite imagery is used to examine the development and areal distribution of 1987 forest fires in this region. Overall trace gas emissions to the atmosphere from these fires are determined using a satellite-derived estimate of area burned in combination with fuel consumption figures and carbon emission ratios for boreal forest fires.

Forest Carbon Storage in the Northern Midwest, USA: A Bottom-Up Scaling Approach Combining Local Meteorological and Biometric Data With Regional Forest Inventories

NASA Astrophysics Data System (ADS)

Curtis, P. S.; Gough, C. M.; Vogel, C. S.

2005-12-01

Carbon (C) storage increasingly is considered an important part of the economic return of forestlands, making easily parameterized models for assessing current and future C storage important for both ecosystem and money managers. For the deciduous forests of the northern midwest, USA, detailed information relating annual C storage to local site characteristics can be combined with spatially extensive forest inventories to produce simple, robust models of C storage useful at a variety of scales. At the University of Michigan Biological Station (45o35`' N, 84o42`' W) we measured C storage, or net ecosystem production (NEP), in 65 forest stands varying in age, disturbance history, and productivity (site index) using biometric methods, and independently measured net C exchange at the landscape level using meteorological methods. Our biometric and meteorological estimates of NEP converged to within 1% of each other over five years, providing important confirmation of the robustness of these two approaches applied within northern deciduous forests (Gough et al. 2005). We found a significant relationship between NEP, stand age ( A, yrs), and site index ( Is, m), where NEP = 0.134 + 0.022 * (LN[ A* Is]) (r2 = 0.50, P < 0.02). Site index is an integrated measure of site quality, expressed as 50 yr canopy height. We then used stand age and site index data from forests of similar species composition reported in the USDA Forest Inventory and Analysis database (ncrs2.fs.fed.us/4801/fiadb/) to estimate forest C storage at different scales across the upper midwest, Great Lakes region. Model estimates were validated against independent estimates of C storage for other forests in the region. At the local ecosystem-level (~1 km2) C storage averaged 1.52 Mg ha-1 yr-1. Scaling to the two-county area surrounding our meteorological and biometric study sites, average stand age decreased and site index increased, resulting in estimated storage of 1.62 Mg C ha-1 yr-1, or 0.22 Tg C yr-1 in the 1350 km2 of deciduous forest in this area. For the state of Michigan (31,537 km2 of deciduous forest), average uptake was estimated at 1.55 Mg C ha-1 yr-1, or 4.9 Tg C yr-1 total storage. For the three state region encompassing Minnesota, Michigan, and Wisconsin (97,769 km2 of deciduous forest), we estimated average storage in these forests of 1.51 Mg C ha-1 yr-1, or 14.1 Tg C yr-1 total storage. This storage represents ~ 13 % of regional anthropogenic C emissions (US Department of Energy, 2003). This modest rate of C storage by forests in the region may decrease due to changes in forest succession and land-use, and also in response to climate-driven shifts in the balance between photosynthesis and respiration. Gough C.M., Vogel C.S., Schmid H.P., Su H.-B., and Curtis P.S. 2005. Multi-year convergence of biometric and meteorological estimates of forest carbon storage. Agricultural and Forest Meteorology, In Press.

Ancient human disturbances may be skewing our understanding of Amazonian forests

PubMed Central

McMichael, Crystal N. H.; Matthews-Bird, Frazer; Farfan-Rios, William; Feeley, Kenneth J.

2017-01-01

Although the Amazon rainforest houses much of Earth’s biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests. PMID:28049821

Predicting Costs of Eastern National Forest Wildernesses.

ERIC Educational Resources Information Center

Guldin, Richard W.

1981-01-01

A method for estimating the total direct social costs for proposed wilderness areas is presented. A cost framework is constructed and equations are developed for cost components. To illustrate the study's method, social costs are estimated for a proposed wilderness area in New England. (Author/JN)

National Scale Monitoring Reporting and Verification of Deforestation and Forest Degradation in Guyana

NASA Astrophysics Data System (ADS)

Bholanath, P.; Cort, K.

2015-04-01

Monitoring deforestation and forest degradation at national scale has been identified as a national priority under Guyana's REDD+ Programme. Based on Guyana's MRV (Monitoring Reporting and Verification) System Roadmap developed in 2009, Guyana sought to establish a comprehensive, national system to monitor, report and verify forest carbon emissions resulting from deforestation and forest degradation in Guyana. To date, four national annual assessments have been conducted: 2010, 2011, 2012 and 2013. Monitoring of forest change in 2010 was completed with medium resolution imagery, mainly Landsat 5. In 2011, assessment was conducted using a combination of Landsat (5 and 7) and for the first time, 5m high resolution imagery, with RapidEye coverage for approximately half of Guyana where majority of land use changes were taking place. Forest change in 2013 was determined using high resolution imagery for the whole of Guyana. The current method is an automated-assisted process of careful systematic manual interpretation of satellite imagery to identify deforestation based on different drivers of change. The minimum mapping unit (MMU) for deforestation is 1 ha (Guyana's forest definition) and a country-specific definition of 0.25 ha for degradation. The total forested area of Guyana is estimated as 18.39 million hectares (ha). In 2012 as planned, Guyana's forest area was reevaluated using RapidEye 5 m imagery. Deforestation in 2013 is estimated at 12 733 ha which equates to a total deforestation rate of 0.068%. Significant progress was made in 2012 and 2013, in mapping forest degradation. The area of forest degradation as measured by interpretation of 5 m RapidEye satellite imagery in 2013 was 4 352 ha. All results are subject to accuracy assessment and independent third party verification.

A research on snow distribution in mountainous area using airborne laser scanning

NASA Astrophysics Data System (ADS)

Nishihara, T.; Tanise, A.

2015-12-01

In snowy cold regions, the snowmelt water stored in dams in early spring meets the water demand for the summer season. Thus, snowmelt water serves as an important water resource. However, snowmelt water also can cause snowmelt floods. Therefore, it's necessary to estimate snow water equivalent in a dam basin as accurately as possible. For this reason, the dam operation offices in Hokkaido, Japan conduct snow surveys every March to estimate snow water equivalent in the dam basin. In estimating, we generally apply a relationship between elevation and snow water equivalent. But above the forest line, snow surveys are generally conducted along ridges due to the risk of avalanches or other hazards. As a result, snow water equivalent above the forest line is significantly underestimated. In this study, we conducted airborne laser scanning to measure snow depth in the high elevation area including above the forest line twice in the same target area (in 2012 and 2015) and analyzed the relationships of snow depth above the forest line and some indicators of terrain. Our target area was the Chubetsu dam basin. It's located in central Hokkaido, a high elevation area in a mountainous region. Hokkaido is a northernmost island of Japan. Therefore it's a cold and snowy region. The target range for airborne laser scanning was 10km2. About 60% of the target range was above the forest line. First, we analyzed the relationship between elevation and snow depth. Below the forest line, the snow depth increased linearly with elevation increase. On the other hand, above the forest line, the snow depth varied greatly. Second, we analyzed the relationship between overground-openness and snow depth above the forest line. Overground-openness is an indicator quantifying how far a target point is above or below the surrounding surface. As a result, a simple relationship was clarified. Snow depth decreased linearly as overground-openness increases. This means that areas with heavy snow cover are distributed in valleys and that of light cover are on ridges. Lastly we compared the result of 2012 and that of 2015. The same characteristic of snow depth, above mentioned, was found. However, regression coefficients of linear equations were different according to the weather conditions of each year.

Analyzing Forest Inventory Data from Geo-Located Photographs

NASA Astrophysics Data System (ADS)

Toivanen, Timo; Tergujeff, Renne; Andersson, Kaj; Molinier, Matthieu; Häme, Tuomas

2015-04-01

Forests are widely monitored using a variety of remote sensing data and techniques. Remote sensing offers benefits compared to traditional in-situ forest inventories made by experts. One of the main benefits is that the number of ground reference plots can be significantly reduced. Remote sensing of forests can provide reduced costs and time requirement compared to full forest inventories. The availability of ground reference data has been a bottleneck in remote sensing analysis over wide forested areas, as the acquisition of this data is an expensive and slow process. In this paper we present a tool for estimating forest inventory data from geo-located photographs. The tool can be used to estimate in-situ forest inventory data including estimated biomass, tree species, tree height and diameter. The collected in-situ forest measurements can be utilized as a ground reference material for spaceborne or airborne remote sensing data analysis. The GPS based location information with measured forest data makes it possible to introduce measurements easily as in-situ reference data. The central projection geometry of digital photographs allows the use of the relascope principle [1] to measure the basal area of stems per area unit, a variable very closely associated with tree biomass. Relascope is applied all over the world for forest inventory. Experiments with independent ground reference data have shown that in-situ data analysed from photographs can be utilised as reference data for satellite image analysis. The concept was validated by comparing mobile measurements with 54 independent ground reference plots from the Hyytiälä forest research station in Finland [2]. Citizen scientists could provide the manpower for analysing photographs from forests on a global level and support researchers working on tasks related to forests. This low-cost solution can also increase the coverage of forest management plans, particularly in regions where possibilities to invest on expensive planning work are limited. References [1] Bitterlich, W. (1984) The Relascope Idea: Relative Measurements in Forestry, Commonwealth Agricultural Bureaux, Farnham Royal, 1984. [2] Molinier, M., Hame, T., Toivanen, T., Andersson, K., Mutanen, T., Relasphone -- Mobile phone and interactive applications to collect ground reference biomass data for satellite image analysis, Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, pp. 836-839, 13-18 July 2014, doi: 10.1109/IGARSS.2014.6946554

Estimation of leaf area index using WorldView-2 and Aster satellite image: a case study from Turkey.

PubMed

Günlü, Alkan; Keleş, Sedat; Ercanlı, İlker; Şenyurt, Muammer

2017-10-04

The objective of this study is to estimate the leaf area index (LAI) of a forest ecosystem using two different satellite images, WorldView-2 and Aster. For this purpose, 108 sample plots were taken from pure Crimean pine forest stands of Yenice Forest Management Planning Unit in Ilgaz Forest Management Enterprise, Turkey. Each sample plot was imaged with hemispherical photographs with a fish-eye camera to determine the LAI. These photographs were analyzed with the help of Hemisfer Hemiview software program, and thus, the LAI of each sample plot was estimated. Furthermore, multiple regression analysis method was used to model the statistical relationships between the LAI values and band spectral reflection values and some vegetation indices (Vis) obtained from satellite images. The results show that the high-resolution WorldView-2 satellite image is better than the medium-resolution Aster satellite image in predicting the LAI. It was also seen that the results obtained by using the VIs are better than the bands when the LAI value is predicted with satellite images.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Remote sensing applied to forest resources

NASA Technical Reports Server (NTRS)

Hernandezfilho, P. (Principal Investigator)

1984-01-01

The development of methodologies to classify reforested areas using remotely sensed data is discussed. A preliminary study was carried out in northeast of the Sao Paulo State in 1978. The reforested areas of Pinus spp and Eucalyptus spp were based on the spectral, spatial and temporal characteristics fo LANDSAT imagery. Afterwards, a more detailed study was carried out in the Mato Grosso do Sul State. The reforested areas were mapped in functions of the age (from: 0 to 1 year, 1 to 2 years, 2 to 3 years, 3 to 4 years, 4 to 5 years and 5 to 6 years) and of the heterogeneity stand (from: 0 to 20%, 20 to 40%, 40 to 60%, 60 to 80% and 80 to 100%). The relative differences between the artificial forest areas, estimated from LANDSAT data and ground information, varied from -8.72 to +9.49%. The estimation of forest volume through a multistage sampling technique, with probability proportional to size, is also discussed.

Distribution of Aboveground Live Biomass in the Amazon Basin

NASA Technical Reports Server (NTRS)

Saatchi, S. S.; Houghton, R. A.; DosSantos Alvala, R. C.; Soares, J. V.; Yu, Y.

2007-01-01

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

Estimates of critical acid loads and exceedances for forest soils across the conterminous United States.

PubMed

McNulty, Steven G; Cohen, Erika C; Moore Myers, Jennifer A; Sullivan, Timothy J; Li, Harbin

2007-10-01

Concern regarding the impacts of continued nitrogen and sulfur deposition on ecosystem health has prompted the development of critical acid load assessments for forest soils. A critical acid load is a quantitative estimate of exposure to one or more pollutants at or above which harmful acidification-related effects on sensitive elements of the environment occur. A pollutant load in excess of a critical acid load is termed exceedance. This study combined a simple mass balance equation with national-scale databases to estimate critical acid load and exceedance for forest soils at a 1-km(2) spatial resolution across the conterminous US. This study estimated that about 15% of US forest soils are in exceedance of their critical acid load by more than 250eqha(-1)yr(-1), including much of New England and West Virginia. Very few areas of exceedance were predicted in the western US.

Timber resource statistics for the Upper Yukon inventory unit, Alaska, 1980.

Treesearch

Willem W.S. van Hees

1987-01-01

The 1980 inventory of the forest resources of the Upper Yukon unit was designed to produce inventory estimates of timberland area, volume of timber, and volumes of timber growth and mortality. Timberland area is estimated at 742,000 acres. Cubic-foot volume on all timberland is estimated at 475 million cubic feet. Timber growth and mortality are estimated at -615,000...

Use of passive UAS imaging to measure biophysical parameters in a southern Rocky Mountain subalpine forest

NASA Astrophysics Data System (ADS)

Caldwell, M. K.; Sloan, J.; Mladinich, C. S.; Wessman, C. A.

