Transformation of the oak forest spatial structure in the Minneapolis/St. Paul metropolitan area, Minnesota, USA over 7 years

Treesearch

Kathleen Ward; Kathryn Kromroy; Jennifer Juzwik

2007-01-01

The Twin Cities Metropolitan Area (TCMA) oak (Quercus spp.) forest area decreased by 5.6% between 1991 and 1998. Accompanying spatial transformation of the forest can have great impacts on forest health, water flow and quality, wildlife habitat, potential for the spread of invasive transformation that occurred along with the loss of oak forest in the...

Monitoring Change in Temperate Coniferous Forest Ecosystems

NASA Technical Reports Server (NTRS)

Williams, Darrel (Technical Monitor); Woodcock, Curtis E.

2004-01-01

The primary goal of this research was to improve monitoring of temperate forest change using remote sensing. In this context, change includes both clearing of forest due to effects such as fire, logging, or land conversion and forest growth and succession. The Landsat 7 ETM+ proved an extremely valuable research tool in this domain. The Landsat 7 program has generated an extremely valuable transformation in the land remote sensing community by making high quality images available for relatively low cost. In addition, the tremendous improvements in the acquisition strategy greatly improved the overall availability of remote sensing images. I believe that from an historical prespective, the Landsat 7 mission will be considered extremely important as the improved image availability will stimulate the use of multitemporal imagery at resolutions useful for local to regional mapping. Also, Landsat 7 has opened the way to global applications of remote sensing at spatial scales where important surface processes and change can be directly monitored. It has been a wonderful experience to have participated on the Landsat 7 Science Team. The research conducted under this project led to contributions in four general domains: I. Improved understanding of the information content of images as a function of spatial resolution; II. Monitoring Forest Change and Succession; III. Development and Integration of Advanced Analysis Methods; and IV. General support of the remote sensing of forests and environmental change. This report is organized according to these topics. This report does not attempt to provide the complete details of the research conducted with support from this grant. That level of detail is provided in the 16 peer reviewed journal articles, 7 book chapters and 5 conference proceedings papers published as part of this grant. This report attempts to explain how the various publications fit together to improve our understanding of how forests are changing and how to monitor forest change with remote sensing. There were no new inventions that resulted from this grant.

The use of airborne imaging spectrometer data to determine experimentally induced variation in coniferous canopy chemistry

NASA Technical Reports Server (NTRS)

Swanberg, Nancy A.; Matson, Pamela A.

1987-01-01

It was experimentally determined whether induced differences in forest canopy chemical composition can be detected using data from the Airborne Imaging Spectrometer (AIS). Treatments were applied to an even-aged forest of Douglas fir trees. Work to date has stressed wet chemical analysis of foilage samples and correction of AIS data. Plot treatments were successful in providing a range of foliar N2 concentrations. Much time was spent investigating and correcting problems with the raw AIS data. Initial problems with groups of drop out lines in the AIS data were traced to the tape recorder and the tape drive. Custom adjustment of the tape drive led to recovery of most missing lines. Remaining individual drop out lines were replaced using average of adjacent lines. Application of a notch filter to the Fourier transform of the image in each band satisfactorily removed vertical striping. The aspect ratio was corrected by resampling the image in the line direction using nearest neighbor interpolation.

Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

NASA Astrophysics Data System (ADS)

Borodinov, A. A.; Myasnikov, V. V.

2018-04-01

The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

Measurement and modeling of diameter distributions of particulate matter in terrestrial solutions

NASA Astrophysics Data System (ADS)

Levia, Delphis F.; Michalzik, Beate; Bischoff, Sebastian; NäThe, Kerstin; Legates, David R.; Gruselle, Marie-Cecile; Richter, Susanne

2013-04-01

Particulate matter (PM) plays an important role in biogeosciences, affecting biosphere-atmosphere interactions and ecosystem health. This is the first known study to quantify and model PM diameter distributions of bulk precipitation, throughfall, stemflow, and organic layer (Oa) solution. Solutions were collected from a European beech (Fagus sylvatica L.) forest during leafed and leafless periods. Following scanning electron microscopy and image analysis, PM distributions were quantified and then modeled with the Box-Cox transformation. Based on an analysis of 43,278 individual particulates, median PM diameter of all solutions was around 3.0 µm. All PM diameter frequency distributions were skewed significantly to the right. Optimal power transformations of PM diameter distributions were between -1.00 and -1.56. The utility of this model reconstruction would be that large samples having a similar probability density function can be developed for similar forests. Further work on the shape and chemical composition of particulates is warranted.

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics.

PubMed

Esbah, Hayriye; Deniz, Bulent; Kara, Baris; Kesgin, Birsen

2010-06-01

Bafa Lake Nature Park is one of Turkey's most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural-natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.

Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests

Treesearch

Elizabeth E. Hoy; Nancy H.F. French; Merritt R. Turetsky; Simon N. Trigg; Eric S. Kasischke

2008-01-01

Satellite remotely sensed data of fire disturbance offers important information; however, current methods to study fire severity may need modifications for boreal regions. We assessed the potential of the differenced Normalized Burn Ratio (dNBR) and other spectroscopic indices and image transforms derived from Landsat TM/ETM+ data for mapping fire severity in Alaskan...

Malignant transformation of a unicameral bone cyst in a cat.

PubMed

Berger, Björn; Brühschwein, Andreas; Eddicks, Lina; Meyer-Lindenberg, Andrea

2016-04-01

A unicameral bone cyst in the proximal humerus of a 3-year-old Norwegian forest cat was diagnosed by dynamic contrast-enhanced magnetic resonance imaging, surgical exploration, and histopathology. Surgical curettage and incorporation of bone cement led to full recovery. An osteosarcoma developed at the surgical site 17 months later. Thoracic radiographs showed pulmonary lesions consistent with metastasis.

Malignant transformation of a unicameral bone cyst in a cat

PubMed Central

Berger, Björn; Brühschwein, Andreas; Eddicks, Lina; Meyer-Lindenberg, Andrea

2016-01-01

A unicameral bone cyst in the proximal humerus of a 3-year-old Norwegian forest cat was diagnosed by dynamic contrast-enhanced magnetic resonance imaging, surgical exploration, and histopathology. Surgical curettage and incorporation of bone cement led to full recovery. An osteosarcoma developed at the surgical site 17 months later. Thoracic radiographs showed pulmonary lesions consistent with metastasis. PMID:27041754

Destriping AIS data using Fourier filtering techniques

NASA Technical Reports Server (NTRS)

Hlavka, C.

1986-01-01

Airborne Imaging Spectrometers (AIS) data collected in 1984 and 1985 showed pronounced striping in the vertical and horizontal directions. This striping reduced the signal to noise ratio so that features of the spectra of forest canopies were obscured or altered by noise. This noise was removed by application of a notch filter to the Fourier transform of the imagery in each waveband.

Combining Radar and Optical Data for Forest Disturbance Studies

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Smith, David E. (Technical Monitor)

2002-01-01

Disturbance is an important factor in determining the carbon balance and succession of forests. Until the early 1990's researchers have focused on using optical or thermal sensors to detect and map forest disturbances from wild fires, logging or insect outbreaks. As part of a NASA Siberian mapping project, a study evaluated the capability of three different radar sensors (ERS, JERS and Radarsat) and an optical sensor (Landsat 7) to detect fire scars, logging and insect damage in the boreal forest. This paper describes the data sets and techniques used to evaluate the use of remote sensing to detect disturbance in central Siberian forests. Using images from each sensor individually and combined an assessment of the utility of using these sensors was developed. Transformed Divergence analysis and maximum likelihood classification revealed that Landsat data was the single best data type for this purpose. However, the combined use of the three radar and optical sensors did improve the results of discriminating these disturbances.

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.

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Investigating the Capability of IRS-P6-LISS IV Satellite Image for Pistachio Forests Density Mapping (case Study: Northeast of Iran)

NASA Astrophysics Data System (ADS)

Hoseini, F.; Darvishsefat, A. A.; Zargham, N.

2012-07-01

In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared. Hard and soft supervised classifications were performed with 5 density classes (0-5%, 5-10%, 10-15%, 15-20% and > 20%). Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0-5%, 5-20%, and > 20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests.

The history and future of the forest industry of Irkutsk province

Treesearch

Dennis V. Dayneko; Eric J. Gustafson

2013-01-01

Multiple global changes are impacting Russia today. Economic transformations in Russia have prompted the establishment of new relations in economic, institutional and ecological spheres, including within the Forest Industry. This paper focuses on the Forest sector in Irkutsk province and beyond, examining the basic problems related to the transformation of the forest...

[Landscape pattern change of Dongzhai Harbour mangrove, South China analyzed with a patch-based method and its driving forces].

PubMed

Huang, Xing; Xin, Kun; Li, Xiu-zhen; Wang, Xue-ping; Ren, Lin-jing; Li, Xi-zhi; Yan, Zhong-zheng

2015-05-01

According to the interpreted results of three satellite images of Dongzhai Harbour obtained in 1988, 1998 and 2009, the changes of landscape pattern and the differences of its driving forces of mangrove forest in Dongzhai Harbour were analyzed with a patch-based method on spatial distribution dynamics. The results showed that the areas of mangrove forest in 1988, 1998 and 2009 were 1809.4, 1738.7 and 1608.2 hm2 respectively, which presented a trend of decrease with enhanced degree of landscape fragmentation. The transformations among different landscape types indicated that the mangrove, agricultural land and forest land were mainly changed into built-up land and aquaculture pond. The statistical results obtained from three different methods, i.e., accumulative counting, percentage counting and main transformation route counting, showed that natural factors were the main reason for the changes of patch number, responsible for 58.6%, 72.2% and 72.1% of patch number change, respectively, while the percentages of patch area change induced by human activities were 70.4%, 70.3% and 76.4%, respectively, indicating that human activities were the primary factors of the change of patch areas.

Identifying species from the air: UAVs and the very high resolution challenge for plant conservation.

PubMed

Baena, Susana; Moat, Justin; Whaley, Oliver; Boyd, Doreen S

2017-01-01

The Pacific Equatorial dry forest of Northern Peru is recognised for its unique endemic biodiversity. Although highly threatened the forest provides livelihoods and ecosystem services to local communities. As agro-industrial expansion and climatic variation transform the region, close ecosystem monitoring is essential for viable adaptation strategies. UAVs offer an affordable alternative to satellites in obtaining both colour and near infrared imagery to meet the specific requirements of spatial and temporal resolution of a monitoring system. Combining this with their capacity to produce three dimensional models of the environment provides an invaluable tool for species level monitoring. Here we demonstrate that object-based image analysis of very high resolution UAV images can identify and quantify keystone tree species and their health across wide heterogeneous landscapes. The analysis exposes the state of the vegetation and serves as a baseline for monitoring and adaptive implementation of community based conservation and restoration in the area.

Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia

NASA Astrophysics Data System (ADS)

Sabajo, Clifton R.; le Maire, Guerric; June, Tania; Meijide, Ana; Roupsard, Olivier; Knohl, Alexander

2017-10-01

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.

Age of oil palm plantations causes a strong change in surface biophysical variables

NASA Astrophysics Data System (ADS)

Sabajo, Clifton; le Maire, Guerric; Knohl, Alexander

2016-04-01

Over the last decades, Indonesia has experienced dramatic land transformations with an expansion of oil palm plantations at the expense of tropical forests. As vegetation is a modifier of the climate near the ground these large-scale land transformations are expected to have major impacts on the surface biophysical variables i.e. surface temperature, albedo, and vegetation indices, e.g. the NDVI. Remote sensing data are needed to assess such changes at regional scale. We used 2 Landsat images from Jambi Province in Sumatra/Indonesia covering a chronosequence of oil palm plantations to study the 20 - 25 years life cycle of oil palm plantations and its relation with biophysical variables. Our results show large differences between the surface temperature of young oil palm plantations and forest (up to 9.5 ± 1.5 °C) indicating that the surface temperature is raised substantially after the establishment of oil palm plantations following the removal of forests. During the oil palm plantation lifecycle the surface temperature differences gradually decreases and approaches zero around an oil palm plantation age of 10 years. Similarly, NDVI increases and the albedo decreases approaching typical values of forests. Our results show that in order to assess the full climate effects of oil palm expansion biophysical processes play an important role and the full life cycle of oil palm plantations need to be considered.

Assessment of ASTER data for forest inventory in Canary Islands

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Arbelo, Manuel; Hernandez-Leal, Pedro A.; González-Calvo, Alejandro; Labrador Garcia, Mauricio

To understand and evaluate the forest structural attributes, forest inventories are conducted, which are costly and lengthy in time. Since the last 10-15 years there has been examining the possibility of using remote sensing data, to save costs and cheapen the process. One of the aims of SATELMAC, a project PCT-MAC 2007-2013 co-financing with FEDER funds, is to automate the forest inventory in Canary Islands using satellite images. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to estimate forest structure of the endemic vegetal specie, Pinus canariensis, located on the island of Tenerife (Spain). The forest structural attributes analyzed have been volume, basal area, stem per hectare and tree height. ASTER is an imaging instrument flying on Terra, a satellite launched in December 1999 as part of NASA's Earth Observing System. ASTER data were used because it have relatively high spatial resolution in the three visible and near-infrared bands (15 m) and in the six spectral bands (30 m) in the shortwave-IR region. To identify the vegetation index that is most suitable to use, about specific forest structural attributes in our study area, we assess the ability of different spectral indices: Normalized Difference Vegetation Index, Transformed Soil Adjusted Vegetation Index, Modified Soil adjusted Vegetation Index, Perpendicular Vegetation Index and Reduced Simple Ratio. The information provided by the ASTER data has been supplemented by the Third National Forest Inventory (III NFI) and field data. The results are analyzed statistically in order to see the degree of correlation (R2) and the mean square error (RMSE) of the values studied.

Time Series of Tropical-Forest Structure from TanDEM-X, Transformed to Time Series of Biomass by MODIS

NASA Astrophysics Data System (ADS)

Treuhaft, R. N.; Baccini, A.; Goncalves, F. G.; Lei, Y.; Keller, M.; Walker, W. S.

2017-12-01

Tropical forests account for about 50% of the world's forested biomass, and play a critical role in the control of atmospheric carbon dioxide. Large-scale (1000's of km) changes in forest structure and biomass bear on global carbon source-sink dynamics, while small-scale (< 100 m) changes bear on deforestation and degradation monitoring. After describing the interferometric SAR (InSAR) phase-height observation, we show forest phase-height time series from the TanDEM-X radar interferometer at X-band (3 cm), taken with monthly and sub-hectare temporal and spatial resolution, respectively. The measurements were taken with more than 30 TanDEM-X passes over Tapajós National Forest in the Brazilian Amazon between 2011 and 2014. The transformation of phase-height rates into aboveground biomass (AGB) rates is based on the idea that the change in AGB due to a change in phase-height depends on the plot's AGB. Plots with higher AGB will produce more AGB for a given increase in height or phase-height. Postulating a power-law dependence of plot-level mass density on physical height, we previously found that the best conversion factors for transforming phase-height rate to AGB rate were indeed dependent on AGB. For 78 plots, we demonstrated AGB rates from InSAR phase-height rates using AGB from field measurements. For regional modeling of the Amazon Basin, field measurements of AGB, to specify the conversion factors, is impractical. Conversion factors from InSAR phase-height rate to AGB rate in this talk will be based on AGB derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). AGB measurement from MODIS is based on the spectral reflectance of 7 bands from the visible to short wave infrared, and auxiliary metrics describing the variance in reflectance. The mapping of MODIS reflectance to AGB is enabled by training a machine learning algorithm with lidar-derived AGB data, which are in turn trained by field measurements for small areas. The performance of TanDEM-X AGB rate from MODIS-derived conversion factors will be compared to that derived from field-based conversion factors. We will also attempt to improve phase-height rate to AGB rate transformation by deriving improved models of mass density dependences on height, based on the aggregation of single-stem allometrics.

Forest economics and policy in a changing environment: how market, policy, and climate transformations affect forests -- Proceedings of the 2016 Meeting of the International Society of Forest Resource Economics

Treesearch

Gregory E. Frey; Prakash Nepal

2016-01-01

Economics can affect decisions about forest resource management and utilization, and in turn, the ecosystem benefits received. In a time of market, policy, and climate transformations, economic analyses are critical to help policy-makers and resource managers make appropriate decisions. At the 2016 Meeting of the International Society of Forest Resource Economics (...

Overview of South‐east Asia land cover using a NOAA AVHRR one kilometer composite

USGS Publications Warehouse

Defourny, Pierre; Pradhan, Udai C.; Vinay, Sritharan; Johnson, Gary E.

1994-01-01

A cloud free AVHRR composite of South‐East Asia at one kilometer resolution has been produced from 38 selected daily NOAA‐11 AVHRR images. Geometric accuracy of about 1 pixel is achieved using a two‐step rectification algorithm (orbital model and transformation by ground control points). A spatial and spectral enhancement has been performed, the sea masked out and political boundaries included in the final product. This AVHRR composite is particularly useful for a comprehensive overview of land cover at a regional scale. Qualitative comparison between a monthly composite and the existing forest maps highlights the forest cover change and points out the hot spots where the maps have to be updated.

Effects of land use change on soil gross nitrogen transformation rates in subtropical acid soils of Southwest China.

PubMed

Xu, Yongbo; Xu, Zhihong

2015-07-01

Land use change affects soil gross nitrogen (N) transformations, but such information is particularly lacking under subtropical conditions. A study was carried out to investigate the potential gross N transformation rates in forest and agricultural (converted from the forest) soils in subtropical China. The simultaneously occurring gross N transformations in soil were quantified by a (15)N tracing study under aerobic conditions. The results showed that change of land use types substantially altered most gross N transformation rates. The gross ammonification and nitrification rates were significantly higher in the agricultural soils than in the forest soils, while the reverse was true for the gross N immobilization rates. The higher total carbon (C) concentrations and C / N ratio in the forest soils relative to the agricultural soils were related to the greater gross N immobilization rates in the forest soils. The lower gross ammonification combined with negligible gross nitrification rates, but much higher gross N immobilization rates in the forest soils than in the agricultural soils suggest that this may be a mechanism to effectively conserve available mineral N in the forest soils through increasing microbial biomass N, the relatively labile organic N. The greater gross nitrification rates and lower gross N immobilization rates in the agricultural soils suggest that conversion of forests to agricultural soils may exert more negative effects on the environment by N loss through NO3 (-) leaching or denitrification (when conditions for denitrification exist).

Satellite optical and radar data used to track wetland forest impact and short-term recovery from Hurricane Katrina

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, A.; Middleton, B.; Lu, Z.

2009-01-01

Satellite Landsat Thematic Mapper (TM) and RADARSAT-1 (radar) satellite image data collected before and after the landfall of Hurricane Katrina in the Pearl River Wildlife Management Area on the Louisiana-Mississippi border, USA, were applied to the study of forested wetland impact and recovery. We documented the overall similarity in the radar and optical satellite mapping of impact and recovery patterns and highlighted some unique differences that could be used to provide consistent and relevant ecological monitoring. Satellite optical data transformed to a canopy foliage index (CFI) indicated a dramatic decrease in canopy cover immediately after the storm, which then recovered rapidly in the Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) forest. Although CFI levels in early October indicated rapid foliage recovery, the abnormally high radar responses associated with the cypress forest suggested a persistent poststorm difference in canopy structure. Impact and recovery mapping results showed that even though cypress forests experienced very high wind speeds, damage was largely limited to foliage loss. Bottomland hardwoods, experiencing progressively lower wind speeds further inland, suffered impacts ranging from increased occurrences of downed trees in the south to partial foliage loss in the north. In addition, bottomland hardwood impact and recovery patterns suggested that impact severity was associated with a difference in stand structure possibly related to environmental conditions that were not revealed in the prehurricane 25-m optical and radar image analyses.

Forest impact estimated with NOAA AVHRR and landsat TM data related to an empirical hurricane wind-field distribution

USGS Publications Warehouse

Ramsey, Elijah W.; Hodgson, M.E.; Sapkota, S.K.; Nelson, G.A.

2001-01-01

An empirical model was used to relate forest type and hurricane-impact distribution with wind speed and duration to explain the variation of hurricane damage among forest types along the Atchafalaya River basin of coastal Louisiana. Forest-type distribution was derived from Landsat Thematic Mapper image data, hurricane-impact distribution from a suite of transformed advanced very high resolution radiometer images, and wind speed and duration from a wind-field model. The empirical model explained 73%, 84%, and 87% of the impact variances for open, hardwood, and cypress-tupelo forests, respectively. These results showed that the estimated impact for each forest type was highly related to the duration and speed of extreme winds associated with Hurricane Andrew in 1992. The wind-field model projected that the highest wind speeds were in the southern basin, dominated by cypress-tupelo and open forests, while lower wind speeds were in the northern basin, dominated by hardwood forests. This evidence could explain why, on average, the impact to cypress-tupelos was more severe than to hardwoods, even though cypress-tupelos are less susceptible to wind damage. Further, examination of the relative importance of wind speed in explaining the impact severity to each forest type showed that the impact to hardwood forests was mainly related to tropical-depression to tropical-storm force wind speeds. Impacts to cypress-tupelo and open forests (a mixture of willows and cypress-tupelo) were broadly related to tropical-storm force wind speeds and by wind speeds near and somewhat in excess of hurricane force. Decoupling the importance of duration from speed in explaining the impact severity to the forests could not be fully realized. Most evidence, however, hinted that impact severity was positively related to higher durations at critical wind speeds. Wind-speed intervals, which were important in explaining the impact severity on hardwoods, showed that higher durations, but not the highest wind speeds, were concentrated in the northern basin, dominated by hardwoods. The extreme impacts associated with the cypress-tupelo forests in the southeast corner of the basin intersected the highest durations as well as the highest wind speeds. ?? 2001 Published by Elsevier Science Inc.

Unsupervised domain adaptation for early detection of drought stress in hyperspectral images

NASA Astrophysics Data System (ADS)

Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.

2017-09-01

Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.

User oriented ERTS-1 images. [vegetation identification in Canada through image enhancement

NASA Technical Reports Server (NTRS)

Shlien, S.; Goodenough, D.

1974-01-01

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

Identifying species from the air: UAVs and the very high resolution challenge for plant conservation

PubMed Central

Moat, Justin; Whaley, Oliver; Boyd, Doreen S.

2017-01-01

The Pacific Equatorial dry forest of Northern Peru is recognised for its unique endemic biodiversity. Although highly threatened the forest provides livelihoods and ecosystem services to local communities. As agro-industrial expansion and climatic variation transform the region, close ecosystem monitoring is essential for viable adaptation strategies. UAVs offer an affordable alternative to satellites in obtaining both colour and near infrared imagery to meet the specific requirements of spatial and temporal resolution of a monitoring system. Combining this with their capacity to produce three dimensional models of the environment provides an invaluable tool for species level monitoring. Here we demonstrate that object-based image analysis of very high resolution UAV images can identify and quantify keystone tree species and their health across wide heterogeneous landscapes. The analysis exposes the state of the vegetation and serves as a baseline for monitoring and adaptive implementation of community based conservation and restoration in the area. PMID:29176860

Brain Tumour Segmentation based on Extremely Randomized Forest with high-level features.

PubMed

Pinto, Adriano; Pereira, Sergio; Correia, Higino; Oliveira, J; Rasteiro, Deolinda M L D; Silva, Carlos A

2015-08-01

Gliomas are among the most common and aggressive brain tumours. Segmentation of these tumours is important for surgery and treatment planning, but also for follow-up evaluations. However, it is a difficult task, given that its size and locations are variable, and the delineation of all tumour tissue is not trivial, even with all the different modalities of the Magnetic Resonance Imaging (MRI). We propose a discriminative and fully automatic method for the segmentation of gliomas, using appearance- and context-based features to feed an Extremely Randomized Forest (Extra-Trees). Some of these features are computed over a non-linear transformation of the image. The proposed method was evaluated using the publicly available Challenge database from BraTS 2013, having obtained a Dice score of 0.83, 0.78 and 0.73 for the complete tumour, and the core and the enhanced regions, respectively. Our results are competitive, when compared against other results reported using the same database.

Can forest transformation help reducing floods in forested watersheds? Certain aspects on soil hydraulics and organic matter properties

NASA Astrophysics Data System (ADS)

Wahl, N. A.; Wöllecke, B.; Bens, O.; Hüttl, R. F.

Former floodplains in many European countries increasingly suffer from serious floods due to intensified human activity. These floods have caused safety and ecological problems as well as they have resulted in economic losses in agricultural used watersheds. In this context, the influence of the management practice of forest transformation in forested areas on soil hydraulic properties is presented and discussed as a means of preventing such disasters at a reasonable cost and during a foreseeable period. Investigations were carried out in northeastern Germany on forest stands differing in tree populations and stand structure. It was found that infiltration capacity and hydraulic conductivity K exhibit overall low values nevertheless the tree species. This finding appears to be related to water repellency, the predominating texture, and a poor macroporosity. During the different stages of forest transformation, the type and amount of soil organic matter and humus in the litter layer change, leading to a decrease of the water capacity of the litter layer and the uppermost part of the mineral soil. Furthermore, these changes affect soil properties connected with water repellency. It is concluded that for the approximate duration of one century the practice of forest transformation does not contribute to flood prevention through enhanced infiltration capacity or water retention.

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.

Detecting forest canopy change due to insect activity using Landsat MSS

NASA Technical Reports Server (NTRS)

Nelson, R. F.

1983-01-01

Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

Transforming Pinus pinaster forest to recreation site: preliminary effects on LAI, some forest floor, and soil properties.

PubMed

Öztürk, Melih; Bolat, İlyas

2014-04-01

This study investigates the effects of forest transformation into recreation site. A fragment of a Pinus pinaster plantation forest was transferred to a recreation site in the city of Bartın located close to the Black Sea coast of northwestern Turkey. During the transformation, some of the trees were selectively removed from the forest to generate more open spaces for the recreationists. As a result, Leaf Area Index (LAI) decreased by 0.20 (about 11%). Additionally, roads and pathways were introduced into the site together with some recreational equipment sealing parts of the soil surface. Consequently, forest environment was altered with a semi-natural landscape within the recreation site. The purpose of this study is to assess the effects of forest transformation into recreation site particularly in terms of the LAI parameter, forest floor, and soil properties. Preliminary monitoring results indicate that forest floor biomass is reduced by 26% in the recreation site compared to the control site. Soil temperature is increased by 15% in the recreation site where selective removal of trees expanded the gaps allowing more light transmission. On the other hand, the soil bulk density which is an indicator of soil compaction is unexpectedly slightly lower in the recreation site. Organic carbon (C(org)) and total nitrogen (N(total)) together with the other physical and chemical parameter values indicate that forest floor and soil have not been exposed to much disturbance. However, subsequent removal of trees that would threaten the vegetation, forest floor, and soil should not be allowed. The activities of the recreationists are to be concentrated on the paved spaces rather than soil surfaces. Furthermore, long-term monitoring and management is necessary for both the observation and conservation of the site.

Optimization of incremental structure from motion combining a random k-d forest and pHash for unordered images in a complex scene

NASA Astrophysics Data System (ADS)

Zhan, Zongqian; Wang, Chendong; Wang, Xin; Liu, Yi

2018-01-01

On the basis of today's popular virtual reality and scientific visualization, three-dimensional (3-D) reconstruction is widely used in disaster relief, virtual shopping, reconstruction of cultural relics, etc. In the traditional incremental structure from motion (incremental SFM) method, the time cost of the matching is one of the main factors restricting the popularization of this method. To make the whole matching process more efficient, we propose a preprocessing method before the matching process: (1) we first construct a random k-d forest with the large-scale scale-invariant feature transform features in the images and combine this with the pHash method to obtain a value of relatedness, (2) we then construct a connected weighted graph based on the relatedness value, and (3) we finally obtain a planned sequence of adding images according to the principle of the minimum spanning tree. On this basis, we attempt to thin the minimum spanning tree to reduce the number of matchings and ensure that the images are well distributed. The experimental results show a great reduction in the number of matchings with enough object points, with only a small influence on the inner stability, which proves that this method can quickly and reliably improve the efficiency of the SFM method with unordered multiview images in complex scenes.

Cancun, Mexico

NASA Image and Video Library

2015-11-02

This image from NASA Terra spacecraft shows Cancun, a resort city on the east side of Mexico Yucatan Peninsula. In 1970, the population was 120 people. The city began as a tourism project in 1974. Since then, it has undergone a comprehensive transformation from being a fisherman's island surrounded by virgin forest and undiscovered shores to being one of the two most well-known Mexican resorts, along with Acapulco. In 1990 the city had grown to 167,000 inhabitants, and by 2014 to 723,000 inhabitants. These two images show the area on March 28, 1985, acquired by Landsat; and May 14, 2014, acquired by ASTER. The images cover an area of 25 x 36 km, and are located at 21.1 degrees north, 86.8 degrees west. http://photojournal.jpl.nasa.gov/catalog/PIA20086

Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

NASA Astrophysics Data System (ADS)

Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

2018-04-01

Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

From State-controlled to Polycentric Governance in Forest Landscape Restoration: The Case of the Ecological Forest Purchase Program in Yong'an Municipality of China.

PubMed

Long, Hexing; Liu, Jinlong; Tu, Chengyue; Fu, Yimin

2018-07-01

Forest landscape restoration is emerging as an effective approach to restore degraded forests for the provision of ecosystem services and to minimize trade-offs between conservation and rural livelihoods. Policy and institutional innovations in China illustrate the governance transformation of forest landscape restoration from state-controlled to polycentric governance. Based on a case study of the Ecological Forest Purchase Program in Yong'an municipality, China's Fujian Province, this paper explores how such forest governance transformation has evolved and how it has shaped the outcomes of forest landscape restoration in terms of multi-dimensionality and actor configurations. Our analysis indicates that accommodating the participation of multiple actors and market-based instruments facilitate a smoother transition from state-centered to polycentric governance in forest landscape restoration. Governance transitions for forest landscape restoration must overcome a number of challenges including ensurance of a formal participation forum, fair participation, and a sustainable legislative and financial system to enhance long-term effectiveness.

An algorithm for retrieving rock-desertification from multispectral remote sensing images

NASA Astrophysics Data System (ADS)

Xia, Xueqi; Tian, Qingjiu; Liao, Yan

2009-06-01

Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

Mapping and spatiotemporal characterization of degraded forests in the Brazilian Amazon through remote sensing

NASA Astrophysics Data System (ADS)

de Souza, Carlos Moreira, Jr.