2013-12-01

Unmanned Aerial Systems (UAS) can provide detailed, fine spatial resolution imagery for ecological uses not otherwise obtainable through standard methods. The use of UAS imagery for ecology is a rapidly -evolving field, where the study of forest landscape ecology can be augmented using UAS imagery to scale and validate biophysical data from field measurements to spaceborne observations. High resolution imagery provided by UAS (30 cm2 pixels) offers detailed canopy cover and forest structure data in a time efficient and inexpensive manner. Using a GoPro Hero2 (2 mm focal length) camera mounted in the nose cone of a Raven unmanned system, we collected aerial and thermal data monthly during the summer 2013, over two subalpine forests in the Southern Rocky Mountains in Colorado. These forests are dominated by lodgepole pine (Pinus ponderosae) and have experienced insect-driven (primarily mountain pine beetle; MPB, Dendroctonus ponderosae) mortality. Objectives of this study include observations of forest health variables such as canopy water content (CWC) from thermal imagery and leaf area index (LAI), biomass and forest productivity from the Normalized Difference Vegetation Index (NDVI) from UAS imagery. Observations were, validated with ground measurements. Images were processed using a combination of AgiSoft Photoscan professional software and ENVI remote imaging software. We utilized the software Leaf Area Index Calculator (LAIC) developed by Córcoles et al. (2013) for calculating LAI from digital images and modified to conform to leaf area of needle-leaf trees as in Chen and Cihlar (1996) . LAIC uses a K-means cluster analysis to decipher the RGB levels for each pixel and distinguish between green aboveground vegetation and other materials, and project leaf area per unit of ground surface area (i.e. half total needle surface area per unit area). Preliminary LAIC UAS data shows summer average LAI was 3.8 in the most dense forest stands and 2.95 in less dense stands. These data correspond to 4.8 and 2.2 respectively from in situ Licor LAI 2200 measurements (Wilcoxon signed rank p value of 0.25, indicating there is no significant difference between LAIC and field measurements). Imagery over plots indicates about 12% canopy cover from standing dead vegetation within plots, which corresponds to about a 10% estimate of standing dead measured in the field. The next steps for analysis include calculating NDVI and CWC for plot-level vegetation, and scaling to the surrounding forested landscape. These high resolution estimates from UAS imagery will provide forest stand-to- landscape level biophysical data for forest health assessments, management, drought and disturbance monitoring and climate change modeling. Chen, J. M., and J. Cihlar. 1996. Retrieving LAI of boreal conifer forests using Landsat TM images. RSE 55:153-162. Córcoles, J., J. Ortega, D. Hernández, and M. Moreno. 2013. Use of digital photography from unmanned aerial vehicles for estimation of LAI in onion. EJoA. 45:96-104.

Estimating erosion risk on forest lands using improved methods of discriminant analysis

Treesearch

J. Lewis; R. M. Rice

1990-01-01

A population of 638 timber harvest areas in northwestern California was sampled for data related to the occurrence of critical amounts of erosion (>153 m3 within 0.81 ha). Separate analyses were done for forest roads and logged areas. Linear discriminant functions were computed in each analysis to contrast site conditions at critical plots with randomly selected...

Tree basal area as an index of thermal cover for elk.

Treesearch

J. Edward Dealy

1985-01-01

The relationship of basal area to crown closure was studied in five major forest types of the Blue Mountains of Oregon and Washington. The regressions developed give wildlife and forest managers a tool for estimating the amount of crown closure if data are not available from stand examinations. Information is used in determining quantity and quality of elk thermal...

Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

Treesearch

S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

2012-01-01

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

Potential impact of air quality restrictions on logging residue burning

Treesearch

Owen P. Cramer; James N. Westwood

1970-01-01

The number of potential burning days and the potential burn acreage under smoke control restrictions were estimated for hypothetical forest areas on both sides of a pollution prone area, the Willamette Valley in western Oregon. On the basis of a sample of 2 dry years, the greatest impact on burning operations applied to low elevation forests west of the Valley. The...

Using a terrestrial ecosystem survey to estimate the historical density of ponderosa pine trees

Treesearch

Scott R. Abella; Charles W. Denton; David G. Brewer; Wayne A. Robbie; Rory W. Steinke; W. Wallace Covington

2011-01-01

Maps of historical tree densities for project areas and landscapes may be useful for a variety of management purposes such as determining site capabilities and planning forest thinning treatments. We used the U.S. Forest Service Region 3 terrestrial ecosystem survey in a novel way to determine if the ecosystem classification is a useful a guide for estimating...

Estimating Pinus palustris tree diameter and stem volume from tree height, crown area and stand-level parameters

Treesearch

C.A. Gonzalez-Benecke; Salvador A. Gezan; Lisa J. Samuelson; Wendell P. Cropper; Daniel J. Leduc; Timothy A. Martin

2014-01-01

Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height (dbh) and merchantable stem volume (V) using data obtained from field measurements. We used...

Detecting and Quantifying Forest Change: The Potential of Existing C- and X-Band Radar Datasets.

PubMed

Tanase, Mihai A; Ismail, Ismail; Lowell, Kim; Karyanto, Oka; Santoro, Maurizio

2015-01-01

This paper evaluates the opportunity provided by global interferometric radar datasets for monitoring deforestation, degradation and forest regrowth in tropical and semi-arid environments. The paper describes an easy to implement method for detecting forest spatial changes and estimating their magnitude. The datasets were acquired within space-borne high spatial resolutions radar missions at near-global scales thus being significant for monitoring systems developed under the United Framework Convention on Climate Change (UNFCCC). The approach presented in this paper was tested in two areas located in Indonesia and Australia. Forest change estimation was based on differences between a reference dataset acquired in February 2000 by the Shuttle Radar Topography Mission (SRTM) and TanDEM-X mission (TDM) datasets acquired in 2011 and 2013. The synergy between SRTM and TDM datasets allowed not only identifying changes in forest extent but also estimating their magnitude with respect to the reference through variations in forest height.

Using aerial photography to estimate wood suitable for charcoal in managed oak forests

NASA Astrophysics Data System (ADS)

Ramírez-Mejía, D.; Gómez-Tagle, A.; Ghilardi, A.

2018-02-01

Mexican oak forests (genus Quercus) are frequently used for traditional charcoal production. Appropriate management programs are needed to ensure their long-term use, while conserving the biodiversity and ecosystem services, and associated benefits. A key variable needed to design these programs is the spatial distribution of standing woody biomass. A state-of-the-art methodology using small format aerial photographs was developed to estimate the total aboveground biomass (AGB) and aboveground woody biomass suitable for charcoal making (WSC) in intensively managed oak forests. We used tree crown area (CAap) measurements from very high-resolution (30 cm) orthorectified small format digital aerial photographs as the predictive variable. The CAap accuracy was validated using field measurements of the crown area (CAf). Allometric relationships between: (a) CAap versus AGB, and (b) CAap versus WSC had a high significance level (R 2 > 0.91, p < 0.0001). This approach shows that it is possible to obtain sound biomass estimates as a function of the crown area derived from digital small format aerial photographs.

Epiphyte Water Retention and Evaporation in Native and Invaded Tropical Montane Cloud Forests in Hawaii

NASA Astrophysics Data System (ADS)

Mudd, R. G.; Giambelluca, T. W.

2006-12-01

Epiphyte water retention was quantified at two montane cloud forest sites in Hawai'i Volcanoes National Park, one native and the other invaded by an alien tree species. Water storage elements measured included all epiphytic mosses, leafy liverworts, and filmy ferns. Tree surface area was estimated and a careful survey was taken to account for all epiphytes in the sample area of the forest. Samples were collected and analyzed in the lab for epiphyte water retention capacity (WRC). Based on the volume of the different kinds of epiphytes and their corresponding WRC, forest stand water retention capacity for each survey area was estimated. Evaporation from the epiphyte mass was quantified using artificial reference samples attached to trees that were weighed at intervals to determine changes in stored water on days without significant rain or fog. In addition, a soil moisture sensor was wrapped in an epiphyte sample and left in the forest for a 6-day period. Epiphyte biomass at the Native Site and Invaded Site were estimated to be 2.89 t ha-1 and 1.05 t ha-1, respectively. Average WRC at the Native Site and Invaded Site were estimated at 1.45 mm and 0.68 mm, respectively. The difference is likely due to the presence of the invasive Psidium cattleianum at the Invaded Site because its smooth stem surface is unable to support a significant epiphytic layer. The evaporation rate from the epiphyte mass near WSC for the forest stand at the Native Site was measured at 0.38 mm day-1, which represented 10.6 % of the total ET from the forest canopy at the Native Site during the period. The above research has been recently complemented by a thorough investigation of the WSC of all water storage elements (tree stems, tree leaves, shrubs, grasses, litter, fallen branches, and epiphytes) at six forested sites at different elevations within, above, and below the zone of frequent cloud-cover. The goal of this study was to create an inexpensive and efficient methodology for acquiring estimates of above-ground water retention in different types of forests by means of minimally-destructive sampling and surveying. The results of this work serve as baseline data providing a range of possible values of the water retention of specific forest elements and the entire above-ground total where no values have been previously recorded.

[Estimation of carbonaceous gases emission from forest fires in Xiao Xing'an Mountains of Northeast China in 1953-2011].

PubMed

Hu, Hai-Qing; Luo, Bi-Zhen; Wei, Shu-Jing; Sun, Long; Wei, Shu-Wei; Wen, Zheng-Min

2013-11-01

Based on the forest resources investigation data and the forest fire inventory in 1953-2011, in combining with our field research in burned areas and our laboratory experiments, this paper estimated the carbonaceous gases carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), and nonmethane hydrocarbons (NMHC) emission from the forest fires in Xiao Xing' an Mountains of Heilongjiang Province, Northeast China in 1953-2011. The total carbon emission from the forest fires in the Xiao Xing'an Mountains in 1953-2011 was 1.12 x 10(7) t, and the annual emission was averagely 1.90 x10(5) t, accounting for 1.7% of the annual average total carbon emission from the forest fires in China. The emission of CO2, CO, CH4, and NMHC was 3.39 x 10(7), 1.94 x 10(5), 1.09 x 10(5), and 7.46 x 10(4) t, respectively, and the corresponding annual average emission was 5.74 x 10(5), 3.29 x 10(4), 1.85 x 10(3), and 1.27 x 10(3) t, accounting for 1.4%, 1.2%, 1.7%, and 1.1% of the annual carbonaceous gases emitted from the forest fires in China, respectively. The combustion efficiency and the carbon emission per unit burned area of different forest types decreased in order of coniferous forest > broad-leaved forest > coniferous broadleaved mixed forest. Some rational forest fire management measures were put forward.

Basic data on forest area and timber volumes from the southern forest survey, 1932-1936

Treesearch

William A. Duerr

1932-01-01

In Response to strong demand, estimates from the Forest Survey of 1932-1936 are presented in this report on forest acreage and timber volumes by county in the states of the lower South. Although these figures are old and are highly unreliable for individual counties, they are useful as source data in compiling information for groups of counties that differ from the...

Secondary forest succession in a tropical dry forest: patterns of development across a 50-year chronosequence in lowland Bolivia

Treesearch

Deborah K. Kennard

2002-01-01

Stand structure, species richness and population structures of tree species were characterized in 12 stands representing 50 y of succession following slash-and-burn agriculture in a tropical dry forest in lowland Bolivia. Estimates of tree species richness, canopy cover and basal area reached or surpassed 75% of mature forest levels in the 5-, 8-, and 23-y-old stands...

The importance of age-related decline in forest NPP for modeling regional carbon balances.

PubMed

Zaehle, Sönke; Sitch, Stephen; Prentice, I Colin; Liski, Jari; Cramer, Wolfgang; Erhard, Markus; Hickler, Thomas; Smith, Benjamin

2006-08-01

We show the implications of the commonly observed age-related decline in aboveground productivity of forests, and hence forest age structure, on the carbon dynamics of European forests in response to historical changes in environmental conditions. Size-dependent carbon allocation in trees to counteract increasing hydraulic resistance with tree height has been hypothesized to be responsible for this decline. Incorporated into a global terrestrial biosphere model (the Lund-Potsdam-Jena model, LPJ), this hypothesis improves the simulated increase in biomass with stand age. Application of the advanced model, including a generic representation of forest management in even-aged stands, for 77 European provinces shows that model-based estimates of biomass development with age compare favorably with inventory-based estimates for different tree species. Model estimates of biomass densities on province and country levels, and trends in growth increment along an annual mean temperature gradient are in broad agreement with inventory data. However, the level of agreement between modeled and inventory-based estimates varies markedly between countries and provinces. The model is able to reproduce the present-day age structure of forests and the ratio of biomass removals to increment on a European scale based on observed changes in climate, atmospheric CO2 concentration, forest area, and wood demand between 1948 and 2000. Vegetation in European forests is modeled to sequester carbon at a rate of 100 Tg C/yr, which corresponds well to forest inventory-based estimates.

Midcycle survey of Arkansas' forest resources

Treesearch

Roy C. Beltz; Randall Leister; Walter R. Smith

1987-01-01

This report summarizes an interim survey of Arkansas’ forest resources. Field work was completed in April 1985. The survey provides new estimates of forest area and inventory for both the State’s softwoods and hardwoods. This survey was cooperative effort with the Arkansas forestry commission, the soil conservation service, the statistical reporting service, and the...

Forest statistics for Maine: 1971 and 1982

Treesearch

Douglas S. Powell; David R. Dickson

1984-01-01

A statistical report on the third forest survey of Maine (1982) and reprocessed data from the second survey (1971). Results of the surveys are displayed in a 169 tables containing estimates of forest and timberland area, numbers of trees, timber volume, tree biomass, timber products output, and components of average annual net change in growing-stock volume for the...

Hardwood timber resources of the Douglas-fir subregion.

Treesearch

Melvin E. Metcalf

1965-01-01

The statistics on hardwood timber volume and type area presented here are being made available in response to the increasing interest in this resource in western Oregon and western Washington. These estimates are based on data obtained by the U.S. Forest Service in the course of timber inventories carried out by National Forest Administration on National Forest lands...

Carbon pools and fluxes in small temperate forest landscapes: Variability and implications for sampling design

Treesearch

John B. Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; Richard A. Birdsey; Scott V. Ollinger; Michael G. Ryan

2010-01-01

Assessing forest carbon storage and cycling over large areas is a growing challenge that is complicated by the inherent heterogeneity of forest systems. Field measurements must be conducted and analyzed appropriately to generate precise estimates at scales large enough for mapping or comparison with remote sensing data. In this study we examined...