Large forested areas have recently been impoverished by degradation caused by selective logging, forest fires and fragmentation in the Amazon region, causing partial change of the original forest structure and composition. As opposed to deforestation that has been monitored with Landsat images since the late 70's, degraded forests have not been monitored in the Amazon region. In this dissertation, remote sensing techniques for identifying and mapping unambiguously degraded forests with Landsat images are proposed. The test area was the region of Sinop, located in the state of Mato Grosso, Brazil. This region was selected because a gradient of degraded forest environments exist and a robust time-series of Landsat images and forest transect data were available. First, statistical analyses were applied to identify the best set of spectral information extracted from Landsat images to detect several types of degraded forest environments. Fraction images derived from Spectral Mixture Analysis (SMA) were the best type of information for that purpose. A new spectral index based on fraction images---Normalized Difference Fraction Index (NDFI)---was proposed to enhance the detection of canopy damaged areas in degraded forests. Second, a contextual classification algorithm was implemented to separate unambiguously forest degradation caused by anthropogenic activities from natural forest disturbances. These techniques were validated using forest transects and high resolution aerial videography images and proved to be highly accurate. Next, these techniques were applied to a time-series data set of Landsat images, encompassing 20 years, to evaluate the relationship between forest degradation and deforestation. The most important finding of the forest change detection analysis was that forest degradation and deforestation are independent events in the study area, making worse the current forest impacts in the Amazon region. Finally, the techniques developed and tested in the Sinop region were successfully applied to forty Landsat images covering other regions of the Brazilian Amazon. Standard fractions and NDFI images were computed for these other regions and both physically and spatially consistent results were obtained. An automated decision tree classification using genetic algorithm was implemented successfully to classify land cover types and sub-classes of degraded forests. The remote sensing techniques proposed in this dissertation are fully automated and have the potential to be used in tropical forest monitoring programs.

Shade images of forested areas obtained from Landsat MSS data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1989-01-01

The objective of this report is to generate a shade (shadow) image of forested areas from Landsat MSS data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure; i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The constrained least-squares method is used to generate shade images for forest of eucalyptus and vegetation of 'cerrado' over the Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on tree crown cover for vegetation of cerrado.

Forest discrimination with multipolarization imaging radar

NASA Technical Reports Server (NTRS)

Ford, J. P.; Wickland, D. E.

1985-01-01

The use of radar polarization diversity for discriminating forest canopy variables on airborne synthetic-aperture radar (SAR) images is evaluated. SAR images were acquired at L-Band (24.6 cm) simultaneously in four linear polarization states (HH, HV, VH, and VV) in South Carolina on March 1, 1984. In order to relate the polarization signatures to biophysical properties, false-color composite images were compared to maps of forest stands in the timber compartment. In decreasing order, the most useful correlative forest data are stand basal area, forest age, site condition index, and forest management type. It is found that multipolarization images discriminate variation in tree density and difference in the amount of understory, but do not discriminate between evergreen and deciduous forest types.

Refining image segmentation by polygon skeletonization

NASA Technical Reports Server (NTRS)

Clarke, Keith C.

1987-01-01

A skeletonization algorithm was encoded and applied to a test data set of land-use polygons taken from a USGS digital land use dataset at 1:250,000. The distance transform produced by this method was instrumental in the description of the shape, size, and level of generalization of the outlines of the polygons. A comparison of the topology of skeletons for forested wetlands and lakes indicated that some distinction based solely upon the shape properties of the areas is possible, and may be of use in an intelligent automated land cover classification system.

Spectral images browsing using principal component analysis and set partitioning in hierarchical tree

NASA Astrophysics Data System (ADS)

Ma, Long; Zhao, Deping

2011-12-01

Spectral imaging technology have been used mostly in remote sensing, but have recently been extended to new area requiring high fidelity color reproductions like telemedicine, e-commerce, etc. These spectral imaging systems are important because they offer improved color reproduction quality not only for a standard observer under a particular illuminantion, but for any other individual exhibiting normal color vision capability under another illuminantion. A possibility for browsing of the archives is needed. In this paper, the authors present a new spectral image browsing architecture. The architecture for browsing is expressed as follow: (1) The spectral domain of the spectral image is reduced with the PCA transform. As a result of the PCA transform the eigenvectors and the eigenimages are obtained. (2) We quantize the eigenimages with the original bit depth of spectral image (e.g. if spectral image is originally 8bit, then quantize eigenimage to 8bit), and use 32bit floating numbers for the eigenvectors. (3) The first eigenimage is lossless compressed by JPEG-LS, the other eigenimages were lossy compressed by wavelet based SPIHT algorithm. For experimental evalution, the following measures were used. We used PSNR as the measurement for spectral accuracy. And for the evaluation of color reproducibility, ΔE was used.here standard D65 was used as a light source. To test the proposed method, we used FOREST and CORAL spectral image databases contrain 12 and 10 spectral images, respectively. The images were acquired in the range of 403-696nm. The size of the images were 128*128, the number of bands was 40 and the resolution was 8 bits per sample. Our experiments show the proposed compression method is suitable for browsing, i.e., for visual purpose.

Forest Restoration following Southern Pine Beetle

Treesearch

John D. Waldron

2011-01-01

Forest restoration is the process of transforming a damaged or unhealthy forest into a healthy one. After the southern pine beetle (SPB) has damaged a forest, it is sometimes, if not most times, necessary to restore that forest. It is important to know the restoration goals, conditions prior to SPB, current conditions, and potential future conditions of the forest...

Optimizing BAO measurements with non-linear transformations of the Lyman-α forest

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

Wang, Xinkang; Font-Ribera, Andreu; Seljak, Uroš, E-mail: xinkang.wang@berkeley.edu, E-mail: afont@lbl.gov, E-mail: useljak@berkeley.edu

2015-04-01

We explore the effect of applying a non-linear transformation to the Lyman-α forest transmitted flux F=e{sup −τ} and the ability of analytic models to predict the resulting clustering amplitude. Both the large-scale bias of the transformed field (signal) and the amplitude of small scale fluctuations (noise) can be arbitrarily modified, but we were unable to find a transformation that increases significantly the signal-to-noise ratio on large scales using Taylor expansion up to the third order. In particular, however, we achieve a 33% improvement in signal to noise for Gaussianized field in transverse direction. On the other hand, we explore anmore » analytic model for the large-scale biasing of the Lyα forest, and present an extension of this model to describe the biasing of the transformed fields. Using hydrodynamic simulations we show that the model works best to describe the biasing with respect to velocity gradients, but is less successful in predicting the biasing with respect to large-scale density fluctuations, especially for very nonlinear transformations.« less

Seed robustness of oriented relative fuzzy connectedness: core computation and its applications

NASA Astrophysics Data System (ADS)

Tavares, Anderson C. M.; Bejar, Hans H. C.; Miranda, Paulo A. V.

2017-02-01

In this work, we present a formal definition and an efficient algorithm to compute the cores of Oriented Relative Fuzzy Connectedness (ORFC), a recent seed-based segmentation technique. The core is a region where the seed can be moved without altering the segmentation, an important aspect for robust techniques and reduction of user effort. We show how ORFC cores can be used to build a powerful hybrid image segmentation approach. We also provide some new theoretical relations between ORFC and Oriented Image Foresting Transform (OIFT), as well as their cores. Experimental results among several methods show that the hybrid approach conserves high accuracy, avoids the shrinking problem and provides robustness to seed placement inside the desired object due to the cores properties.

Degradation of Root Community Traits as Indicator for Transformation of Tropical Lowland Rain Forests into Oil Palm and Rubber Plantations

PubMed Central

Edy, Nur; Meyer, Marike; Corre, Marife D.; Polle, Andrea

2015-01-01

Conversion of tropical forests into intensely managed plantations is a threat to ecosystem functions. On Sumatra, Indonesia, oil palm (Elaeis guineensis) plantations are rapidly expanding, displacing rain forests and extensively used rubber (Hevea brasiliensis) agro-forests. Here, we tested the influence of land use systems on root traits including chemical traits (carbon, nitrogen, mineral nutrients, potentially toxic elements [aluminium, iron] and performance traits (root mass, vitality, mycorrhizal colonization). Traits were measured as root community-weighed traits (RCWTs) in lowland rain forests, in rubber agro-forests mixed with rain forest trees, in rubber and oil palm plantations in two landscapes (Bukit Duabelas and Harapan, Sumatra). We hypothesized that RCWTs vary with land use system indicating increasing transformation intensity and loss of ecosystem functions. The main factors found to be related to increasing transformation intensity were declining root vitality and root sulfur, nitrogen, carbon, manganese concentrations and increasing root aluminium and iron concentrations as well as increasing spore densities of arbuscular mycorrhizas. Mycorrhizal abundance was high for arbuscular and low for ectomycorrhizas and unrelated to changes in RCWTs. The decline in RCWTs showed significant correlations with soil nitrogen, soil pH and litter carbon. Thus, our study uncovered a relationship between deteriorating root community traits and loss of ecosystem functionality and showed that increasing transformation intensity resulted in decreasing root nutrition and health. Based on these results we suggest that land management that improves root vitality may enhance the ecological functions of intense tropical production systems. PMID:26366576

Degradation of Root Community Traits as Indicator for Transformation of Tropical Lowland Rain Forests into Oil Palm and Rubber Plantations.

PubMed

Sahner, Josephine; Budi, Sri Wilarso; Barus, Henry; Edy, Nur; Meyer, Marike; Corre, Marife D; Polle, Andrea

2015-01-01

Conversion of tropical forests into intensely managed plantations is a threat to ecosystem functions. On Sumatra, Indonesia, oil palm (Elaeis guineensis) plantations are rapidly expanding, displacing rain forests and extensively used rubber (Hevea brasiliensis) agro-forests. Here, we tested the influence of land use systems on root traits including chemical traits (carbon, nitrogen, mineral nutrients, potentially toxic elements [aluminium, iron] and performance traits (root mass, vitality, mycorrhizal colonization). Traits were measured as root community-weighed traits (RCWTs) in lowland rain forests, in rubber agro-forests mixed with rain forest trees, in rubber and oil palm plantations in two landscapes (Bukit Duabelas and Harapan, Sumatra). We hypothesized that RCWTs vary with land use system indicating increasing transformation intensity and loss of ecosystem functions. The main factors found to be related to increasing transformation intensity were declining root vitality and root sulfur, nitrogen, carbon, manganese concentrations and increasing root aluminium and iron concentrations as well as increasing spore densities of arbuscular mycorrhizas. Mycorrhizal abundance was high for arbuscular and low for ectomycorrhizas and unrelated to changes in RCWTs. The decline in RCWTs showed significant correlations with soil nitrogen, soil pH and litter carbon. Thus, our study uncovered a relationship between deteriorating root community traits and loss of ecosystem functionality and showed that increasing transformation intensity resulted in decreasing root nutrition and health. Based on these results we suggest that land management that improves root vitality may enhance the ecological functions of intense tropical production systems.

Detecting of forest afforestation and deforestation in Hainan Jianfengling Forest Park (China) using yearly Landsat time-series images

NASA Astrophysics Data System (ADS)

Jiao, Quanjun; Zhang, Xiao; Sun, Qi

2018-03-01

The availability of dense time series of Landsat images pro-vides a great chance to reconstruct forest disturbance and change history with high temporal resolution, medium spatial resolution and long period. This proposal aims to apply forest change detection method in Hainan Jianfengling Forest Park using yearly Landsat time-series images. A simple detection method from the dense time series Landsat NDVI images will be used to reconstruct forest change history (afforestation and deforestation). The mapping result showed a large decrease occurred in the extent of closed forest from 1980s to 1990s. From the beginning of the 21st century, we found an increase in forest areas with the implementation of forestry measures such as the prohibition of cutting and sealing in our study area. Our findings provide an effective approach for quickly detecting forest changes in tropical original forest, especially for afforestation and deforestation, and a comprehensive analysis tool for forest resource protection.

Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2014-12-01

Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images acquired in 2010. The comparison showed exceptional performance of our method. This method can be applied to emergency management and decision support systems with a need for real-time data, and it shows great potential for rapid data analysis in other areas, including volcano detection, flood boundaries, forest health, and wildfires.

Vegetation indicators of transformation in the urban forest ecosystems of "Kuzminki-Lyublino" Park

NASA Astrophysics Data System (ADS)

Buyvolova, Anna; Trifonova, Tatiana; Bykova, Elena

2017-04-01

Forest ecosystems in the city are at the same time a component of its natural environment and part of urban developmental planning. It imposes upon urban forests a large functional load, both environmental (formation of environment, air purification, noise pollution reducing, etc.) and social (recreational, educational) which defines the special attitude to their management and study. It is not a simple task to preserve maximum accessibility to the forest ecosystems of the large metropolises with a minimum of change. The urban forest vegetates in naturally formed soil, it has all the elements of a morphological structure (canopy layers), represented by natural species of the zonal vegetation. Sometimes it is impossible for a specialist to distinguish between an urban forest and a rural one. However, the urban forests are changing, being under the threat of various negative influences of the city, of which pollution is arguably the most significant. This article presents some indicators of structural changes to the plant communities, which is a response of forest ecosystems to an anthropogenic impact. It is shown that the indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The assessment of the impact of the urban environment on the state of vegetation in the "Kuzminki-Lyublino" Natural-Historical Park was conducted in two key areas least affected by anthropogenic impacts under different plant communities represented by complex pine and birch forests and in similar forest types in the Prioksko-Terrasny Biosphere Reserve. The selection of pine forests as a model is due to the fact that, according to some scientists, pine (Pinus Sylvestris L.), a very ductile and widespread species, is a sensitive indicator of anthropogenic burden, responding to the impact of defoliation and needles discoloration, and survives even at fairly high levels of pollution. The vegetation cover is one of the most dynamic components of the ecosystem and under the conditions of urban existence it is subject to transformation. The indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The further study of plant communities with a view to identifying indicators of transformation in urban environmental conditions will help for the early detection of reversible changes in the ecosystems of urban forests and the development of rational urban forest care technologies.

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

1982-01-01

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

NASA Technical Reports Server (NTRS)

Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)

2001-01-01

Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

Soils of Mountainous Forests and Their Transformation under the Impact of Fires in Baikal Region

NASA Astrophysics Data System (ADS)

Krasnoshchekov, Yu. N.

2018-04-01

Data on postpyrogenic dynamics of soils under mountainous taiga cedar ( Pinus sibirica) and pine ( Pinus sylvestris) forests and subtaiga-forest-steppe pine ( Pinus sylvestris) forests in the Baikal region are analyzed. Ground litter-humus fires predominating in this region transform the upper diagnostic organic soil horizons and lead to the formation of new pyrogenic organic horizons (Opir). Adverse effects of ground fires on the stock, fractional composition, and water-physical properties of forest litters are shown. Some quantitative parameters of the liquid and solid surface runoff in burnt areas related to the slope gradient, fire intensity, and the time passed after the fire are presented. Pyrogenic destruction of forest ecosystems inevitably induces the degradation of mountainous soils, whose restoration after fires takes tens of years. The products of soil erosion from the burnt out areas complicate the current situation with the pollution of coastal waters of Lake Baikal.

Seeing Below the Drop: Direct Nano-to-microscale Imaging of Complex Interfaces involving Solid, Liquid, and Gas Phases

NASA Astrophysics Data System (ADS)

Rykaczewski, Konrad; Landin, Trevan; Walker, Marlon L.; Scott, John Henry J.; Varanasi, Kripa K.

2012-11-01

Nanostructured surfaces with special wetting properties have the potential to transform number of industries, including power generation, water desalination, gas and oil production, and microelectronics thermal management. Predicting the wetting properties of these surfaces requires detailed knowledge of the geometry and the composition of the contact volume linking the droplet to the underlying substrate. Surprisingly, a general nano-to-microscale method for direct imaging of such interfaces has previously not been developed. Here we introduce a three dimensional imaging method which resolves this one-hundred-year-old metrology gap in wetting research. Specifically, we demonstrate direct nano-to-microscale imaging of complex fluidic interfaces using cryofixation in combination with cryo-FIB/SEM. We show that application of this method yields previously unattainable quantitative information about the interfacial geometry of water condensed on silicon nanowire forests with hydrophilic and hydrophobic surface termination in the presence or absence of an intermediate water repelling oil. We also discuss imaging artifacts and the advantages of secondary and backscatter electron imaging, Energy Dispersive Spectrometry (EDS), and three dimensional FIB/SEM tomography.

Integration of Remote Sensing Products with Ground-Based Measurements to Understand the Dynamics of Nepal's Forests and Plantation Sites

NASA Astrophysics Data System (ADS)

Gilani, H.; Jain, A. K.

2016-12-01

This study assembles information from three sources - remote sensing, terrestrial photography and ground-based inventory data, to understand the dynamics of Nepal's tropical and sub-tropical forests and plantation sites for the period 1990-2015. Our study focuses on following three specific district areas, which have conserved forests through social and agroforestry management practices: 1. Dolakha district: This site has been selected to study the impact of community-based forest management on land cover change using repeat photography and satellite imagery, in combination with interviews with community members. The study time period is during the period 1990-2010. We determined that satellite data with ground photographs can provide transparency for long term monitoring. The initial results also suggests that community-based forest management program in the mid-hills of Nepal was successful. 2. Chitwan district: Here we use high resolution remote sensing data and optimized community field inventories to evaluate potential application and operational feasibility of community level REDD+ measuring, reporting and verification (MRV) systems. The study uses temporal dynamics of land cover transitions, tree canopy size classes and biomass over a Kayar khola watershed REDD+ study area with community forest to evaluate satellite Image segmentation for land cover, linear regression model for above ground biomass (AGB), and estimation and monitoring field data for tree crowns and AGB. We study three specific years 2002, 2009, 2012. Using integration of WorldView-2 and airborne LiDAR data for tree species level. 3. Nuwakot district: This district was selected to study the impact of establishment of tree plantation on total barren/fallow. Over the last 40 year, this area has went through a drastic changes, from barren land to forest area with tree species consisting of Dalbergia sissoo, Leucaena leucocephala, Michelia champaca, etc. In 1994, this district area was registered and established to grow and process high quality trees shaded of Arabica coffee beans. Here we use temporal satellite images and repeat terrestrial and aerial photographs, along with plot level biomass to show impact of this positive transformation of the landscape on above and below ground carbon masses. The study time period is 1990-2015.

Programmable Remapper with Single Flow Architecture

NASA Technical Reports Server (NTRS)

Fisher, Timothy E. (Inventor)

1993-01-01

An apparatus for image processing comprising a camera for receiving an original visual image and transforming the original visual image into an analog image, a first converter for transforming the analog image of the camera to a digital image, a processor having a single flow architecture for receiving the digital image and producing, with a single algorithm, an output image, a second converter for transforming the digital image of the processor to an analog image, and a viewer for receiving the analog image, transforming the analog image into a transformed visual image for observing the transformations applied to the original visual image. The processor comprises one or more subprocessors for the parallel reception of a digital image for producing an output matrix of the transformed visual image. More particularly, the processor comprises a plurality of subprocessors for receiving in parallel and transforming the digital image for producing a matrix of the transformed visual image, and an output interface means for receiving the respective portions of the transformed visual image from the respective subprocessor for producing an output matrix of the transformed visual image.

Insect-plant interactions in anthropogenically transformed ecosystems

Treesearch

Evgeny V. Kultunov; Victor I. Ponomarev; Sergey I. Fedorenko

1991-01-01

Structural and functional changes in forests due to anthropogenic factors have a considerable impact on the interaction of phytophagous insects with the phytocenosis. Many features of these processes have yet to be investigated in the deciduous forest conditions of the forest-steppe zone. We investigated birch forests disturbed by anthropogenic factors in the middle...

Water, Forests, People: The Swedish Experience in Building Resilient Landscapes.

PubMed

Eriksson, Mats; Samuelson, Lotta; Jägrud, Linnéa; Mattsson, Eskil; Celander, Thorsten; Malmer, Anders; Bengtsson, Klas; Johansson, Olof; Schaaf, Nicolai; Svending, Ola; Tengberg, Anna

2018-07-01

A growing world population and rapid expansion of cities increase the pressure on basic resources such as water, food and energy. To safeguard the provision of these resources, restoration and sustainable management of landscapes is pivotal, including sustainable forest and water management. Sustainable forest management includes forest conservation, restoration, forestry and agroforestry practices. Interlinkages between forests and water are fundamental to moderate water budgets, stabilize runoff, reduce erosion and improve biodiversity and water quality. Sweden has gained substantial experience in sustainable forest management in the past century. Through significant restoration efforts, a largely depleted Swedish forest has transformed into a well-managed production forest within a century, leading to sustainable economic growth through the provision of forest products. More recently, ecosystem services are also included in management decisions. Such a transformation depends on broad stakeholder dialog, combined with an enabling institutional and policy environment. Based on seminars and workshops with a wide range of key stakeholders managing Sweden's forests and waters, this article draws lessons from the history of forest management in Sweden. These lessons are particularly relevant for countries in the Global South that currently experience similar challenges in forest and landscape management. The authors argue that an integrated landscape approach involving a broad array of sectors and stakeholders is needed to achieve sustainable forest and water management. Sustainable landscape management-integrating water, agriculture and forests-is imperative to achieving resilient socio-economic systems and landscapes.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

Diversity of Medicinal Plants among Different Forest-use Types of the Pakistani Himalaya.

PubMed

Adnan, Muhammad; Hölscher, Dirk

2012-12-01

Diversity of Medicinal Plants among Different Forest-use Types of the Pakistani Himalaya Medicinal plants collected in Himalayan forests play a vital role in the livelihoods of regional rural societies and are also increasingly recognized at the international level. However, these forests are being heavily transformed by logging. Here we ask how forest transformation influences the diversity and composition of medicinal plants in northwestern Pakistan, where we studied old-growth forests, forests degraded by logging, and regrowth forests. First, an approximate map indicating these forest types was established and then 15 study plots per forest type were randomly selected. We found a total of 59 medicinal plant species consisting of herbs and ferns, most of which occurred in the old-growth forest. Species number was lowest in forest degraded by logging and intermediate in regrowth forest. The most valuable economic species, including six Himalayan endemics, occurred almost exclusively in old-growth forest. Species composition and abundance of forest degraded by logging differed markedly from that of old-growth forest, while regrowth forest was more similar to old-growth forest. The density of medicinal plants positively correlated with tree canopy cover in old-growth forest and negatively in degraded forest, which indicates that species adapted to open conditions dominate in logged forest. Thus, old-growth forests are important as refuge for vulnerable endemics. Forest degraded by logging has the lowest diversity of relatively common medicinal plants. Forest regrowth may foster the reappearance of certain medicinal species valuable to local livelihoods and as such promote acceptance of forest expansion and medicinal plants conservation in the region. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12231-012-9213-4) contains supplementary material, which is available to authorized users.

Shade images of forested areas obtained from LANDSAT MSS data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1989-01-01

The pixel size in the present day Remote Sensing systems is large enough to include different types of land cover. Depending upon the target area, several components may be present within the pixel. In forested areas, generally, three main components are present: tree canopy, soil (understory), and shadow. The objective is to generate a shade (shadow) image of forested areas from multispectral measurements of LANDSAT MSS (Multispectral Scanner) data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure, i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The Constrained Least Squares (CLS) method is used to generate shade images for forest of eucalyptus and vegetation of cerrado using LANDSAT MSS imagery over Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on three crown cover for vegetation of cerrado.

Application of AIS Technology to Forest Mapping

NASA Technical Reports Server (NTRS)

Yool, S. R.; Star, J. L.

1985-01-01

Concerns about environmental effects of large scale deforestation have prompted efforts to map forests over large areas using various remote sensing data and image processing techniques. Basic research on the spectral characteristics of forest vegetation are required to form a basis for development of new techniques, and for image interpretation. Examination of LANDSAT data and image processing algorithms over a portion of boreal forest have demonstrated the complexity of relations between the various expressions of forest canopies, environmental variability, and the relative capacities of different image processing algorithms to achieve high classification accuracies under these conditions. Airborne Imaging Spectrometer (AIS) data may in part provide the means to interpret the responses of standard data and techniques to the vegetation based on its relatively high spectral resolution.

Analyses of changes in vegetation cover in the South and Sub-Taiga of Western Siberia using Landsat data

NASA Astrophysics Data System (ADS)

Dyukarev, Egor; Pologova, Nina; Golovatskaya, Eugenia

2010-05-01

Understanding human impact on vegetation composition and structure, at scales from the patch to the globe, and capacity to monitor change over time is fundamental research problem to address Global Change and ensure sustainable development. Natural ecosystems at the South and Sob-Taiga zone of Western Siberia are characterized by development of an early successional states, given the projected increase in disturbance, or will be converted into human-dominated terrestrial production systems. Disturbances (e.g., fire, dieback due to insect attacks) appear to be increasing in some regions, leading to fragmentation of natural ecosystems and to a generally "weedier," structurally simpler biosphere with fewer systems in a more ecologically complex old-growth state. The analysis of structure of vegetation cover at two test sites located at the south-west part of the West-Siberian Plain in the South and Sub-Taiga zone was made using LANDSAT space images and ground data. The studied area of the first test site ("Bakchar") is occupied by bogs, paludificated forests and cultivated lands. Test site "Tomsk" covered by cultivated lands in the south, dark coniferous forest complexes an early and old-growth state in the north part. Mire types at the test sites are presented by open fens, ridge-hollow / ridge-lake complexes and pine-shrub-sphagnum communities with different tree height and layer density. During the XX century the vegetation cover was exposed to natural and anthropogenic changes. Comparison of space images from different years (1990, 1999 and 2007) allowed revealing dynamics in vegetation cover. Forest change was calculated using the Disturbance Index (Healey, 2006). Decrease of forest area in 1990-1999 are primary occurs due to intense forest cutting for timber industry and local use. A strong wind have damaged forests between 1990 and 1999 in stripes oriented from south-west to north -east in the prevailing wind direction. Strong winds were registered in 2003, 2005, and 2007. Tree cutting in 1999-2007 was significantly smaller than in previous time due to depression in economical activity. Some invasion of young trees in to abandoned agricultural lands also can be found at comparison of 1999 and 2007 images. After 1999 many agricultural lands stopped to plug, transformed to unmanaged meadows (grassland) and now occupying by young birch. Small burned areas are exists on the studied territory primary at drainage peatlands but fires does not affect forests significantly. Work was performed under project "Human Impact on Land-cover Changes in the Heart of Asia" supported by Asia-Pacific Network (ARCP2009-02CMY).

Influence of harvesting on biogeochemical exchange in sheetflow and soil processes in a eutrophic floodplain forest

Treesearch

B.G. Lockaby; R.G. Clawson; K. Flynn; Robert Rummer; S. Meadows; B Stokes; John A. Stanturf

1997-01-01

Floodplain forests contribute to the maintenance of water quality as a result of various biogeochemical transformations which occur within them. In particular, they can serve as sinks for nutrient run-off from adjacent uplands or as nutrient transformers as water moves downstream. However, little is known about the potential that land management activities may have for...

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, Alexander; Meijide, Ana; Fan, Yuanchao; Gunawan, Dodo; Hölscher, Dirk; June, Tania; Niu, Furong; Panferov, Oleg; Ringeler, Andre; Röll, Alexander; Sabajo, Clifton; Tiralla, Nina

2016-04-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, A.; Meijide, A.; Fan, Y.; Hölscher, D.; June, T.; Niu, F.; Panferov, O.; Ringeler, A.; Röll, A.; Sabajo, C.; Tiralla, N.

2015-12-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Rocky to bullwinkle: understanding flying squirrels helps us restore dry forest ecosystems.

Treesearch

Jonathan Thompson

2006-01-01

A century of effective fire suppression has radically transformed many forested landscapes on the east side of the Cascades. Managers of dry forests critically need information to help plan for and implement forest restoration . Management priorities include the stabilization of fire regimes and the maintenance of habitat for the northern spotted owl and other old-...

Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies.

PubMed

Koh, Joel E W; Acharya, U Rajendra; Hagiwara, Yuki; Raghavendra, U; Tan, Jen Hong; Sree, S Vinitha; Bhandary, Sulatha V; Rao, A Krishna; Sivaprasad, Sobha; Chua, Kuang Chua; Laude, Augustinus; Tong, Louis

2017-05-01

Vision is paramount to humans to lead an active personal and professional life. The prevalence of ocular diseases is rising, and diseases such as glaucoma, Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD) are the leading causes of blindness in developed countries. Identifying these diseases in mass screening programmes is time-consuming, labor-intensive and the diagnosis can be subjective. The use of an automated computer aided diagnosis system will reduce the time taken for analysis and will also reduce the inter-observer subjective variabilities in image interpretation. In this work, we propose one such system for the automatic classification of normal from abnormal (DR, AMD, glaucoma) images. We had a total of 404 normal and 1082 abnormal fundus images in our database. As the first step, 2D-Continuous Wavelet Transform (CWT) decomposition on the fundus images of two classes was performed. Subsequently, energy features and various entropies namely Yager, Renyi, Kapoor, Shannon, and Fuzzy were extracted from the decomposed images. Then, adaptive synthetic sampling approach was applied to balance the normal and abnormal datasets. Next, the extracted features were ranked according to the significances using Particle Swarm Optimization (PSO). Thereupon, the ranked and selected features were used to train the random forest classifier using stratified 10-fold cross validation. Overall, the proposed system presented a performance rate of 92.48%, and a sensitivity and specificity of 89.37% and 95.58% respectively using 15 features. This novel system shows promise in detecting abnormal fundus images, and hence, could be a valuable adjunct eye health screening tool that could be employed in polyclinics, and thereby reduce the workload of specialists at hospitals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Poor textural image tie point matching via graph theory

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Chen, Shiyu; Yuan, Wei; Cai, Yang

2017-07-01

Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.

Land use effects on gaseous nitrogen emissions and gross nitrogen transformations in Amazonian Dark Earth

NASA Astrophysics Data System (ADS)

Barbosa Lima, Amanda; Westphal Muniz, Aleksander; Lenhart, Katharina; Moser, Gerald; Brenzinger, Kristof; Ha, Mi-Kyung; Eckhardt, Christian; Steffens, Diedrich; Kammann, Claudia; Müller, Christoph

2017-04-01

Amazonian Dark Earth (ADE) in the Brazilian Amazon provide a strong indication that soils lacking in nutrients can be converted into highly fertile land. These soils have been considered as a model soil when compared to the surrounding soil due to the high concentrations of P, Ca, Mg, Zn, Mn, stable organic matter and soil organic C (SOC). Soils with high SOC contents can lead to extensive emissions of the greenhouse gas N2O. In this context, we measured the fluxes of CO2, N2O and CH4 in ADE and adjacent (ADJ) soils under secondary forest and manioc plantation. Moreover, we added 15N-NH4+ and -NO3- and measured N2O emissions and gross-N transformations of the different N species for two weeks (15N signal, N concentrations; work on-going), to quantify the simultaneousyl operating N transformation rates (method see: Müller et al. (2004; 2007). We observed higher amounts of NO3- in both ADE and ADJ soils under forest. High consumption rates for NH4+ were shown by both ADE soils under forest followed by manioc plantation. CO2 effluxes from ADJ were higher than from ADE soils, and higher from the forest compared to the manioc plantation. N2O fluxes were much lower in ADE under forest and higher in the other soils. The results of the gross N transformations are distinctively different among ADE and Adjacent sites, providing a strong indication how the dynamics of the individual N transformation rates have been affected by the long-term management. References cited Müller et al. (2004) A 15N tracing model to analyse N-transformations in old grassland soil. SBB 36:619-632. Müller et al. (2007) Estimation of parameters in complex 15N tracing models by Monte Carlo sampling. SBB 39:715-726.

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...

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Treesearch

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

Treesearch

Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

2009-01-01

Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

RGB-NDVI colour composites for visualizing forest change dynamics

NASA Technical Reports Server (NTRS)

Sader, S. A.; Winne, J. C.

1992-01-01

The study presents a simple and logical technique to display and quantify forest change using three dates of satellite imagery. The normalized difference vegetation index (NDVI) was computed for each date of imagery to define high and low vegetation biomass. Color composites were generated by combining each date of NDVI with either the red, green, or blue (RGB) image planes in an image display monitor. Harvest and regeneration areas were quantified by applying a modified parallelepiped classification creating an RGB-NDVI image with 27 classes that were grouped into nine major forest change categories. Aerial photographs and stand history maps are compared with the forest changes indicated by the RGB-NDVI image. The utility of the RGB-NDVI technique for supporting forest inventories and updating forest resource information systems are presented and discussed.

Mapping of forested wetland: use of Seasat radar images to complement conventional sources ( USA).

USGS Publications Warehouse

Place, J.L.

1985-01-01

Distinguishing forested wetland from dry forest using aerial photographs is handicapped because photographs often do not reveal the presence of water below tree canopies. Radar images obtained by the Seasat satellite reveal forested wetland as highly reflective patterns on the coastal plain between Maryland and Florida. Seasat radar images may complement aerial photographs for compiling maps of wetland. A test with experienced photointerpreters revealed that interpretation accuracy was significantly higher when using Seasat radar images than when using only conventional sources.-Author

Space Radar Image of Bahia

NASA Image and Video Library

1999-05-01

This is a color composite image of southern Bahia, Brazil, centered at 15.22 degree south latitude and 39.07 degrees west longitude. The image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on its 38th orbit of Earth on October 2, 1994. The image covers an area centered over the Una Biological Reserve, one the largest protected areas in northeastern Brazil. The 7,000-hectare reserve is administered by the Brazilian Institute for the Environment and is part of the larger Atlantic coastal forest, a narrow band of rain forest extending along the eastern coast of Brazil. The Atlantic coastal forest of southern Bahia is one of the world's most threatened and diverse ecosystems. Due to widespread settlement, only 2 to 5 percent of the original forest cover remains. Yet the region still contains an astounding variety of plants and animals, including a large number of endemic species. More than half of the region's tree species and 80 percent of its animal species are indigenous and found nowhere else on Earth. The Una Reserve is also the only federally protected habitat for the golden-headed lion tamarin, the yellow-breasted capuchin monkey and many other endangered species. In the past few years, scientists from Brazilian and international conservation organizations have coordinated efforts to study the biological diversity of this region and to develop practical and economically viable options for preserving the remaining primary forests in southern Bahia. The shuttle imaging radar is used in this study to identify various land uses and vegetation types, including remaining patches of primary forest, cabruca forest (cacao planted in the understory of the native forest), secondary forest, pasture and coastal mangrove. Standard remote-sensing technology that relies on light reflected from the forest canopy cannot accurately distinguish between cabruca and undisturbed forest. Optical remote sensing is also limited by the nearly continuous cloud cover in the region and heavy rainfall, which occurs more than 150 days each year. The ability of the shuttle radars to "see" through the forest canopy to the cultivated cacao below -- independent of weather or sunlight conditions --will allow researchers to distinguish forest from cabruca in unprecedented detail. This SIR-C/X-SAR image was produced by assigning red to the L-band, green to the C-band and blue to the X-band. The Una Reserve is located in the middle of the image west of the coastline and slightly northwest of Comandatuba River. The reserve's primary forests are easily detected by the pink areas in the image. The intensity of red in these areas is due to the high density of forest vegetation (biomass) detected by the radar's L-band (horizontally transmitted and vertically received) channel. Secondary forest is visible along the reserve's eastern border. The Serrado Mar mountain range is located in the top left portion of the image. Cabruca forest to the west of Una Reserve has a different texture and a yellow color. The removal of understory in cabruca forest reduces its biomass relative to primary forest, which changes the L-band and C-band penetration depth and returns, and produces a different texture and color in the image. The region along the Atlantic is mainly mangrove swamp, agricultural fields and urban areas. The high intensity of blue in this region is a result of increasing X-band return in areas covered with swamp and low vegetation. The image clearly separates the mangrove region (east of coastal Highway 001, shown in blue) from the taller and dryer forest west of the highway. The high resolution capability of SIR-C/X-SAR imaging and the sensitivity of its frequency and polarization channels to various land covers will be used for monitoring and mapping areas of importance for conservation. http://photojournal.jpl.nasa.gov/catalog/PIA01764

Synergies for Improving Oil Palm Production and Forest Conservation in Floodplain Landscapes

PubMed Central

Abram, Nicola K.; Xofis, Panteleimon; Tzanopoulos, Joseph; MacMillan, Douglas C.; Ancrenaz, Marc; Chung, Robin; Peter, Lucy; Ong, Robert; Lackman, Isabelle; Goossens, Benoit; Ambu, Laurentius; Knight, Andrew T.

2014-01-01

Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world’s tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha− yr–$637/ha− yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha− yr-$-65/ha− yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes. PMID:24887555

Synergies for improving oil palm production and forest conservation in floodplain landscapes.

PubMed

Abram, Nicola K; Xofis, Panteleimon; Tzanopoulos, Joseph; MacMillan, Douglas C; Ancrenaz, Marc; Chung, Robin; Peter, Lucy; Ong, Robert; Lackman, Isabelle; Goossens, Benoit; Ambu, Laurentius; Knight, Andrew T

2014-01-01

Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world's tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha-yr-$637/ha-yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha-yr-$-65/ha-yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes.

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

NASA Astrophysics Data System (ADS)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Automatic Sub-Pixel Co-Registration of LandSat-8 OLI and Sentinel-2A MSI Images Using Phase Correlation and Machine Learning Based Mapping

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Roger, Jean-Claude; Vermote, Eric F.; Masek, Jeffrey G.; Justice, Christopher O.

2017-01-01

This study investigates misregistration issues between Landsat-8/OLI and Sentinel-2A/MSI at 30 m resolution, and between multi-temporal Sentinel-2A images at 10 m resolution using a phase correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30 m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10 m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear Random Forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07+/-0.02 pixels at 30 m resolution, and 0.09+/-0.05 and 0.15+/-0.06 pixels at 10 m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08+/-0.02 pixels at 30 m resolution and 0.12+/-0.06 (same Sentinel-2A orbits) and 0.20+/-0.09 (adjacent orbits) pixels at 10 m resolution.

GIS based Cadastral level Forest Information System using World View-II data in Bir Hisar (Haryana)

NASA Astrophysics Data System (ADS)

Mothi Kumar, K. E.; Singh, S.; Attri, P.; Kumar, R.; Kumar, A.; Sarika; Hooda, R. S.; Sapra, R. K.; Garg, V.; Kumar, V.; Nivedita

2014-11-01

Identification and demarcation of Forest lands on the ground remains a major challenge in Forest administration and management. Cadastral forest mapping deals with forestlands boundary delineation and their associated characterization (forest/non forest). The present study is an application of high resolution World View-II data for digitization of Protected Forest boundary at cadastral level with integration of Records of Right (ROR) data. Cadastral vector data was generated by digitization of spatial data using scanned mussavies in ArcGIS environment. Ortho-images were created from World View-II digital stereo data with Universal Transverse Mercator coordinate system with WGS 84 datum. Cadastral vector data of Bir Hisar (Hisar district, Haryana) and adjacent villages was spatially adjusted over ortho-image using ArcGIS software. Edge matching of village boundaries was done with respect to khasra boundaries of individual village. The notified forest grids were identified on ortho-image and grid vector data was extracted from georeferenced cadastral data. Cadastral forest boundary vectors were digitized from ortho-images. Accuracy of cadastral data was checked by comparison of randomly selected geo-coordinates points, tie lines and boundary measurements of randomly selected parcels generated from image data set with that of actual field measurements. Area comparison was done between cadastral map area, the image map area and RoR area. The area covered under Protected Forest was compared with ROR data and within an accuracy of less than 1 % from ROR area was accepted. The methodology presented in this paper is useful to update the cadastral forest maps. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. The study introduces the use of very high resolution satellite data to develop a method for cadastral surveying through on - screen digitization in a less time as compared to the old fashioned cadastral parcel boundaries surveying method.

An analysis of tree mortality using high resolution remotely-sensed data for mixed-conifer forests in San Diego county

NASA Astrophysics Data System (ADS)

Freeman, Mary Pyott

ABSTRACT An Analysis of Tree Mortality Using High Resolution Remotely-Sensed Data for Mixed-Conifer Forests in San Diego County by Mary Pyott Freeman The montane mixed-conifer forests of San Diego County are currently experiencing extensive tree mortality, which is defined as dieback where whole stands are affected. This mortality is likely the result of the complex interaction of many variables, such as altered fire regimes, climatic conditions such as drought, as well as forest pathogens and past management strategies. Conifer tree mortality and its spatial pattern and change over time were examined in three components. In component 1, two remote sensing approaches were compared for their effectiveness in delineating dead trees, a spatial contextual approach and an OBIA (object based image analysis) approach, utilizing various dates and spatial resolutions of airborne image data. For each approach transforms and masking techniques were explored, which were found to improve classifications, and an object-based assessment approach was tested. In component 2, dead tree maps produced by the most effective techniques derived from component 1 were utilized for point pattern and vector analyses to further understand spatio-temporal changes in tree mortality for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Results indicate that conifer mortality was significantly clustered, increased substantially between 2002 and 2005, and was non-random with respect to tree species and diameter class sizes. In component 3, multiple environmental variables were used in Generalized Linear Model (GLM-logistic regression) and decision tree classifier model development, revealing the importance of climate and topographic factors such as precipitation and elevation, in being able to predict areas of high risk for tree mortality. The results from this study highlight the importance of multi-scale spatial as well as temporal analyses, in order to understand mixed-conifer forest structure, dynamics, and processes of decline, which can lead to more sustainable management of forests with continued natural and anthropogenic disturbance.

Wavelet-based energy features for glaucomatous image classification.

PubMed

Dua, Sumeet; Acharya, U Rajendra; Chowriappa, Pradeep; Sree, S Vinitha

2012-01-01

Texture features within images are actively pursued for accurate and efficient glaucoma classification. Energy distribution over wavelet subbands is applied to find these important texture features. In this paper, we investigate the discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and biorthogonal (bio3.3, bio3.5, and bio3.7) wavelet filters. We propose a novel technique to extract energy signatures obtained using 2-D discrete wavelet transform, and subject these signatures to different feature ranking and feature selection strategies. We have gauged the effectiveness of the resultant ranked and selected subsets of features using a support vector machine, sequential minimal optimization, random forest, and naïve Bayes classification strategies. We observed an accuracy of around 93% using tenfold cross validations to demonstrate the effectiveness of these methods.

Louisiana’s Palustris Experimental Forest: 75 years of research that transformed the South

Treesearch

James P. Barnett; James D. Haywood; Henry A. Pearson

2011-01-01

The Palustris Experimental Forest, located on Kisatchie National Forest, has been in existence for 75 years. Research at Palustris has focused on southern pine reforestation technology, including seed production, bareroot nursery production, direct seeding, and planting container seedlings. After establishing pine plantations, researchers developed stand management...

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Treesearch

T.A. Kennaway; E.H. Helmer; M.A. Lefsky; T.A. Brandeis; K.R. Sherill

2008-01-01

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researchers for accurate forest inventory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the...

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Treesearch

Todd Kennaway; Eileen Helmer; Michael Lefsky; Thomas Brandeis; Kirk Sherrill

2009-01-01

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researachers for accurate forest inverntory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the...

Investigation to develop a multistage forest sampling inventory system using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. W. (Principal Investigator); Wert, S. L.

1975-01-01

The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.

Space Radar Image of Lozere Department, Mende, France

NASA Image and Video Library

1999-05-01

This is an X-band seasonal image of the central part of Lozere Departement situated south of the Massif Central in France. The image is 10 kilometers by 25 kilometers (6 miles by 15.5 miles) and is centered at approximately 44.3 degrees north latitude and 3 degrees east longitude. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on April 15, 1994 and on October 6, 1994. The image channels have the following color assignments: red was acquired in April; green was acquired in October; and blue is the ratio of the two data sets combined. Seasonal differences in the vegetation are visible in pink, which are heaths growing in the spring. This research area features two large limestone plateaus cut by the famous Gorges du Tarn, standing in parallel with the granite mountain range known as the Cevennes Mountains nearby. Land-use consists mainly of grasslands, heaths and forests. Forest types seen in the images are Austrian pines,Scots pines, spruce, fir and beech trees. Most forests were planted at the end of the 19th century through a national reforestation program aimed at reducing the strong erosion risks in these areas. This program was so successful that today the forests are exploited for forest pulpwood and sawlogs, but also remain protected as conservation regions. The study being performed in this area will assess the potential of spaceborne radar remote sensing for temperate forest type mapping and forest resource monitoring. The combination of X-band SAR data with lower frequency data (such as the SIR-C L-band data) allows scientists to distinguish forest tree species and biomass, or areas of ground vegetation. The lessons learned from the radar images of these controlled forest regions can be applied to larger areas and naturally grown forests to help ecologists protect and maintain them. The SIR-C/X-SAR images will be investigated by scientists from the remote sensing laboratory Cemagref in Montpellier and the National Forestry Board in Mende, France. http://photojournal.jpl.nasa.gov/catalog/PIA01755

Complex land use and cover trajectories in the northern Choco bioregion of Colombia

NASA Astrophysics Data System (ADS)

Santos, Carolina

The Choco bioregion in Northwestern Colombia is a lowland rain forest and hotspot of biodiversity. Significant land use and cover change (LUCC) is occurring throughout the region driven by global markets, illicit drug production, and civil unrest. The dominant land cover conversion is from primary forest to African Palm plantations, mediated and modified by complex combinations of social and biophysical drivers. This research combined a remote sensing based methodology to monitor LUCC in the region with an analytical approach for evaluating the possible trajectories of LUCC in a complex biological, socio-economical, and political environment. Synoptic LUCC models were developed using textural classification derived from Synthetic Aperture Radar (SAR) images for the period 1995 to 2010. LUCC models along with empirical social and spatial biophysical drivers were used to project historical land use trajectories. DINAMICA EGO a complex systems based spatial analytical framework was adopted as the platform to model land use change. The RADAR backscatter was able to capture areas were forest has been converted to African Oil Palm Plantations. However, an in depth characterization of the LUC dynamics was problematic given the spectral and spatial limitations of the sensor combined with the lack of ground data. The results of the LUC model suggest that under the current socio-political conditions African oil palm plantations will continue to expand toward forested areas into the territories traditionally inhabited by Afro-Colombians and Indigenous populations. Insecure land tenure appears as a main driver of the transformation in close association with the conditions created by the armed conflict, and the drug traffic. The rate of the transformation appears to slow down in the period after 2007. However, according to the model by 2020 most of the area inhabited by ethnic groups will be transform to AOP. This study contributes towards the understanding of land use change in the context of social conflict. Although, it is recognized that conflicts impact the land--use and land-cover, few studies have address the linkages between particular circumstances and events in the conflict and the consequences for the land. As resource conflicts spread around the globe a better understanding of how it impacts the land and the people is paramount.

Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Aber, John D.; Peterson, David L.; Melillo, Jerry M.

1988-01-01

The use of images acquired by the Airborne Imaging Spectrometer, an experimental high-spectral resolution imaging sensor developed by NASA, to estimate the lignin concentration of whole forest canopies in Wisconsin is reported. The observed strong relationship between canopy lignin concentration and nitrogen availability in seven undisturbed forest ecosystems on Blackhawk Island, Wisconsin, suggests that canopy lignin may serve as an index for site nitrogen status. This predictive relationship presents the opportunity to estimate nitrogen-cycling rates across forested landscapes through remote sensing.

A model-based approach to estimating forest area

Treesearch

Ronald E. McRoberts

2006-01-01

A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...

Wildfires in Chernobyl-contaiminated forests and risks to the population and the environment: A new nuclear disaster about to happen?

Treesearch

Nikolaos Evangeliou; Yves Balkanski; Anne Cozic; Wei Min Hao; Anders Pape Moller

2014-01-01

Radioactive contamination in Ukraine, Belarus and Russia after the Chernobyl accident left large rural and forest areas to their own fate. Forest succession in conjunction with lack of forest management started gradually transforming the landscape. During the last 28 years dead wood and litter have dramatically accumulated in these areas, whereas climate change has...

Transforming round pegs to fill square holes:Facing the challenge of forest inventories as tools of environmental policy for the 21st century

Treesearch

Victor A. Rudis

1993-01-01

Todays forest inventory specialist is challenged to combine inventories and analysis of timber with range recreation, soil, water, and wildlife resources, related human uses, and social and economic concerns.Lessons learned in adapting timber-oriented forest inventories toward holistic forest resources assessment are provided.Discussed are ways to maintain dialogue...

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.

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

Method of determining forest production from remotely sensed forest parameters

DOEpatents

Corey, J.C.; Mackey, H.E. Jr.

1987-08-31

A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

Coastal Land-Use Dynamics in Southern Sonora, Mexico Between 1973-2001

NASA Astrophysics Data System (ADS)

Luers, A. L.; Seto, K. C.; Matson, P. A.; Matson, P. A.; Naylor, R.; Moreno, G. C.

2001-12-01

Human activities, such as urbanization, agriculture, and shrimp farming are dramatically changing the coastal landscape of southern Sonora, Mexico, and threatening the ecosystems goods and services these natural systems provide. In this study we investigate the trends of human-induced transformations of coastal lands between 1973 and the present. Subscenes from two mosaicked Landsat images from 1973 (MSS), 1986 (MSS), 1992 (MSS), 1994 (TM), 2000 (ETM), 2001 (ETM) were analyzed to evaluate land use and cover changes. We used a combination of supervised and unsupervised maximum likelihood classification to produce thematic land use and land cover maps for change detection and modeling. The results show that the most prevalent form of land-use change in the region over the study period has been the transformation of Pithaya forest and coastal wetlands to shrimp aquaculture. Shrimp farms that did not exist in the region in the early 1980s now represent over 12 percent of the study area. Our analysis suggests that this boom in shrimp farming was influenced by a series of policy reforms instituted by the Mexican Government over the last decade intended to open the rural economy to global markets. These reforms include modifications to the Fisheries, Foreign Investment and Land Tenure Laws, changes in the rural credit system, and liberalization of international trade policies (NAFTA). The data indicate overall increased rates of land conversion from natural covers (Pithaya forest, Mesquite forest, Choyal, salt flats) to human dominated ecosystems (aquaculture, agriculture, salt ponds, urban) in the post-reform period (1994 - 2001) compared to the pre-reform period (1973 - 1992). Our results highlight the importance of monitoring local impacts in evaluating national policies.

Interpretation of forest characteristics from computer-generated images.

Treesearch

T.M. Barrett; H.R. Zuuring; T. Christopher

2006-01-01

The need for effective communication in the management and planning of forested landscapes has led to a substantial increase in the use of visual information. Using forest plots from California, Oregon, and Washington, and a survey of 183 natural resource professionals in these states, we examined the use of computer-generated images to convey information about forest...

[Carbon emissions and low-carbon regulation countermeasures of land use change in the city and town concentrated area of central Liaoning Province, China].

PubMed

Xi, Feng-ming; Liang, Wen-juan; Niu, Ming-fen; Wang, Jiao-yue

2016-02-01

Carbon emissions due to land use change have an important impact on global climate change. Adjustment of regional land use patterns has a great scientific significance to adaptation to a changing climate. Based on carbon emission/absorption parameters suitable for Liaoning Province, this paper estimated the carbon emission of land use change in the city and town concentrated area of central Liaoning Province. The results showed that the carbon emission and absorption were separately 308.51 Tg C and 11.64 Tg C from 1997 to 2010. It meant 3.8% of carbon emission. was offset by carbon absorption. Among the 296.87 Tg C net carbon emission of land use change, carbon emission of remaining land use type was 182.24 Tg C, accounting for 61.4% of the net carbon emission, while the carbon emission of land use transformation was 114.63 Tg C, occupying the rest 38.6% of net carbon emission. Through quantifying the mapping relationship between land use change and carbon emission, it was shown that during 1997-2004 the contributions of remaining construction land (40.9%) and cropland transform ation to construction land (40.6%) to carbon emission were larger, but the greater contributions to carbon absorption came from cropland transformation to forest land (38.6%) and remaining forest land (37.5%). During 2004-2010, the land use types for carbon emission and absorption were the same to the period of 1997-2004, but the contribution of remaining construction land to carbon emission increased to 80.6%, and the contribution of remaining forest land to carbon absorption increased to 71.7%. Based on the carbon emission intensity in different land use types, we put forward the low-carbon regulation countermeasures of land use in two aspects. In carbon emission reduction, we should strict control land transformation to construction land, increase the energy efficiency of construction land, and avoid excessive development of forest land and water. In carbon sink increase, we should improve forest coverage rate, implement cropland, grassland transform to forest land, strengthen forest land and water protection, and adjust cropland internal structure and scientifically implement cropland management.

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...

Special forest products: biodiversity meets the marketplace.

Treesearch

Nan C. Vance; Jane Thomas

1997-01-01

Although North American forests traditionally have been viewed as a source of wood and paper,a variety of profitable products are being discovered that come not only from trees, but from nonwoody plants, lichens, fungi, algae, and microorganisms. The northern temperate forests’ abundant biotic resources are being transformed into medicinals, botanicals, decoratives,...

Leaky nitrogen cycle in pristine African montane rainforest soil

NASA Astrophysics Data System (ADS)

Rütting, Tobias; Cizungu Ntaboba, Landry; Roobroeck, Dries; Bauters, Marijn; Huygens, Dries; Boeckx, Pascal

2015-10-01

Many pristine humid tropical forests show simultaneously high nitrogen (N) richness and sustained loss of bioavailable N forms. To better understand this apparent upregulation of the N cycle in tropical forests, process-based understanding of soil N transformations, in geographically diverse locations, remains paramount. Field-based evidence is limited and entirely lacking for humid tropical forests on the African continent. This study aimed at filling both knowledge gaps by monitoring N losses and by conducting an in situ 15N labeling experiment in the Nyungwe tropical montane forest in Rwanda. Here we show that this tropical forest shows high nitrate (NO3-) leaching losses, confirming findings from other parts of the world. Gross N transformation rates point to an open soil N cycle with mineralized N nitrified rather than retained via immobilization; gross immobilization of NH4+ and NO3- combined accounted for 37% of gross mineralization, and plant N uptake is dominated by ammonium (NH4+). This study provided new process understanding of soil N cycling in humid tropical forests and added geographically independent evidence that humid tropical forests are characterized by soil N dynamics and N inputs sustaining bioavailable N loss.

The Radon cumulative distribution transform and its application to image classification

PubMed Central

Kolouri, Soheil; Park, Se Rim; Rohde, Gustavo K.

2016-01-01

Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g. Fourier, Wavelet, etc.) are linear transforms, and, by themselves, are unable to substantially simplify the representation of image classes for classification. Here we describe a nonlinear, invertible, low-level image processing transform based on combining the well known Radon transform for image data, and the 1D Cumulative Distribution Transform proposed earlier. We describe a few of the properties of this new transform, and with both theoretical and experimental results show that it can often render certain problems linearly separable in transform space. PMID:26685245

Comparison of U.S. Forest Land AreaEstimates From Forest Inventory and Analysis, National Resources Inventory, and Four Satellite Image-Derived Land Cover Data Sets

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Veronica C. Lessard

2005-01-01

Our objective was to test one application of remote sensing technology for complementing forest resource assessments by comparing a variety of existing satellite image-derived land cover maps with national inventory-derived estimates of United States forest land area. National Resources Inventory (NRI) 1997 estimates of non-Federal forest land area differed by 7.5...

Urbanization effects on soil nitrogen transformations and microbial biomass in the subtropics

Treesearch

Heather A. Enloe; B. Graeme Lockaby; Wayne C. Zipperer; Greg L. Somers

2015-01-01

As urbanization can involve multiple alterations to the soil environment, it is uncertain how urbanization effects soil nitrogen cycling. We established 22–0.04 ha plots in six different land cover types—rural slash pine (Pinus elliottii) plantations (n=3), rural natural pine forests (n=3), rural natural oak forests (n=4), urban pine forests (n=3), urban oak forests (n...

Early forest fire detection using principal component analysis of infrared video

NASA Astrophysics Data System (ADS)

Saghri, John A.; Radjabi, Ryan; Jacobs, John T.

2011-09-01

A land-based early forest fire detection scheme which exploits the infrared (IR) temporal signature of fire plume is described. Unlike common land-based and/or satellite-based techniques which rely on measurement and discrimination of fire plume directly from its infrared and/or visible reflectance imagery, this scheme is based on exploitation of fire plume temporal signature, i.e., temperature fluctuations over the observation period. The method is simple and relatively inexpensive to implement. The false alarm rate is expected to be lower that of the existing methods. Land-based infrared (IR) cameras are installed in a step-stare-mode configuration in potential fire-prone areas. The sequence of IR video frames from each camera is digitally processed to determine if there is a fire within camera's field of view (FOV). The process involves applying a principal component transformation (PCT) to each nonoverlapping sequence of video frames from the camera to produce a corresponding sequence of temporally-uncorrelated principal component (PC) images. Since pixels that form a fire plume exhibit statistically similar temporal variation (i.e., have a unique temporal signature), PCT conveniently renders the footprint/trace of the fire plume in low-order PC images. The PC image which best reveals the trace of the fire plume is then selected and spatially filtered via simple threshold and median filter operations to remove the background clutter, such as traces of moving tree branches due to wind.

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

NASA Astrophysics Data System (ADS)

Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

2016-09-01

Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

Institutional innovations in the forest industry in Russia: a case study of Irkutsk province

Treesearch

Dennis V. Dayneko; Eric J. Gustafson

2014-01-01

Multiple global changes are impacting Russia today. Economic transformations in Russia have prompted the establishment of new business relations, which are based on innovations in the economic, institutional and ecological spheres, including within the Forest industry. This paper focuses on the Forest sector in Irkutsk province and beyond, examining the basic problems...

A Characterization of the Nonindustrial Private Forest Landowners of Arkansas

Treesearch

Tamara Walkingstick; Donald E. Voth; Richard A. Williams; Jeffery Earl; Carl P. Hitt

2001-01-01

Forest and timber and forest and timberland management are issues of great importance to Arkansas. The timber industry plays a major role in the State's economy and is constantly being transformed as it becomes more capital intensive and as the southern region, including Arkansas, becomes a more important player in the provision of the nation's supply of...

Do canopy disturbances drive forest plantations into more natural conditions? — A case study from Can Gio Biosphere Reserve, Viet Nam

NASA Astrophysics Data System (ADS)

Vogt, Juliane; Kautz, Markus; Fontalvo Herazo, Martha Liliana; Triet, Tran; Walther, Denny; Saint-Paul, Ulrich; Diele, Karen; Berger, Uta

2013-11-01

Large areas of mangrove forests were devastated in South Viet Nam during the second Indochina war. After its end in 1975, extensive reforestation with monocultures took place. Can Gio, one of the biggest replanted sites with about 20,000 ha of mangroves mainly Rhizophora apiculata, was declared a biosphere reserve by the UNESCO in 2000. Although this status now enables progressive forest dynamics, there are still drawbacks resulting from the unnatural character of the plantations. For example, the homogeneous size and age structure as well as the regular arrangement of the planted trees make larger forest stands more vulnerable to synchronized collapsing which can be triggered by stronger winds and storms. A transformation into a more natural forest characterized by a heterogeneous age and size structure and a mixed species composition is of urgent need to avoid a synchronized dieback. In this study we test the capability of natural canopy disturbances (e.g. lightning strikes) to facilitate this transformation.Canopy gaps created by lightning strikes were detected and quantified by remote sensing techniques. SPOT satellite images from the years 2003, 2005 and 2007 provided information about the spatial distribution, size, shape, and formation frequency of the gaps. Lightning strike gaps were identified based on their shape and size. They form small openings (mean: 0.025 ha) and their yearly probability of occurrence was determined to be approximately 0.012 per hectare. Selected gaps were surveyed in the field in 2008 to complement the remote sensing data and to provide information upon forest structure and regeneration.Simulation experiments were carried out with the individual-based KiWi mangrove model for quantifying the influence of different lightning regimes on the vertical and horizontal structure of the R. apiculata plantation. In addition, we conducted simulations with a natural and thus randomly generated forest to compare the structure of the two different cultivation types (i.e. plantation and natural forest). The simulation shows that even small disturbances can already partly buffer the risk of cohort senescence of monospecific even-aged plantations. However, after the decline of the plantation, the disturbance regime does not play an important role for further stand development. After the break-up of the initial strongly regular structure of the simulated plantation, a vertical pattern, i.e. height distribution of the trees, similar to the one of the natural forest, emerged quickly. However, the convergence for the horizontal structure i.e. the distance of trees to their nearest neighbor, took twice as long as for the vertical structure. Our results highlight the importance of small disturbances such as lightning strikes to mitigate vulnerability against synchronous windfall in homogenous forest structures. Hence, creating small openings artificially may be an appropriate management measure in areas where the frequency of natural small-scale disturbances is low.

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

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

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

DOE PAGES

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

2016-04-04

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Pseudo CT estimation from MRI using patch-based random forest

NASA Astrophysics Data System (ADS)

Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian

2017-02-01

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

Mapping forest height, foliage height profiles and disturbance characteristics with time series of gap-filled Landsat and ALI imagery

NASA Astrophysics Data System (ADS)

Helmer, E.; Ruzycki, T. S.; Wunderle, J. M.; Kwit, C.; Ewert, D. N.; Voggesser, S. M.; Brandeis, T. J.

2011-12-01

We mapped tropical dry forest height (RMSE = 0.9 m, R2 = 0.84, range 0.6-7 m) and foliage height profiles with a time series of gap-filled Landsat and Advanced Land Imager (ALI) imagery for the island of Eleuthera, The Bahamas. We also mapped disturbance type and age with decision tree classification of the image time series. Having mapped these variables in the context of studies of wintering habitat of an endangered Nearctic-Neotropical migrant bird, the Kirtland's Warbler (Dendroica kirtlandii), we then illustrated relationships between forest vertical structure, disturbance type and counts of forage species important to the Kirtland's Warbler. The ALI imagery and the Landsat time series were both critical to the result for forest height, which the strong relationship of forest height with disturbance type and age facilitated. Also unique to this study was that seven of the eight image time steps were cloud-gap-filled images: mosaics of the clear parts of several cloudy scenes, in which cloud gaps in a reference scene for each time step are filled with image data from alternate scenes. We created each cloud-cleared image, including a virtually seamless ALI image mosaic, with regression tree normalization of the image data that filled cloud gaps. We also illustrated how viewing time series imagery as red-green-blue composites of tasseled cap wetness (RGB wetness composites) aids reference data collection for classifying tropical forest disturbance type and age.

Integrating Landsat-derived disturbance maps with FIA inventory data: Applications for state-Level forest resource assessments

Treesearch

Sonja Oswalt; Chengquan Huang; Hua Shi; James Vogelmann; Zhiliang Zhu; Samuel N. Goward; John Coulston

2009-01-01

Landsat images have been widely used for assessing forest characteristics and dynamics. Recently, significant progress has been made towards indepth exploration of the rich Landsat archive kept by the U.S. Geological Survey to improve our under standing of forest disturbance and recovery processes. In this study, we used Landsat images to map forest disturbances at...

Forest cover type analysis of New England forests using innovative WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Kovacs, Jenna M.