Commonwealth of the Northern Mariana Islands' forest resources, 2004

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 37 field plots on the islands of Rota, Tinian, and Saipan in the Commonwealth of the Northern Mariana Islands (CNMI). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Timber resource statistics of south-central Alaska, 2003.

Treesearch

Willem W.S. van Hees

2005-01-01

Estimates of timber resources for south-central Alaska are presented. Data collection began in 2000 and was completed in 2003. All forest lands over all ownerships were considered for sampling. The inventory unit was, roughly, the region between Icy Bay to the east and Kodiak Island to the west. Forest lands within national forest wilderness study areas and recommended...

Estimating leaf area and leaf biomass of open-grown deciduous urban trees

Treesearch

David J. Nowak

1996-01-01

Logarithmic regression equations were developed to predict leaf area and leaf biomass for open-grown deciduous urban trees based on stem diameter and crown parameters. Equations based on crown parameters produced more reliable estimates. The equations can be used to help quantify forest structure and functions, particularly in urbanizing and urban/suburban areas.

Monitoring of reforestation on burnt areas in Western Russia using Landsat time series

NASA Astrophysics Data System (ADS)

Vorobev, Oleg; Kurbanov, Eldar

2017-04-01

Forest fires are main disturbance factor for the natural ecosystems, especially in boreal forests. Monitoring for the dynamic of forest cover regeneration in the post-fire period of ecosystem recovery is crucial to both estimation of forest stands and forest management. In this study, on the example of burnt areas of 2010 wildfires in Republic Mari El of Russian Federation we estimated post-fire dynamic of different classes of vegetation cover between 2011-2016 years with the use of time series Landsat satellite images. To validate the newly obtained thematic maps we used 80 test sites with independent field data, as well Canopus-B images of high spatial resolution. For the analysis of the satellite images we referred to Normalized Differenced Vegetation Index (NDVI) and Tasseled Cap transformation. The research revealed that at the post-fire period the area of thematic classes "Reforestation of the middle and low density" has maximum cover (44%) on the investigated burnt area. On the burnt areas of 2010 there is ongoing active process of grass overgrowing (up to 20%), also there are thematic classes of deadwood (15%) and open spaces (10%). The results indicate that there is mostly natural regeneration of tree species pattern corresponding to the pre-fire condition. Forest plantations cover only 2% of the overall burnt area. By the 2016 year the NDVI parameters of young vegetation cover were recovered to the pre-fire level as well. The overall unsupervised classification accuracy of more than 70% shows high degree of agreement between the thematic map and the ground truth data. The research results can be applied for the long term succession monitoring and management plan development for the reforestation activities on the lands disturbed by fire.

Application of Remote Sensing for Forest Management in Nepal

NASA Astrophysics Data System (ADS)

Bajracharya, B.; Matin, M. A.

2016-12-01

Large area of the Hindu Kush Himalayan (HKH) region is covered by forest that is playing a vital role to address the challenges of climate change and livelihood options for a growing population. Effective management of forest cover needs establishment of regular monitoring system for forest. Supporting REDD assessment needs reliable baseline assessment of forest biomass and its monitoring at multiple scale. Adaptation of forest to climate change needs understanding vulnerability of forests and dependence of local communities on these forest. We present here different forest monitoring products developed under the SERVIR-Himalaya programme to address these issues. Landsat 30 meter images were used for decadal land cover change assessment and annual forest change hotspot monitoring. Methodology developed for biomass estimation at national and sub-national level biomass estimation. Decision support system was developed for analysis of forest vulnerability and dependence and selection of adaptation options based on resource availability. These products are forming the basis for development of an integrated system that will be very useful for comprehensive forest monitoring and long term strategy development for sustainable forest management.

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks.

PubMed

Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong

2014-11-01

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.

Where Occupation and Environment Overlap: US Forest Service Worker Exposure to Libby Amphibole Fibers

PubMed Central

Harper, Martin; Butler, Corey; Berry, David; Wroble, Julie

2015-01-01

The National Institute for Occupational Safety and Health (NIOSH) conducted an evaluation of exposures to asbestiform amphibole, known as Libby Amphibole (LA), to personnel from the US Department of Agriculture-Forest Service (USFS) working in the Kootenai National Forest near a former vermiculite mine close to Libby, Montana. LA is associated with vermiculite that was obtained from this mine; mining and processing over many years have resulted in the spread of LA into the surrounding Kootenai Forest where it has been found in tree bark, soil, and forest floor litter. As a result of this and other contamination, Libby and surrounding areas have been designated a “Superfund” site by the US Environmental Protection Agency (EPA). This article describes the application of EPA methods for assessing cancer risks to NIOSH sampling results. Phase-contrast microscopy for airborne asbestos fiber evaluation was found to be less useful than transmission electron microscopy in the presence of interfering organic (plant) fibers. NIOSH Method 7402 was extended by examination of larger areas of the filter, but fiber counts remained low. There are differences between counting rules in NIOSH 7402 and the ISO method used by EPA but these are minor in the context of the uncertainty in concentration estimates from the low counts. Estimates for cancer risk are generally compatible with those previously estimated by the EPA. However, there are limitations to extrapolating these findings of low risk throughout the entire area and to tasks that were not evaluated. PMID:25715191

Where occupation and environment overlap: US Forest Service worker exposure to Libby Amphibole fibers.

PubMed

Harper, Martin; Butler, Corey; Berry, David; Wroble, Julie

2015-01-01

The National Institute for Occupational Safety and Health (NIOSH) conducted an evaluation of exposures to asbestiform amphibole, known as Libby Amphibole (LA), to personnel from the US Department of Agriculture-Forest Service (USFS) working in the Kootenai National Forest near a former vermiculite mine close to Libby, Montana. LA is associated with vermiculite that was obtained from this mine; mining and processing over many years have resulted in the spread of LA into the surrounding Kootenai Forest where it has been found in tree bark, soil, and forest floor litter. As a result of this and other contamination, Libby and surrounding areas have been designated a "Superfund" site by the US Environmental Protection Agency (EPA). This article describes the application of EPA methods for assessing cancer risks to NIOSH sampling results. Phase-contrast microscopy for airborne asbestos fiber evaluation was found to be less useful than transmission electron microscopy in the presence of interfering organic (plant) fibers. NIOSH Method 7402 was extended by examination of larger areas of the filter, but fiber counts remained low. There are differences between counting rules in NIOSH 7402 and the ISO method used by EPA but these are minor in the context of the uncertainty in concentration estimates from the low counts. Estimates for cancer risk are generally compatible with those previously estimated by the EPA. However, there are limitations to extrapolating these findings of low risk throughout the entire area and to tasks that were not evaluated.

Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

PubMed Central

Avtar, Ram; Suzuki, Rikie; Sawada, Haruo

2014-01-01

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal. PMID:24465908

Carbon Storages in Plantation Ecosystems in Sand Source Areas of North Beijing, China

PubMed Central

Liu, Xiuping; Zhang, Wanjun; Cao, Jiansheng; Shen, Huitao; Zeng, Xinhua; Yu, Zhiqiang; Zhao, Xin

2013-01-01

Afforestation is a mitigation option to reduce the increased atmospheric carbon dioxide levels as well as the predicted high possibility of climate change. In this paper, vegetation survey data, statistical database, National Forest Resource Inventory database, and allometric equations were used to estimate carbon density (carbon mass per hectare) and carbon storage, and identify the size and spatial distribution of forest carbon sinks in plantation ecosystems in sand source areas of north Beijing, China. From 2001 to the end of 2010, the forest areas increased more than 2.3 million ha, and total carbon storage in forest ecosystems was 173.02 Tg C, of which 82.80 percent was contained in soil in the top 0–100 cm layer. Younger forests have a large potential for enhancing carbon sequestration in terrestrial ecosystems than older ones. Regarding future afforestation efforts, it will be more effective to increase forest area and vegetation carbon density through selection of appropriate tree species and stand structure according to local climate and soil conditions, and application of proper forest management including land-shaping, artificial tending and fencing plantations. It would be also important to protect the organic carbon in surface soils during forest management. PMID:24349223

Survey of Hylobates agilis albibarbis in a logged peat-swamp forest: Sabangau catchment, Central Kalimantan.

PubMed

Buckley, Cara; Nekaris, K A I; Husson, Simon John

2006-10-01

Few data are available on gibbon populations in peat-swamp forest. In order to assess the importance of this habitat for gibbon conservation, a population of Hylobates agilis albibarbis was surveyed in the Sabangau peat-swamp forest, Central Kalimantan, Indonesia. This is an area of about 5,500 km(2) of selectively logged peat-swamp forest, which was formally gazetted as a national park during 2005. The study was conducted during June and July 2004 using auditory sampling methods. Five sample areas were selected and each was surveyed for four consecutive days by three teams of researchers at designated listening posts. Researchers recorded compass bearings of, and estimated distances to, singing groups. Nineteen groups were located. Population density is estimated to be 2.16 (+/-0.46) groups/km(2). Sightings occurring either at the listening posts or that were obtained by tracking in on calling groups yielded a mean group size of 3.4 individuals, hence individual gibbon density is estimated to be 7.4 (+/-1.59) individuals/km(2). The density estimates fall at the mid-range of those calculated for other gibbon populations, thus suggesting that peat-swamp forest is an important habitat for gibbon conservation in Borneo. A tentative extrapolation of results suggests a potential gibbon population size of 19,000 individuals within the mixed-swamp forest habitat sub-type in the Sabangau. This represents one of the largest remaining continuous populations of Bornean agile gibbons. The designation of the Sabangau forest as a national park will hopefully address the problem of illegal logging and hunting in the region. Further studies should note any difference in gibbon density post protection.

Extracting Features of Acacia Plantation and Natural Forest in the Mountainous Region of Sarawak, Malaysia by ALOS/AVNIR2 Image

NASA Astrophysics Data System (ADS)

Fadaei, H.; Ishii, R.; Suzuki, R.; Kendawang, J.

2013-12-01

The remote sensing technique has provided useful information to detect spatio-temporal changes in the land cover of tropical forests. Land cover characteristics derived from satellite image can be applied to the estimation of ecosystem services and biodiversity over an extensive area, and such land cover information would provide valuable information to global and local people to understand the significance of the tropical ecosystem. This study was conducted in the Acacia plantations and natural forest situated in the mountainous region which has different ecological characteristic from that in flat and low land area in Sarawak, Malaysia. The main objective of this study is to compare extract the characteristic of them by analyzing the ALOS/AVNIR2 images and ground truthing obtained by the forest survey. We implemented a ground-based forest survey at Aacia plantations and natural forest in the mountainous region in Sarawak, Malaysia in June, 2013 and acquired the forest structure data (tree height, diameter at breast height (DBH), crown diameter, tree spacing) and spectral reflectance data at the three sample plots of Acacia plantation that has 10 x 10m area. As for the spectral reflectance data, we measured the spectral reflectance of the end members of forest such as leaves, stems, road surface, and forest floor by the spectro-radiometer. Such forest structure and spectral data were incorporated into the image analysis by support vector machine (SVM) and object-base/texture analysis. Consequently, land covers on the AVNIR2 image were classified into three forest types (natural forest, oil palm plantation and acacia mangium plantation), then the characteristic of each category was examined. We additionally used the tree age data of acacia plantation for the classification. A unique feature was found in vegetation spectral reflectance of Acacia plantations. The curve of the spectral reflectance shows two peaks around 0.3μm and 0.6 - 0.8μm that can be assumed to be corresponded to the reflectance from the bare land part (soil) and forest crown in the Acacia forest, respectively. In accordance with this spectral characteristic, we can estimate the proportional areas of the bare land and crown cover of the tree in the acacia plantation forest that will provide essential information for evaluating the forest ecosystem. We will define Bare land and Tree Crown Ratio Index (BTRI) that represent ratio of the areas of tree crown to areas of their access roads. Such information will delineate the characteristics of Acacia plantation and natural forest in mountainous region, and enable us to compare them with the plantation and forest in flat and low land.

Updating stand-level forest inventories using airborne laser scanning and Landsat time series data

NASA Astrophysics Data System (ADS)

Bolton, Douglas K.; White, Joanne C.; Wulder, Michael A.; Coops, Nicholas C.; Hermosilla, Txomin; Yuan, Xiaoping

2018-04-01

Vertical forest structure can be mapped over large areas by combining samples of airborne laser scanning (ALS) data with wall-to-wall spatial data, such as Landsat imagery. Here, we use samples of ALS data and Landsat time-series metrics to produce estimates of top height, basal area, and net stem volume for two timber supply areas near Kamloops, British Columbia, Canada, using an imputation approach. Both single-year and time series metrics were calculated from annual, gap-free Landsat reflectance composites representing 1984-2014. Metrics included long-term means of vegetation indices, as well as measures of the variance and slope of the indices through time. Terrain metrics, generated from a 30 m digital elevation model, were also included as predictors. We found that imputation models improved with the inclusion of Landsat time series metrics when compared to single-year Landsat metrics (relative RMSE decreased from 22.8% to 16.5% for top height, from 32.1% to 23.3% for basal area, and from 45.6% to 34.1% for net stem volume). Landsat metrics that characterized 30-years of stand history resulted in more accurate models (for all three structural attributes) than Landsat metrics that characterized only the most recent 10 or 20 years of stand history. To test model transferability, we compared imputed attributes against ALS-based estimates in nearby forest blocks (>150,000 ha) that were not included in model training or testing. Landsat-imputed attributes correlated strongly to ALS-based estimates in these blocks (R2 = 0.62 and relative RMSE = 13.1% for top height, R2 = 0.75 and relative RMSE = 17.8% for basal area, and R2 = 0.67 and relative RMSE = 26.5% for net stem volume), indicating model transferability. These findings suggest that in areas containing spatially-limited ALS data acquisitions, imputation models, and Landsat time series and terrain metrics can be effectively used to produce wall-to-wall estimates of key inventory attributes, providing an opportunity to update estimates of forest attributes in areas where inventory information is either out of date or non-existent.