For many years, remote sensing has been used to generate land cover type maps to create a visual representation of what is occurring on the ground. One significant use of remote sensing is the identification of forest cover types. New England forests are notorious for their especially complex forest structure and as a result have been, and continue to be, a challenge when classifying forest cover types. To most accurately depict forest cover types occurring on the ground, it is essential to utilize image data that have a suitable combination of both spectral and spatial resolution. The WorldView-2 (WV2) commercial satellite, launched in 2009, is the first of its kind, having both high spectral and spatial resolutions. WV2 records eight bands of multispectral imagery, four more than the usual high spatial resolution sensors, and has a pixel size of 1.85 meters at the nadir. These additional bands have the potential to improve classification detail and classification accuracy of forest cover type maps. For this reason, WV2 imagery was utilized on its own, and in combination with Landsat 5 TM (LS5) multispectral imagery, to evaluate whether these image data could more accurately classify forest cover types. In keeping with recent developments in image analysis, an Object-Based Image Analysis (OBIA) approach was used to segment images of Pawtuckaway State Park and nearby private lands, an area representative of the typical complex forest structure found in the New England region. A Classification and Regression Tree (CART) analysis was then used to classify image segments at two levels of classification detail. Accuracies for each forest cover type map produced were generated using traditional and area-based error matrices, and additional standard accuracy measures (i.e., KAPPA) were generated. The results from this study show that there is value in analyzing imagery with both high spectral and spatial resolutions, and that WV2's new and innovative bands can be useful for the classification of complex forest structures.

Image compression system and method having optimized quantization tables

NASA Technical Reports Server (NTRS)

Ratnakar, Viresh (Inventor); Livny, Miron (Inventor)

1998-01-01

A digital image compression preprocessor for use in a discrete cosine transform-based digital image compression device is provided. The preprocessor includes a gathering mechanism for determining discrete cosine transform statistics from input digital image data. A computing mechanism is operatively coupled to the gathering mechanism to calculate a image distortion array and a rate of image compression array based upon the discrete cosine transform statistics for each possible quantization value. A dynamic programming mechanism is operatively coupled to the computing mechanism to optimize the rate of image compression array against the image distortion array such that a rate-distortion-optimal quantization table is derived. In addition, a discrete cosine transform-based digital image compression device and a discrete cosine transform-based digital image compression and decompression system are provided. Also, a method for generating a rate-distortion-optimal quantization table, using discrete cosine transform-based digital image compression, and operating a discrete cosine transform-based digital image compression and decompression system are provided.

NITROGEN DEPOSITION AND ORGANIC MATTER MANIPULATIONS AFFECT GROSS AND NET NITROGEN TRANSFORMATIONS IN TWO TEMPERATE FORESTS SOILS

EPA Science Inventory

Soil nitrogen transformations are intricately linked to carbon transformations. We utilized two existing organic matter manipulation sites in western Oregon, USA and Hungary to investigate these linkages. Our questions were: 1) Does the quantity and quality of organic matter af...

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery

USGS Publications Warehouse

Helmer, E.H.; Kennaway, T.A.; Pedreros, D.H.; Clark, M.L.; Marcano-Vega, H.; Tieszen, L.L.; Ruzycki, T.R.; Schill, S.R.; Carrington, C.M.S.

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering lowland forest clearing for agriculture. Copyright 2008 College of Arts and Sciences.

Deeply learnt hashing forests for content based image retrieval in prostate MR images

NASA Astrophysics Data System (ADS)

Shah, Amit; Conjeti, Sailesh; Navab, Nassir; Katouzian, Amin

2016-03-01

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.

Space Radar Image of Raco, Michigan

NASA Image and Video Library

1999-05-01

These are two false-color composites of Raco, Michigan, located at the eastern end of Michigan upper peninsula, west of Sault Ste. Marie and south of Whitefish Bay on Lake Superior. The two images (centered at 46.39 degrees north latitude, 84.88 degrees west longitude) show significant seasonal changes in the mid-latitude region of mixed deciduous and coniferous forests. The images were acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the shuttle Endeavour on the sixth orbit of each mission. In these images, red is L-band (23 cm) with horizontal/vertical polarization; green is C-band (6 cm) with horizontal/vertical polarization; blue is C-band with horizontal/horizontal polarization. The region shown is largely forested and includes a large portion of Hiawatha National Forest, as well as an agricultural region near the bottom of each image. In early April, the area was snow-covered with up to 50 centimeters (19.5 inches) of snow in forest clearings and agricultural fields. Buds had not yet broken on deciduous trees, but the trees were not frozen and sap was generally flowing. Lake Superior, in the upper right, and the small inland lakes were frozen and snow-covered on April 9, 1994. By the end of September, deciduous trees were just beginning to change color after a relatively wet period. Leaf loss was estimated at about 30 percent, depending on the species, and the soil was moist to wet after a heavy rainfall on September 28, 1994. Most agricultural fields were covered with grasses of up to 60 centimeters (23 inches) in height. In the two images the colors are related to the types of land cover (i.e. vegetation type) and the brightness is related to the amount of plant material and its relative moisture content. Significant seasonal changes between early spring and early fall are illustrated by this pair of images. For the agricultural region near the bottom of the images, the change from snow-cover to moist soil with short vegetation cover is shown by the color change from blue to green and blue. The green color corresponds to significant increases in vegetation cover and field-to-field differences in blue are the result of differences in surface roughness and soil moisture. In the forested areas, many of the conifer forests appear similar in both images (red pine forests appear red in both images). However, there is more blue and green in the September 30, 1994 image as a consequence of greater foliage and more moisture in the forest crowns. Lowland conifer forests (spruce and northern white cedars) appear as bright green in both images. Deciduous forests produce very strong radar returns at these frequencies and polarization combinations, resulting in a nearly white appearance on the images (the specific color mix is related to the local species mix). In the September 30, 1994 image, the areas of deciduous forest appear darker than in the April image because of the weaker radar signal from the foliage in the crown layer. The clear-cut areas (shown in April by the irregularly shaped dark areas in the center) change dramatically in appearance due to loss of snow cover and increases in soil moisture and vegetation cover by the end of September. http://photojournal.jpl.nasa.gov/catalog/PIA01730

Imaging soil litter decomposition: Integrating sychrotron-based elemental and molecular imaging techniques

EPA Science Inventory

Forest ecosystems contain approximately one-half of the Earths terrestrial carbon (C) (1146 Pg), with two-thirds (787 Pg) of this pool residing in forest soils. Given the magnitude of the forest soil C pool, it is critical to understand the mechanisms that control soil organic ma...

Forest height estimation from mountain forest areas using general model-based decomposition for polarimetric interferometric synthetic aperture radar images

NASA Astrophysics Data System (ADS)

Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi

2014-01-01

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

Ransom, K. J.; Sun, G.; Kharuk, V. I.; Howl, J.

2011-01-01

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

Application of Laser Imaging for Bio/geophysical Studies

NASA Technical Reports Server (NTRS)

Hummel, J. R.; Goltz, S. M.; Depiero, N. L.; Degloria, D. P.; Pagliughi, F. M.

1992-01-01

SPARTA, Inc. has developed a low-cost, portable laser imager that, among other applications, can be used in bio/geophysical applications. In the application to be discussed here, the system was utilized as an imaging system for background features in a forested locale. The SPARTA mini-ladar system was used at the International Paper Northern Experimental Forest near Howland, Maine to assist in a project designed to study the thermal and radiometric phenomenology at forest edges. The imager was used to obtain data from three complex sites, a 'seed' orchard, a forest edge, and a building. The goal of the study was to demonstrate the usefulness of the laser imager as a tool to obtain geometric and internal structure data about complex 3-D objects in a natural background. The data from these images have been analyzed to obtain information about the distributions of the objects in a scene. A range detection algorithm has been used to identify individual objects in a laser image and an edge detection algorithm then applied to highlight the outlines of discrete objects. An example of an image processed in such a manner is shown. Described here are the results from the study. In addition, results are presented outlining how the laser imaging system could be used to obtain other important information about bio/geophysical systems, such as the distribution of woody material in forests.

Using satellite image-based maps and ground inventory data to estimate the area of the remaining Atlantic forest in the Brazilian state of Santa Catarina

Treesearch

Alexander C. Vibrans; Ronald E. McRoberts; Paolo Moser; Adilson L. Nicoletti

2013-01-01

Estimation of large area forest attributes, such as area of forest cover, from remote sensing-based maps is challenging because of image processing, logistical, and data acquisition constraints. In addition, techniques for estimating and compensating for misclassification and estimating uncertainty are often unfamiliar. Forest area for the state of Santa Catarina in...

PASSIVELY ESTIMATING INDEX OF REFRACTION FOR SPECULAR REFLECTORS USING POLARIMETRIC HYPERSPECTRAL IMAGING

DTIC Science & Technology

2016-12-22

23 6 Band-averaged radiance image with checkerboard is shown in the upper left. The 2-D Fourier transform of the image is...red is 1) that is multiplied by the Fourier transform of the original image. The inverse Fourier transform is then taken to get the final image with...Polarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 IFTS Imaging Fourier Transform Spectrometer

The tropical forest and fire emissions experiment: Laboratory fire measurement and synthesis of campaign data

Treesearch

R. J. Yokelson; T. J. Christian; T. G. Karl; A. Guenther

2008-01-01

As part of the Tropical Forest and Fire Emissions Experiment (TROFFEE), tropical forest fuels were burned in a large, biomass-fire simulation facility and the smoke was characterized with open-path Fourier transform infrared spectroscopy (FTIR), proton-transfer reaction mass spectrometry (PTR-MS), gas chromatography (GC), GC/PTRMS, and filter sampling of the particles...

Ecosystem transformation by emerging infectious disease: loss of large tanoak from California forests

Treesearch

Richard C. Cobb; Joao A.N. Filipe; Ross K. Meentemeyer; Christopher A. Gilligan; David M. Rizzo

2012-01-01

1. Few pathogens are the sole or primary cause of species extinctions, but forest disease has caused spectacular declines in North American overstorey trees and restructured forest ecosystems at large spatial scales over the past 100 years. These events threaten biodiversity associated with impacted host trees and other resources valued by human societies even when...

Space images processing methodology for assessment of atmosphere pollution impact on forest-swamp territories

NASA Astrophysics Data System (ADS)

Polichtchouk, Yuri; Tokareva, Olga; Bulgakova, Irina V.

2003-03-01

Methodical problems of space images processing for assessment of atmosphere pollution impact on forest ecosystems using geoinformation systems are developed. An approach to quantitative assessment of atmosphere pollution impact on forest ecosystems is based on calculating relative squares of forest landscapes which are inside atmosphere pollution zones. Landscape structure of forested territories in the southern part of Western Siberia are determined on the basis of procession of middle resolution space images from spaceborn Resource-O. Particularities of atmosphere pollution zones modeling caused by gas burning in torches on territories of oil fields are considered. Pollution zones were revealed by modeling of contaminants dispersal in atmosphere with standard models. Polluted landscapes squares are calculated depending on atmosphere pollution level.

Forestry impacts on the hidden fungal biodiversity associated with bryophytes.

PubMed

Davey, Marie L; Kauserud, Håvard; Ohlson, Mikael

2014-10-01

Recent studies have revealed an unexpectedly high, cryptic diversity of fungi associated with boreal forest bryophytes. Forestry practices heavily influence the boreal forest and fundamentally transform the landscape. However, little is known about how bryophyte-associated fungal communities are affected by these large-scale habitat transformations. This study assesses to what degree bryophyte-associated fungal communities are structured across the forest successional stages created by current forestry practices. Shoots of Hylocomium splendens were collected in Picea abies dominated forests of different ages, and their associated fungal communities were surveyed by pyrosequencing of ITS2 amplicons. Although community richness, diversity and evenness were relatively stable across the forest types and all were consistently dominated by ascomycete taxa, there was a marked shift in fungal community composition between young and old forests. Numerous fungal operational taxonomic units (OTUs) showed distinct affinities for different forest ages. Spatial structure was also detected among the sites, suggesting that environmental gradients resulting from the topography of the study area and dispersal limitations may also significantly affect bryophyte-associated fungal community structure. This study confirms that Hylocomium splendens hosts an immense diversity of fungi and demonstrates that this community is structured in part by forest age, and as such is highly influenced by modern forestry practices. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

Fast image interpolation via random forests.

PubMed

Huang, Jun-Jie; Siu, Wan-Chi; Liu, Tian-Rui

2015-10-01

This paper proposes a two-stage framework for fast image interpolation via random forests (FIRF). The proposed FIRF method gives high accuracy, as well as requires low computation. The underlying idea of this proposed work is to apply random forests to classify the natural image patch space into numerous subspaces and learn a linear regression model for each subspace to map the low-resolution image patch to high-resolution image patch. The FIRF framework consists of two stages. Stage 1 of the framework removes most of the ringing and aliasing artifacts in the initial bicubic interpolated image, while Stage 2 further refines the Stage 1 interpolated image. By varying the number of decision trees in the random forests and the number of stages applied, the proposed FIRF method can realize computationally scalable image interpolation. Extensive experimental results show that the proposed FIRF(3, 2) method achieves more than 0.3 dB improvement in peak signal-to-noise ratio over the state-of-the-art nonlocal autoregressive modeling (NARM) method. Moreover, the proposed FIRF(1, 1) obtains similar or better results as NARM while only takes its 0.3% computational time.

Image Fusion Algorithms Using Human Visual System in Transform Domain

NASA Astrophysics Data System (ADS)

Vadhi, Radhika; Swamy Kilari, Veera; Samayamantula, Srinivas Kumar

2017-08-01

The endeavor of digital image fusion is to combine the important visual parts from various sources to advance the visibility eminence of the image. The fused image has a more visual quality than any source images. In this paper, the Human Visual System (HVS) weights are used in the transform domain to select appropriate information from various source images and then to attain a fused image. In this process, mainly two steps are involved. First, apply the DWT to the registered source images. Later, identify qualitative sub-bands using HVS weights. Hence, qualitative sub-bands are selected from different sources to form high quality HVS based fused image. The quality of the HVS based fused image is evaluated with general fusion metrics. The results show the superiority among the state-of-the art resolution Transforms (MRT) such as Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Contourlet Transform (CT), and Non Sub Sampled Contourlet Transform (NSCT) using maximum selection fusion rule.

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

Geometric and Radiometric Evaluation of Rasat Images

NASA Astrophysics Data System (ADS)

Cam, Ali; Topan, Hüseyin; Oruç, Murat; Özendi, Mustafa; Bayık, Çağlar

2016-06-01

RASAT, the second remote sensing satellite of Turkey, was designed and assembled, and also is being operated by TÜBİTAK Uzay (Space) Technologies Research Institute (Ankara). RASAT images in various levels are available free-of-charge via Gezgin portal for Turkish citizens. In this paper, the images in panchromatic (7.5 m GSD) and RGB (15 m GSD) bands in various levels were investigated with respect to its geometric and radiometric characteristics. The first geometric analysis is the estimation of the effective GSD as less than 1 pixel for radiometrically processed level (L1R) of both panchromatic and RGB images. Secondly, 2D georeferencing accuracy is estimated by various non-physical transformation models (similarity, 2D affine, polynomial, affine projection, projective, DLT and GCP based RFM) reaching sub-pixel accuracy using minimum 39 and maximum 52 GCPs. The radiometric characteristics are also investigated for 8 bits, estimating SNR between 21.8-42.2, and noise 0.0-3.5 for panchromatic and MS images for L1R when the sea is masked to obtain the results for land areas. The analysis show that RASAT images satisfies requirements for various applications. The research is carried out in Zonguldak test site which is mountainous and partly covered by dense forest and urban areas.

Invasive plants transform the three-dimensional structure of rain forests

PubMed Central

Asner, Gregory P.; Hughes, R. Flint; Vitousek, Peter M.; Knapp, David E.; Kennedy-Bowdoin, Ty; Boardman, Joseph; Martin, Roberta E.; Eastwood, Michael; Green, Robert O.

2008-01-01

Biological invasions contribute to global environmental change, but the dynamics and consequences of most invasions are difficult to assess at regional scales. We deployed an airborne remote sensing system that mapped the location and impacts of five highly invasive plant species across 221,875 ha of Hawaiian ecosystems, identifying four distinct ways that these species transform the three-dimensional (3D) structure of native rain forests. In lowland to montane forests, three invasive tree species replace native midcanopy and understory plants, whereas one understory invader excludes native species at the ground level. A fifth invasive nitrogen-fixing tree, in combination with a midcanopy alien tree, replaces native plants at all canopy levels in lowland forests. We conclude that this diverse array of alien plant species, each representing a different growth form or functional type, is changing the fundamental 3D structure of native Hawaiian rain forests. Our work also demonstrates how an airborne mapping strategy can identify and track the spread of certain invasive plant species, determine ecological consequences of their proliferation, and provide detailed geographic information to conservation and management efforts. PMID:18316720

Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery

NASA Astrophysics Data System (ADS)

Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.

2015-04-01

Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2-37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations.

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

Measurements of canopy chemistry with 1992 AVIRIS data at Blackhawk Island and Harvard Forest

NASA Technical Reports Server (NTRS)

Martin, Mary E.; Aber, John D.

1993-01-01

The research described in this paper was designed to determine if high spectral resolution imaging spectrometer data can be used to measure the chemical composition of forest foliage, specifically nitrogen and lignin concentration. Information about the chemical composition of forest canopies can be used to determine nutrient cycling rates and carbon balances in forest ecosystems. This paper will describe the results relating data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) to field measured canopy chemistry at Blackhawk Island, WI and Harvard Forest, MA.

Analyzing Landsat time-series data across adjacent path/rows and across multiple cycles of FIA: Lessons learned in southern Missouri

Treesearch

Mark Nelson; Sean Healey; W. Keith Moser; Mark Hansen; Warren Cohen; Mark Hatfield; Nancy Thomas; Jeff Masek

2009-01-01

The North American Forest Dynamics (NAFD) Program is assessing disturbance and regrowth in the forests of the continent. These forest dynamics are interpreted from per-pixel estimates of forest biomass, which are produced for a time series of Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced TM Plus images. Image data are combined with sample plot data from the...

Table-driven image transformation engine algorithm

NASA Astrophysics Data System (ADS)

Shichman, Marc

1993-04-01

A high speed image transformation engine (ITE) was designed and a prototype built for use in a generic electronic light table and image perspective transformation application code. The ITE takes any linear transformation, breaks the transformation into two passes and resamples the image appropriately for each pass. The system performance is achieved by driving the engine with a set of look up tables computed at start up time for the calculation of pixel output contributions. Anti-aliasing is done automatically in the image resampling process. Operations such as multiplications and trigonometric functions are minimized. This algorithm can be used for texture mapping, image perspective transformation, electronic light table, and virtual reality.

Responses of vegetation to a rise in water level at Kerkini Reservoir (1982-1991), a Ramsar site in northern Greece

NASA Astrophysics Data System (ADS)

Crivelli, A. J.; Grillas, P.; Lacaze, B.

1995-05-01

The floodplain of the river Strymon at Kerkini (northern Greece) was transformed into an irrigation reservoir by the construction of a dam in 1932 and subsequently enlarged in 1982. The aims of this study were to quantify the changes occurring in the various habitat types following raising of the waterlevel and to assess the stability of the plant communities present at this Ramsar site. The current hydrological regime, which has been stable since 1986, is typified by an increase in mean annual reservoir level of 2.2 m and by an increase in the annual range in level of 1.3 m. Landsat (1980, 1981, 1984, 1986, and 1988) and SPOT (1990) satellite images show a decrease in the area of grassland and shallow water areas, the very rapid disappearance of reedbeds, the appearance of beds of Nymphaea and the disappearance of half the forest area. The flooded forest, dominated by Salix alba, is a key habitat contributing to the biological richness of this wetland of international importance. The decrease in the forested area will continue because of the death of standing trees, the absence of regeneration under the new regime, the felling of trees and grazing. Management could be undertaken to ensure the survival of forested habitat and reedbeds at Kerkini, but this would require that the authorities take into account nature conservation and the protected status of the site and not raise the water level again.

Image compression-encryption algorithms by combining hyper-chaotic system with discrete fractional random transform

NASA Astrophysics Data System (ADS)

Gong, Lihua; Deng, Chengzhi; Pan, Shumin; Zhou, Nanrun

2018-07-01

Based on hyper-chaotic system and discrete fractional random transform, an image compression-encryption algorithm is designed. The original image is first transformed into a spectrum by the discrete cosine transform and the resulting spectrum is compressed according to the method of spectrum cutting. The random matrix of the discrete fractional random transform is controlled by a chaotic sequence originated from the high dimensional hyper-chaotic system. Then the compressed spectrum is encrypted by the discrete fractional random transform. The order of DFrRT and the parameters of the hyper-chaotic system are the main keys of this image compression and encryption algorithm. The proposed algorithm can compress and encrypt image signal, especially can encrypt multiple images once. To achieve the compression of multiple images, the images are transformed into spectra by the discrete cosine transform, and then the spectra are incised and spliced into a composite spectrum by Zigzag scanning. Simulation results demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.

View of west end of Childs Powerhouse, including transformer station ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View of west end of Childs Powerhouse, including transformer station and associated sheds. Looking downstream (east) - Childs-Irving Hydroelectric Project, Childs System, Childs Powerhouse, Forest Service Road 708/502, Camp Verde, Yavapai County, AZ

Comparison and evaluation on image fusion methods for GaoFen-1 imagery

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Zhao, Junqing; Zhang, Ling

2016-10-01

Currently, there are many research works focusing on the best fusion method suitable for satellite images of SPOT, QuickBird, Landsat and so on, but only a few of them discuss the application of GaoFen-1 satellite images. This paper proposes a novel idea by using four fusion methods, such as principal component analysis transform, Brovey transform, hue-saturation-value transform, and Gram-Schmidt transform, from the perspective of keeping the original image spectral information. The experimental results showed that the transformed images by the four fusion methods not only retain high spatial resolution on panchromatic band but also have the abundant spectral information. Through comparison and evaluation, the integration of Brovey transform is better, but the color fidelity is not the premium. The brightness and color distortion in hue saturation-value transformed image is the largest. Principal component analysis transform did a good job in color fidelity, but its clarity still need improvement. Gram-Schmidt transform works best in color fidelity, and the edge of the vegetation is the most obvious, the fused image sharpness is higher than that of principal component analysis. Brovey transform, is suitable for distinguishing the Gram-Schmidt transform, and the most appropriate for GaoFen-1 satellite image in vegetation and non-vegetation area. In brief, different fusion methods have different advantages in image quality and class extraction, and should be used according to the actual application information and image fusion algorithm.

Space Radar Image of Bahia

NASA Technical Reports Server (NTRS)

1994-01-01

This is a color composite image of southern Bahia, Brazil, centered at 15.22 degree south latitude and 39.07 degrees west longitude. The image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on its 38th orbit of Earth on October 2, 1994. The image covers an area centered over the Una Biological Reserve, one the largest protected areas in northeastern Brazil. The 7,000-hectare reserve is administered by the Brazilian Institute for the Environment and is part of the larger Atlantic coastal forest, a narrow band of rain forest extending along the eastern coast of Brazil. The Atlantic coastal forest of southern Bahia is one of the world's most threatened and diverse ecosystems. Due to widespread settlement, only 2 to 5 percent of the original forest cover remains. Yet the region still contains an astounding variety of plants and animals, including a large number of endemic species. More than half of the region's tree species and 80 percent of its animal species are indigenous and found nowhere else on Earth. The Una Reserve is also the only federally protected habitat for the golden-headed lion tamarin, the yellow-breasted capuchin monkey and many other endangered species. In the past few years, scientists from Brazilian and international conservation organizations have coordinated efforts to study the biological diversity of this region and to develop practical and economically viable options for preserving the remaining primary forests in southern Bahia. The shuttle imaging radar is used in this study to identify various land uses and vegetation types, including remaining patches of primary forest, cabruca forest (cacao planted in the understory of the native forest), secondary forest, pasture and coastal mangrove. Standard remote-sensing technology that relies on light reflected from the forest canopy cannot accurately distinguish between cabruca and undisturbed forest. Optical remote sensing is also limited by the nearly continuous cloud cover in the region and heavy rainfall, which occurs more than 150 days each year. The ability of the shuttle radars to 'see' through the forest canopy to the cultivated cacao below -- independent of weather or sunlight conditions --will allow researchers to distinguish forest from cabruca in unprecedented detail. This SIR-C/X-SAR image was produced by assigning red to the L-band, green to the C-band and blue to the X-band. The Una Reserve is located in the middle of the image west of the coastline and slightly northwest of Comandatuba River. The reserve's primary forests are easily detected by the pink areas in the image. The intensity of red in these areas is due to the high density of forest vegetation (biomass) detected by the radar's L-band (horizontally transmitted and vertically received) channel. Secondary forest is visible along the reserve's eastern border. The Serrado Mar mountain range is located in the top left portion of the image. Cabruca forest to the west of Una Reserve has a different texture and a yellow color. The removal of understory in cabruca forest reduces its biomass relative to primary forest, which changes the L-band and C-band penetration depth and returns, and produces a different texture and color in the image. The region along the Atlantic is mainly mangrove swamp, agricultural fields and urban areas. The high intensity of blue in this region is a result of increasing X-band return in areas covered with swamp and low vegetation. The image clearly separates the mangrove region (east of coastal Highway 001, shown in blue) from the taller and dryer forest west of the highway. The high resolution capability of SIR-C/X-SAR imaging and the sensitivity of its frequency and polarization channels to various land covers will be used for monitoring and mapping areas of importance for conservation. Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar(SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI) with the Deutsche Forschungsanstalt fuer luft und Raumfahrt e.V.(DLR), the major partner in science, operations and data processing of X-SAR.

Indirect quantification of fine root production in a near tropical wet mountainous region

NASA Astrophysics Data System (ADS)

Lu, X.; Zhang, J.; Huang, C.

2016-12-01

The main functions of fine root (defined as diameter <= 2 mm) are water and nutrient transports. Besides being a carbon (C) storage pool, it also provides a C flux pathway through soil and plant. Fine root takes up a small portion, normally 5%, of biomass in forest ecosystems, but 30% to 70% of total net primary production. Therefore, quantifying fine root productivity is important to study the forest C budget. Presumably, belowground growth can be indirectly estimated by the more accessible aboveground vegetation structure dynamics. To verify the relationship with fine root productivity, we take internal (floristic) and external (environmental) factors into account, including litter production, canopy density (leaf area index), leaf nutrients (N, K, Ca, Mg, P), weather and/or soil physical conditions (air temperature, humidity, precipitation, solar radiation and soil moisture). The study was conducted in near tropical broadleaf (700 m asl) and conifer (1700 m asl) forests in northeastern Taiwan, generally receiving more than 4000 mm of precipitation per year. For each site, 16 50-cm long minirhizotron tubes were installed. Fine root images were acquired every three weeks. Growth and decline, newly presence and absence of fine roots were delineated by image processing algorithms to derive fine-root productivity through time. Aforementioned internal and external attributes were simultaneously collected as well. Some of these variables were highly correlated and were detrended using principal component analysis. We found that these transformed variables (mainly associated with litter production, precipitation and solar radiation) can delineate the spatiotemporal dynamics of root production well (r2 = 0.87, p = 0.443). In conclusion, this study demonstrated the feasibility of utilized aboveground variables to indirectly assess fine root growth, which could be further developed for the regional scale mapping with aid of remote sensing.

Mapping disturbances in a mangrove forest using multi-date landsat TM imagery.

PubMed

Kovacs, J M; Wang, J; Blanco-Correa, M

2001-05-01

To evaluate the accounts of local fishermen, Landsat TM images (1986, 1993, 1999) were examined to assess potential losses in the mangrove forests of the Teacapán-Agua Brava lagoon system, Mexico. A binary change mask derived from image differencing of a band 4/3 ratio was employed to calculate any changes within this forested wetland. The results indicate that by 1986 approximately 18% (or 86 km2) of the mangrove area under study was either dead or in poor condition. The majority of this damage had occurred in the eastern section of the Agua Brava basin, which coincides, with the reports of the elderly fishermen. Examination of aerial photographs from 1970 revealed no adverse impacts in this area and would suggest, as postulated by the fishermen and other scientists, that modifications in environmental conditions following the opening of a canal, Cuautlá canal, in 1972 may have initiated the large-scale mortality. Although these areas of impact are still developing, the results from the satellite data indicate that the majority of the more recent changes are occurring elsewhere in the system. Obvious in the 1999 satellite data, but not so in the 1993, are large areas of mangrove degradation in the northern section of the Teacapán region. In the Agua Brava basin, the more recent transformations are appearing on the western side of the basin. Since long-term records of environmental conditions are absent, it is difficult to determine why these latest changes are occurring or even if the earlier losses were the result of the canal. Potential agents of change that have recently been observed include a hurricane, a second canal, and the uncontrolled expansion of the Cuautlá canal since 1994.

Biogeochemistry of vertebrate decomposition in a forest ecosystem

USDA-ARS?s Scientific Manuscript database

Decomposing plants and animals provide critical nutrients for ecosystems, including forests. During vertebrate decay, the rapid release of limiting nutrients, including N, P, C, and S fundamentally transforms the soil environment by stimulating endogenous organisms. The goal of this study was t...

Trends and patterns of anthropogenic evolution of chernozems in lands of agricultural afforestation within the territory of forest-steppe in the center of eastern Europe

USDA-ARS?s Scientific Manuscript database

The anthropogenic evolution of chernozems as a result of plowing and the creation of forest shelterbelts on three meadow-steppe areas of forest-steppe were studied. It was established, that in all areas there are similar patterns, caused by the transformation of virgin soils into arable soils and vi...

Effects of fire at two frequencies on nitrogen transformations and soil chemistry in a nitrogen-enriched forest landscape

Treesearch

R. E. J. Boerner; J. A. Brinkman; E. K. Sutherland

2004-01-01

This study reports results of the application of dormant-season prescribed fire at two frequencies (periodic (two fires in 4 years) and annual) at four southern Ohio mixed-oak (Quercus spp.) forest sites to restore the ecosystem functional properties these sites had before the onset of fire suppression and chronic atmospheric deposition. Each forest...

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

Monitoring Forest Regrowth Using a Multi-Platform Time Series

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Smith, Milton O.; Adams, John B.; Gillespie, Alan R.; Tucker, Compton J.

1996-01-01

Over the past 50 years, the forests of western Washington and Oregon have been extensively harvested for timber. This has resulted in a heterogeneous mosaic of remaining mature forests, clear-cuts, new plantations, and second-growth stands that now occur in areas that formerly were dominated by extensive old-growth forests and younger forests resulting from fire disturbance. Traditionally, determination of seral stage and stand condition have been made using aerial photography and spot field observations, a methodology that is not only time- and resource-intensive, but falls short of providing current information on a regional scale. These limitations may be solved, in part, through the use of multispectral images which can cover large areas at spatial resolutions in the order of tens of meters. The use of multiple images comprising a time series potentially can be used to monitor land use (e.g. cutting and replanting), and to observe natural processes such as regeneration, maturation and phenologic change. These processes are more likely to be spectrally observed in a time series composed of images taken during different seasons over a long period of time. Therefore, for many areas, it may be necessary to use a variety of images taken with different imaging systems. A common framework for interpretation is needed that reduces topographic, atmospheric, instrumental, effects as well as differences in lighting geometry between images. The present state of remote-sensing technology in general use does not realize the full potential of the multispectral data in areas of high topographic relief. For example, the primary method for analyzing images of forested landscapes in the Northwest has been with statistical classifiers (e.g. parallelepiped, nearest-neighbor, maximum likelihood, etc.), often applied to uncalibrated multispectral data. Although this approach has produced useful information from individual images in some areas, landcover classes defined by these techniques typically are not consistent for the same scene imaged under different illumination conditions, especially in the mountainous regions. In addition, it is difficult to correct for atmospheric and instrumental differences between multiple scenes in a time series. In this paper, we present an approach for monitoring forest cutting/regrowth in a semi-mountainous portion of the southern Gifford Pinchot National Forest using a multisensor-time series composed of MSS, TM, and AVIRIS images.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

Object-based class modelling for multi-scale riparian forest habitat mapping

NASA Astrophysics Data System (ADS)

Strasser, Thomas; Lang, Stefan

2015-05-01

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

Microclimatic conditions in different land-use systems in Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Meijide, Ana; Tiralla, Nina; Sabajo, Clifton; Panferov, Oleg; Gunawan, Dodo; Knohl, Alexander

2015-04-01

Over the last decades, Indonesia has experienced an unprecedented transformation of the land surface through deforestation and conversion from forest to other land-uses such as oil palm and rubber plantations. These transformations are expected to affect not only biodiversity and carbon storage, but also the biophysical conditions of the land surface, i.e. air and surface temperature, surface albedo, air humidity, and soil moisture. There is, however, a lack of quantitative information characterizing these differences with a systematic experimental design. We report results from micrometeorological measurements in four different land-use types (forest, rubber plantation, jungle rubber, and oil palm plantation, n=4) in two different landscapes in Jambi Province in Sumatra/Indonesia as well as remote sensing data from Landsat. Preliminary results show differences on the average within-canopy air temperature, with lowest values in the forest (24.70°C ± 0.01°C) and highest in oil palm and rubber plantations (25.45°C ± 0.02°C and 25.55°C ± 0.01°C respectively). The temperature ranges also varied between different land uses, from 6.27°C in the forest and up to 9.40 °C in oil palm between the 5 and 95% percentile. Relative air humidity followed an inverse trend to air temperature, with rubber and oil palm plantations being on average 6.29 and 5.37 % drier than the forest. Soil temperature was up to 1°C warmer in oil palm than in forest plots, while soil moisture was more influenced by the soil type in the different landscapes than by the land uses. In conclusion, our data demonstrate that land transformation in Indonesia results in distinctly different microclimatic conditions across land-use types.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

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.

Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy

PubMed Central

Asner, Gregory P.; Nepstad, Daniel; Cardinot, Gina; Ray, David

2004-01-01

Amazônia contains vast stores of carbon in high-diversity ecosystems, yet this region undergoes major changes in precipitation affecting land use, carbon dynamics, and climate. The extent and structural complexity of Amazon forests impedes ground studies of ecosystem functions such as net primary production (NPP), water cycling, and carbon sequestration. Traditional modeling and remote-sensing approaches are not well suited to tropical forest studies, because (i) biophysical mechanisms determining drought effects on canopy water and carbon dynamics are poorly known, and (ii) remote-sensing metrics of canopy greenness may be insensitive to small changes in leaf area accompanying drought. New spaceborne imaging spectroscopy may detect drought stress in tropical forests, helping to monitor forest physiology and constrain carbon models. We combined a forest drought experiment in Amazônia with spaceborne imaging spectrometer measurements of this area. With field data on rainfall, soil water, and leaf and canopy responses, we tested whether spaceborne hyperspectral observations quantify differences in canopy water and NPP resulting from drought stress. We found that hyperspectral metrics of canopy water content and light-use efficiency are highly sensitive to drought. Using these observations, forest NPP was estimated with greater sensitivity to drought conditions than with traditional combinations of modeling, remote-sensing, and field measurements. Spaceborne imaging spectroscopy will increase the accuracy of ecological studies in humid tropical forests. PMID:15071182

Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM) data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/ forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest Inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM} data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

NASA Technical Reports Server (NTRS)

Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

2010-01-01

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

Pan-Tropical Forest Mapping by Exploiting Textures of Multi-Temporal High Resolution SAR Data

NASA Astrophysics Data System (ADS)

Knuth, R.; Eckardt, R.; Richter, N.; Schmullius, C.

2012-12-01

Even though the first commitment period of the Kyoto Protocol is in the offing, there is still a strong demand for profound, reliable, and up to date information in order to bridge the gap of knowledge of the land cover conversion. Despite the fact that land use change is one of the largest carbon contribution factors, it is still poorly quantified. This is particularly true for many tropical forest areas worldwide. Here, preservation of such pristine forest areas is critically endangered. Enormous population growth, the increasing global demand for various resources, and the ongoing unsustainable management practices put the remaining tropical forests under a huge pressure. Yet, only the United Nations Food and Agriculture Organization's (FAO) global Forest Resources Assessment (FRA) report provides the crucial quantitative information every 5 years on a regional scale. Nonetheless, the assembled information of the FRA reports bear the burden of ambiguity and vagueness, because they were compiled based on autonomously gathered statistics, which are usually driven by the individual country needs. There is a broad consensus among the different scientific disciplines, that only the remote sensing technology allows for a large scale robust monitoring of these widespread, and remote forest areas. Consequently, the FAO decided to supplementary analyze remote sensing data for the present (2010) and upcoming FRAs. However, it is also widely accepted that currently only microwave remote sensing techniques allow for an all-day, weather independent monitoring of the frequently cloud-covered tropics. In this context, high resolution Synthetic Aperture Radar (SAR) images of the German satellites TerraSAR-X and TanDEM-X have been investigated within the pan-tropics to support the latest FRA 2010 report. Data of more than 304 predominantly cloud-covered sites in Latin America (188), Central Africa (45) and Southeast Asia (71) have been acquired. Upon delivery, the corresponding radar images were processed using an operational processing chain that includes radiometric transformation, noise reduction, and georeferencing of the SAR data. In places with pronounced topography both satellites were used as single pass interferometer to derive a digital surface model in order to perform an orthorectification followed by a topographic normalization of the SAR backscatter values. As prescribed by the FAO, the final segment-based classification algorithm was fed by multi-temporal backscatter information, a set of textural features, and information on the degree of coherence between the multi-temporal acquisitions. Validation with available high resolution optical imagery suggests that the produced forest maps possess an overall accuracy of 75 percent or higher.

ORGANIC MATTER MANIPULATIONS HAVE LITTLE EFFECT ON GROSS AND NET NITROGEN TRANSFORMATIONS IN TWO TEMPERATE FOREST MINERAL SOILS IN THE USA AND CENTRAL EUROPE

EPA Science Inventory

Soil nitrogen transformations are intricately linked to carbon transformations. We utilized two existing organic matter manipulation sites in western Oregon, USA and Hungary to investigate these linkages. Our questions were: 1) Does the quantity and quality of organic matter af...

Subband/Transform MATLAB Functions For Processing Images

NASA Technical Reports Server (NTRS)

Glover, D.

1995-01-01

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010

PubMed Central

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Roy, Partha Sarathi; Joshi, Pawan Kumar; Gilani, Hammad; Murthy, Manchiraju Sri Ramachandra; Jin, Cui; Wang, Jie; Zhang, Yao; Chen, Bangqian; Menarguez, Michael Angelo; Biradar, Chandrashekhar M.; Bajgain, Rajen; Li, Xiangping; Dai, Shengqi; Hou, Ying; Xin, Fengfei; Moore III, Berrien

2016-01-01

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 106 km2. The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests. PMID:26864143

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Roy, Partha Sarathi; Joshi, Pawan Kumar; Gilani, Hammad; Murthy, Manchiraju Sri Ramachandra; Jin, Cui; Wang, Jie; Zhang, Yao; Chen, Bangqian; Menarguez, Michael Angelo; Biradar, Chandrashekhar M; Bajgain, Rajen; Li, Xiangping; Dai, Shengqi; Hou, Ying; Xin, Fengfei; Moore, Berrien

2016-02-11

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 10(6 )km(2). The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests.

FFT-enhanced IHS transform method for fusing high-resolution satellite images

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2007-01-01

Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

NASA Astrophysics Data System (ADS)

Matsuoka, M.

2012-07-01

A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

Use of Semivariances for Studies of Landsat TM Image Textural Properties of Loblolly Pine Forests

Treesearch

Jarek Zawadzki; Chris J. Cieszewski; Roger C. Lowe; Michael Zasada

2005-01-01

We evaluate the applicability of Landsat TM imagery for analyzing textural information of pine forest images by exploring the spatial correlation between pixels measured by semivariances and cross-semivariances calculated from transects of the Landsat TM images. Then, we explore differences in semivariances associated with images of young, middle-aged, and old, and...

Radar Mosaic of Africa

NASA Technical Reports Server (NTRS)

1999-01-01

This is an image of equatorial Africa, centered on the equator at longitude 15degrees east. This image is a mosaic of almost 4,000 separate images obtained in 1996 by the L-band imaging radar onboard the Japanese Earth Resources Satellite. Using radar to penetrate the persistent clouds prevalent in tropical forests, the Japanese Earth Resources Satellite was able for the first time to image at high resolution this continental scale region during single flooding seasons. The area shown covers about 7.4 million square kilometers (2.8 million square miles) of land surface, spans more than 5,000 kilometers(3,100 miles) east and west and some 2,000 kilometers (1,240 miles) north and south. North is up in this image. At the full resolution of the mosaic (100 meters or 330 feet), this image is more than 500 megabytes in size, and was processed from imagery totaling more than 60 gigabytes.

Central Africa was imaged twice in 1996, once between January and March, which is the major low-flood season in the Congo Basin, and once between October and November, which is the major high-flood season in the Congo Basin. The red color corresponds to the data from the low-flood season, the green to the high-flood season, and the blue to the 'texture' of the low-flood data. The forests appear green as a result, the flooded and palm forests, as well as urban areas, appear yellow, the ocean and lakes appear black, and savanna areas appear blue, black or green, depending on the savanna type, surface topography and other factors. The areas of the image that are black and white were mapped only between January and March 1996. In these areas, the black areas are savanna or open water, the gray are forests, and the white areas are flooded forests or urban areas. The Congo River dominates the middle of the image, where the nearby forests that are periodically flooded by the Congo and its tributaries stand out as yellow. The Nile River flows north from Lake Victoria in the middle right of the color portion of the mosaic.

This image is one of the products resulting from the Global Rain Forest Mapping project, a joint project between the National Space Development Agency of Japan, the Space Applications Institute of the Joint Research Centre of the European Commission, NASA's Jet Propulsion Laboratory and an international team of scientists. The goal of the Global Rain Forest Mapping mission is to map with the Japanese Earth Resources Satellite the world's tropical rain forests. The Japanese satellite was launched in 1992 by the National Space Development Agency of Japan and the Japanese Ministry of International Trade and Industry, with support from the Remote Sensing Technology Center of Japan.

Shuttle radar images for geologic mapping in tropical rainforest

NASA Technical Reports Server (NTRS)

Ford, J. P.; Da Cunha, R.

1986-01-01

Images of forested low-relief terrain in the Amazon basin of Brazil, obtained with airborne imaging radar in the Radambrasil project, are compared with SIR-A and Landsat MSS band-7 images to evaluate their usefulness in constructing geologic maps. Sample images are shown, and it is found that Radam images are more useful in distinguishing drainage patterns and mapping the region distribution of stream channels due to their relatively low depression angles (less than 25 deg as opposed to 43-37 deg for SIR-A), but that SIR-A images give superior discrimination of alluvial forest, where trees stand in water, due to the higher reflectivity of branches and water at the SIR-A wavelength (23.5 cm as opposed to 3 cm for Radam). Alluvial forest is also identified by Landsat band 7.

25m-resolution Global Mosaic and Forest/Non-Forest map using PALSAR-2 data set

NASA Astrophysics Data System (ADS)

Itoh, T.; Shimada, M.; Motooka, T.; Hayashi, M.; Tadono, T.; DAN, R.; Isoguchi, O.; Yamanokuchi, T.

2017-12-01

A continuous observation of forests is important as information necessary for monitoring deforestation, climate change and environmental changes i.e. Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD+). Japan Aerospace Exploration Agency (JAXA) is conducting research on forest monitoring using satellite-based L-Band Synthetic Aperture Radars (SARs) continuously. Using the FBD (Fine Beam Dual polarizations) data of the Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS), JAXA created the global 25 m-resolution mosaic images and the Forest/Non-Forest (FNF) maps dataset for forest monitoring. SAR can monitor forest areas under all weather conditions, and L-band is highly sensitive to forests and their changes, therefore it is suitable for forest observation. JAXA also created the global 25 m mosaics and FNF maps using ALOS-2/PALSAR-2 launched on 2014 as a successor to ALOS. FNF dataset by PALSAR and PALSAR-2 covers from 2007 to 2010, and from 2015 to 2016, respectively. Therefore, it is possible to monitor forest changes during approx. 10 years. The classification method is combination of the object-based classification and the thresholding of HH and HV polarized images, and the result of FNF was compared with Forest Resource Assessment (FRA, developed by FAO) and their inconsistency is less than 10 %. Also, by comparing with the optical image of Google Earth, rate of coincidence was 80 % or more. We will create PALSAR-2 global mosaics and FNF dataset continuously to contribute global forest monitoring.

Global Boreal Forest Mapping with JERS-1: North America

NASA Technical Reports Server (NTRS)

Williams, Cynthia L.; McDonald, Kyle; Chapman, Bruce

2000-01-01

Collaborative effort is underway to map boreal forests worldwide using L-band, single polarization Synthetic Aperture Radar (SAR) imagery from the Japanese Earth Resources (JERS-1) satellite. Final products of the North American Boreal Forest Mapping Project will include two continental scale radar mosaics and supplementary multitemporal mosaics for Alaska, central Canada, and eastern Canada. For selected sites, we are also producing local scale (100 km x 100 km) and regional scale maps (1000 km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web. Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR Facility.

Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification

Treesearch

Michael Hoppus; Stan Arner; Andrew Lister

2001-01-01

A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...

Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

NASA Astrophysics Data System (ADS)

Jude Hemanth, Duraisamy; Umamaheswari, Subramaniyan; Popescu, Daniela Elena; Naaji, Antoanela

2016-01-01

Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT) and Finite Ridgelet Transform (FRIT) are used in combination with GA and PSO to improve the efficiency of the image steganography system.

Determining subcanopy Psidium cattleianum invasion in Hawaiian forests using imaging spectroscopy

Treesearch

Jomar Barbosa; Gregory Asner; Roberta Martin; Claire Baldeck; Flint Hughes; Tracy Johnson

2016-01-01

High-resolution airborne imaging spectroscopy represents a promising avenue for mapping the spread of invasive tree species through native forests, but for this technology to be useful to forest managers there are two main technical challenges that must be addressed: (1) mapping a single focal species amongst a diverse array of other tree species; and (2) detecting...

A comparison of FIA plot data derived from image pixels and image objects

Treesearch

Charles E. Werstak

2012-01-01

The use of Forest Inventory and Analysis (FIA) plot data for producing continuous and thematic maps of forest attributes (e.g., forest type, canopy cover, volume, and biomass) at the regional level from satellite imagery can be challenging due to differences in scale. Specifically, classification errors that may result from assumptions made between what the field data...

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...

Detecting leaf phenology of seasonally moist tropical forests in South America with multi-temporal MODIS images.

Treesearch

Xiangming Xiao; Stephen Hagen; Qingyuan Zhang; Michael Keller; Berrien Moore III

2006-01-01

Leaf phenology of tropical evergreen forests affects carbon and water fluxes. In an earlier study of a seasonally moist evergreen tropical forest site in the Amazon basin, time series data of Enhanced Vegetation Index (EVI) from the VEGETATION and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors showed an unexpected seasonal pattern, with higher EVI in the...

A GIS-based protocol for the simulation and evaluation of realistic 3-D thinning scenarios in recreational forest management.

PubMed

Lin, Chinsu; Thomson, Gavin; Hung, Shih-Hsiang; Lin, Yu-Dung

2012-12-30

This study introduces a GIS-based protocol for the simulation and evaluation of thinning treatments in recreational forest management. The protocol was implemented in a research study based on an area of recreational forest in Alishan National Scenic Area, Taiwan. Ground survey data were mapped to a GIS database, to create a precise, yet flexible, GIS-based digital forest. The digital forest model was used to generate 18 different thinning scenario images and one image of the existing unthinned forest. A questionnaire was completed by 456 participants while simultaneously viewing the scenario images. The questionnaire was used to determine the scenic beauty preferences of the respondents. Statistical analysis of the data revealed that the respondents preferred low density, upper-storey thinning treatments and a dispersed retention pattern of the remaining trees. High density upper-storey treatments evoked a strongly negative reaction in the observers. The experiment demonstrated that the proposed protocol is suitable for selecting an appropriate thinning strategy for recreational forest and that the protocol has practical value in recreational forest management. Copyright © 2012 Elsevier Ltd. All rights reserved.

Joint graph cut and relative fuzzy connectedness image segmentation algorithm.

PubMed

Ciesielski, Krzysztof Chris; Miranda, Paulo A V; Falcão, Alexandre X; Udupa, Jayaram K

2013-12-01

We introduce an image segmentation algorithm, called GC(sum)(max), which combines, in novel manner, the strengths of two popular algorithms: Relative Fuzzy Connectedness (RFC) and (standard) Graph Cut (GC). We show, both theoretically and experimentally, that GC(sum)(max) preserves robustness of RFC with respect to the seed choice (thus, avoiding "shrinking problem" of GC), while keeping GC's stronger control over the problem of "leaking though poorly defined boundary segments." The analysis of GC(sum)(max) is greatly facilitated by our recent theoretical results that RFC can be described within the framework of Generalized GC (GGC) segmentation algorithms. In our implementation of GC(sum)(max) we use, as a subroutine, a version of RFC algorithm (based on Image Forest Transform) that runs (provably) in linear time with respect to the image size. This results in GC(sum)(max) running in a time close to linear. Experimental comparison of GC(sum)(max) to GC, an iterative version of RFC (IRFC), and power watershed (PW), based on a variety medical and non-medical images, indicates superior accuracy performance of GC(sum)(max) over these other methods, resulting in a rank ordering of GC(sum)(max)>PW∼IRFC>GC. Copyright © 2013 Elsevier B.V. All rights reserved.

High definition infrared spectroscopic imaging for lymph node histopathology.

PubMed

Leslie, L Suzanne; Wrobel, Tomasz P; Mayerich, David; Bindra, Snehal; Emmadi, Rajyasree; Bhargava, Rohit

2015-01-01

Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Cruise, James F.; Rickman, Douglas L.; Quattrochi, Dale A.

2007-01-01

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Transformations of snow chemistry in the boreal forest: Accumulation and volatilization

USGS Publications Warehouse

Pomeroy, J.W.; Davies, T.D.; Jones, H.G.; Marsh, P.; Peters, N.E.; Tranter, M.

1999-01-01

This paper examines the processes and dynamics of ecologically-important inorganic chemical (primarily NO3-N) accumulation and loss in boreal forest snow during the cold winter period at a northern and southern location in the boreal forest of western Canada. Field observations from Inuvik, Northwest Territories and Waskesiu, Saskatchewan, Canada were used to link chemical transformations and physical processes in boreal forest snow. Data on the disposition and overwinter transformation of snow water equivalent, NO3-, SO42- and other major ions were examined. No evidence of enhanced dry deposition of chemical species to intercepted snow was found at either site except where high atmospheric aerosol concentrations prevailed. At Inuvik, concentrations of SO42- and Cl- were five to six times higher in intercepted snow than in surface snow away from the trees. SO4-S and Cl loads at Inuvik were correspondingly enhanced three-fold within the nearest 0.5 m to individual tree stems. Measurements of snow affected by canopy interception without rapid sublimation provided no evidence of ion volatilization from intercepted snow. Where intercepted snow sublimation rates were significant, ion loads in sub-canopy snow suggested that NO3- volatized with an efficiency of about 62% per snow mass sublimated. Extrapolating this measurement from Waskesiu to sublimation losses observed in other southern boreal environments suggests that 19-25% of snow inputs of NO3- can be lost during intercepted snow sublimation. The amount of N lost during sublimation may be large in high-snowfall, high N load southern boreal forests (Quebec) where 0.42 kg NO3-N ha-1 is estimated as a possible seasonal NO3- volatilization. The sensitivity of the N fluxes to climate and forest canopy variation and implications of the winter N losses for N budgets in the boreal forest are discussed.This paper examines the processes and dynamics of ecologically-important inorganic chemical (primarily NO3-N) accumulation and loss in boreal forest snow during the cold winter period at a northern and southern location in the boreal forest of western Canada. Field observations from Inuvik. Northwest Territories and Waskesiu, Saskatchewan, Canada were used to link chemical transformations and physical processes in boreal forest snow. Data on the disposition and overwinter transformation of snow water equivalent, NO3-, SO42- and other major ions were examined. No evidence of enhanced dry deposition of chemical species to intercepted snow was found at either site except where high atmospheric aerosol concentrations prevailed. At Inuvik, concentrations of SO42- and Cl- were five to six times higher in intercepted snow than in surface snow away from the trees. SO4-S and Cl loads at Inuvik were correspondingly enhanced three-fold within the nearest 0.5 m to individual tree stems. Measurements of snow affected by canopy interception without rapid sublimation provided no evidence of ion volatilization from intercepted snow. Where intercepted snow sublimation rates were significant, ion loads in sub-canopy snow suggested that NO3- volatized with an efficiency of about 62% per snow mass sublimated. Extrapolating this measurement from Waskesiu to sublimation losses observed in other southern boreal environments suggests that 19-25% of snow inputs of NO3- can be lost during intercepted snow sublimation. The amount of N lost during sublimation may be large in high-snowfall, high N load southern boreal forests (Quebec) where 0.42 kg NO3-N ha-1 is estimated as a possible seasonal NO3- volatilization. The sensitivity of the N fluxes to climate and forest canopy variation and implications of the winter N losses for N budgets in the boreal forest are discussed.

Cross-system comparisons of soil nitrogen transformations and nitrous oxide flux in tropical forest ecosystems

NASA Technical Reports Server (NTRS)

Matson, Pamela A.; Vitousek, Peter M.

1987-01-01

Soil nitrogen transformations and nitrous oxide flux across the soil-air interface have been measured in a variety of tropical forest sites and correlated with patterns of nitrogen circulation. Nitrogen mineralizaton and nitrification potentials were found to be high in the relatively fertile Costa Rica sites and the Amazonian oxisol/ultisols, intermediate in Amazonian white sand soils, and low in the Hawaiian montane sites. Nitrous oxide fluxes ranged from 0 to 6.2 ng/sq cm per h, and the mean flux per site was shown to be highly correlated with mean nitrogen mineralization.

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.

Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions

PubMed Central

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-01-01

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. PMID:24811079

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

PubMed

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

USGS Publications Warehouse

Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.

2016-01-01

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

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.

Analysis of Radarsat-2 Full Polarimetric Data for Forest Mapping

NASA Astrophysics Data System (ADS)

Maghsoudi, Yasser

Forests are a major natural resource of the Earth and control a wide range of environmental processes. Forests comprise a major part of the planet's plant biodiversity and have an important role in the global hydrological and biochemical cycles. Among the numerous potential applications of remote sensing in forestry, forest mapping plays a vital role for characterization of the forest in terms of species. Particularly, in Canada where forests occupy 45% of the territory, representing more than 400 million hectares of the total Canadian continental area. In this thesis, the potential of polarimetric SAR (PolSAR) Radarsat-2 data for forest mapping is investigated. This thesis has two principle objectives. First is to propose algorithms for analyzing the PolSAR image data for forest mapping. There are a wide range of SAR parameters that can be derived from PolSAR data. In order to make full use of the discriminative power offered by all these parameters, two categories of methods are proposed. The methods are based on the concept of feature selection and classifier ensemble. First, a nonparametric definition of the evaluation function is proposed and hence the methods NFS and CBFS. Second, a fast wrapper algorithm is proposed for the evaluation function in feature selection and hence the methods FWFS and FWCBFS. Finally, to incorporate the neighboring pixels information in classification an extension of the FWCBFS method i.e. CCBFS is proposed. The second objective of this thesis is to provide a comparison between leaf-on (summer) and leaf-off (fall) season images for forest mapping. Two Radarsat-2 images acquired in fine quad-polarized mode were chosen for this study. The images were collected in leaf-on and leaf-off seasons. We also test the hypothesis whether combining the SAR parameters obtained from both images can provide better results than either individual datasets. The rationale for this combination is that every dataset has some parameters which may be useful for forest mapping. To assess the potential of the proposed methods their performance have been compared with each other and with the baseline classifiers. The baseline methods include the Wishart classifier, which is a commonly used classification method in PolSAR community, as well as an SVM classifier with the full set of parameters. Experimental results showed a better performance of the leaf-off image compared to that of leaf-on image for forest mapping. It is also shown that combining leaf-off parameters with leaf-on parameters can significantly improve the classification accuracy. Also, the classification results (in terms of the overall accuracy) compared to the baseline classifiers demonstrate the effectiveness of the proposed nonparametric scheme for forest mapping.

Vegetation survey in Amazonia using LANDSAT data. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Shimabukuro, Y. E.; Dossantos, J. R.; Deaquino, L. C. S.

1982-01-01

Automatic Image-100 analysis of LANDSAT data was performed using the MAXVER classification algorithm. In the pilot area, four vegetation units were mapped automatically in addition to the areas occupied for agricultural activities. The Image-100 classified results together with a soil map and information from RADAR images, permitted the establishment of the final legend with six classes: semi-deciduous tropical forest; low land evergreen tropical forest; secondary vegetation; tropical forest of humid areas, predominant pastureland and flood plains. Two water types were identified based on their sediments indicating different geological and geomorphological aspects.

Deforestation in Sumatra

NASA Technical Reports Server (NTRS)

2002-01-01

Indonesia is rapidly losing its lowland forests to logging, much of it illegal. At present, logging is claiming the forests at a rate of nearly two million hectares (slightly less than 5 million acres: roughly the same area as the state of Massachusetts) each year. At this rate, the island of Sumatra will have no more lowland forests by 2005, a fate already befallen the island of Sulawesi. Indonesia's lowland forests are home to a wide variety of wildlife and are considered among the richest ecosystems in the world. Among the unique life forms in these forests are the Orangutan and the Sumatra Tiger. Sixteen percent of the entire world's bird species, eleven percent of its plants, and ten percent of all mammals on Earth call these forests home. Many are found nowhere else. In the two Landsat scenes shown above, the pattern of deforestation can be clearly discerned. Deep green in these images shows lush vegetation in the forest cover. In both scenes, deep and pale red shows areas where there is little or no vegetation, often bare ground from where forest has been completely stripped. The latter Landsat scene from 2001 not only shows extensive clear cut areas, but also new logging roads built into the remaining forest to facilitate future cutting. This lowland forest region is located on Indonesia's largest island, Sumatra, roughly 100 km southwest of the provincial capital of Jambi. The first image was acquired by Landsat 5's Thematic Mapper (TM) sensor on June 22, 1992, the second by Landsat 7's Enhanced Thematic Mapper plus (ETM+) sensor on January 14, 2001. Both are false-color composite images made using shortwave infrared, infrared, and green wavelengths. The area shown above is roughly 30 km x 22 km (19 miles x 14 miles). The large versions of these images show the same general area covering 60 km x 60 km. Images provided by the Tropical Rain Forest Information Center (TRFIC) through the Basic Science and Remote Sensing Initiative (BSRSI) based at Michigan State University, and the Landsat 7 Project Science Office at NASA Goddard Space Flight Center

Frontal sinus recognition for human identification

NASA Astrophysics Data System (ADS)

Falguera, Juan Rogelio; Falguera, Fernanda Pereira Sartori; Marana, Aparecido Nilceu

2008-03-01

Many methods based on biometrics such as fingerprint, face, iris, and retina have been proposed for person identification. However, for deceased individuals, such biometric measurements are not available. In such cases, parts of the human skeleton can be used for identification, such as dental records, thorax, vertebrae, shoulder, and frontal sinus. It has been established in prior investigations that the radiographic pattern of frontal sinus is highly variable and unique for every individual. This has stimulated the proposition of measurements of the frontal sinus pattern, obtained from x-ray films, for skeletal identification. This paper presents a frontal sinus recognition method for human identification based on Image Foresting Transform and shape context. Experimental results (ERR = 5,82%) have shown the effectiveness of the proposed method.

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Dem Generation with WORLDVIEW-2 Images

NASA Astrophysics Data System (ADS)

Büyüksalih, G.; Baz, I.; Alkan, M.; Jacobsen, K.

2012-07-01

For planning purposes 42 km coast line of the Black Sea, starting at the Bosporus going in West direction, with a width of approximately 5 km, was imaged by WorldView-2. Three stereo scenes have been oriented at first by 3D-affine transformation and later by bias corrected RPC solution. The result is nearly the same, but it is limited by identification of the control points in the images. Nevertheless after blunder elimination by data snooping root mean square discrepancies below 1 pixel have been reached. The root mean square discrepancy at control point height reached 0.5 m up to 1.3 m with a base to height relation between 1:1.26 and 1:1.80. Digital Surface models (DSM) with 4 m spacing have been generated by least squares matching with region growing, supported by image pyramids. A higher percentage of the mountainous area is covered by forest, requiring the approximation based on image pyramids. In the forest area the approximation just by region growing leads to larger gaps in the DSM. Caused by the good image quality of WorldView-2 the correlation coefficients reached by least squares matching are high and even in most forest areas a satisfying density of accepted points was reached. Two stereo models have an overlapping area of 1.6 km times 6.7 km allowing an accuracy evaluation. Small, but nevertheless significant differences in scene orientation have been eliminated by least squares shift of both overlapping height models to each other. The root mean square differences of both independent DSM are 1.06m or as a function of terrain inclination 0.74 m + 0.55 m  tangent (slope). The terrain inclination in the average is 7° with 12% exceeding 17°. The frequency distribution of height discrepancies is not far away from normal distribution, but as usual, larger discrepancies are more often available as corresponding to normal distribution. This also can be seen by the normalized medium absolute deviation (NMAS) related to 68% probability level of 0.83m being significant smaller as the root mean square differences. Nevertheless the results indicate a standard deviation of the single height models of 0.75 m or 0.52 m + 0.39* tangent (slope), corresponding to approximately 0.6 pixels for the x-parallax in flat terrain, being very satisfying for the available land cover. An interpolation over 10 m enlarged the root mean square differences of both height models nearly by 50%.

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Ryan, Robert E.; McKellip, Rodney

2008-01-01

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

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.

Harvest Influences on Floodwater Properties in a Forested Floodplain

Treesearch

R.G. Clawson; B.G Lockaby; R.B. Rummer

1999-01-01

Abstract: Floodplain forests directly influence water quality by serving as sinks, sources, or transformers of nutrients. Increases in the demand for timber raise the question of how silvicultural disturbance may affect this function. The objective of this research was to compare biogeochemical relationships between undisturbed vs. disturbed...

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests. Ph.D. Thesis, 10 Sep. 1991 Abstract Only

NASA Technical Reports Server (NTRS)

Bradshaw, G. A.

1995-01-01

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Development of a Unique Web2.0 Interface for Global Collaboration in Land Cover Change Research

NASA Astrophysics Data System (ADS)

Dunham, M.; Boriah, S.; Mithal, V.; Garg, A.; Steinbach, M.; Kumar, V.; Potter, C. S.; Klooster, S.; Castilla-Rubio, J.