Study and Evaluation of the Alcublas (Valencia, Spain) forest fire of Summer 2012

NASA Astrophysics Data System (ADS)

Mora Sanchez, Francisco; Lopez-Baeza, Ernesto

This work studies and quantifies the forest fire that took place in the province of Valencia, Spain, that particularly affected the municipality of Alcublas. This fire was one of the most intense and catastrophic fires that extended over the Valencian Community. Besides quantifying the area affected by the fire according to a severity index, the analysis was carried out from different viewpoints, namely land use, municipal, and cadastral. The data used were, on the one hand, two images from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite, respectively before and after the fire. On the other hand, we also used CORINE Land Cover 2006 Land Use data, a digital terrain model (DTM), the cadastre or land registration from Alcublas and the Spanish topographic map at scale 1:25000 (MTN25). The method used consisted of different steps: atmospheric correction of the images with the dark-object subtraction technique, topographic correction of the images with a 5 m resolution DTM and the Minnaert method, and the elimination of the Landsat 7 Scan Line Corrector (SLC-off) effect by using the Delaunay triangulation method. Once the images were corrected, we computed the Normalized Burn Ratio (NBR) to highlight and characterise the areas that were burnt by means of a standard severity index. The estimation of the affected area was done through the difference of the images respectively before and after the fire that was also trimmed off to actually obtain the affected area. Once the forest fire was classified, the total affected area was estimated for each severity index and overlaid the Spanish topographic map (1:25000) thus being able to calculate the affected area for each municipality, land use and cadastrial property. The total burnt area was 19910 ha, the most affected municipality -in extension- was Andilla with 4966 ha. But the most significant one was precisely Alcublas with 60,64% of its area burnt. The area burnt for each land use was also estimated according to its severity by using the CORINE Land Cover Map. The most affected uses were transition forest shrubs (matorral) (11313 ha), sclerophyllous matorral (3966 ha) and coniferous forests (2821 ha). Finally, for the Alcublas cadastre, it was checked that the fire devastated all the natural vegetation of the hilly forests around the village but practically did not affect any urban or rural plot.

Forest cutting and impacts on carbon in the eastern United States

USGS Publications Warehouse

Zhou, Decheng; Liu, Shuguang; Oeding, Jennifer; Zhao, Shuqing

2013-01-01

Forest cutting is a major anthropogenic disturbance that affects forest carbon (C) storage and fluxes. Yet its characteristics and impacts on C cycling are poorly understood over large areas. Using recent annualized forest inventory data, we estimated cutting-related loss of live biomass in the eastern United States was 168 Tg C yr−1 from 2002 to 2010 (with C loss per unit forest area of 1.07 Mg ha−1 yr−1), which is equivalent to 70% of the total U.S. forest C sink or 11% of the national annual CO2 emissions from fossil-fuel combustion over the same period. We further revealed that specific cutting-related C loss varied with cutting intensities, forest types, stand ages, and geographic locations. Our results provide new insights to the characteristics of forest harvesting activities in the eastern United States and highlight the significance of partial cutting to regional and national carbon budgets.

Application of ERTS imagery in estimating the environmental impact of a freeway through the Knysna area of South Africa

NASA Technical Reports Server (NTRS)

Williamson, D. T.; Gilbertson, B.

1974-01-01

In the coastal areas north-east and south-west of Knysna, South Africa lie natural forests, lakes and lagoons highly regarded by many for their aesthetic and ecological richness. A freeway construction project has given rise to fears of the degradation or destruction of these natural features. The possibility was investigated of using ERTS imagery to estimate the environmental impact of the freeway and found that: (1) All threatened features could readily be identified on the imagery. (2) It was possible within a short time to provide an area estimate of damage to indigenous forest. (3) In several important respects the imagery has advantages over maps and aerial photos for this type of work. (4) The imagery will enable monitoring of the actual environmental impact of the freeway when completed.

Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

PubMed

Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

2018-02-21

Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated with great care. The uncertainties in the LiDAR-estimated AGB propagate further in the wall-to-wall map and can be up to 150%. Thus, when a two-stage up-scaling method is applied, it is crucial to characterize the uncertainties at all stages in order to generate robust results. Considering the findings mentioned above LiDAR can be used as an extension to NFI for example for areas that are difficult or not possible to access.

Association between climatic variables and malaria incidence: a study in Kokrajhar district of Assam, India.

PubMed

Nath, Dilip C; Mwchahary, Dimacha Dwibrang

2012-11-11

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with forest malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models.

The Characteristics of Peats and Co2 Emission Due to Fire in Industrial Plant Forests

NASA Astrophysics Data System (ADS)

Ratnaningsih, Ambar Tri; Rayahu Prasytaningsih, Sri

2017-12-01

Riau Province has a high threat to forest fire in peat soils, especially in industrial forest areas. The impact of fires will produce carbon (CO2) emissions in the atmosphere. The magnitude of carbon losses from the burning of peatlands can be estimated by knowing the characteristics of the fire peat and estimating CO2 emissions produced. The objectives of the study are to find out the characteristics of fire-burning peat, and to estimate carbon storage and CO2 emissions. The location of the research is in the area of industrial forest plantations located in Bengkalis Regency, Riau Province. The method used to measure peat carbon is the method of lost in ignation. The results showed that the research location has a peat depth of 600-800 cm which is considered very deep. The Peat fiber content ranges from 38 to 75, classified as hemic peat. The average bulk density was 0.253 gram cm-3 (0.087-0,896 gram cm-3). The soil ash content is 2.24% and the stored peat carbon stock with 8 meter peat thickness is 10723,69 ton ha-1. Forest fire was predicted to burn peat to a depth of 100 cm and produced CO2 emissions of 6,355,809 tons ha-1.

Spot-mapping underestimates song-territory size and use of mature forest by breeding golden-winged warblers in Minnesota, USA

USGS Publications Warehouse

Streby, Henry M.; Loegering, John P.; Andersen, David E.

2012-01-01

Studies of songbird breeding habitat often compare habitat characteristics of used and unused areas. Although there is usually meticulous effort to precisely and consistently measure habitat characteristics, accuracy of methods for estimating which areas are used versus which are unused by birds remains generally untested. To examine accuracy of spot-mapping to identify singing territories of golden-winged warblers (Vermivora chrysoptera), which are considered an early successional forest specialists, we used spot-mapping and radiotelemetry to record song perches and delineate song territories for breeding male golden-winged warblers in northwestern Minnesota, USA. We also used radiotelemetry to record locations (song and nonsong perches) of a subsample (n = 12) of males throughout the day to delineate home ranges. We found that telemetry-based estimates of song territories were 3 times larger and included more mature forest than those estimated from spot-mapping. In addition, home ranges estimated using radiotelemetry included more mature forest than spot-mapping- and telemetry-based song territories, with 75% of afternoon perches located in mature forest. Our results suggest that mature forest comprises a larger component of golden-winged warbler song territories and home ranges than is indicated based on spot-mapping in Minnesota. Because it appears that standard observational methods can underestimate territory size and misidentify cover-type associations for golden-winged warblers, we caution that management and conservation plans may be misinformed, and that similar studies are needed for golden-winged warblers across their range and for other songbird species.

Microclimate and Hydrology of Native Cloud Forest in Hawaii Volcanoes National Park

NASA Astrophysics Data System (ADS)

Giambelluca, T. W.; Asner, G. P.; Martin, R. E.; Delay, J. K.; Mudd, R. G.; Nullet, M. A.; Takahashi, M.

2006-12-01

The water balance of cloud forests on Kilauea Volcano are of interest for improving understanding of regional hydrologic and ecological processes. Exceptionally high rates of forest evapotranspiration (ET) have been found in recent studies on other tropical oceanic islands, raising questions about current estimates of water balance and groundwater recharge for forested areas in Hawai'i. Previous studies in the same area have shown fog to be the dominant pathway for atmospheric nitrogen deposition derived from atmospheric sources associated with the nearby Pu'u O'o eruption. A 25-m tower equipped with eddy covariance and other micrometeorological instrumentation was constructed within 17-m-tall native Metrosideros polymorpha cloud forest in Hawai'i Volcanoes National Park. Measurements of stand-level ET, tree transpiration, throughfall, stemflow, and soil moisture are underway to quantify the canopy water balance and to estimate the direct deposition of cloud water to the system. Based on these measurements, mean monthly stand level ET is estimated to range from 1.69 (March) to 3.43 (July) mm per day. These rates are slightly lower than expected for this site, and much lower than rates recently found at forest sites on other tropical islands. The ratio of throughfall to gross rainfall was 1.096, 1.065, and 1.034 for 2004, 2005, and 2006, respectively. These values imply cloud water interception of approximately 600 to 1000 mm per year. Measurements of stemflow and sapflow have recently begun and will be useful in refining the canopy water balance and improving estimates of cloud water interception.

The Impact of Charcoal Production on Forest Degradation: a Case Study in Tete, Mozambique

NASA Technical Reports Server (NTRS)

Sedano, F.; Silva. J. A.; Machoco, R.; Meque, C. H.; Sitoe, A.; Ribeiro, N.; Anderson, K.; Ombe, Z. A.; Baule, S. H.; Tucker, C. J.

2016-01-01

Charcoal production for urban energy consumption is a main driver of forest degradation in sub-Saharan Africa. Urban growth projections for the continent suggest that the relevance of this process will increase in the coming decades. Forest degradation associated to charcoal production is difficult to monitor and commonly overlooked and underrepresented in forest cover change and carbon emission estimates. We use a multi-temporal dataset of very high-resolution remote sensing images to map kiln locations in a representative study area of tropical woodlands in central Mozambique. The resulting maps provided a characterization of the spatial extent and temporal dynamics of charcoal production. Using an indirect approach we combine kiln maps and field information on charcoal making to describe the magnitude and intensity of forest degradation linked to charcoal production, including aboveground biomass and carbon emissions. Our findings reveal that forest degradation associated to charcoal production in the study area is largely independent from deforestation driven by agricultural expansion and that its impact on forest cover change is in the same order of magnitude as deforestation. Our work illustrates the feasibility of using estimates of urban charcoal consumption to establish a link between urban energy demands and forest degradation. This kind of approach has potential to reduce uncertainties in forest cover change and carbon emission assessments in sub-Saharan Africa.

Secondary Forest Age and Tropical Forest Biomass Estimation Using TM

NASA Technical Reports Server (NTRS)

Nelson, R. F.; Kimes, D. S.; Salas, W. A.; Routhier, M.

1999-01-01

The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.

Soil Quality of Bauxite Mining Areas

NASA Astrophysics Data System (ADS)

Terezinha Gonçalves Bizuti, Denise; Dinarowski, Marcela; Casagrande, José Carlos; Silva, Luiz Gabriel; Soares, Marcio Roberto; Henrique Santin Brancalion, Pedro

2015-04-01

The study on soil quality index (SQI) aims to assess the current state of the soil after use and estimating its recovery through sustainable management practices This type of study is being used in this work in order to check the efficiency of forest recovery techniques in areas that have been deeply degraded by bauxite mining process, and compare them with the area of native forest, through the determination of SQI. Treatments were newly mined areas, areas undergoing restoration (topsoil use with planting of native forest species), areas in rehabilitation (employment of the green carpet with topsoil and planting of native forest species) and areas of native forests, with six repetitions, in areas of ALCOA, in the municipality of Poços de Caldas/MG. To this end, we used the additive pondered model, establishing three functions: Fertility, water movement and root development, based on chemical parameters (organic matter, base saturation, aluminum saturation and calcium content); physical (macroporosity, soil density and clay content); and microbiological testing (basal respiration by the emission of CO2 ). The SQIs obtained for each treatment was 41%, 56%, 63% and 71% for newly mined areas, native forest, areas in restoration and rehabilitation, respectively. The recovering technique that most approximates the degraded soil to the soil of reference is the restoration, where there was no statistically significant difference of areas restored with native forest. It was found that for the comparison of the studied areas must take into account the nutrient cycling, that disappear with plant removal in mining areas, once the soil of native forest features low fertility and high saturation by aluminum, also taking in account recovering time.

Application of two regression-based methods to estimate the effects harvest on forest structure using Landsat data

Treesearch

Sean P. Healey; Zhiqiang Yang; Warren B. Cohen; D. John Pierce

2006-01-01

Although partial harvests are common in many forest types globally, there has been little assessment of the potential to map the intensity of these harvests using Landsat data. We modeled basal area removal and percent cover change in a study area in central Washington (northwestern USA) using biennial Landsat imagery and reference data from historical aerial photos...

Timber resource statistics for the Juneau inventory unit, Alaska, 1970.

Treesearch

Vernon J. LaBau; Willem W.S. Van Hees

1983-01-01

Statistics on forest area, total gross and net timber volumes, and annual net growth and mortality are presented for the 1970 timber inventory of the Juneau unit, Alaska. Estimates for commercial forest land area total 1.3 million acres (535 000 ha) with a net growing stock volume of 8.3 billion cubic feet (234 million m3), and annual net growth...

A model for estimating air-pollutant uptake by forests: calculation of absorption of sulfur dioxide from dispersed sources

Treesearch

C. E., Jr. Murphy; T. R. Sinclair; K. R. Knoerr

1977-01-01

The computer model presented in this paper is designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used with only minor changes for any gaseous pollutant...

Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

2014-12-01

Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest biomass assessment without compromising the accuracy of estimation, which may further be improved using development density.

Brush control on forest lands with emphasis on promising methods for the Pacific Northwest: a review of selected references.

Treesearch

Walter G. Dahms; George A. James

1955-01-01

Brush encroachment on forest land is greatly reducing the amount of wood grown in forests of the Pacific Northwest. Reliable estimates show that brush has reduced the productivity of more than one-fourth of the forest land of southwestern Oregon. Red alder alone, which is a commercial tree on some areas but a weed species on others, accounts for poor conifer stocking...

Forest resources of Puerto Rico, 1990. Resour. Bull. SRS-22. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 4.5 p.

Treesearch

Peter A. Franco; Peter L. Weaver; Susan. Eggen-McIntosh

1997-01-01

The principal findings of the second forest survey of Puerto Rico (1990) and changes that have occurred since the survey was established in 1980 are presented. The forest inventory estimates describe the timber resource found within the potential commercial region designated in the first survey. The timber resource addressed consists primarily of regrown areas on...

Estimates of carbon stored in harvested wood products from United States Forest Service's Sierra Nevada Bio-Regional Assessment Area of the Pacific Southwest Region, 1909-2012

Treesearch

Keith Stockmann; Nathaniel Anderson; Jesse Young; Ken Skog; Sean Healey; Dan Loeffler; Edward Butler; J. Greg Jones; James Morrison

2014-01-01

Global forests capture and store significant amounts of carbon through photosynthesis. When carbon is removed from forests through harvest, a portion of the harvested carbon is stored in wood products, often for many decades. The United States Forest Service (USFS) and other agencies are interested in accurately accounting for carbon flux associated with harvested wood...

Estimating Forest Species Composition Using a Multi-Sensor Approach

NASA Astrophysics Data System (ADS)

Wolter, P. T.

2009-12-01

The magnitude, duration, and frequency of forest disturbance caused by the spruce budworm and forest tent caterpillar has increased over the last century due to a shift in forest species composition linked to historical fire suppression, forest management, and pesticide application that has fostered the increase in dominance of host tree species. Modeling approaches are currently being used to understand and forecast potential management effects in changing insect disturbance trends. However, detailed forest composition data needed for these efforts is often lacking. Here, we used partial least squares (PLS) regression to integrate satellite sensor data from Landsat, Radarsat-1, and PALSAR, as well as pixel-wise forest structure information derived from SPOT-5 sensor data (Wolter et al. 2009), to estimate species-level forest composition of 12 species required for modeling efforts. C-band Radarsat-1 data and L-band PALSAR data were frequently among the strongest predictors of forest composition. Pixel-level forest structure data were more important for estimating conifer rather than hardwood forest composition. The coefficients of determination for species relative basal area (RBA) ranged from 0.57 (white cedar) to 0.94 (maple) with RMSE of 8.88 to 6.44 % RBA, respectively. Receiver operating characteristic (ROC) curves were used to determine the effective lower limits of usefulness of species RBA estimates which ranged from 5.94 % (jack pine) to 39.41 % (black ash). These estimates were then used to produce a dominant forest species map for the study region with an overall accuracy of 78 %. Most notably, this approach facilitated discrimination of aspen from birch as well as spruce and fir from other conifer species which is crucial for the study of forest tent caterpillar and spruce budworm dynamics, respectively, in the Upper Midwest. Thus, use of PLS regression as a data fusion strategy has proven to be an effective tool for regional characterization of forest composition within spatially heterogeneous forests using large-format satellite sensor data.

Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data

NASA Astrophysics Data System (ADS)

Churches, Christopher E.; Wampler, Peter J.; Sun, Wanxiao; Smith, Andrew J.

2014-08-01

This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates.

Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use

USGS Publications Warehouse

Paschoal, Ana Maria; Massara, Rodrigo; Bailey, Larissa L.; Kendall, William L.; Doherty, Paul F.; Hirsch, Andre; Chiarello, Adriano; Paglia, Adriano

2016-01-01

Worldwide, domestic dogs (Canis familiaris) are one of the most common carnivoran species in natural areas and their populations are still increasing. Dogs have been shown to impact wildlife populations negatively, and their occurrence can alter the abundance, behavior, and activity patterns of native species. However, little is known about abundance and density of the free-ranging dogs that use protected areas. Here, we used camera trap data with an open-robust design mark–recapture model to estimate the number of dogs that used protected areas in Brazilian Atlantic Forest. We estimated the time period these dogs used the protected areas, and explored factors that influenced the probability of continued use (e.g., season, mammal richness, proportion of forest), while accounting for variation in detection probability. Dogs in the studied system were categorized as rural free-ranging, and their abundance varied widely across protected areas (0–73 individuals). Dogs used protected areas near human houses for longer periods (e.g., >50% of sampling occasions) compared to more distant areas. We found no evidence that their probability of continued use varied with season or mammal richness. Dog detection probability decreased linearly among occasions, possibly due to the owners confining their dogs after becoming aware of our presence. Comparing our estimates to those for native carnivoran, we found that dogs were three to 85 times more abundant than ocelots (Leopardus pardalis), two to 25 times more abundant than puma (Puma concolor), and approximately five times more abundant than the crab-eating fox (Cerdocyon thous). Combining camera trapping data with modern mark–recapture methods provides important demographic information on free-ranging dogs that can guide management strategies to directly control dogs' abundance and ranging behavior.

Development of deforestation and land cover database for Bhutan (1930-2014).

PubMed

Reddy, C Sudhakar; Satish, K V; Jha, C S; Diwakar, P G; Murthy, Y V N Krishna; Dadhwal, V K

2016-12-01

Bhutan is a mountainous country located in the Himalayan biodiversity hotspot. This study has quantified the total area under land cover types, estimated the rate of forest cover change, analyzed the changes across forest types, and modeled forest cover change hotpots in Bhutan. The topographical maps and satellite remote sensing images were analyzed to get the spatial patterns of forest and associated land cover changes over the past eight decades (1930-1977-1987-1995-2005-2014). Forest is the largest land cover in Bhutan and constitutes 68.3% of the total geographical area in 2014. Subtropical broad leaved hill forest is predominant type occupies 34.1% of forest area in Bhutan, followed by montane dry temperate (20.9%), montane wet temperate (18.9%), Himalayan moist temperate (10%), and tropical moist sal (8.1%) in 2014. The major forest cover loss is observed in subtropical broad leaved hill forest (64.5 km 2 ) and moist sal forest (9.9 km 2 ) from 1977 to 2014. The deforested areas have mainly been converted into agriculture and contributed for 60.9% of forest loss from 1930 to 2014. In spite of major decline of forest cover in time interval of 1930-1977, there is no net rate of deforestation is recorded in Bhutan since 1995. Forest cover change analysis has been carried out to evaluate the conservation effectiveness in "Protected Areas" of Bhutan. Hotspots that have undergone high transformation in forest cover for afforestation and deforestation were highlighted in the study for conservation prioritisation. Forest conservation policies in Bhutan are highly effective in controlling deforestation as compared to neighboring Asian countries and such service would help in mitigating climate change.

Restoring dry and moist forests of the inland northwestern U.S.

Treesearch

Theresa B. Jain; Russell T. Graham

2005-01-01

The complex topography of the inland northwestern U.S. (58.4 million ha) interacts with continental and maritime air masses to create a highly variable climate, which results in a variety of forest settings. Historically (1850 to 1900), approximately 20% of the area was covered by dry forests (Pinus ponderosa, Pseudotsuga menziesii), and an estimated 18% was covered by...

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

Foliar and ecosystem respiration in an old-growth tropical rain forest

Treesearch

Molly A. Cavaleri; Steven F. Oberbauer; Michael G. Ryan

2008-01-01

Foliar respiration is a major component of ecosystem respiration, yet extrapolations are often uncertain in tropical forests because of indirect estimates of leaf area index (LAI).A portable tower was used to directly measure LAI and night-time foliar respiration from 52 vertical transects throughout an old-growth tropical rain forest in Costa Rica. In this study, we (...

South Dakota's forest resources in 2002.

Treesearch

Ronald J. Piva; Douglas Haugan; Gregory J. Josten; Gary J Brand

2004-01-01

Results of the 2002 annual inventory of South Dakota show an estimated 1.7 million acres of forest land in the State. Timberland accounts for 92 percent of the forest land area. Nearly 70 percent of the timberland is publicly owned. Over 80 percent (1.3 billion cubic feet) of the growing-stock volume on timberland comes from ponderosa pine. All live aboveground...

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Field methods and data processing techniques associated with mapped inventory plots

Treesearch

William A. Bechtold; Stanley J. Zarnoch

1999-01-01

The U.S. Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs utilize a fixed-area mapped-plot design as the national standard for extensive forest inventories. The mapped-plot design is explained, as well as the rationale for its selection as the national standard. Ratio-of-means estimators am presented as a method to process data from...

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

PubMed Central

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). PMID:23305341

Baseline map of carbon emissions from deforestation in tropical regions.

PubMed

Harris, Nancy L; Brown, Sandra; Hagen, Stephen C; Saatchi, Sassan S; Petrova, Silvia; Salas, William; Hansen, Matthew C; Potapov, Peter V; Lotsch, Alexander

2012-06-22

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit, statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Baseline Map of Carbon Emissions from Deforestation in Tropical Regions

NASA Astrophysics Data System (ADS)

Harris, Nancy L.; Brown, Sandra; Hagen, Stephen C.; Saatchi, Sassan S.; Petrova, Silvia; Salas, William; Hansen, Matthew C.; Potapov, Peter V.; Lotsch, Alexander

2012-06-01

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit, statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Population density of red langurs in Sabangau tropical peat-swamp forest, Central Kalimantan, Indonesia.

PubMed

Ehlers Smith, David A; Ehlers Smith, Yvette C

2013-08-01

Because of the large-scale destruction of Borneo's rainforests on mineral soils, tropical peat-swamp forests (TPSFs) are increasingly essential for conserving remnant biodiversity, particularly in the lowlands where the majority of habitat conversion has occurred. Consequently, effective strategies for biodiversity conservation are required, which rely on accurate population density and distribution estimates as a baseline. We sought to establish the first population density estimates of the endemic red langur (Presbytis rubicunda) in Sabangau TPSF, the largest remaining contiguous lowland forest-block on Borneo. Using Distance sampling principles, we conducted line transect surveys in two of Sabangau's three principle habitat sub-classes and calculated group density at 2.52 groups km⁻² (95% CI 1.56-4.08) in the mixed-swamp forest sub-class. Based on an average recorded group size of 6.95 individuals, population density was 17.51 ind km⁻², the second highest density recorded in this species. The accessible area of the tall-interior forest, however, was too disturbed to yield density estimates representative of the entire sub-class, and P. rubicunda was absent from the low-pole forest, likely as a result of the low availability of the species' preferred foods. This absence in 30% of Sabangau's total area indicates the importance of in situ population surveys at the habitat-specific level for accurately informing conservation strategies. We highlight the conservation value of TPSFs for P. rubicunda given the high population density and large areas remaining, and recommend 1) quantifying the response of P. rubicunda to the logging and burning of its habitats; 2) surveying degraded TPSFs for viable populations, and 3) effectively delineating TPSF sub-class boundaries from remote imagery to facilitate population estimates across the wider peat landscape, given the stark contrast in densities found across the habitat sub-classes of Sabangau. © 2013 Wiley Periodicals, Inc.

A small subset of protected areas are a highly significant source of carbon emissions

PubMed Central

Collins, Murray B.; Mitchard, Edward T. A.

2017-01-01

Protected areas (PAs) aim to protect multiple ecosystem services. However, not all are well protected. For the first time, using published carbon and forest loss maps, we estimate carbon emissions in large forest PAs in tropical countries (N = 2018). We found 36 ± 16 Pg C stored in PA trees, representing 14.5% of all tropical forest biomass carbon. However the PAs lost forest at a mean rate of 0.18% yr−1 from 2000–2012. Lower protection status areas experienced higher forest losses (e.g. 0.39% yr−1 in IUCN cat III), yet even highest status areas lost 0.13% yr−1 (IUCN Cat I). Emissions were not evenly distributed: 80% of emissions derived from 8.3% of PAs (112 ± 49.5 Tg CO2 yr−1; n = 171). Unsurprisingly the largest emissions derived from PAs that started with the greatest total forest area; accounting for starting forest area and relating that to carbon lost using a linear model (r2 = 0.41), we found 1.1% outlying PAs (residuals >2σ; N = 23), representing 1.3% of the total PA forest area, yet causing 27.3% of all PA emissions. These results suggest PAs have been a successful means of protecting biomass carbon, yet a subset causing a disproportionately high share of emissions should be an urgent priority for management interventions. PMID:28186155

Association between Climatic Variables and Malaria Incidence: A Study in Kokrajhar District of Assam, India

PubMed Central

Nath, Dilip C.; Mwchahary, Dimacha Dwibrang

2013-01-01

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models. PMID:23283041

Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Keller, Michael M.; Silva, Jose Natalino; Zweede, Johan C.; Pereira, Rodrigo, Jr.

2002-01-01

Major uncertainties exist regarding the rate and intensity of logging in tropical forests worldwide: these uncertainties severely limit economic, ecological, and biogeochemical analyses of these regions. Recent sawmill surveys in the Amazon region of Brazil show that the area logged is nearly equal to total area deforested annually, but conversion of survey data to forest area, forest structural damage, and biomass estimates requires multiple assumptions about logging practices. Remote sensing could provide an independent means to monitor logging activity and to estimate the biophysical consequences of this land use. Previous studies have demonstrated that the detection of logging in Amazon forests is difficult and no studies have developed either the quantitative physical basis or remote sensing approaches needed to estimate the effects of various logging regimes on forest structure. A major reason for these limitations has been a lack of sufficient, well-calibrated optical satellite data, which in turn, has impeded the development and use of physically-based, quantitative approaches for detection and structural characterization of forest logging regimes. We propose to use data from the EO-1 Hyperion imaging spectrometer to greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin. Our approach is based on four "biogeophysical indicators" not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

Estimating forest crown area removed by selection cutting: a linked regression-GIS approach based on stump diameters

USGS Publications Warehouse

Anderson, S.C.; Kupfer, J.A.; Wilson, R.R.; Cooper, R.J.

2000-01-01

The purpose of this research was to develop a model that could be used to provide a spatial representation of uneven-aged silvicultural treatments on forest crown area. We began by developing species-specific linear regression equations relating tree DBH to crown area for eight bottomland tree species at White River National Wildlife Refuge, Arkansas, USA. The relationships were highly significant for all species, with coefficients of determination (r(2)) ranging from 0.37 for Ulmus crassifolia to nearly 0.80 for Quercus nuttalliii and Taxodium distichum. We next located and measured the diameters of more than 4000 stumps from a single tree-group selection timber harvest. Stump locations were recorded with respect to an established gl id point system and entered into a Geographic Information System (ARC/INFO). The area occupied by the crown of each logged individual was then estimated by using the stump dimensions (adjusted to DBHs) and the regression equations relating tree DBH to crown area. Our model projected that the selection cuts removed roughly 300 m(2) of basal area from the logged sites resulting in the loss of approximate to 55 000 m(2) of crown area. The model developed in this research represents a tool that can be used in conjunction with remote sensing applications to assist in forest inventory and management, as well as to estimate the impacts of selective timber harvest on wildlife.