2010-12-01

The ability to detect changes in forest cover is of critical importance for both economic and scientific reasons, e.g. using forests for economic carbon sink management and studying natural and anthropogenic impacts on ecosystems. The contribution of greenhouse gases from deforestation is one of the most uncertain elements of the global carbon cycle. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, a key ingredient for effective forest management, whether for carbon trading or other purposes, is quantifiable knowledge about changes in forest cover. Rich amounts of data from remotely-sensed images are now becoming available for detecting changes in forests or more generally, land cover. However, in spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data acquisition, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. We have developed innovations in a number of technical areas with the goal of providing actionable knowledge to end users: (i) identification of changes in global forest cover, (ii) characterization of those changes, (iii) discovery of relationships between the number, magnitude, and type of these changes with natural and anthropogenic variables, and (iv) a web-based platform that supports interactive visualization of disturbances and relationships. The focus of this abstract is on the interactive web-based platform. This key component of the project is a graphical user interface built on the Flash framework. The viewer is a groundbreaking, multi-purpose application used for everything from algorithm refinement and data analysis for the team to a demonstration platform for research partners. The team continues to develop the utility to allow for worldwide researcher and community contributions with the hopes of enhancing global understanding of environmental change.

Programmable remapper for image processing

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor); Sampsell, Jeffrey B. (Inventor)

1991-01-01

A video-rate coordinate remapper includes a memory for storing a plurality of transformations on look-up tables for remapping input images from one coordinate system to another. Such transformations are operator selectable. The remapper includes a collective processor by which certain input pixels of an input image are transformed to a portion of the output image in a many-to-one relationship. The remapper includes an interpolative processor by which the remaining input pixels of the input image are transformed to another portion of the output image in a one-to-many relationship. The invention includes certain specific transforms for creating output images useful for certain defects of visually impaired people. The invention also includes means for shifting input pixels and means for scrolling the output matrix.

Geometric registration of images by similarity transformation using two reference points

NASA Technical Reports Server (NTRS)

Kang, Yong Q. (Inventor); Jo, Young-Heon (Inventor); Yan, Xiao-Hai (Inventor)

2011-01-01

A method for registering a first image to a second image using a similarity transformation. The each image includes a plurality of pixels. The first image pixels are mapped to a set of first image coordinates and the second image pixels are mapped to a set of second image coordinates. The first image coordinates of two reference points in the first image are determined. The second image coordinates of these reference points in the second image are determined. A Cartesian translation of the set of second image coordinates is performed such that the second image coordinates of the first reference point match its first image coordinates. A similarity transformation of the translated set of second image coordinates is performed. This transformation scales and rotates the second image coordinates about the first reference point such that the second image coordinates of the second reference point match its first image coordinates.

Displaying radiologic images on personal computers: image storage and compression--Part 2.

PubMed

Gillespy, T; Rowberg, A H

1994-02-01

This is part 2 of our article on image storage and compression, the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Image compression is classified as lossless (nondestructive) or lossy (destructive). Common lossless compression algorithms include variable-length bit codes (Huffman codes and variants), dictionary-based compression (Lempel-Ziv variants), and arithmetic coding. Huffman codes and the Lempel-Ziv-Welch (LZW) algorithm are commonly used for image compression. All of these compression methods are enhanced if the image has been transformed into a differential image based on a differential pulse-code modulation (DPCM) algorithm. The LZW compression after the DPCM image transformation performed the best on our example images, and performed almost as well as the best of the three commercial compression programs tested. Lossy compression techniques are capable of much higher data compression, but reduced image quality and compression artifacts may be noticeable. Lossy compression is comprised of three steps: transformation, quantization, and coding. Two commonly used transformation methods are the discrete cosine transformation and discrete wavelet transformation. In both methods, most of the image information is contained in a relatively few of the transformation coefficients. The quantization step reduces many of the lower order coefficients to 0, which greatly improves the efficiency of the coding (compression) step. In fractal-based image compression, image patterns are stored as equations that can be reconstructed at different levels of resolution.

Optical Logarithmic Transformation of Speckle Images with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

The application of logarithmic transformations to speckle images is sometimes desirable in converting the speckle noise distribution into an additive, constant-variance noise distribution. The optical transmission properties of some bacteriorhodopsin films are well suited to implement such a transformation optically in a parallel fashion. I present experimental results of the optical conversion of a speckle image into a transformed image with signal-independent noise statistics, using the real-time photochromic properties of bacteriorhodopsin. The original and transformed noise statistics are confirmed by histogram analysis.

Temperate forest health in an era of emerging megadisturbance

USGS Publications Warehouse

Millar, Constance I.; Stephenson, Nathan L.

2015-01-01

Although disturbances such as fire and native insects can contribute to natural dynamics of forest health, exceptional droughts, directly and in combination with other disturbance factors, are pushing some temperate forests beyond thresholds of sustainability. Interactions from increasing temperatures, drought, native insects and pathogens, and uncharacteristically severe wildfire are resulting in forest mortality beyond the levels of 20th-century experience. Additional anthropogenic stressors, such as atmospheric pollution and invasive species, further weaken trees in some regions. Although continuing climate change will likely drive many areas of temperate forest toward large-scale transformations, management actions can help ease transitions and minimize losses of socially valued ecosystem services.

Using Landsat and a Bayesian hard classifier to study forest change in the Salmon Creek Watershed area from 1972-2013

NASA Astrophysics Data System (ADS)

Mullis, David Stone

The Salmon Creek Watershed in Sonoma County, California, USA, is home to a variety of wildlife, and many of its residents are mindful of their place in its ecology. In the past half century, several of its native and rare species have become threatened, endangered, or extinct, most notably the once common Coho salmon and Chinook salmon. The cause of this decline is believed to be a combination of global climate change, local land use, and land cover change. More specifically, the clearing of forested land to create vineyards, as well as other agricultural and residential uses, has led to a decline in biodiversity and habitat structure. I studied sub-scenes of Landsat data from 1972 to 2013 for the Salmon Creek Watershed area to estimate forest cover over this period. I used a maximum likelihood hard classifier to determine forest area, a Mahalanobis distance soft classifier to show the software's uncertainty in classification, and manually digitized forest cover to test and compare results for the 2013 30 m image. Because the earliest images were lower spatial resolution, I also tested the effects of resolution on these statistics. The images before 1985 are at 60 m spatial resolution while the later images are at 30 m resolution. Each image was processed individually and the training data were based on knowledge of the area and a mosaic of aerial photography. Each sub-scene was classified into five categories: water, forest, pasture, vineyard/orchard, and developed/barren. The research shows a decline in forest area from 1972 to around the mid-1990s, then an increase in forest area from the mid-1990s to present. The forest statistics can be helpful for conservation and restoration purposes, while the study on resolution can be helpful for landscape analysis on many levels.

Single-image super-resolution based on Markov random field and contourlet transform

NASA Astrophysics Data System (ADS)

Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai

2011-04-01

Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Local wavelet transform: a cost-efficient custom processor for space image compression

NASA Astrophysics Data System (ADS)

Masschelein, Bart; Bormans, Jan G.; Lafruit, Gauthier

2002-11-01

Thanks to its intrinsic scalability features, the wavelet transform has become increasingly popular as decorrelator in image compression applications. Throuhgput, memory requirements and complexity are important parameters when developing hardware image compression modules. An implementation of the classical, global wavelet transform requires large memory sizes and implies a large latency between the availability of the input image and the production of minimal data entities for entropy coding. Image tiling methods, as proposed by JPEG2000, reduce the memory sizes and the latency, but inevitably introduce image artefacts. The Local Wavelet Transform (LWT), presented in this paper, is a low-complexity wavelet transform architecture using a block-based processing that results in the same transformed images as those obtained by the global wavelet transform. The architecture minimizes the processing latency with a limited amount of memory. Moreover, as the LWT is an instruction-based custom processor, it can be programmed for specific tasks, such as push-broom processing of infinite-length satelite images. The features of the LWT makes it appropriate for use in space image compression, where high throughput, low memory sizes, low complexity, low power and push-broom processing are important requirements.

Principal components technique analysis for vegetation and land use discrimination. [Brazilian cerrados

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Formaggio, A. R.; Dossantos, J. R.; Dias, L. A. V.

1984-01-01

Automatic pre-processing technique called Principal Components (PRINCO) in analyzing LANDSAT digitized data, for land use and vegetation cover, on the Brazilian cerrados was evaluated. The chosen pilot area, 223/67 of MSS/LANDSAT 3, was classified on a GE Image-100 System, through a maximum-likehood algorithm (MAXVER). The same procedure was applied to the PRINCO treated image. PRINCO consists of a linear transformation performed on the original bands, in order to eliminate the information redundancy of the LANDSAT channels. After PRINCO only two channels were used thus reducing computer effort. The original channels and the PRINCO channels grey levels for the five identified classes (grassland, "cerrado", burned areas, anthropic areas, and gallery forest) were obtained through the MAXVER algorithm. This algorithm also presented the average performance for both cases. In order to evaluate the results, the Jeffreys-Matusita distance (JM-distance) between classes was computed. The classification matrix, obtained through MAXVER, after a PRINCO pre-processing, showed approximately the same average performance in the classes separability.

Relating microbial community structure to functioning in forest soil organic carbon transformation and turnover.

PubMed

You, Yeming; Wang, Juan; Huang, Xueman; Tang, Zuoxin; Liu, Shirong; Sun, Osbert J

2014-03-01

Forest soils store vast amounts of terrestrial carbon, but we are still limited in mechanistic understanding on how soil organic carbon (SOC) stabilization or turnover is controlled by biotic and abiotic factors in forest ecosystems. We used phospholipid fatty acids (PLFAs) as biomarker to study soil microbial community structure and measured activities of five extracellular enzymes involved in the degradation of cellulose (i.e., β-1,4-glucosidase and cellobiohydrolase), chitin (i.e., β-1,4-N-acetylglucosaminidase), and lignin (i.e., phenol oxidase and peroxidase) as indicators of soil microbial functioning in carbon transformation or turnover across varying biotic and abiotic conditions in a typical temperate forest ecosystem in central China. Redundancy analysis (RDA) was performed to determine the interrelationship between individual PFLAs and biotic and abiotic site factors as well as the linkage between soil microbial structure and function. Path analysis was further conducted to examine the controls of site factors on soil microbial community structure and the regulatory pathway of changes in SOC relating to microbial community structure and function. We found that soil microbial community structure is strongly influenced by water, temperature, SOC, fine root mass, clay content, and C/N ratio in soils and that the relative abundance of Gram-negative bacteria, saprophytic fungi, and actinomycetes explained most of the variations in the specific activities of soil enzymes involved in SOC transformation or turnover. The abundance of soil bacterial communities is strongly linked with the extracellular enzymes involved in carbon transformation, whereas the abundance of saprophytic fungi is associated with activities of extracellular enzymes driving carbon oxidation. Findings in this study demonstrate the complex interactions and linkage among plant traits, microenvironment, and soil physiochemical properties in affecting SOC via microbial regulations.

Time Series of Images to Improve Tree Species Classification

NASA Astrophysics Data System (ADS)

Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.

2017-10-01

Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.

Transformational restoration: novel ecosystems in Denmark

Treesearch

John A. Stanturf; Palle Madsen; Khosro Sagheb-Talebi; Ole K. Hansen

2018-01-01

Restoring the estimated 1 billion hectares of degraded forests must consider future climate accompanied by novel ecosystems. Transformational restoration can play a key role in adaptation to climate change but it is conceptually the most divergent from contemporary approaches favoring native species and natural disturbance regimes. Here...

Fourier Transform Infrared (FT-IR) and Laser Ablation Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) Imaging of Cerebral Ischemia: Combined Analysis of Rat Brain Thin Cuts Toward Improved Tissue Classification.

PubMed

Balbekova, Anna; Lohninger, Hans; van Tilborg, Geralda A F; Dijkhuizen, Rick M; Bonta, Maximilian; Limbeck, Andreas; Lendl, Bernhard; Al-Saad, Khalid A; Ali, Mohamed; Celikic, Minja; Ofner, Johannes

2018-02-01

Microspectroscopic techniques are widely used to complement histological studies. Due to recent developments in the field of chemical imaging, combined chemical analysis has become attractive. This technique facilitates a deepened analysis compared to single techniques or side-by-side analysis. In this study, rat brains harvested one week after induction of photothrombotic stroke were investigated. Adjacent thin cuts from rats' brains were imaged using Fourier transform infrared (FT-IR) microspectroscopy and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The LA-ICP-MS data were normalized using an internal standard (a thin gold layer). The acquired hyperspectral data cubes were fused and subjected to multivariate analysis. Brain regions affected by stroke as well as unaffected gray and white matter were identified and classified using a model based on either partial least squares discriminant analysis (PLS-DA) or random decision forest (RDF) algorithms. The RDF algorithm demonstrated the best results for classification. Improved classification was observed in the case of fused data in comparison to individual data sets (either FT-IR or LA-ICP-MS). Variable importance analysis demonstrated that both molecular and elemental content contribute to the improved RDF classification. Univariate spectral analysis identified biochemical properties of the assigned tissue types. Classification of multisensor hyperspectral data sets using an RDF algorithm allows access to a novel and in-depth understanding of biochemical processes and solid chemical allocation of different brain regions.

Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.

PubMed

Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong

2017-11-01

Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.

Design of FPGA ICA for hyperspectral imaging processing

NASA Astrophysics Data System (ADS)

Nordin, Anis; Hsu, Charles C.; Szu, Harold H.

2001-03-01

The remote sensing problem which uses hyperspectral imaging can be transformed into a blind source separation problem. Using this model, hyperspectral imagery can be de-mixed into sub-pixel spectra which indicate the different material present in the pixel. This can be further used to deduce areas which contain forest, water or biomass, without even knowing the sources which constitute the image. This form of remote sensing allows previously blurred images to show the specific terrain involved in that region. The blind source separation problem can be implemented using an Independent Component Analysis algorithm. The ICA Algorithm has previously been successfully implemented using software packages such as MATLAB, which has a downloadable version of FastICA. The challenge now lies in implementing it in a form of hardware, or firmware in order to improve its computational speed. Hardware implementation also solves insufficient memory problem encountered by software packages like MATLAB when employing ICA for high resolution images and a large number of channels. Here, a pipelined solution of the firmware, realized using FPGAs are drawn out and simulated using C. Since C code can be translated into HDLs or be used directly on the FPGAs, it can be used to simulate its actual implementation in hardware. The simulated results of the program is presented here, where seven channels are used to model the 200 different channels involved in hyperspectral imaging.

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

PubMed Central

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-01-01

Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation. PMID:27618903

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images.

PubMed

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-08-27

Characterizations of up to date information of the Earth's surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

Hypercomplex Fourier transforms of color images.

PubMed

Ell, Todd A; Sangwine, Stephen J

2007-01-01

Fourier transforms are a fundamental tool in signal and image processing, yet, until recently, there was no definition of a Fourier transform applicable to color images in a holistic manner. In this paper, hypercomplex numbers, specifically quaternions, are used to define a Fourier transform applicable to color images. The properties of the transform are developed, and it is shown that the transform may be computed using two standard complex fast Fourier transforms. The resulting spectrum is explained in terms of familiar phase and modulus concepts, and a new concept of hypercomplex axis. A method for visualizing the spectrum using color graphics is also presented. Finally, a convolution operational formula in the spectral domain is discussed.

Security Analysis of Image Encryption Based on Gyrator Transform by Searching the Rotation Angle with Improved PSO Algorithm.

PubMed

Sang, Jun; Zhao, Jun; Xiang, Zhili; Cai, Bin; Xiang, Hong

2015-08-05

Gyrator transform has been widely used for image encryption recently. For gyrator transform-based image encryption, the rotation angle used in the gyrator transform is one of the secret keys. In this paper, by analyzing the properties of the gyrator transform, an improved particle swarm optimization (PSO) algorithm was proposed to search the rotation angle in a single gyrator transform. Since the gyrator transform is continuous, it is time-consuming to exhaustedly search the rotation angle, even considering the data precision in a computer. Therefore, a computational intelligence-based search may be an alternative choice. Considering the properties of severe local convergence and obvious global fluctuations of the gyrator transform, an improved PSO algorithm was proposed to be suitable for such situations. The experimental results demonstrated that the proposed improved PSO algorithm can significantly improve the efficiency of searching the rotation angle in a single gyrator transform. Since gyrator transform is the foundation of image encryption in gyrator transform domains, the research on the method of searching the rotation angle in a single gyrator transform is useful for further study on the security of such image encryption algorithms.

An Evaluation of Data Fusion Products for the Analysis of Dryland Forest Phenology

NASA Astrophysics Data System (ADS)

Walker, J. J.; de Beurs, K.; Wynne, R. H.; Gao, F.

2010-12-01

Semi-arid forest areas cover a significant proportion of the world’s land surface; in the interior western U.S. alone, dryland forests extend across more than 56 million hectares. The scarcity of water in these systems makes them acutely sensitive to sustained weather fluctuations, such as the higher temperatures and altered water regimes predicted under most climate change scenarios. To understand, monitor, and predict the anticipated spatial and temporal changes in these areas, it is vital to characterize current phenological patterns. Phenological analysis of western U.S. drylands is complicated by patchy land cover and mosaics of plant phenology states at a variety of spatial scales. Our aim is to use complementary satellite sensors to mitigate these difficulties and gain greater insight into phenological patterns in dryland forests. In this study we applied the spatial and temporal adaptive reflectance model (STARFM; Gao et al. 2006) to fuse Landsat and MODIS imagery to create synthetic images at Landsat spatial resolution and MODIS temporal resolution. To determine which MODIS dataset is most appropriate for the creation of synthetic images intended for the analysis of dryland forest phenology, we examined the effect of temporal compositing and BRDF function adjustment on the accuracy of STARFM imagery. We assembled seven Landsat 5 scenes (path/row 37/36) and temporally-coincident 500m MODIS datasets (seven daily (MOD09GA), seven 8-day composite (MOD09A1), and fourteen 16-day nadir BRDF-adjusted composite (MCD43A4) images) spanning the 2006 April - October growing season in northern Arizona, which is characterized by large tracts of dryland forest. The STARFM algorithm was applied to each MODIS data series to produce four synthetic images (one daily; one 8-day composite; and two 16-day composites) corresponding to each Landsat image. Validation of the accuracy of the synthetic images was achieved by comparing the reflectance values of a random sample of the identified dryland forest pixels in both images. Preliminary data analysis of the effect of the temporal resolution and dataset parameters indicates that the MODIS 8-day composite image may be a suitable and sufficient dataset for phenological analysis in this dryland forest ecosystem. Overall, this work demonstrates the feasibility of using data fusion products to assemble an imagery dataset at sufficiently high temporal and spatial scales to permit a more detailed examination of the underlying phenological processes and trends in dryland forest areas.

Registering coherent change detection products associated with large image sets and long capture intervals

DOEpatents

Perkins, David Nikolaus; Gonzales, Antonio I

2014-04-08

A set of co-registered coherent change detection (CCD) products is produced from a set of temporally separated synthetic aperture radar (SAR) images of a target scene. A plurality of transformations are determined, which transformations are respectively for transforming a plurality of the SAR images to a predetermined image coordinate system. The transformations are used to create, from a set of CCD products produced from the set of SAR images, a corresponding set of co-registered CCD products.

Conversion of tropical lowland forest reduces nutrient return through litterfall, and alters nutrient use efficiency and seasonality of net primary production.

PubMed

Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Hertel, Dietrich

2016-02-01

Tropical landscapes are not only rapidly transformed by ongoing land-use change, but are additionally confronted by increasing seasonal climate variation. There is an increasing demand for studies analyzing the effects and feedbacks on ecosystem functioning of large-scale conversions of tropical natural forest into intensively managed cash crop agriculture. We analyzed the seasonality of aboveground litterfall, fine root litter production, and aboveground woody biomass production (ANPP(woody)) in natural lowland forests, rubber agroforests under natural tree cover ("jungle rubber"), rubber and oil palm monocultures along a forest-to-agriculture transformation gradient in Sumatra. We hypothesized that the temporal fluctuation of litter production increases with increasing land-use intensity, while the associated nutrient fluxes and nutrient use efficiency (NUE) decrease. Indeed, the seasonal variation of aboveground litter production and ANPP(woody) increased from the natural forest to the plantations, while aboveground litterfall generally decreased. Nutrient return through aboveground litter was mostly highest in the natural forest; however, it was significantly lower only in rubber plantations. NUE of N, P and K was lowest in the oil palm plantations, with natural forest and the rubber systems showing comparably high values. Root litter production was generally lower than leaf litter production in all systems, while the root-to-leaf ratio of litter C flux increased along the land-use intensity gradient. Our results suggest that nutrient and C cycles are more directly affected by climate seasonality in species-poor agricultural systems than in species-rich forests, and therefore might be more susceptible to inter-annual climate fluctuation and climate change.

Analysis of two dimensional signals via curvelet transform

NASA Astrophysics Data System (ADS)

Lech, W.; Wójcik, W.; Kotyra, A.; Popiel, P.; Duk, M.

2007-04-01

This paper describes an application of curvelet transform analysis problem of interferometric images. Comparing to two-dimensional wavelet transform, curvelet transform has higher time-frequency resolution. This article includes numerical experiments, which were executed on random interferometric image. In the result of nonlinear approximations, curvelet transform obtains matrix with smaller number of coefficients than is guaranteed by wavelet transform. Additionally, denoising simulations show that curvelet could be a very good tool to remove noise from images.

Gray-scale transform and evaluation for digital x-ray chest images on CRT monitor

NASA Astrophysics Data System (ADS)

Furukawa, Isao; Suzuki, Junji; Ono, Sadayasu; Kitamura, Masayuki; Ando, Yutaka

1997-04-01

In this paper, an experimental evaluation of a super high definition (SHD) imaging system for digital x-ray chest images is presented. The SHD imaging system is proposed as a platform for integrating conventional image media. We are involved in the use of SHD images in the total digitizing of medical records that include chest x-rays and pathological microscopic images, both which demand the highest level of quality among the various types of medical images. SHD images use progressive scanning and have a spatial resolution of 2000 by 2000 pixels or more and a temporal resolution (frame rate) of 60 frames/sec or more. For displaying medical x-ray images on a CRT, we derived gray scale transform characteristics based on radiologists' comments during the experiment, and elucidated the relationship between that gray scale transform and the linearization transform for maintaining the linear relationship with the luminance of film on a light box (luminance linear transform). We then carried out viewing experiments based on a five-stage evaluation. Nine radiologists participated in our experiment, and the ten cases evaluated included pulmonary fibrosis, lung cancer, and pneumonia. The experimental results indicated that conventional film images and those on super high definition CRT monitors have nearly the same quality. They also show that the gray scale transform for CRT images decided according to radiologists' comments agrees with the luminance linear transform in the high luminance region. And in the low luminance region, it was found that the gray scale transform had the characteristics of level expansion to increase the number of levels that can be expressed.

Subband/transform functions for image processing

NASA Technical Reports Server (NTRS)

Glover, Daniel

1993-01-01

Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

NASA Technical Reports Server (NTRS)

Freeman, A.; Kramer, C.; Alves, M.; Chapman, B.

1994-01-01

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

AmeriFlux US-Prr Poker Flat Research Range Black Spruce Forest

DOE Data Explorer

Suzuki, Rikie [Japan Agency for Marine-Earth Science and Technology

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site US-Prr Poker Flat Research Range Black Spruce Forest. Site Description - This site is located in a blackspruce forest within the property of the Poker Flat Research Range, University of Alaska, Fairbanks. Time-lapse image of the canopy is measured at the same time to relate flux data to satellite images.

Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data

Treesearch

Ronald E. McRoberts; Steen Magnussen; Erkki O. Tomppo; Gherardo Chirici

2011-01-01

Nearest neighbors techniques have been shown to be useful for estimating forest attributes, particularly when used with forest inventory and satellite image data. Published reports of positive results have been truly international in scope. However, for these techniques to be more useful, they must be able to contribute to scientific inference which, for sample-based...

Space Radar Image of Harvard Forest

NASA Technical Reports Server (NTRS)

1999-01-01

This is a radar image of the area surrounding the Harvard Forest in north-central Massachusetts that has been operated as a ecological research facility by Harvard University since 1907. At the center of the image is the Quabbin Reservoir, and the Connecticut River is at the lower left of the image. The Harvard Forest itself is just above the reservoir. Researchers are comparing the naturally occurring physical disturbances in the forest and the recent and projected chemical disturbances and their effects on the forest ecosystem. Agricultural land appears dark blue/purple, along with low shrub vegetation and some wetlands. Urban development is bright pink; the yellow to green tints are conifer-dominated vegetation with the pitch pine sand plain at the middle left edge of the image appearing very distinctive. The green tint may indicate pure pine plantation stands, and deciduous broadleaf trees appear gray/pink with perhaps wetter sites being pinker. This image was acquired by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour. SIR-C/X-SAR, a joint mission of the German, Italian and the United States space agencies, is part of NASA's Mission to Planet Earth. The image is centered at 42.50 degrees North latitude and 72.33 degrees West longitude and covers an area of 53 kilometers 63 by kilometers (33 miles by 39 miles). The colors in the image are assigned to different frequencies and polarizations of the radar as follows: red is L-band horizontally transmitted and horizontally received; green is L-band horizontally transmitted and vertically received; and blue is C-band horizontally transmitted and horizontally received.

Space Radar Image of Harvard Forest

NASA Image and Video Library

1999-04-15

This is a radar image of the area surrounding the Harvard Forest in north-central Massachusetts that has been operated as a ecological research facility by Harvard University since 1907. At the center of the image is the Quabbin Reservoir, and the Connecticut River is at the lower left of the image. The Harvard Forest itself is just above the reservoir. Researchers are comparing the naturally occurring physical disturbances in the forest and the recent and projected chemical disturbances and their effects on the forest ecosystem. Agricultural land appears dark blue/purple, along with low shrub vegetation and some wetlands. Urban development is bright pink; the yellow to green tints are conifer-dominated vegetation with the pitch pine sand plain at the middle left edge of the image appearing very distinctive. The green tint may indicate pure pine plantation stands, and deciduous broadleaf trees appear gray/pink with perhaps wetter sites being pinker. This image was acquired by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour. SIR-C/X-SAR, a joint mission of the German, Italian and the United States space agencies, is part of NASA's Mission to Planet Earth. The image is centered at 42.50 degrees North latitude and 72.33 degrees West longitude and covers an area of 53 kilometers 63 by kilometers (33 miles by 39 miles). The colors in the image are assigned to different frequencies and polarizations of the radar as follows: red is L-band horizontally transmitted and horizontally received; green is L-band horizontally transmitted and vertically received; and blue is C-band horizontally transmitted and horizontally received. http://photojournal.jpl.nasa.gov/catalog/PIA01788

Rectification of elemental image set and extraction of lens lattice by projective image transformation in integral imaging.

PubMed

Hong, Keehoon; Hong, Jisoo; Jung, Jae-Hyun; Park, Jae-Hyeung; Lee, Byoungho

2010-05-24

We propose a new method for rectifying a geometrical distortion in the elemental image set and extracting an accurate lens lattice lines by projective image transformation. The information of distortion in the acquired elemental image set is found by Hough transform algorithm. With this initial information of distortions, the acquired elemental image set is rectified automatically without the prior knowledge on the characteristics of pickup system by stratified image transformation procedure. Computer-generated elemental image sets with distortion on purpose are used for verifying the proposed rectification method. Experimentally-captured elemental image sets are optically reconstructed before and after the rectification by the proposed method. The experimental results support the validity of the proposed method with high accuracy of image rectification and lattice extraction.

The effect of input data transformations on object-based image analysis

PubMed Central

LIPPITT, CHRISTOPHER D.; COULTER, LLOYD L.; FREEMAN, MARY; LAMANTIA-BISHOP, JEFFREY; PANG, WYSON; STOW, DOUGLAS A.

2011-01-01

The effect of using spectral transform images as input data on segmentation quality and its potential effect on products generated by object-based image analysis are explored in the context of land cover classification in Accra, Ghana. Five image data transformations are compared to untransformed spectral bands in terms of their effect on segmentation quality and final product accuracy. The relationship between segmentation quality and product accuracy is also briefly explored. Results suggest that input data transformations can aid in the delineation of landscape objects by image segmentation, but the effect is idiosyncratic to the transformation and object of interest. PMID:21673829

Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

PubMed Central

Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

2009-01-01

Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data. PMID:22573971

Landsat 7 - First Cloud-free Image of Yellowstone National Park

NASA Technical Reports Server (NTRS)

2002-01-01

This image of Yellowstone Lake, in the center of Yellowstone National Park, was taken by Landsat 7 on July 13, 1999. Bands 5 (1.65um),4 (.825um), and 2 (.565um) were used for red, green, and blue, respectively. Water appears blue/black, snow light blue, mature forest red/green, young forest pink, and grass and fields appear light green. Southwest of the lake is young forest that is growing in the wake of the widespread fires of 1988. For more information, see: Landsat 7 Fact Sheet Landsat 7 in Mission Control Image by Rich Irish, NASA GSFC

Fast downscaled inverses for images compressed with M-channel lapped transforms.

PubMed

de Queiroz, R L; Eschbach, R

1997-01-01

Compressed images may be decompressed and displayed or printed using different devices at different resolutions. Full decompression and rescaling in space domain is a very expensive method. We studied downscaled inverses where the image is decompressed partially, and a reduced inverse transform is used to recover the image. In this fashion, fewer transform coefficients are used and the synthesis process is simplified. We studied the design of fast inverses, for a given forward transform. General solutions are presented for M-channel finite impulse response (FIR) filterbanks, of which block and lapped transforms are a subset. Designs of faster inverses are presented for popular block and lapped transforms.

Simulate the volcanic radiation features in medium wave infrared channels

NASA Astrophysics Data System (ADS)

Gong, Cailan; Jiang, Shan; Liu, Fengyi; Hu, Yong

2015-10-01

There are different scales and intensities of the volcanic eruption in the world every year. Existing medium wave infrared (MWI) remote sensing channels are often at atmospheric window in 3-5μm, lack of water vapor and carbon dioxide(CO2) absorption channels data, such as 2.2μm, 2.7μm and so on, however the 2.7μm absorption bands can be used as volcanoes, forest fires and other hot target identification. In order to obtain the high-temperature targets (HTT)radiation features, such as volcanic eruptions and forest fires in the water vapor absorption channels, Firstly, the HTT should be identified from the existing bands based on the temperature differences between the objects and the surrounding environment. Then, the HTT radiation features were simulated, and the correlation between the radiations of different bands were established with statistical analysis method. The HTT reorganization from remote sensing data, radiation characteristics simulation in different atmospheric models were described, then the bands transformed models were set up. The volcanic HTT radiation characteristics were simulated in wavelength 2.7μm and 4.433-4.498μm (band 24 of MODIS) based on the known bands of 3.55 -3.93μm (band 3 of FengYun-3 Visible and Infrared Scanning Radiometer (VIRR)). The simulated results were tested by the volcanic HTT radiation characteristics with 4.433-4.498μm by known bands of MODIS image and the simulated 4.433-4.498μm image. The causes of errors generated were analyzed. The study methods were useful to the new remote sensor bands imaging characteristics simulation analysis.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Enhancing forest value productivity through fiber quality

Treesearch

D. Briggs

2010-01-01

Developing markets for carbon storage and bioenergy, shifting of the pulp and paper industry to biorefineries, and the potential of new technologies present the forest sector with exciting transformative opportunities and challenges. One of these challenges will be to understand the implications for fiber (wood) quality. This article provides a definitional context for...