Impact of forest fires on particulate matter and ozone levels during the 2003, 2004 and 2005 fire seasons in Portugal.

PubMed

Martins, V; Miranda, A I; Carvalho, A; Schaap, M; Borrego, C; Sá, E

2012-01-01

The main purpose of this work is to estimate the impact of forest fires on air pollution applying the LOTOS-EUROS air quality modeling system in Portugal for three consecutive years, 2003-2005. Forest fire emissions have been included in the modeling system through the development of a numerical module, which takes into account the most suitable parameters for Portuguese forest fire characteristics and the burnt area by large forest fires. To better evaluate the influence of forest fires on air quality the LOTOS-EUROS system has been applied with and without forest fire emissions. Hourly concentration results have been compared to measure data at several monitoring locations with better modeling quality parameters when forest fire emissions were considered. Moreover, hourly estimates, with and without fire emissions, can reach differences in the order of 20%, showing the importance and the influence of this type of emissions on air quality. Copyright © 2011 Elsevier B.V. All rights reserved.

Protected Areas’ Impacts on Brazilian Amazon Deforestation: Examining Conservation – Development Interactions to Inform Planning

PubMed Central

Pfaff, Alexander; Robalino, Juan; Herrera, Diego; Sandoval, Catalina

2015-01-01

Protected areas are the leading forest conservation policy for species and ecoservices goals and they may feature in climate policy if countries with tropical forest rely on familiar tools. For Brazil's Legal Amazon, we estimate the average impact of protection upon deforestation and show how protected areas’ forest impacts vary significantly with development pressure. We use matching, i.e., comparisons that are apples-to-apples in observed land characteristics, to address the fact that protected areas (PAs) tend to be located on lands facing less pressure. Correcting for that location bias lowers our estimates of PAs’ forest impacts by roughly half. Further, it reveals significant variation in PA impacts along development-related dimensions: for example, the PAs that are closer to roads and the PAs closer to cities have higher impact. Planners have multiple conservation and development goals, and are constrained by cost, yet still conservation planning should reflect what our results imply about future impacts of PAs. PMID:26225922

Mapping the Philippines' mangrove forests using Landsat imagery

USGS Publications Warehouse

Long, Jordan; Giri, Chandra

2011-01-01

Current, accurate, and reliable information on the areal extent and spatial distribution of mangrove forests in the Philippines is limited. Previous estimates of mangrove extent do not illustrate the spatial distribution for the entire country. This study, part of a global assessment of mangrove dynamics, mapped the spatial distribution and areal extent of the Philippines’ mangroves circa 2000. We used publicly available Landsat data acquired primarily from the Global Land Survey to map the total extent and spatial distribution. ISODATA clustering, an unsupervised classification technique, was applied to 61 Landsat images. Statistical analysis indicates the total area of mangrove forest cover was approximately 256,185 hectares circa 2000 with overall classification accuracy of 96.6% and a kappa coefficient of 0.926. These results differ substantially from most recent estimates of mangrove area in the Philippines. The results of this study may assist the decision making processes for rehabilitation and conservation efforts that are currently needed to protect and restore the Philippines’ degraded mangrove forests.

Two new species of Scirtothrips genus-group (Thripidae) of Northern Peninsular Malaysia.

PubMed

Ng, Y F; Mound, L A

2016-03-07

The survey of Thysanoptera in peninsular Malaysia has been concentrated largely in areas growing crops and flowers around Kuala Lumpur, and the Cameron Highlands, and there are few records of these insects from native forests particularly in the northern part of the country. The two species described here were collected during a recent visit to Belum-Temengor Forest Complex, in Perak State, part of the second largest forested area on the peninsular, and connected to the Bang Lang National Park, in Yala Province, Thailand. This forest has been well known as home to a number of endangered animals, including Malayan tigers and Asian elephants, as well as remarkable plant species such as Rafflesia with the world's largest flowers (Abdullah et al. 2011). Despite this, forest areas are facing a major challenge from the insatiable demand for timber, palm oil and minerals, with an 80% increase in deforestation rate in Malaysia between 1990 and 2005 (FAO 2010). Forested land in peninsular Malaysia has been estimated at 5.88 million-ha or 44% of total area, but the coverage of reserved virgin forest is about 0.40 % or 23,002-ha (Dahlan 2008).

Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012

NASA Astrophysics Data System (ADS)

Turubanova, S.; Potapov, P.; Krylov, A.; Tyukavina, A.; McCarty, J. L.; Radeloff, V. C.; Hansen, M. C.

2015-04-01

Dramatic political and economic changes in Eastern European countries following the dissolution of the "Eastern Bloc" and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers.

Nitrous oxide emission inventory of German forest soils

NASA Astrophysics Data System (ADS)

Schulte-Bisping, Hubert; Brumme, Rainer; Priesack, Eckart

2003-02-01

Annual fluxes of N2O trace gas emissions were assessed after stratifying German forest soils into Seasonal Emission Pattern (SEP) and Background Emission Pattern (BEP). Broad-leaved forests with soil pH(KCl) ≤ 3.3 were assigned to have SEP, broad-leaved forests with soil pH(KCl) > 3.3 and all needle-leaved forests to have BEP. BEPs were estimated by a relationship between annual N2O emissions and carbon content of the O-horizon. SEPs were primarily controlled by temperature and moisture and simulated by the model Expert-N after calibration to a 9-year record of N2O measurements. Analysis with different climate and soil properties indicated that the model reacts highly sensitive to changes in soil temperature, soil moisture, and soil texture. A geographic information system (ARC/INFO) was used for a spatial resolution of 1 km × 1 km grid where land cover, dominant soil units, and hygro climate classes were combined. The mean annual N2O emission flux from German forest soils was estimated as 0.32 kg ha-1 yr-1. Broad-leaved forests with SEP had the highest emissions (2.05 kg ha-1 yr-1) followed by mixed forests (0.38 kg ha-1 yr-1), broad-leaved forests (0.37 kg ha-1 yr-1), and needle-leaved forests with BEP (0.17 kg ha-1 yr-1). The annual N2O emission from German forest soils was calculated as 3.26 Gg N2O-N yr-1. Although needle-leaved trees cover about 57% of the entire forest area in Germany, their contribution is low (0.96 Gg N2O-N yr-1). Broad-leaved forests cover about 22% of the forest area but have 55% higher emissions (1.49 Gg N2O-N yr-1) than needle-leaved. Mixed forests cover 21% of the area and contribute 0.81 Gg N2O-N yr-1. Compared to the total N2O emissions in Germany of 170 Gg N yr-1, forest soils contribute only 1.9%. However, there are some uncertainties in this emission inventory, which are intensely discussed.

Estimating allowable-cut by area-scheduling

Treesearch

William B. Leak

2011-01-01

Estimation of the regulated allowable-cut is an important step in placing a forest property under management and ensuring a continued supply of timber over time. Regular harvests also provide for the maintenance of needed wildlife habitat. There are two basic approaches: (1) volume, and (2) area/volume regulation, with many variations of each. Some require...

Land ownership patterns in the Tanana River basin, Alaska, 1984.

Treesearch

Willem W.S. Van Hees

1985-01-01

Aerial photo sampling coupled with information taken on the ground provided data for development of estimates of land and forest area by ownership group within the boundaries of the 1971-75 Tanana River Basin timber inventory unit, Alaska. Area of privately owned timberland is estimated at 280,634 acres (113 569 hectares).

Forest height Mapping using the fusion of Lidar and MULTI-ANGLE spectral data

NASA Astrophysics Data System (ADS)

Pang, Y.; Li, Z.

2016-12-01

Characterizing the complexity of forest ecosystem over large area is highly complex. Light detection and Ranging (LIDAR) approaches have demonstrated a high capacity to accurately estimate forest structural parameters. A number of satellite mission concepts have been proposed to fuse LiDAR with other optical imagery allowing Multi-angle spectral observations to be captured using the Bidirectional Reflectance Distribution Function (BRDF) characteristics of forests. China is developing the concept of Chinese Terrestrial Carbon Mapping Satellite. A multi-beam waveform Lidar is the main sensor. A multi-angle imagery system is considered as the spatial mapping sensor. In this study, we explore the fusion potential of Lidar and multi-angle spectral data to estimate forest height across different scales. We flew intensive airborne Lidar and Multi-angle hyperspectral data in Genhe Forest Ecological Research Station, Northeast China. Then extended the spatial scale with some long transect flights to cover more forest structures. Forest height data derived from airborne lidar data was used as reference data and the multi-angle hyperspectral data was used as model inputs. Our results demonstrate that the multi-angle spectral data can be used to estimate forest height with the RMSE of 1.1 m with an R2 approximately 0.8.

Application of two regression-based methods to estimate the effects of partial harvest on forest structure using Landsat data.

Treesearch

S.P. Healey; Z. Yang; W.B. Cohen; D.J. Pierce

2006-01-01

Although partial harvests are common in many forest types globally, there has been little assessment of the potential to map the intensity of these harvests using Landsat data. We modeled basal area removal and percentage cover change in a study area in central Washington (northwestern USA) using biennial Landsat imagery and reference data from historical aerial photos...

Comparing line-intersect, fixed-area, and point relascope sampling for dead and downed coarse woody material in a managed northern hardwood forest

Treesearch

G. J. Jordan; M. J. Ducey; J. H. Gove

2004-01-01

We present the results of a timed field trial comparing the bias characteristics and relative sampling efficiency of line-intersect, fixed-area, and point relascope sampling for downed coarse woody material. Seven stands in a managed northern hardwood forest in New Hampshire were inventoried. Significant differences were found among estimates in some stands, indicating...

Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks.

PubMed

Campbell, J Elliott; Moen, Jeremie C; Ney, Richard A; Schnoor, Jerald L

2008-03-01

Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively.

Deorientation of PolSAR coherency matrix for volume scattering retrieval

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Garg, R. D.; Kushwaha, S. P. S.

2016-05-01

Polarimetric SAR data has proven its potential to extract scattering information for different features appearing in single resolution cell. Several decomposition modelling approaches have been developed to retrieve scattering information from PolSAR data. During scattering power decomposition based on physical scattering models it becomes very difficult to distinguish volume scattering as a result from randomly oriented vegetation from scattering nature of oblique structures which are responsible for double-bounce and volume scattering , because both are decomposed in same scattering mechanism. The polarization orientation angle (POA) of an electromagnetic wave is one of the most important character which gets changed due to scattering from geometrical structure of topographic slopes, oriented urban area and randomly oriented features like vegetation cover. The shift in POA affects the polarimetric radar signatures. So, for accurate estimation of scattering nature of feature compensation in polarization orientation shift becomes an essential procedure. The prime objective of this work was to investigate the effect of shift in POA in scattering information retrieval and to explore the effect of deorientation on regression between field-estimated aboveground biomass (AGB) and volume scattering. For this study Dudhwa National Park, U.P., India was selected as study area and fully polarimetric ALOS PALSAR data was used to retrieve scattering information from the forest area of Dudhwa National Park. Field data for DBH and tree height was collect for AGB estimation using stratified random sampling. AGB was estimated for 170 plots for different locations of the forest area. Yamaguchi four component decomposition modelling approach was utilized to retrieve surface, double-bounce, helix and volume scattering information. Shift in polarization orientation angle was estimated and deorientation of coherency matrix for compensation of POA shift was performed. Effect of deorientation on RGB color composite for the forest area can be easily seen. Overestimation of volume scattering and under estimation of double bounce scattering was recorded for PolSAR decomposition without deorientation and increase in double bounce scattering and decrease in volume scattering was noticed after deorientation. This study was mainly focused on volume scattering retrieval and its relation with field estimated AGB. Change in volume scattering after POA compensation of PolSAR data was recorded and a comparison was performed on volume scattering values for all the 170 forest plots for which field data were collected. Decrease in volume scattering after deorientation was noted for all the plots. Regression between PolSAR decomposition based volume scattering and AGB was performed. Before deorientation, coefficient determination (R2) between volume scattering and AGB was 0.225. After deorientation an improvement in coefficient of determination was found and the obtained value was 0.613. This study recommends deorientation of PolSAR data for decomposition modelling to retrieve reliable volume scattering information from forest area.

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

NASA Technical Reports Server (NTRS)

Nelson, Ross F.

2010-01-01

Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

Synthesizing Global and Local Datasets to Estimate Jurisdictional Forest Carbon Fluxes in Berau, Indonesia

PubMed Central

Griscom, Bronson W.; Ellis, Peter W.; Baccini, Alessandro; Marthinus, Delon; Evans, Jeffrey S.; Ruslandi

2016-01-01

Background Forest conservation efforts are increasingly being implemented at the scale of sub-national jurisdictions in order to mitigate global climate change and provide other ecosystem services. We see an urgent need for robust estimates of historic forest carbon emissions at this scale, as the basis for credible measures of climate and other benefits achieved. Despite the arrival of a new generation of global datasets on forest area change and biomass, confusion remains about how to produce credible jurisdictional estimates of forest emissions. We demonstrate a method for estimating the relevant historic forest carbon fluxes within the Regency of Berau in eastern Borneo, Indonesia. Our method integrates best available global and local datasets, and includes a comprehensive analysis of uncertainty at the regency scale. Principal Findings and Significance We find that Berau generated 8.91 ± 1.99 million tonnes of net CO2 emissions per year during 2000–2010. Berau is an early frontier landscape where gross emissions are 12 times higher than gross sequestration. Yet most (85%) of Berau’s original forests are still standing. The majority of net emissions were due to conversion of native forests to unspecified agriculture (43% of total), oil palm (28%), and fiber plantations (9%). Most of the remainder was due to legal commercial selective logging (17%). Our overall uncertainty estimate offers an independent basis for assessing three other estimates for Berau. Two other estimates were above the upper end of our uncertainty range. We emphasize the importance of including an uncertainty range for all parameters of the emissions equation to generate a comprehensive uncertainty estimate–which has not been done before. We believe comprehensive estimates of carbon flux uncertainty are increasingly important as national and international institutions are challenged with comparing alternative estimates and identifying a credible range of historic emissions values. PMID:26752298

Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data

Treesearch

Peter T. Wolter; Phillip A. Townsend; Brian R. Sturtevant

2009-01-01

Large areas of forest in the US and Canada are affected by insects and disease each year. Over the past century, outbreaks of the Eastern spruce budworm have become more frequent and severe. The notion of designing a more pest resistant landscape through prescriptive management practices hinges on our ability to effectively model forest?insect dynamics at regional...