The Forest Indians in the Present Political Situation of Peru.

ERIC Educational Resources Information Center

Varese, Stefano

The article focuses on tribal minorities (American Indians) of the Peruvian tropical forest from the point of view of the political circumstances and the general administrative conditions of the country. In 1968 the revolutionary military government initiated a series of structural reforms which aimed at transforming Peru. This article poses and…

The emerging era of novel tropical forests

Treesearch

A.E. Lugo

2009-01-01

In 1966 Eugene P. Odum delivered a speech before the Ecological Society of America that transformed the way ecologists looked at succession. His comparison of mature and successional systems lead ecologists to place secondary forests in an inferior position relative to mature ones to the point that today, prominent tropical biologists argue for and against the...

Radar Mosaic of Africa

NASA Image and Video Library

1999-09-23

This is an image of equatorial Africa, centered on the equator at longitude 15degrees east. This image is a mosaic of almost 4,000 separate images obtained in 1996 by the L-band imaging radar onboard the Japanese Earth Resources Satellite. Using radar to penetrate the persistent clouds prevalent in tropical forests, the Japanese Earth Resources Satellite was able for the first time to image at high resolution this continental scale region during single flooding seasons. The area shown covers about 7.4 million square kilometers (2.8 million square miles) of land surface, spans more than 5,000 kilometers(3,100 miles) east and west and some 2,000 kilometers (1,240 miles) north and south. North is up in this image. At the full resolution of the mosaic (100 meters or 330 feet), this image is more than 500 megabytes in size, and was processed from imagery totaling more than 60 gigabytes. Central Africa was imaged twice in 1996, once between January and March, which is the major low-flood season in the Congo Basin, and once between October and November, which is the major high-flood season in the Congo Basin. The red color corresponds to the data from the low-flood season, the green to the high-flood season, and the blue to the "texture" of the low-flood data. The forests appear green as a result, the flooded and palm forests, as well as urban areas, appear yellow, the ocean and lakes appear black, and savanna areas appear blue, black or green, depending on the savanna type, surface topography and other factors. The areas of the image that are black and white were mapped only between January and March 1996. In these areas, the black areas are savanna or open water, the gray are forests, and the white areas are flooded forests or urban areas. The Congo River dominates the middle of the image, where the nearby forests that are periodically flooded by the Congo and its tributaries stand out as yellow. The Nile River flows north from Lake Victoria in the middle right of the color portion of the mosaic. http://photojournal.jpl.nasa.gov/catalog/PIA01348

On the potential of long wavelength imaging radars for mapping vegetation types and woody biomass in tropical rain forests

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Zimmermann, Reiner; Oren, Ram

1995-01-01

In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.

Geocoding and stereo display of tropical forest multisensor datasets

NASA Technical Reports Server (NTRS)

Welch, R.; Jordan, T. R.; Luvall, J. C.

1990-01-01

Concern about the future of tropical forests has led to a demand for geocoded multisensor databases that can be used to assess forest structure, deforestation, thermal response, evapotranspiration, and other parameters linked to climate change. In response to studies being conducted at the Braulino Carrillo National Park, Costa Rica, digital satellite and aircraft images recorded by Landsat TM, SPOT HRV, Thermal Infrared Multispectral Scanner, and Calibrated Airborne Multispectral Scanner sensors were placed in register using the Landsat TM image as the reference map. Despite problems caused by relief, multitemporal datasets, and geometric distortions in the aircraft images, registration was accomplished to within + or - 20 m (+ or - 1 data pixel). A digital elevation model constructed from a multisensor Landsat TM/SPOT stereopair proved useful for generating perspective views of the rugged, forested terrain.

Geometric processing of digital images of the planets

NASA Technical Reports Server (NTRS)

Edwards, Kathleen

1987-01-01

New procedures and software have been developed for geometric transformation of images to support digital cartography of the planets. The procedures involve the correction of spacecraft camera orientation of each image with the use of ground control and the transformation of each image to a Sinusoidal Equal-Area map projection with an algorithm which allows the number of transformation calculations to vary as the distortion varies within the image. When the distortion is low in an area of an image, few transformation computations are required, and most pixels can be interpolated. When distortion is extreme, the location of each pixel is computed. Mosaics are made of these images and stored as digital databases. Completed Sinusoidal databases may be used for digital analysis and registration with other spatial data. They may also be reproduced as published image maps by digitally transforming them to appropriate map projections.

Field theory of pattern identification

NASA Astrophysics Data System (ADS)

Agu, Masahiro

1988-06-01

Based on the psychological experimental fact that images in mental space are transformed into other images for pattern identification, a field theory of pattern identification of geometrical patterns is developed with the use of gauge field theory in Euclidean space. Here, the ``image'' or state function ψ[χ] of the brain reacting to a geometrical pattern χ is made to correspond to the electron's wave function in Minkowski space. The pattern identification of the pattern χ with the modified pattern χ+Δχ is assumed to be such that their images ψ[χ] and ψ[χ+Δχ] in the brain are transformable with each other through suitable transformation groups such as parallel transformation, dilatation, or rotation. The transformation group is called the ``image potential'' which corresponds to the vector potential of the gauge field. An ``image field'' derived from the image potential is found to be induced in the brain when the two images ψ[χ] and ψ[χ+Δχ] are not transformable through suitable transformation groups or gauge transformations. It is also shown that, when the image field exists, the final state of the image ψ[χ] is expected to be different, depending on the paths of modifications of the pattern χ leading to a final pattern. The above fact is interpreted as a version of the Aharonov and Bohm effect of the electron's wave function [A. Aharonov and D. Bohm, Phys. Rev. 115, 485 (1959)]. An excitation equation of the image field is also derived by postulating that patterns are identified maximally for the purpose of minimizing the number of memorized standard patterns.

Combining forest inventory, satellite remote sensing, and geospatial data for mapping forest attributes of the conterminous United States

Treesearch

Mark Nelson; Greg Liknes; Charles H. Perry

2009-01-01

Analysis and display of forest composition, structure, and pattern provides information for a variety of assessments and management decision support. The objective of this study was to produce geospatial datasets and maps of conterminous United States forest land ownership, forest site productivity, timberland, and reserved forest land. Satellite image-based maps of...

Consistency of forest presence and biomass predictions modeled across overlapping spatial and temporal extents

Treesearch

Mark D. Nelson; Sean Healey; W. Keith Moser; J.G. Masek; Warren Cohen

2011-01-01

We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical...

Spaceborne Applications of P Band Imaging Radars for Measuring Forest Biomass

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Zimmermann, Reiner; vanZyl, Jakob J.

1995-01-01

In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.

CW-SSIM kernel based random forest for image classification

NASA Astrophysics Data System (ADS)

Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

2010-07-01

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

Double Density Dual Tree Discrete Wavelet Transform implementation for Degraded Image Enhancement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

Wavelet transform is a main tool for image processing applications in modern existence. A Double Density Dual Tree Discrete Wavelet Transform is used and investigated for image denoising. Images are considered for the analysis and the performance is compared with discrete wavelet transform and the Double Density DWT. Peak Signal to Noise Ratio values and Root Means Square error are calculated in all the three wavelet techniques for denoised images and the performance has evaluated. The proposed techniques give the better performance when comparing other two wavelet techniques.

Estimates of phytomass and net primary productivity in terrestrial ecosystems of the former Soviet Union identified by classified Global Vegetation Index

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

Gaston, G.G.; Kolchugina, T.P.

1995-12-01

Forty-two regions with similar vegetation and landcover were identified in the former Soviet Union (FSU) by classifying Global Vegetation Index (GVI) images. Image classes were described in terms of vegetation and landcover. Image classes appear to provide more accurate and precise descriptions for most ecosystems when compared to general thematic maps. The area of forest lands were estimated at 1,330 Mha and the actual area of forest ecosystems at 875 Mha. Arable lands were estimated to be 211 Mha. The area of the tundra biome was estimated at 261 Mha. The areas of the forest-tundra/dwarf forest, taiga, mixed-deciduous forest andmore » forest-steppe biomes were estimated t 153, 882, 196, and 144 Mha, respectively. The areas of desert-semidesert biome and arable land with irrigated land and meadows, were estimated at 126 and 237 Mha, respectively. Vegetation and landcover types were associated with the Bazilevich database of phytomass and NPP for vegetation in the FSU. The phytomass in the FSU was estimated at 97.1 Gt C, with 86.8 in forest vegetation, 9.7 in natural non-forest and 0.6 Gt C in arable lands. The NPP was estimated at 8.6 Gt C/yr, with 3.2, 4.8, and 0.6 Gt C/yr of forest, natural non-forest, and arable ecosystems, respectively. The phytomass estimates for forests were greater than previous assessments which considered the age-class distribution of forest stands in the FSU. The NPP of natural ecosystems estimated in this study was 23% greater than previous estimates which used thematic maps to identify ecosystems. 47 refs., 4 figs., 2 tabs.« less

[Effects of climate change on forest soil organic carbon storage: a review].

PubMed

Zhou, Xiao-yu; Zhang, Cheng-yi; Guo, Guang-fen

2010-07-01

Forest soil organic carbon is an important component of global carbon cycle, and the changes of its accumulation and decomposition directly affect terrestrial ecosystem carbon storage and global carbon balance. Climate change would affect the photosynthesis of forest vegetation and the decomposition and transformation of forest soil organic carbon, and further, affect the storage and dynamics of organic carbon in forest soils. Temperature, precipitation, atmospheric CO2 concentration, and other climatic factors all have important influences on the forest soil organic carbon storage. Understanding the effects of climate change on this storage is helpful to the scientific management of forest carbon sink, and to the feasible options for climate change mitigation. This paper summarized the research progress about the distribution of organic carbon storage in forest soils, and the effects of elevated temperature, precipitation change, and elevated atmospheric CO2 concentration on this storage, with the further research subjects discussed.

Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables

NASA Astrophysics Data System (ADS)

Nurminen, Kimmo; Karjalainen, Mika; Yu, Xiaowei; Hyyppä, Juha; Honkavaara, Eija

2013-09-01

Recent research results have shown that the performance of digital surface model extraction using novel high-quality photogrammetric images and image matching is a highly competitive alternative to laser scanning. In this article, we proceed to compare the performance of these two methods in the estimation of plot-level forest variables. Dense point clouds extracted from aerial frame images were used to estimate the plot-level forest variables needed in a forest inventory covering 89 plots. We analyzed images with 60% and 80% forward overlaps and used test plots with off-nadir angles of between 0° and 20°. When compared to reference ground measurements, the airborne laser scanning (ALS) data proved to be the most accurate: it yielded root mean square error (RMSE) values of 6.55% for mean height, 11.42% for mean diameter, and 20.72% for volume. When we applied a forward overlap of 80%, the corresponding results from aerial images were 6.77% for mean height, 12.00% for mean diameter, and 22.62% for volume. A forward overlap of 60% resulted in slightly deteriorated RMSE values of 7.55% for mean height, 12.20% for mean diameter, and 22.77% for volume. According to our results, the use of higher forward overlap produced only slightly better results in the estimation of these forest variables. Additionally, we found that the estimation accuracy was not significantly impacted by the increase in the off-nadir angle. Our results confirmed that digital aerial photographs were about as accurate as ALS in forest resources estimation as long as a terrain model was available.

27. DUCT LINES AND HOLES TO BE LEFT IN TRANSFORMER ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

27. DUCT LINES AND HOLES TO BE LEFT IN TRANSFORMER ROOM AND GALLERY, MENTONE, MAR. 13, 1904. R.S. MASSON, CONSULTING ELECTRICAL ENGINEER, SAN FRANCISCO AND LOS ANGELES. SCE drawing no. 52319. - Santa Ana River Hydroelectric System, SAR-3 Powerhouse, San Bernardino National Forest, Redlands, San Bernardino County, CA

A transformation-aware perceptual image metric

NASA Astrophysics Data System (ADS)

Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2015-03-01

Predicting human visual perception has several applications such as compression, rendering, editing and retargeting. Current approaches however, ignore the fact that the human visual system compensates for geometric transformations, e. g., we see that an image and a rotated copy are identical. Instead, they will report a large, false-positive difference. At the same time, if the transformations become too strong or too spatially incoherent, comparing two images indeed gets increasingly difficult. Between these two extrema, we propose a system to quantify the effect of transformations, not only on the perception of image differences, but also on saliency. To this end, we first fit local homographies to a given optical flow field and then convert this field into a field of elementary transformations such as translation, rotation, scaling, and perspective. We conduct a perceptual experiment quantifying the increase of difficulty when compensating for elementary transformations. Transformation entropy is proposed as a novel measure of complexity in a flow field. This representation is then used for applications, such as comparison of non-aligned images, where transformations cause threshold elevation, and detection of salient transformations.

Spatial transform coding of color images.

NASA Technical Reports Server (NTRS)

Pratt, W. K.

1971-01-01

The application of the transform-coding concept to the coding of color images represented by three primary color planes of data is discussed. The principles of spatial transform coding are reviewed and the merits of various methods of color-image representation are examined. A performance analysis is presented for the color-image transform-coding system. Results of a computer simulation of the coding system are also given. It is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation. If luminance coding is also employed, the average rate reduces to about 2.0 bits per element or less.

Polychlorinated biphenyls and polybrominated diphenylethers in soils from planted forests and adjacent natural forests on a tropical island.

PubMed

Liu, Xin; Wang, Shuai; Jiang, Yishan; Sun, Yingtao; Li, Jun; Zhang, Gan

2017-08-01

Transformation from natural forests to planted forests in tropical regions is an expanding global phenomenon causing major modifications of land cover and soil properties, e.g. soil organic carbon (SOC). This study investigated accumulations of POPs in soils under eucalyptus and rubber forests as compared with adjacent natural forests on Hainan Island, China. Results showed that due to the greater forest filter effect and the higher SOC, the natural forest have accumulated larger amounts of POPs in the top 20 cm soil. Based on correlation and air-soil equilibrium analysis, we highlighted the importance of SOC in the distribution of POPs. It is assumed that the elevated mobility of POPs in the planted forests was caused by greater loss of SOC and extensive leaching in the soil profile. This suggests that a better understanding of global POPs fate should take into consideration the role of planted forests. Copyright © 2017 Elsevier Ltd. All rights reserved.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

NASA Astrophysics Data System (ADS)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

Digital watermarking algorithm research of color images based on quaternion Fourier transform

NASA Astrophysics Data System (ADS)

An, Mali; Wang, Weijiang; Zhao, Zhen

2013-10-01

A watermarking algorithm of color images based on the quaternion Fourier Transform (QFFT) and improved quantization index algorithm (QIM) is proposed in this paper. The original image is transformed by QFFT, the watermark image is processed by compression and quantization coding, and then the processed watermark image is embedded into the components of the transformed original image. It achieves embedding and blind extraction of the watermark image. The experimental results show that the watermarking algorithm based on the improved QIM algorithm with distortion compensation achieves a good tradeoff between invisibility and robustness, and better robustness for the attacks of Gaussian noises, salt and pepper noises, JPEG compression, cropping, filtering and image enhancement than the traditional QIM algorithm.

Changes in the vegetation cover and soils under natural overgrowth of felled areas in fir forests of the Yenisei Ridge

NASA Astrophysics Data System (ADS)

Trefilova, O. V.; Efimov, D. Yu.

2015-08-01

The results of the integrated analysis of changes in the state of vegetation and soils (Cutanic Albeluvisol) at the different stages of natural forest regeneration (4-, 11- and 24-year-old felled areas) and in a mature fir forest of the short grass-green moss forest types in the northern part of the western slope of the Yenisei Ridge are presented. A dynamic trend of fir forests restoration to the formation of the structure characteristics of the initial forest types is shown to be performed through the stages of forest meadows and secondary short grass (forbs) and birch stands. The changes in vegetation are accompanied by the fast transformation of the soil properties towards the improvement of soil fertilization However, these changes are temporary.

GEOMETRIC PROCESSING OF DIGITAL IMAGES OF THE PLANETS.

USGS Publications Warehouse

Edwards, Kathleen

1987-01-01

New procedures and software have been developed for geometric transformations of images to support digital cartography of the planets. The procedures involve the correction of spacecraft camera orientation of each image with the use of ground control and the transformation of each image to a Sinusoidal Equal-Area map projection with an algorithm which allows the number of transformation calculations to vary as the distortion varies within the image. When the distortion is low in an area of an image, few transformation computations are required, and most pixels can be interpolated. When distortion is extreme, the location of each pixel is computed. Mosaics are made of these images and stored as digital databases.

Blind Forensics of Successive Geometric Transformations in Digital Images Using Spectral Method: Theory and Applications.

PubMed

Chen, Chenglong; Ni, Jiangqun; Shen, Zhaoyi; Shi, Yun Qing

2017-06-01

Geometric transformations, such as resizing and rotation, are almost always needed when two or more images are spliced together to create convincing image forgeries. In recent years, researchers have developed many digital forensic techniques to identify these operations. Most previous works in this area focus on the analysis of images that have undergone single geometric transformations, e.g., resizing or rotation. In several recent works, researchers have addressed yet another practical and realistic situation: successive geometric transformations, e.g., repeated resizing, resizing-rotation, rotation-resizing, and repeated rotation. We will also concentrate on this topic in this paper. Specifically, we present an in-depth analysis in the frequency domain of the second-order statistics of the geometrically transformed images. We give an exact formulation of how the parameters of the first and second geometric transformations influence the appearance of periodic artifacts. The expected positions of characteristic resampling peaks are analytically derived. The theory developed here helps to address the gap left by previous works on this topic and is useful for image security and authentication, in particular, the forensics of geometric transformations in digital images. As an application of the developed theory, we present an effective method that allows one to distinguish between the aforementioned four different processing chains. The proposed method can further estimate all the geometric transformation parameters. This may provide useful clues for image forgery detection.

Landsat-based Analysis of Mountain Forest-tundra Ecotone Response to Climate Trends in Sayan Mountains

NASA Technical Reports Server (NTRS)

Kharuk, Viatcheslav I.; Im, Sergey T.; Ranson, K. Jon

2007-01-01

observations of temperatures Siberia has shown a several degree warming over the past 30 years. It is expected that forest will respond to warming at high latitudes through increased tree growth and northward or upward slope migration. migration. Tree response to climate trends is most likely observable in the forest-tundra ecotone, where temperature mainly limits tree growth. Making repeated satellite observations over several decades provides an opportunity to track vegetation response to climate change. Based on Landsat data of the Sayan Mountains, Siberia, there was an increase in forest stand crown closure and an upward tree-line shift in the of the forest-tundra ecotone during the last quarter of the 2oth century,. On-ground observations, supporting these results, also showed regeneration of Siberian pine in the alpine tundra, and the transformation of prostrate Siberian pine and fir into arboreal (upright) forms. During this time period sparse stands transformed into closed stands, with existing closed stands increasing in area at a rate of approx. 1 %/yr, and advancing their upper border at a vertical rate of approx. 1.0 m/yr. In addition, the vertical rate of regeneration propagation is approx. 5 m/yr. It was also found that these changes correlated positively with temperature trends

Space Radar Image of Manaus, Brazil

NASA Image and Video Library

1999-05-01

These two false-color images of the Manaus region of Brazil in South America were acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar on board the space shuttle Endeavour. The image at left was acquired on April 12, 1994, and the image at right was acquired on October 3, 1994. The area shown is approximately 8 kilometers by 40 kilometers (5 miles by 25 miles). The two large rivers in this image, the Rio Negro (at top) and the Rio Solimoes (at bottom), combine at Manaus (west of the image) to form the Amazon River. The image is centered at about 3 degrees south latitude and 61 degrees west longitude. North is toward the top left of the images. The false colors were created by displaying three L-band polarization channels: red areas correspond to high backscatter, horizontally transmitted and received, while green areas correspond to high backscatter, horizontally transmitted and vertically received. Blue areas show low returns at vertical transmit/receive polarization; hence the bright blue colors of the smooth river surfaces can be seen. Using this color scheme, green areas in the image are heavily forested, while blue areas are either cleared forest or open water. The yellow and red areas are flooded forest or floating meadows. The extent of the flooding is much greater in the April image than in the October image and appears to follow the 10-meter (33-foot) annual rise and fall of the Amazon River. The flooded forest is a vital habitat for fish, and floating meadows are an important source of atmospheric methane. These images demonstrate the capability of SIR-C/X-SAR to study important environmental changes that are impossible to see with optical sensors over regions such as the Amazon, where frequent cloud cover and dense forest canopies block monitoring of flooding. Field studies by boat, on foot and in low-flying aircraft by the University of California at Santa Barbara, in collaboration with Brazil's Instituto Nacional de Pesguisas Estaciais, during the first and second flights of the SIR-C/X-SAR system have validated the interpretation of the radar images. http://photojournal.jpl.nasa.gov/catalog/PIA01735

Image encryption with chaotic map and Arnold transform in the gyrator transform domains

NASA Astrophysics Data System (ADS)

Sang, Jun; Luo, Hongling; Zhao, Jun; Alam, Mohammad S.; Cai, Bin

2017-05-01

An image encryption method combing chaotic map and Arnold transform in the gyrator transform domains was proposed. Firstly, the original secret image is XOR-ed with a random binary sequence generated by a logistic map. Then, the gyrator transform is performed. Finally, the amplitude and phase of the gyrator transform are permutated by Arnold transform. The decryption procedure is the inverse operation of encryption. The secret keys used in the proposed method include the control parameter and the initial value of the logistic map, the rotation angle of the gyrator transform, and the transform number of the Arnold transform. Therefore, the key space is large, while the key data volume is small. The numerical simulation was conducted to demonstrate the effectiveness of the proposed method and the security analysis was performed in terms of the histogram of the encrypted image, the sensitiveness to the secret keys, decryption upon ciphertext loss, and resistance to the chosen-plaintext attack.

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2017-09-01

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

NASA Astrophysics Data System (ADS)

Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira

2014-03-01

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.

Quantifying Foliar Pigment Concentrations of Temperate Forest Species Using Digital Photography and Hyperspectral Reflectance Indices

NASA Astrophysics Data System (ADS)

Gagnon, M. T.; Rock, B. N.; Jahnke, L. S.; Lee, T. D.

2008-12-01

Determination of leaf chlorophyll content is a common and important procedure for plant scientists. There are many multispectral techniques for non destructive in-vivo, estimation of chlorophyll in foliage. Although much has been done to explore the estimation of foliar pigments using remote sensing, very little work has been done exploring the potential that basic, affordable, digital cameras may have for such analysis. This study utilizes a combination of digital photography, hyperspectral laboratory remote sensing, and chlorophyll extractions to determine if digital photographs can be used to accurately predict foliar chlorophyll concentrations as well to compare this digital approach with several common spectral indices used for estimating foliar chlorophyll content. Foliar materials for this study come from three sources. A large collection of samples were collected (60) from 9 common temperate forest species in July and late September over a 1 kilometer area at the Bartlett Experimental Forest in northern New Hampshire. Secondly, 15 trees were selected in a forested setting near the University of New Hampshire for more intensive phenological analysis. These samples consist of 5 white pine (Pinus strobus), 5 black oak (Quercus velutina) and 5 sugar maple (Acer saccharum). Finally, dozens of samples of white pine utilized in Forest Watch, a successful K-12 science outreach which assesses the impact of tropospheric ozone on forest health in New England, were also analyzed for this study. For all samples in this study, chlorophyll extractions were conducted to determine chlorophyll a, chlorophyll b, and total chlorophyll concentrations. Laboratory spectral analysis was performed using a GER 2600 Spectroradiometer to determine hyperspectral estimates of chlorophyll content using a Red Edge Inflection Point (REIP) approach, as well as a Transformed Chlorophyll Absorption Reflectance Index/Optimized Soil Adjusted Vegetation Index (TCARI/OSAVI) approach. These measures of chlorophyll estimation were utilized to determine whether red, green and blue spectral data from digital images taken with a Kodak C713 model camera could be used to estimate foliar chlorophyll concentrations in forest foliage. Preliminary results of this study will be presented.

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.

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.

Space Radar Image of Baikal Lake, Russia

NASA Technical Reports Server (NTRS)

1994-01-01

This is an X-band black-and-white image of the forests east of the Baikal Forest in the Jablonowy Mountains of Russia. The image is centered at 52.5 degrees north latitude and 116 degrees east longitude near the mining town of Bukatschatscha. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on October 4, 1994, during the second flight of the spaceborne radar. This area is part of an international research project known as the Taiga Aerospace Investigation using Geographic Information System Applications.

Estimating tropical-forest density profiles from multibaseline interferometric SAR

NASA Technical Reports Server (NTRS)

Treuhaft, Robert; Chapman, Bruce; dos Santos, Joao Roberto; Dutra, Luciano; Goncalves, Fabio; da Costa Freitas, Corina; Mura, Jose Claudio; de Alencastro Graca, Paulo Mauricio

2006-01-01

Vertical profiles of forest density are potentially robust indicators of forest biomass, fire susceptibility and ecosystem function. Tropical forests, which are among the most dense and complicated targets for remote sensing, contain about 45% of the world's biomass. Remote sensing of tropical forest structure is therefore an important component to global biomass and carbon monitoring. This paper shows preliminary results of a multibasline interfereomtric SAR (InSAR) experiment over primary, secondary, and selectively logged forests at La Selva Biological Station in Costa Rica. The profile shown results from inverse Fourier transforming 8 of the 18 baselines acquired. A profile is shown compared to lidar and field measurements. Results are highly preliminary and for qualitative assessment only. Parameter estimation will eventually replace Fourier inversion as the means to producing profiles.

Satellite Imagery Data: Dynamic Systems Model for sustainable urban forest in area of Halim Perdana Kusuma, East Jakarta

NASA Astrophysics Data System (ADS)

Sundara, D. M.; Hartono, D. M.; Suganda, E.; Haeruman, JS H.

2018-05-01

East Jakarta icon as a buffer and the lungs of the city is still a big dream of Jakarta. It is a classic problem that there is a struggle for land between current economic interests and sustainable environmental interests for the future. This paper discusses the development of urban forest area of Halim Perdana Kusuma, East Jakarta. The forest area according to regulations of existing city local governments is not enough to support sustainable urban development indicators. Therefore, it requires an extensive mapping of urban forest potential development accurately by utilizing satellite imaging technology. Landsat-TM satellite imagery data can provide a full picture of the potential land width for urban forest area development. The results of this satellite image will then be made into a model of urban forest as one of the indicators of sustainable urban development. This research aims to support sustainable urban development through environmental balance in the form of a green neighborhood revitalization and development of urban forests and to create socio-economic balance. This paper uses a dynamic system model to simulate the conditions of the region against the intervention performed in the potential area for development of urban forests which are derived from urban spatial analysis based on satellite image data, using GIS program as a tool. The result is a model of urban forest area which is integrated with a social and economic function to encourage the development of sustainable cities.

Symbolic feature detection for image understanding

NASA Astrophysics Data System (ADS)

Aslan, Sinem; Akgül, Ceyhun Burak; Sankur, Bülent

2014-03-01

In this study we propose a model-driven codebook generation method used to assign probability scores to pixels in order to represent underlying local shapes they reside in. In the first version of the symbol library we limited ourselves to photometric and similarity transformations applied on eight prototypical shapes of flat plateau , ramp, valley, ridge, circular and elliptic respectively pit and hill and used randomized decision forest as the statistical classifier to compute shape class ambiguity of each pixel. We achieved90% accuracy in identification of known objects from alternate views, however, we could not outperform texture, global and local shape methods, but only color-based method in recognition of unknown objects. We present a progress plan to be accomplished as a future work to improve the proposed approach further.

Future forestland area in the U.S. South

Treesearch

David N. Wear

2006-01-01

The southeastern United States has been heavily transformed by various forms of resource exploitation. A review of historical data shows that net change in forest area has been minimal while much of the land in the region has experienced some change over time. Recent economic changes have accelerated urbanization in the region. Future forest area depends both on these...

Temporal Dynamics in Soil Oxygen and Greenhouse Gases in Two Humid Tropical Forests

Treesearch

Daniel Liptzin; Whendee L. Silver; Matteo Detto

2011-01-01

Soil redox plays a key role in regulating biogeochemical transformations in terrestrial ecosystems, but the temporal and spatial patterns in redox and associated controls within and across ecosystems are poorly understood. Upland humid tropical forest soils may be particularly prone to fluctuating redox as abundant rainfall limits oxygen (O2) diffusion through finely...

Soil nitrogen transformations under alternative management strategies in Appalachian forests

Treesearch

T. Adam Coates; Ralph E.J. Boerner; Thomas A. Waldrop; Daniel A. Yaussy

2008-01-01

Once subject to frequent fire and strongly N limited, the forests of the Appalachian Mountain region of eastern North America have experienced almost a century of fire suppression, and changes in tree species composition, understory density and composition, and accumulations of detritus have paralleled the changes in fire frequency. In an effort to restore these...

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection.

Treesearch

Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Olga N. Krankina

2005-01-01

Landsat satellite data has become ubiquitous in regional-scale forest disturbance detection. The Tasseled Cap (TC) transformation for Landsat data has been used in several disturbance-mapping projects because of its ability to highlight relevant vegetation changes. We used an automated composite analysis procedure to test four multi-date variants of the TC...

Global modelling to predict timber production and prices: the GFPM approach

Treesearch

Joseph Buongiorno

2014-01-01

Timber production and prices are determined by the global demand for forest products, and the capability of producers from many countries to grow and harvest trees, transform them into products and export. The Global Forest Products Model (GFPM) simulates how this global demand and supply of multiple products among many countries determines prices and attendant...

A Cross-Site Comparison of Factors Influencing Soil Nitrification Rates in Northeastern USA Forested Watersheds

Treesearch

Donald S. Ross; Beverley C. Wemple; Austin E. Jamison; Guinevere Fredriksen; James B. Shanley; Gregory B. Lawrence; Scott W. Bailey; John L. Campbell

2009-01-01

Elevated N deposition is continuing on many forested landscapes around the world and our understanding of ecosystem response is incomplete. Soil processes, especially nitrification, are critical. Many studies of soil N transformations have focused on identifying relationships within a single watershed but these results are often not transferable. We studied 10 small...

Using soil temperature and moisture to predict forest soil nitrogen mineralization

Treesearch

Jennifer D. Knoepp; Wayne T. Swank

2002-01-01

Due to the importance of N in forest productivity ecosystem and nutrient cycling research often includes measurement of soil N transformation rates as indices of potential availability and ecosystem losses of N. We examined the feasibility of using soil temperature and moisture content to predict soil N mineralization rates (Nmin) at the Coweeta Hydrologic Laboratory...

Fourier removal of stripe artifacts in IRAS images

NASA Technical Reports Server (NTRS)

Van Buren, Dave

1987-01-01

By working in the Fourier plane, approximate removal of stripe artifacts in IRAS images can be effected. The image of interest is smoothed and subtracted from the original, giving the high-spatial-frequency part. This 'filtered' image is then clipped to remove point sources and then Fourier transformed. Subtracting the Fourier components contributing to the stripes in this image from the Fourier transform of the original and transforming back to the image plane yields substantial removal of the stripes.