Factors Affecting Salamander Density and Distribution within Four Forest Types in Southern Appalachian Mountains

Treesearch

Craig A. Harper; David C. Guynn

1999-01-01

We used a terrestrial vacuum to sample known area plots in order to obtain density estimates of salamanders and their primary prey, invertebrates of the forest floor. We sampled leaf litter and measured various vegetative and topographic parameters within four forest types (oak-pine, oak-hickory, mixed mesophytic and northern hardwoods) and three age classes (0-12,13-...

Culvert flow in small drainages in montane tropical forests: observations from the Luquillo Experimental Forest of Puerto Rico.

Treesearch

F. N. Scatena

1990-01-01

This paper describe the hydraulics of unsubmerged flow for 5 culverts in the Luiquillo Esperimental Forest of Puerto Rico. A General equation based on empirical data is presented to estimate culvert discharge during unsubmerged conditions. Large culverts are needed in humid tropical montane areas than in humid temperatute watersheds and are usually appropriate only...

Fire's importance in South Central U.S. forests: distribution of fire evidence

Treesearch

Victor A. Rudis; Thomas V. Skinner

1991-01-01

Evidence of past fire occurrence is estimated to occur on 26 percent of the 87.2 million acres of forests in Alabama, Arkansas, southeast Louisiana, Mississippi, east Oklahoma, Tennessee, and east Texas.Data are drawn from a systematic survey of fire evidence conducted in conjunction with recent inventories of private and public forested areas in the South Central U.S....

The extent of forest in dryland biomes

Treesearch

Jean-Francois Bastin; Nora Berrahmouni; Alan Grainger; Danae Maniatis; Danilo Mollicone; Rebecca Moore; Chiara Patriarca; Nicolas Picard; Ben Sparrow; Elena Maria Abraham; Kamel Aloui; Ayhan Atesoglu; Fabio Attore; Caglar Bassullu; Adia Bey; Monica Garzuglia; Luis G. GarcÌa-Montero; Nikee Groot; Greg Guerin; Lars Laestadius; Andrew J. Lowe; Bako Mamane; Giulio Marchi; Paul Patterson; Marcelo Rezende; Stefano Ricci; Ignacio Salcedo; Alfonso Sanchez-Paus Diaz; Fred Stolle; Venera Surappaeva; Rene Castro

2017-01-01

Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high...

Total belowground carbon flux in subalpine forests is related to leaf area index, soil nitrogen, and tree height

Treesearch

E. Berryman; Michael Ryan; J. B. Bradford; T. J. Hawbaker; R. Birdsey

2016-01-01

In forests, total belowground carbon (C) flux (TBCF) is a large component of the C budget and represents a critical pathway for delivery of plant C to soil. Reducing uncertainty around regional estimates of forest C cycling may be aided by incorporating knowledge of controls over soil respiration and TBCF. Photosynthesis, and presumably TBCF, declines with...

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution. [Sam Houston National Forest, Texas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.

1976-01-01

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Mapping Robinia pseudoacacia forest health in the Yellow River delta by using high-resolution IKONOS imagery and object-based image analysis

NASA Astrophysics Data System (ADS)

Wang, Hong; Lu, Kaiyu; Pu, Ruiliang

2016-10-01

The Robinia pseudoacacia forest in the Yellow River delta of China has been planted since the 1970s, and a large area of dieback of the forest has occurred since the 1990s. To assess the condition of the R. pseudoacacia forest in three forest areas (i.e., Gudao, Machang, and Abandoned Yellow River) in the delta, we combined an estimation of scale parameters tool and geometry/topology assessment criteria to determine the optimal scale parameters, selected optimal predictive variables determined by stepwise discriminant analysis, and compared object-based image analysis (OBIA) and pixel-based approaches using IKONOS data. The experimental results showed that the optimal segmentation scale is 5 for both the Gudao and Machang forest areas, and 12 for the Abandoned Yellow River forest area. The results produced by the OBIA method were much better than those created by the pixel-based method. The overall accuracy of the OBIA method was 93.7% (versus 85.4% by the pixel-based) for Gudao, 89.0% (versus 72.7%) for Abandoned Yellow River, and 91.7% (versus 84.4%) for Machang. Our analysis results demonstrated that the OBIA method was an effective tool for rapidly mapping and assessing the health levels of forest.

36 CFR 223.83 - Contents of prospectus.

Code of Federal Regulations, 2011 CFR

2011-07-01

....83 Section 223.83 Parks, Forests, and Public Property FOREST SERVICE, DEPARTMENT OF AGRICULTURE SALE... Timber Sale Contracts Advertisement and Bids § 223.83 Contents of prospectus. (a) A timber sale.... (4) The location and area of the sale, including harvest acreage. (5) The estimated volumes, quality...

Land use change in Ohio, 1952 to 1979

Treesearch

Thomas W. Birch; Wharton Eric H.; Wharton Eric H.

1982-01-01

An analytical report on trends of major land uses in Ohio from 1952 to 1979. The relationship between the decline in farm area and increase in forest land is emphasized. The losses of wood fiber attributable to clearing forest land between 1968 and 1979 are also estimated.

Temporal evolution of carbon budgets of the Appalachian forests in the U.S. from 1972 to 2000

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.

2006-01-01

Estimating dynamic terrestrial ecosystem carbon (C) sources and sinks over large areas is difficult. The scaling of C sources and sinks from the field level to the regional level has been challenging due to the variations of climate, soil, vegetation, and disturbances. As part of an effort to estimate the spatial, temporal, and sectional dimensions of the United States C sources and sinks (the U.S. Carbon Trends Project), this study estimated the forest ecosystem C sequestration of the Appalachian region (186,000 km2) for the period of 1972–2000 using the General Ensemble Biogeochemical Modeling System (GEMS) that has a strong capability of assimilating land use and land cover change (LUCC) data. On 82 sampling blocks in the Appalachian region, GEMS used sequential 60 m resolution land cover change maps to capture forest stand-replacing events and used forest inventory data to estimate non-stand-replacing changes. GEMS also used Monte Carlo approaches to deal with spatial scaling issues such as initialization of forest age and soil properties. Ensemble simulations were performed to incorporate the uncertainties of input data. Simulated results show that from 1972 to 2000 the net primary productivity (NPP), net ecosystem productivity (NEP), and net biome productivity (NBP) averaged 6.2 Mg C ha−1 y−1 (±1.1), 2.2 Mg C ha−1 y−1 (±0.6), and 1.8 Mg C ha−1 y−1(±0.6), respectively. The inter-annual variability was driven mostly by climate. Detailed C budgets for the year 2000 were also calculated. Within a total 148,000 km2 forested area, average forest ecosystem C density was estimated to be 186 Mg C ha−1 (±20), of which 98 Mg C ha−1 (±12) was in biomass and 88 Mg C ha−1 (±13) was in litter and soil. The total simulated C stock of the Appalachian forests was estimated to be 2751 Tg C (±296), including 1454 Tg C (±178) in living biomass and 1297 Tg C (±192) in litter and soil. The total net C sequestration (i.e. NBP) of the forest ecosystem in 2000 was estimated to be 19.5 Tg C y−1 (±6.8).

ALOS-PALSAR multi-temporal observation for describing land use and forest cover changes in Malaysia

NASA Astrophysics Data System (ADS)

Avtar, R.; Suzuki, R.; Ishii, R.; Kobayashi, H.; Nagai, S.; Fadaei, H.; Hirata, R.; Suhaili, A. B.

2012-12-01

The establishment of plantations in carbon rich peatland of Southeast Asia has shown an increase in the past decade. The need to support development in countries such as Malaysia has been reflected by having a higher rate of conversion of its forested areas to agricultural land use in particular oilpalm plantation. Use of optical data to monitor changes in peatland forests is difficult because of the high cloudiness in tropical region. Synthetic Aperture Radar (SAR) based remote sensing can potentially be used to monitor changes in such forested landscapes. In this study, we have demonstrated the capability of multi-temporal Fine-Beam Dual (FBD) data of Phased Array L-band Synthetic Aperture Radar (PALSAR) to detect forest cover changes in peatland to other landuse such as oilpalm plantation. Here, the backscattering properties of radar were evaluated to estimate changes in the forest cover. Temporal analysis of PALSAR FBD data shows that conversion of peatland forest to oilpalm can be detected by analyzing changes in the value of σoHH and σoHV. This is characterized by a high value of σoHH (-7.89 dB) and σoHV (-12.13 dB) for areas under peat forests. The value of σoHV decreased about 2-4 dB due to the conversion of peatland to a plantation area. There is also an increase in the value of σoHH/σoHV. Changes in σoHV is more prominent to identify the peatland conversion than in the σoHH. The results indicate the potential of PALSAR to estimate peatland forest conversion based on thresholding of σoHV or σoHH/σoHV for monitoring changes in peatland forest. This would improve our understanding of the temporal change and its effect on the peatland forest ecosystem.

Estimating Population Density of the San Martin Titi Monkey (Callicebus oenanthe) in Peru Using Vocalisations.

PubMed

van Kuijk, Silvy M; García-Suikkanen, Carolina; Tello-Alvarado, Julio C; Vermeer, Jan; Hill, Catherine M

2015-01-01

We calculated the population density of the critically endangered Callicebus oenanthe in the Ojos de Agua Conservation Concession, a dry forest area in the department of San Martin, Peru. Results showed significant differences (p < 0.01) in group densities between forest boundaries (16.5 groups/km2, IQR = 21.1-11.0) and forest interior (4.0 groups/km2, IQR = 5.0-0.0), suggesting the 2,550-ha area harbours roughly 1,150 titi monkeys. This makes Ojos de Agua an important cornerstone in the conservation of the species, because it is one of the largest protected areas where the species occurs. © 2016 S. Karger AG, Basel.

Simulating high spatial resolution high severity burned area in Sierra Nevada forests for California Spotted Owl habitat climate change risk assessment and management.

NASA Astrophysics Data System (ADS)

Keyser, A.; Westerling, A. L.; Jones, G.; Peery, M. Z.

2017-12-01

Sierra Nevada forests have experienced an increase in very large fires with significant areas of high burn severity, such as the Rim (2013) and King (2014) fires, that have impacted habitat of endangered species such as the California spotted owl. In order to support land manager forest management planning and risk assessment activities, we used historical wildfire histories from the Monitoring Trends in Burn Severity project and gridded hydroclimate and land surface characteristics data to develope statistical models to simulate the frequency, location and extent of high severity burned area in Sierra Nevada forest wildfires as functions of climate and land surface characteristics. We define high severity here as BA90 area: the area comprising patches with ninety percent or more basal area killed within a larger fire. We developed a system of statistical models to characterize the probability of large fire occurrence, the probability of significant BA90 area present given a large fire, and the total extent of BA90 area in a fire on a 1/16 degree lat/lon grid over the Sierra Nevada. Repeated draws from binomial and generalized pareto distributions using these probabilities generated a library of simulated histories of high severity fire for a range of near (50 yr) future climate and fuels management scenarios. Fuels management scenarios were provided by USFS Region 5. Simulated BA90 area was then downscaled to 30 m resolution using a statistical model we developed using Random Forest techniques to estimate the probability of adjacent 30m pixels burning with ninety percent basal kill as a function of fire size and vegetation and topographic features. The result is a library of simulated high resolution maps of BA90 burned areas for a range of climate and fuels management scenarios with which we estimated conditional probabilities of owl nesting sites being impacted by high severity wildfire.

Growing stock and woody biomass assessment in Asola-Bhatti Wildlife Sanctuary, Delhi, India.

PubMed

Kushwaha, S P S; Nandy, S; Gupta, Mohini

2014-09-01

Biomass is an important entity to understand the capacity of an ecosystem to sequester and accumulate carbon over time. The present study, done in collaboration with the Delhi Forest Department, focused on the estimation of growing stock and the woody biomass in the so-called lungs of Delhi--the Asola-Bhatti Wildlife Sanctuary in northern Aravalli hills. The satellite-derived vegetation strata were field-inventoried using stratified random sampling procedure. Growing stock was calculated for the individual sample plots using field data and species-specific volume equations. Biomass was estimated from the growing stock and the specific gravity of the wood. Among the four vegetation types, viz. Prosopis juliflora, Anogeissus pendula, forest plantation and the scrub, the P. juliflora was found to be the dominant vegetation in the area, covering 23.43 km(2) of the total area. The study revealed that P. juliflora forest with moderate density had the highest (10.7 m(3)/ha) while A. pendula forest with moderate density had the lowest (3.6 m(3)/ha) mean volume. The mean woody biomass was also found to be maximum in P. juliflora forest with moderate density (10.3 t/ha) and lowest in A. pendula forest with moderate density (3.48 t/ha). The total growing stock was estimated to be 20,772.95 m(3) while total biomass worked out to be 19,366.83 t. A strong correlation was noticed between the normalized difference vegetation index (NDVI) and the growing stock (R(2) = 0.84)/biomass (R(2) = 0.88). The study demonstrated that growing stock and the biomass of the woody vegetation in Asola-Bhatti Wildlife Sanctuary could be estimated with high accuracy using optical remote sensing data.

Integration of ground and satellite data to estimate the forest carbon fluxes of a Mediterranean region

NASA Astrophysics Data System (ADS)

Chiesi, M.; Maselli, F.; Moriondo, M.; Fibbi, L.; Bindi, M.; Running, S. W.

2009-04-01

The current paper reports on the development and testing of a methodology capable of simulating the main terms of forest carbon budget (gross primary production, GPP, net primary production, NPP, and net ecosystem exchange, NEE) in the Mediterranean environment. The study area is Tuscany, a region of Central Italy which is covered by forests over about half of its surface. It is peculiar for its extremely heterogeneous morphological and climatic features which ranges from typically Mediterranean to temperate warm or cool according to the altitudinal and latitudinal gradients and the distance from the sea (Rapetti and Vittorini, 1995). The simulation of forest carbon budget is based on the preliminary collection of several data layers to characterize the eco-climatic and forest features of the region (i.e. maps of forest type and volume, daily meteorological data and monthly NDVI-derived FAPAR - fraction of absorbed photosynthetically active radiation - estimates for the years 1999-2003). In particular, the 1:250.000 forest type map describes the distribution of 18 forest classes and was obtained by the Regional Cartographic Service. The volume map, with a 30 m spatial resolution and a mean accuracy of about 90 m3/ha, was produced by combining the available regional forest inventory data and Landsat TM images (Maselli and Chiesi, 2006). Daily meteorological data (minimum and maximum air temperatures and precipitation) were extrapolated by the use of the DAYMET algorithm (Thornton et al., 1997) from measurements taken at existing whether stations for the years 1996-2003 (calibration plus application periods); solar radiation was then estimated by the model MT-CLIM (Thornton et al., 2000). Monthly NDVI-derived FAPAR estimates were obtained using the Spot-VEGETATION satellite sensor data for the whole study period (1999-2003). After the collection of these data layers, a simplified, remote sensing based parametric model (C-Fix), is applied for the production of a reference series of monthly gross primary production (GPP) estimates. In particular this model estimates forest GPP as function of photosynthetically active radiation absorbed by vegetation (Veroustraete et al., 2002) combined with ground based estimates of incoming solar radiation and air temperature. These GPP values are used as reference data to both calibrate and integrate the functions of a more complex bio-geochemical model, BIOME-BGC, which is capable of simulating all main ecosystem processes. This model requires: daily climate data, information on the general environment (i.e. soil, vegetation and site conditions) and parameters describing the ecophysiological characteristics of vegetation. Both C-Fix and BIOME-BGC compute GPP as an expression of total, or potential, productivity of an ecosystem in equilibrium with the environment. This makes the GPP estimates of the two models practically inter-comparable and opens the possibility of using the more accurate GPP estimates of C-Fix to both calibrate BIOME-BGC and stabilize its outputs (Chiesi et al., 2007). In particular, by integrating BIOME-BGC respiration estimates to those of C-Fix, forest fluxes for the entire region are obtained, which are referable to ecosystems at equilibrium (climax) condition. These estimates are converted into NPP and NEE of real forests relying on a specifically developed conceptual framework which uses the ratio of actual over potential stand volume as indicator of ecosystem distance from climax. The accuracy of the estimated net carbon exchanges is finally evaluated against ground data derived from a recent forest inventory and from two eddy covariance flux towers located in Tuscany (San Rossore and Lecceto). The results of both these comparisons were quite positive, indicating the good capability of the method for forest carbon flux estimation in Mediterranean areas.

Forest fire risk zonation mapping using remote sensing technology

NASA Astrophysics Data System (ADS)

Chandra, Sunil; Arora, M. K.

2006-12-01

Forest fires cause major losses to forest cover and disturb the ecological balance in our region. Rise in temperature during summer season causing increased dryness, increased activity of human beings in the forest areas, and the type of forest cover in the Garhwal Himalayas are some of the reasons that lead to forest fires. Therefore, generation of forest fire risk maps becomes necessary so that preventive measures can be taken at appropriate time. These risk maps shall indicate the zonation of the areas which are in very high, high, medium and low risk zones with regard to forest fire in the region. In this paper, an attempt has been made to generate the forest fire risk maps based on remote sensing data and other geographical variables responsible for the occurrence of fire. These include altitude, temperature and soil variations. Key thematic data layers pertaining to these variables have been generated using various techniques. A rule-based approach has been used and implemented in GIS environment to estimate fuel load and fuel index leading to the derivation of fire risk zonation index and subsequently to fire risk zonation maps. The fire risk maps thus generated have been validated on the ground for forest types as well as for forest fire risk areas. These maps would help the state forest departments in prioritizing their strategy for combating forest fires particularly during the fire seasons.

Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests

NASA Astrophysics Data System (ADS)

Liu, Jing; Skidmore, Andrew K.; Heurich, Marco; Wang, Tiejun

2017-10-01

As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data.

Vietnam's forest transition in retrospect: demonstrating weaknesses in business-as-usual scenarios for REDD.

PubMed

Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

2015-05-01

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Vietnam's Forest Transition in Retrospect: Demonstrating Weaknesses in Business-as-Usual Scenarios for REDD+

NASA Astrophysics Data System (ADS)

Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

2015-05-01

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Estimating gross primary productivity (GPP) of forests across southern England at high spatial and temporal resolution using the FLIGHT model

NASA Astrophysics Data System (ADS)

Pankaew, Prasan; Milton, Edward; Dawson, Terry; Dash, Jadu

2013-04-01

Forests and woodlands play an important role in CO2 flux and in the storage of carbon, therefore it is important to be able to estimate gross primary productivity (GPP) and its change over time. The MODIS GPP product (MOD17) provides near-global GPP, but at relatively coarse spatial resolution (1km pixel size) and only every eight days. In order to study the dynamics of GPP over shorter time periods and over smaller areas it is necessary to make ground measurements or use a plant canopy model. The most reliable ground-based GPP data are those from the FLUXNET network, which comprises over 500 sites worldwide, each of which measures GPP using the eddy covariance method. Each FLUXNET measurement corresponds to GPP from an area around the sampling tower, the size and shape of which varies with weather conditions, notably wind speed and direction. The FLIGHT forest light simulation model (North, 1996) is a Monte Carlo based model to estimate the GPP from forest canopies, which does not take into account the spatial complexity of the site or the wind conditions at the time. Forests in southern England are small and embedded in a matrix of other land cover types (agriculture, urban etc.), so GPP estimated from FLIGHT needs to be adjusted to match that measured from a FLUXNET tower. The aim of this paper is to develop and test a method to adjust FLIGHT GPP so that it matches FLUXNET GPP. The advantage of this is that GPP can then be estimated over many other forests which do not possess FLUXNET sites. The study was based on data from two mixed broadleaf forests in southern England (Wytham Woods and Alice Holt forest), both of which have FLUXNET sites located within them. The FLUXNET meteorological data were prepared for use in the FLIGHT model by converting broadband irradiance to photosynthetically active radiance (PAR) and estimating diffuse PAR, using methods developed in previous work by the authors. The standard FLIGHT model tended to overestimate GPP in the winter and spring period and under-estimate GPP in the summer months. Correction factors were computed based on the midday GPP for each month of the year. The modified FLIGHT model was used to estimate GPP from each of the two forest sites at hourly intervals over a year. Both sites showed a strong linear relationship between GPP estimated from FLIGHT and GPP measured by FLUXNET (Alice Holt forest, R2=0.96, RMSE = 2.39 μmol m-2 s-1, MBE = 1.32 μmol m-2 s-1 , Wytham Wood R2 = 0.97, RMSE = 1.42 μmol m-2 s-1, MBE = 0.57 μmol m-2 s-1). The results suggest that the modified FLIGHT model could be used to estimate GPP at hourly intervals over non-instrumented forest sites across southern England, and thereby obtain regional estimates of GPP at high spatial and temporal resolution. Reference North, P. R. J. (1996). Three-Dimensional Forest Light Interaction Model Using a Monte Carlo Method. IEEE Transactions on Geoscience and Remote Sensing, 34(4), 946-956.

Vulnerability of forest vegetation to anthropogenic climate change in China.

PubMed

Wan, Ji-Zhong; Wang, Chun-Jing; Qu, Hong; Liu, Ran; Zhang, Zhi-Xiang

2018-04-15

China has large areas of forest vegetation that are critical to biodiversity and carbon storage. It is important to assess vulnerability of forest vegetation to anthropogenic climate change in China because it may change the distributions and species compositions of forest vegetation. Based on the equilibrium assumption of forest communities across different spatial and temporal scales, we used species distribution modelling coupled with endemics-area relationship to assess the vulnerability of 204 forest communities across 16 vegetation types under different climate change scenarios in China. By mapping the vulnerability of forest vegetation to climate change, we determined that 78.9% and 61.8% of forest vegetation should be relatively stable in the low and high concentration scenarios, respectively. There were large vulnerable areas of forest vegetation under anthropogenic climate change in northeastern and southwestern China. The vegetation of subtropical mixed broadleaf evergreen and deciduous forest, cold-temperate and temperate mountains needleleaf forest, and temperate mixed needleleaf and broadleaf deciduous forest types were the most vulnerable under climate change. Furthermore, the vulnerability of forest vegetation may increase due to high greenhouse gas concentrations. Given our estimates of forest vegetation vulnerability to anthropogenic climate change, it is critical that we ensure long-term monitoring of forest vegetation responses to future climate change to assess our projections against observations. We need to better integrate projected changes of temperature and precipitation into climate-adaptive conservation strategies for forest vegetation in China. Copyright © 2017 Elsevier B.V. All rights reserved.

A method for estimating mean and low flows of streams in national forests of Montana

USGS Publications Warehouse

Parrett, Charles; Hull, J.A.

1985-01-01

Equations were developed for estimating mean annual discharge, 80-percent exceedance discharge, and 95-percent exceedance discharge for streams on national forest lands in Montana. The equations for mean annual discharge used active-channel width, drainage area and mean annual precipitation as independent variables, with active-channel width being most significant. The equations for 80-percent exceedance discharge and 95-percent exceedance discharge used only active-channel width as an independent variable. The standard error or estimate for the best equation for estimating mean annual discharge was 27 percent. The standard errors of estimate for the equations were 67 percent for estimating 80-percent exceedance discharge and 75 percent for estimating 95-percent exceedance discharge. (USGS)

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

NASA Technical Reports Server (NTRS)

Lagomasino, David; Fatoyinbo, Temilola; Lee, Seung-Kuk; Simard, Marc

2015-01-01

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

Carbon Dioxide Emissions Due to Forest Fires in Bukit Batu Area, Bengkalis Regency, Indonesia

NASA Astrophysics Data System (ADS)

Anita, Sofia; Ariful Amri, T.; Abu Hanifah, T.; Furnando, Edo; Lukas, Amos

2017-05-01

High concentration of carbon dioxide in the atmosphere is the major cause of global warming. This study focuses on estimation of carbon emissions from forest fires in Indonesia, especially Bukit Batu area, Bengkalis Regency. Peatlands in this area are widely used as an agricultural cultivation and plantations. The aim of this study is to measure the concentration of CO2 emitted based on the relationship of physical and chemical properties of peat soil. Measurements carried out on these peatlands with different vegetation covered, i.e. bush land, palm plantations and secondary forests. Methods used in this research were Infrared Gas Analyzer and Gas Chromatography. The average of CO2 emissions obtained of bush land, palm plantations, and secondary forest were 497.4 ppm; 523. 2 ppm; and 457.2 ppm, respectively.

Low tortoise abundances in pine forest plantations in forest-shrubland transition areas

PubMed Central

Rodríguez-Caro, Roberto C.; Oedekoven, Cornelia S.; Graciá, Eva; Anadón, José D.; Buckland, Stephen T.; Esteve-Selma, Miguel A.; Martinez, Julia; Giménez, Andrés

2017-01-01

In the transition between Mediterranean forest and the arid subtropical shrublands of the southeastern Iberian Peninsula, humans have transformed habitat since ancient times. Understanding the role of the original mosaic landscapes in wildlife species and the effects of the current changes as pine forest plantations, performed even outside the forest ecological boundaries, are important conservation issues. We studied variation in the density of the endangered spur-thighed tortoise (Testudo graeca) in three areas that include the four most common land types within the species’ range (pine forests, natural shrubs, dryland crop fields, and abandoned crop fields). Tortoise densities were estimated using a two-stage modeling approach with line transect distance sampling. Densities in dryland crop fields, abandoned crop fields and natural shrubs were higher (>6 individuals/ha) than in pine forests (1.25 individuals/ha). We also found large variation in density in the pine forests. Recent pine plantations showed higher densities than mature pine forests where shrub and herbaceous cover was taller and thicker. We hypothesize that mature pine forest might constrain tortoise activity by acting as partial barriers to movements. This issue is relevant for management purposes given that large areas in the tortoise’s range have recently been converted to pine plantations. PMID:28273135

Low tortoise abundances in pine forest plantations in forest-shrubland transition areas.

PubMed

Rodríguez-Caro, Roberto C; Oedekoven, Cornelia S; Graciá, Eva; Anadón, José D; Buckland, Stephen T; Esteve-Selma, Miguel A; Martinez, Julia; Giménez, Andrés

2017-01-01

In the transition between Mediterranean forest and the arid subtropical shrublands of the southeastern Iberian Peninsula, humans have transformed habitat since ancient times. Understanding the role of the original mosaic landscapes in wildlife species and the effects of the current changes as pine forest plantations, performed even outside the forest ecological boundaries, are important conservation issues. We studied variation in the density of the endangered spur-thighed tortoise (Testudo graeca) in three areas that include the four most common land types within the species' range (pine forests, natural shrubs, dryland crop fields, and abandoned crop fields). Tortoise densities were estimated using a two-stage modeling approach with line transect distance sampling. Densities in dryland crop fields, abandoned crop fields and natural shrubs were higher (>6 individuals/ha) than in pine forests (1.25 individuals/ha). We also found large variation in density in the pine forests. Recent pine plantations showed higher densities than mature pine forests where shrub and herbaceous cover was taller and thicker. We hypothesize that mature pine forest might constrain tortoise activity by acting as partial barriers to movements. This issue is relevant for management purposes given that large areas in the tortoise's range have recently been converted to pine plantations.