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

Minor Distortions with Major Consequences: Correcting Distortions in Imaging Spectrographs

PubMed Central

Esmonde-White, Francis W. L.; Esmonde-White, Karen A.; Morris, Michael D.

2010-01-01

Projective transformation is a mathematical correction (implemented in software) used in the remote imaging field to produce distortion-free images. We present the application of projective transformation to correct minor alignment and astigmatism distortions that are inherent in dispersive spectrographs. Patterned white-light images and neon emission spectra were used to produce registration points for the transformation. Raman transects collected on microscopy and fiber-optic systems were corrected using established methods and compared with the same transects corrected using the projective transformation. Even minor distortions have a significant effect on reproducibility and apparent fluorescence background complexity. Simulated Raman spectra were used to optimize the projective transformation algorithm. We demonstrate that the projective transformation reduced the apparent fluorescent background complexity and improved reproducibility of measured parameters of Raman spectra. Distortion correction using a projective transformation provides a major advantage in reducing the background fluorescence complexity even in instrumentation where slit-image distortions and camera rotation were minimized using manual or mechanical means. We expect these advantages should be readily applicable to other spectroscopic modalities using dispersive imaging spectrographs. PMID:21211158

Improvement and extension of a radar forest backscattering model

NASA Technical Reports Server (NTRS)

Simonett, David S.; Wang, Yong

1989-01-01

Radar modeling of mangal forest stands, in the Sundarbans area of Southern Bangladesh, was developed. The modeling employs radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water (including slightly conductive water), content both in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed, which are required to explain the contributions of various forest species combinations in the attenuation and scattering of mangal vegetated nonflooded or flooded surfaces. Statistical data of simulated images were compared with those of SIR-B images both to refine the modeling procedures and to appropriately characterize the model output. The possibility of delineation of flooded or nonflooded boundaries is discussed.

Hurricane Katrina's carbon footprint on U.S. Gulf Coast forests.

PubMed

Chambers, Jeffrey Q; Fisher, Jeremy I; Zeng, Hongcheng; Chapman, Elise L; Baker, David B; Hurtt, George C

2007-11-16

Hurricane Katrina's impact on U.S. Gulf Coast forests was quantified by linking ecological field studies, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) image analyses, and empirically based models. Within areas affected by relatively constant wind speed, tree mortality and damage exhibited strong species-controlled gradients. Spatially explicit forest disturbance maps coupled with extrapolation models predicted mortality and severe structural damage to approximately 320 million large trees totaling 105 teragrams of carbon, representing 50 to 140% of the net annual U.S. forest tree carbon sink. Changes in disturbance regimes from increased storm activity expected under a warming climate will reduce forest biomass stocks, increase ecosystem respiration, and may represent an important positive feedback mechanism to elevated atmospheric carbon dioxide.

Comparison of Hyperspectral and Multispectral Satellites for Forest Alliance Classification in the San Francisco Bay Area

NASA Astrophysics Data System (ADS)

Clark, M. L.

2016-12-01

The goal of this study was to assess multi-temporal, Hyperspectral Infrared Imager (HyspIRI) satellite imagery for improved forest class mapping relative to multispectral satellites. The study area was the western San Francisco Bay Area, California and forest alliances (e.g., forest communities defined by dominant or co-dominant trees) were defined using the U.S. National Vegetation Classification System. Simulated 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery were processed from image data acquired by NASA's AVIRIS airborne sensor in year 2015, with summer and multi-temporal (spring, summer, fall) data analyzed separately. HyspIRI reflectance was used to generate a suite of hyperspectral metrics that targeted key spectral features related to chemical and structural properties. The Random Forests classifier was applied to the simulated images and overall accuracies (OA) were compared to those from real Landsat 8 images. For each image group, broad land cover (e.g., Needle-leaf Trees, Broad-leaf Trees, Annual agriculture, Herbaceous, Built-up) was classified first, followed by a finer-detail forest alliance classification for pixels mapped as closed-canopy forest. There were 5 needle-leaf tree alliances and 16 broad-leaf tree alliances, including 7 Quercus (oak) alliance types. No forest alliance classification exceeded 50% OA, indicating that there was broad spectral similarity among alliances, most of which were not spectrally pure but rather a mix of tree species. In general, needle-leaf (Pine, Redwood, Douglas Fir) alliances had better class accuracies than broad-leaf alliances (Oaks, Madrone, Bay Laurel, Buckeye, etc). Multi-temporal data classifications all had 5-6% greater OA than with comparable summer data. For simulated data, HyspIRI metrics had 4-5% greater OA than Landsat 8 and Sentinel-2 multispectral imagery and 3-4% greater OA than HyspIRI reflectance. Finally, HyspIRI metrics had 8% greater OA than real Landsat 8 imagery. In conclusion, forest alliance classification was found to be a difficult remote sensing application with moderate resolution (30 m) satellite imagery; however, of the data tested, HyspIRI spectral metrics had the best performance relative to multispectral satellites.

Evaluation of Forest Health Conditions using Unmanned Aircraft Systems (UAS)

NASA Astrophysics Data System (ADS)

Hatfield, M. C.; Heutte, T. M.

2016-12-01

US Forest Service Alaska Region Forest Health Protection (FHP) and University of Alaska Fairbanks, Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) are evaluating capability of Unmanned Aerial Systems (UAS) to monitor forest health conditions in Alaska's Interior Region. In July 2016, the team deployed UAS at locations in the Tanana Valley near Fairbanks in order to familiarize FHP staff with capabilities of UAS for evaluating insect and disease damage. While many potential uses of UAS to evaluate and monitor forest health can be envisioned, this project focused on use of a small UAS for rapid assessment of insect and disease damage. Traditional ground-based methods are limited by distance from ground to canopy and inaccessibility of forest stands due to terrain conditions. Observation from fixed-wing aircraft provide a broad overview of conditions but are limited by minimum safe flying altitude (500' AGL) and aircraft speed ( 100 mph). UAS may provide a crucial bridge to fill in gaps between ground and airborne methods, and offer significant cost savings and greater flexibility over helicopter-based observations. Previous uses of UAS for forest health monitoring are limited - this project focuses on optimizing choice of vehicle, sensors, resolution and area scanned from different altitudes, and use of visual spectrum vs NIR image collection. The vehicle selected was the ACUASI Ptarmigan, a small hexacopter (based on DJI S800 airframe and 3DR autopilot) capable of carrying a 1.5 kg payload for 15 min for close-range environmental monitoring missions. Sites were chosen for conditions favorable to UAS operation and presence of forest insect and disease agents including spruce broom rust, aspen leaf miner, birch leaf roller, and willow leafblotch miner. A total of 29 flights were conducted with 9000+ images collected. Mission variables included camera height, UAS speed, and medium- (Sony NEX-7) vs low-resolution (GoPro Hero) cameras. Invaluable knowledge was gained as to limitations and opportunities for field deployment of UAS relative to local conditions of terrain and forest type. Analysis will include image suitability for orthocorrection and production of stand level image mosaic, with further optimization of image collection parameters to detect known insect- and disease-caused disturbance.

Object-based methods for individual tree identification and tree species classification from high-spatial resolution imagery

NASA Astrophysics Data System (ADS)

Wang, Le

2003-10-01

Modern forest management poses an increasing need for detailed knowledge of forest information at different spatial scales. At the forest level, the information for tree species assemblage is desired whereas at or below the stand level, individual tree related information is preferred. Remote Sensing provides an effective tool to extract the above information at multiple spatial scales in the continuous time domain. To date, the increasing volume and readily availability of high-spatial-resolution data have lead to a much wider application of remotely sensed products. Nevertheless, to make effective use of the improving spatial resolution, conventional pixel-based classification methods are far from satisfactory. Correspondingly, developing object-based methods becomes a central challenge for researchers in the field of Remote Sensing. This thesis focuses on the development of methods for accurate individual tree identification and tree species classification. We develop a method in which individual tree crown boundaries and treetop locations are derived under a unified framework. We apply a two-stage approach with edge detection followed by marker-controlled watershed segmentation. Treetops are modeled from radiometry and geometry aspects. Specifically, treetops are assumed to be represented by local radiation maxima and to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate overlapping trees and to produce a segmented image comprised of individual tree crowns. The image segmentation method developed achieves a promising result for a 256 x 256 CASI image. Then further effort is made to extend our methods to the multiscales which are constructed from a wavelet decomposition. A scale consistency and geometric consistency are designed to examine the gradients along the scale-space for the purpose of separating true crown boundary from unwanted textures occurring due to branches and twigs. As a result from the inverse wavelet transform, the tree crown boundary is enhanced while the unwanted textures are suppressed. Based on the enhanced image, an improvement is achieved when applying the two-stage methods to a high resolution aerial photograph. To improve tree species classification, we develop a new method to choose the optimal scale parameter with the aid of Bhattacharya Distance (BD), a well-known index of class separability in traditional pixel-based classification. The optimal scale parameter is then fed in the process of a region-growing-based segmentation as a break-off value. Our object classification achieves a better accuracy in separating tree species when compared to the conventional Maximum Likelihood Classification (MLC). In summary, we develop two object-based methods for identifying individual trees and classifying tree species from high-spatial resolution imagery. Both methods achieve promising results and will promote integration of Remote Sensing and GIS in forest applications.

Optimization of PET-MR Registrations for Nonhuman Primates Using Mutual Information Measures: A Multi-Transform Method (MTM)

PubMed Central

Sandiego, Christine M.; Weinzimmer, David; Carson, Richard E.

2012-01-01

An important step in PET brain kinetic analysis is the registration of functional data to an anatomical MR image. Typically, PET-MR registrations in nonhuman primate neuroreceptor studies used PET images acquired early post-injection, (e.g., 0–10 min) to closely resemble the subject’s MR image. However, a substantial fraction of these registrations (~25%) fail due to the differences in kinetics and distribution for various radiotracer studies and conditions (e.g., blocking studies). The Multi-Transform Method (MTM) was developed to improve the success of registrations between PET and MR images. Two algorithms were evaluated, MTM-I and MTM-II. The approach involves creating multiple transformations by registering PET images of different time intervals, from a dynamic study, to a single reference (i.e., MR image) (MTM-I) or to multiple reference images (i.e., MR and PET images pre-registered to the MR) (MTM-II). Normalized mutual information was used to compute similarity between the transformed PET images and the reference image(s) to choose the optimal transformation. This final transformation is used to map the dynamic dataset into the animal’s anatomical MR space, required for kinetic analysis. The chosen transformed from MTM-I and MTM-II were evaluated using visual rating scores to assess the quality of spatial alignment between the resliced PET and reference. One hundred twenty PET datasets involving eleven different tracers from 3 different scanners were used to evaluate the MTM algorithms. Studies were performed with baboons and rhesus monkeys on the HR+, HRRT, and Focus-220. Successful transformations increased from 77.5%, 85.8%, to 96.7% using the 0–10 min method, MTM-I, and MTM-II, respectively, based on visual rating scores. The Multi-Transform Methods proved to be a robust technique for PET-MR registrations for a wide range of PET studies. PMID:22926293

Forest and wildlife habitat analysis using remote sensing and geographic information systems. M.S. Thesis, 26 May 1992 Abstract Only

NASA Technical Reports Server (NTRS)

Fiorella, Maria

1995-01-01

Forest and wildlife habitat analyses were conducted at the H.J. Andrews Experimental Forest in the Central Cascade Mountains of Oregon using remotely sensed data and a geographic information system (GIS). Landsat Thematic Mapper (TM) data were used to determine forest successional stages, and to analyze the structure of both old and young conifer forests. Two successional stage maps were developed. One was developed from six TM spectral bands alone, and the second was developed from six TM spectral bands and a relative sun incidence band. Including the sun incidence band in the classification improved the mapping accuracy in the two youngest successional stages, but did not improve overall accuracy or accuracy of the two oldest successional stages. Mean spectral values for old-growth and mature stands were compared in seven TM bands and seven band transformations. Differences between mature and old-growth successional stages were greatest for the band ratio of TM 4/5 (P = 0.00005) and the multiband transformation of wetness (P = 0.00003). The age of young conifer stands had the highest correlation to TM 4/5 values (r = 0.9559) of any of the TM band or band transformations used. TM 4/5 ratio values of poorly regenerated conifer stands were significantly different from well regenerated conifer stands after age 15 (P = 0.0000). TM 4/5 was named a 'Successional Stage Index' (SSI) because of its ability to distinguish forest successional stages. The forest successional stage map was used as input into a vertebrate richness model using GIS. The three variables of (1) successional stage, (2) elevation, and (3) site moisture were used in the GIS to predict the spatial occurrence of small mammal, amphibian, and reptile species based on primary and secondary habitat requirements. These occurrence or habitat maps were overlayed to tally the predicted number of vertebrate at any given point in the study area. Overall, sixty-three and sixty-seven percent of the model predictions for vertebrate occurrence matched the vertebrates that were trapped in the field in eight forested stands. Of the three model variables, site moisture appeared to have the greatest influence on the pattern of high vertebrate richness in all vertebrate classes.

A method to perform a fast fourier transform with primitive image transformations.

PubMed

Sheridan, Phil

2007-05-01

The Fourier transform is one of the most important transformations in image processing. A major component of this influence comes from the ability to implement it efficiently on a digital computer. This paper describes a new methodology to perform a fast Fourier transform (FFT). This methodology emerges from considerations of the natural physical constraints imposed by image capture devices (camera/eye). The novel aspects of the specific FFT method described include: 1) a bit-wise reversal re-grouping operation of the conventional FFT is replaced by the use of lossless image rotation and scaling and 2) the usual arithmetic operations of complex multiplication are replaced with integer addition. The significance of the FFT presented in this paper is introduced by extending a discrete and finite image algebra, named Spiral Honeycomb Image Algebra (SHIA), to a continuous version, named SHIAC.

Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area

NASA Astrophysics Data System (ADS)

Hoang, Nguyen Tien; Koike, Katsuaki

2018-03-01

Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.

Geodetic Imaging: Expanding the Boundaries of Geodesy in the 21st Century

NASA Astrophysics Data System (ADS)

Fernandez Diaz, J. C.; Carter, W. E.; Shrestha, R. L.; Glennie, C. L.

2013-12-01

High resolution (sub-meter) geodetic images covering tens to thousands of square kilometers have extended the boundaries of geodesy into related areas of the earth sciences, such as geomorphology and geodynamics, during the past decade, to archaeological exploration and site mapping during the past few years, and are now poised to transform studies of flora and fauna in the more remote regions of the world. Geodetic images produced from airborne laser scanning (ALS), a.k.a. airborne light detection and ranging (LiDAR) have proven transformative to the modern practice of geomorphology where researchers have used decimeter resolution digital elevation models (DEMs) to determine the spatial frequencies of evenly spaced features in terrain, and developed models and mathematical equations to explain how the terrain evolved to its present state and how it is expected to change in the future (Perron et al., 2009). In geodynamics researchers have used ';before' and ';after' geodetic images of the terrain near earthquakes, such as the 2010 El Mayor-Cucapah Earthquake, to quantify surface displacements and suggest models to explain the observed deformations (Oskin et. al., 2012). In archaeology, the ability of ALS to produce ';bare earth' DEMs of terrain covered with dense vegetation, including even tropical rain forests, has revolutionized the study of archaeology in highly forested areas, finding ancient structures and human modifications of landscapes not discovered by archaeologists working at sites for decades (Chase et al., 2011 & Evans et al., 2013), and finding previously unknown ruins in areas that ground exploration has not been able to penetrate since the arrival of the conquistadors in the new world in the 17th century (Carter et al., 2012). The improved spatial resolution and ability of the third generation ALS units to obtain high resolution bare earth DEMs and canopy models in areas covered in dense forests, brush, and even shallow water (steams, lakes, and coastal waters) is just beginning to attract the attention of researchers studying such plant life as marsh vegetation and sea grasses, and the habitats of animals as diverse as fish, migratory birds, and lions (Vierling et al., 2008). From thousands and thousands of survey markers covering large regions of the earth common to geodesy a half century ago, the focus of some geodesist has changed to billions and billions of points covering landscapes, which are enabling them to redefine and extend the limits of geodesy in the 21st century. References: Carter, W. E. et al., (2012), 'Geodetic Imaging: A New Tool for Mesoamerican Archaeology,' Eos, Trans. American Geophysical Union, Vol. 93, No. 42, pages 413-415. Chase, A. F. et al., (2010) 'Airborne LiDAR, archaeology, and the ancient Maya landscape at Caracol, Belize,' Journal Of Archaeological Science, vol. 38, no. 2, p. 387-398. Evans, D. H. et al., (2013), 'Uncovering archaeological landscapes at Angkor using lidar.' PNAS. Oskin, M. E. et al., (2012), 'Near-Field Deformation from the El Mayor-Cucapah Earthquake Revealed by Differential LIDAR,' Science. Vol. 335 no.6069, pp. 702-705. Perron, J. Taylor, et al (2009), 'Formation of evenly spaced ridges and valleys,' Nature, Vol. 460/23. Vierling, K. T. et al., (2008),'Lidar: shedding new light on habitat characterization and modeling,' Front Ecol Environ 2008, 6(2): 90-98.

Electro-Optical Imaging Fourier-Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Zhou, Hanying

2006-01-01

An electro-optical (E-O) imaging Fourier-transform spectrometer (IFTS), now under development, is a prototype of improved imaging spectrometers to be used for hyperspectral imaging, especially in the infrared spectral region. Unlike both imaging and non-imaging traditional Fourier-transform spectrometers, the E-O IFTS does not contain any moving parts. Elimination of the moving parts and the associated actuator mechanisms and supporting structures would increase reliability while enabling reductions in size and mass, relative to traditional Fourier-transform spectrometers that offer equivalent capabilities. Elimination of moving parts would also eliminate the vibrations caused by the motions of those parts. Figure 1 schematically depicts a traditional Fourier-transform spectrometer, wherein a critical time delay is varied by translating one the mirrors of a Michelson interferometer. The time-dependent optical output is a periodic representation of the input spectrum. Data characterizing the input spectrum are generated through fast-Fourier-transform (FFT) post-processing of the output in conjunction with the varying time delay.

Optical asymmetric image encryption using gyrator wavelet transform

NASA Astrophysics Data System (ADS)

Mehra, Isha; Nishchal, Naveen K.

2015-11-01

In this paper, we propose a new optical information processing tool termed as gyrator wavelet transform to secure a fully phase image, based on amplitude- and phase-truncation approach. The gyrator wavelet transform constitutes four basic parameters; gyrator transform order, type and level of mother wavelet, and position of different frequency bands. These parameters are used as encryption keys in addition to the random phase codes to the optical cryptosystem. This tool has also been applied for simultaneous compression and encryption of an image. The system's performance and its sensitivity to the encryption parameters, such as, gyrator transform order, and robustness has also been analyzed. It is expected that this tool will not only update current optical security systems, but may also shed some light on future developments. The computer simulation results demonstrate the abilities of the gyrator wavelet transform as an effective tool, which can be used in various optical information processing applications, including image encryption, and image compression. Also this tool can be applied for securing the color image, multispectral, and three-dimensional images.

Learning to represent spatial transformations with factored higher-order Boltzmann machines.

PubMed

Memisevic, Roland; Hinton, Geoffrey E

2010-06-01

To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicative interactions that use the intensity of a pixel in the first image as a multiplicative gain on a learned, symmetric weight between a pixel in the second image and a hidden unit. This creates cubically many parameters, which form a three-dimensional interaction tensor. We describe a low-rank approximation to this interaction tensor that uses a sum of factors, each of which is a three-way outer product. This approximation allows efficient learning of transformations between larger image patches. Since each factor can be viewed as an image filter, the model as a whole learns optimal filter pairs for efficiently representing transformations. We demonstrate the learning of optimal filter pairs from various synthetic and real image sequences. We also show how learning about image transformations allows the model to perform a simple visual analogy task, and we show how a completely unsupervised network trained on transformations perceives multiple motions of transparent dot patterns in the same way as humans.

A laboratory demonstration of high-resolution hard X-ray and gamma-ray imaging using Fourier-transform techniques

NASA Technical Reports Server (NTRS)

Palmer, David; Prince, Thomas A.

1987-01-01

A laboratory imaging system has been developed to study the use of Fourier-transform techniques in high-resolution hard X-ray and gamma-ray imaging, with particular emphasis on possible applications to high-energy astronomy. Considerations for the design of a Fourier-transform imager and the instrumentation used in the laboratory studies is described. Several analysis methods for image reconstruction are discussed including the CLEAN algorithm and maximum entropy methods. Images obtained using these methods are presented.

Optical Double Image Hiding in the Fractional Hartley Transform Using Structured Phase Filter and Arnold Transform

NASA Astrophysics Data System (ADS)

Yadav, Poonam Lata; Singh, Hukum

2018-06-01

To maintain the security of the image encryption and to protect the image from intruders, a new asymmetric cryptosystem based on fractional Hartley Transform (FrHT) and the Arnold transform (AT) is proposed. AT is a method of image cropping and edging in which pixels of the image are reorganized. In this cryptosystem we have used AT so as to extent the information content of the two original images onto the encrypted images so as to increase the safety of the encoded images. We have even used Structured Phase Mask (SPM) and Hybrid Mask (HM) as the encryption keys. The original image is first multiplied with the SPM and HM and then transformed with direct and inverse fractional Hartley transform so as to obtain the encrypted image. The fractional orders of the FrHT and the parameters of the AT correspond to the keys of encryption and decryption methods. If both the keys are correctly used only then the original image would be retrieved. Recommended method helps in strengthening the safety of DRPE by growing the key space and the number of parameters and the method is robust against various attacks. By using MATLAB 8.3.0.52 (R2014a) we calculate the strength of the recommended cryptosystem. A set of simulated results shows the power of the proposed asymmetric cryptosystem.

Sparsity prediction and application to a new steganographic technique

NASA Astrophysics Data System (ADS)

Phillips, David; Noonan, Joseph

2004-10-01

Steganography is a technique of embedding information in innocuous data such that only the innocent data is visible. The wavelet transform lends itself to image steganography because it generates a large number of coefficients representing the information in the image. Altering a small set of these coefficients allows embedding of information (payload) into an image (cover) without noticeably altering the original image. We propose a novel, dual-wavelet steganographic technique, using transforms selected such that the transform of the cover image has low sparsity, while the payload transform has high sparsity. Maximizing the sparsity of the payload transform reduces the amount of information embedded in the cover, and minimizing the sparsity of the cover increases the locations that can be altered without significantly altering the image. Making this system effective on any given image pair requires a metric to indicate the best (maximum sparsity) and worst (minimum sparsity) wavelet transforms to use. This paper develops the first stage of this metric, which can predict, averaged across many wavelet families, which of two images will have a higher sparsity. A prototype implementation of the dual-wavelet system as a proof of concept is also developed.

Minimizing bias in biomass allometry: Model selection and log transformation of data

Treesearch

Joseph Mascaro; undefined undefined; Flint Hughes; Amanda Uowolo; Stefan A. Schnitzer

2011-01-01

Nonlinear regression is increasingly used to develop allometric equations for forest biomass estimation (i.e., as opposed to the raditional approach of log-transformation followed by linear regression). Most statistical software packages, however, assume additive errors by default, violating a key assumption of allometric theory and possibly producing spurious models....

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.

1978-01-01

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Forested land cover classification on the Cumberland Plateau, Jackson County, Alabama: a comparison of Landsat ETM+ and SPOT5 images

Treesearch

Yong Wang; Shanta Parajuli; Callie Schweitzer; Glendon Smalley; Dawn Lemke; Wubishet Tadesse; Xiongwen Chen

2010-01-01

Forest cover classifications focus on the overall growth form (physiognomy) of the community, dominant vegetation, and species composition of the existing forest. Accurately classifying the forest cover type is important for forest inventory and silviculture. We compared classification accuracy based on Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and Satellite...

Parameterized approximation of lacunarity functions derived from airborne laser scanning point clouds of forested areas

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Varga, Katalin; Heilmeier, Hermann

2017-04-01

Lacunarity, a measure of the spatial distribution of the empty space is found to be a useful descriptive quantity of the forest structure. Its calculation, based on laser-scanned point clouds, results in a four-dimensional data set. The evaluation of results needs sophisticated tools and visualization techniques. To simplify the evaluation, it is straightforward to use approximation functions fitted to the results. The lacunarity function L(r), being a measure of scale-independent structural properties, has a power-law character. Previous studies showed that log(log(L(r))) transformation is suitable for analysis of spatial patterns. Accordingly, transformed lacunarity functions can be approximated by appropriate functions either in the original or in the transformed domain. As input data we have used a number of laser-scanned point clouds of various forests. The lacunarity distribution has been calculated along a regular horizontal grid at various (relative) elevations. The lacunarity data cube then has been logarithm-transformed and the resulting values became the input of parameter estimation at each point (point of interest, POI). This way at each POI a parameter set is generated that is suitable for spatial analysis. The expectation is that the horizontal variation and vertical layering of the vegetation can be characterized by this procedure. The results show that the transformed L(r) functions can be typically approximated by exponentials individually, and the residual values remain low in most cases. However, (1) in most cases the residuals may vary considerably, and (2) neighbouring POIs often give rather differing estimates both in horizontal and in vertical directions, of them the vertical variation seems to be more characteristic. In the vertical sense, the distribution of estimates shows abrupt changes at places, presumably related to the vertical structure of the forest. In low relief areas horizontal similarity is more typical, in higher relief areas horizontal similarity fades out in short distances. Some of the input data have been acquired in the framework of the ChangeHabitats2 project financed by the European Union. BS contributed as an Alexander von Humboldt Research Fellow.

Climate-induced forest dieback: An escalating global phenomenon?

USGS Publications Warehouse

Allen, Craig D.

2009-01-01

Forests, which today cover 30 percent of the world’s land surface (FAO, 2006), are being rapidly and directly transformed in many areas by the impacts of expanding human populations and economies. Less evident are the pervasive effects of ongoing climatic changes on the condition and status of forests around the world. Recent examples of drought and heat-related forest stress and dieback (defined here as tree mortality noticeably above usual mortality levels) are being documented from all forested continents, making it possible to begin to see global patterns. This article introduces these patterns and considers the possibility that many forests and woodlands today are at increasing risk of climate-induced dieback. A more comprehensive article (Allen et al., 2009) addresses this topic in considerably greater detail. While climate events can damage forests in many ways ranging from ice storms to tornadoes and hurricanes, the emphasis here is on climatic water stress, driven by drought and warm temperatures.

Performance Evaluation of Frequency Transform Based Block Classification of Compound Image Segmentation Techniques

NASA Astrophysics Data System (ADS)

Selwyn, Ebenezer Juliet; Florinabel, D. Jemi

2018-04-01

Compound image segmentation plays a vital role in the compression of computer screen images. Computer screen images are images which are mixed with textual, graphical, or pictorial contents. In this paper, we present a comparison of two transform based block classification of compound images based on metrics like speed of classification, precision and recall rate. Block based classification approaches normally divide the compound images into fixed size blocks of non-overlapping in nature. Then frequency transform like Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are applied over each block. Mean and standard deviation are computed for each 8 × 8 block and are used as features set to classify the compound images into text/graphics and picture/background block. The classification accuracy of block classification based segmentation techniques are measured by evaluation metrics like precision and recall rate. Compound images of smooth background and complex background images containing text of varying size, colour and orientation are considered for testing. Experimental evidence shows that the DWT based segmentation provides significant improvement in recall rate and precision rate approximately 2.3% than DCT based segmentation with an increase in block classification time for both smooth and complex background images.

False-color L-band image of Manaus region of Brazil

NASA Technical Reports Server (NTRS)

1994-01-01

This false-color L-band image of the Manaus region of Brazil was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperature Radar (SIR-C/X-SAR) flying on the Space Shuttle Endeavour on its 46th orbit. The area shown is approximately 8 kilometers by 40 kilometers (5 by 25 miles). At the top of the image are the Solimoes and Rio Negro River. The image is centered at about 3 degrees south latitude, and 61 degrees west longitude. Blue areas show low returns at VV poloarization; hence the bright blue colors of the smooth river surfaces. Green areas in the image are heavily forested, while blue areas are either cleared forest or open water. The yellow and red areas are flooded forest. Between Rio Solimoes and Rio Negro, a road can be seen running from some cleared areas (visible as blue rectangles north of Rio Solimoes) north toward a tributary or Rio Negro. The Jet Propulsion Laboratory alternative photo number is P-43895.

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.

Hyperspectral Imaging of Forest Resources: The Malaysian Experience

NASA Astrophysics Data System (ADS)

Mohd Hasmadi, I.; Kamaruzaman, J.

2008-08-01

Remote sensing using satellite and aircraft images are well established technology. Remote sensing application of hyperspectral imaging, however, is relatively new to Malaysian forestry. Through a wide range of wavelengths hyperspectral data are precisely capable to capture narrow bands of spectra. Airborne sensors typically offer greatly enhanced spatial and spectral resolution over their satellite counterparts, and able to control experimental design closely during image acquisition. The first study using hyperspectral imaging for forest inventory in Malaysia were conducted by Professor Hj. Kamaruzaman from the Faculty of Forestry, Universiti Putra Malaysia in 2002 using the AISA sensor manufactured by Specim Ltd, Finland. The main objective has been to develop methods that are directly suited for practical tropical forestry application at the high level of accuracy. Forest inventory and tree classification including development of single spectral signatures have been the most important interest at the current practices. Experiences from the studies showed that retrieval of timber volume and tree discrimination using this system is well and some or rather is better than other remote sensing methods. This article reviews the research and application of airborne hyperspectral remote sensing for forest survey and assessment in Malaysia.

Quantization Distortion in Block Transform-Compressed Data

NASA Technical Reports Server (NTRS)

Boden, A. F.

1995-01-01

The popular JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into block that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. A generic block transform model is introduced.

Soil nitrogen transformation responses to seasonal precipitation changes are regulated by changes in functional microbial abundance in a subtropical forest

NASA Astrophysics Data System (ADS)

Chen, Jie; Xiao, Guoliang; Kuzyakov, Yakov; Jenerette, G. Darrel; Ma, Ying; Liu, Wei; Wang, Zhengfeng; Shen, Weijun

2017-05-01

The frequency of dry-season droughts and wet-season storms has been predicted to increase in subtropical areas in the coming decades. Since subtropical forest soils are significant sources of N2O and NO3-, it is important to understand the features and determinants of N transformation responses to the predicted precipitation changes. A precipitation manipulation field experiment was conducted in a subtropical forest to reduce dry-season precipitation and increase wet-season precipitation, with annual precipitation unchanged. Net N mineralization, net nitrification, N2O emission, nitrifying (bacterial and archaeal amoA) and denitrifying (nirK, nirS and nosZ) gene abundance, microbial biomass carbon (MBC), extractable organic carbon (EOC), NO3-, NH4+ and soil water content (SWC) were monitored to characterize and explain soil N transformation responses. Dry-season precipitation reduction decreased net nitrification and N mineralization rates by 13-20 %, while wet-season precipitation addition increased both rates by 50 %. More than 20 % of the total variation of net nitrification and N mineralization could be explained by microbial abundance and SWC. Notably, archaeal amoA abundance showed the strongest correlation with net N transformation rates (r ≥ 0.35), suggesting the critical role of archaeal amoA abundance in determining N transformations. Increased net nitrification in the wet season, together with large precipitation events, caused substantial NO3- losses via leaching. However, N2O emission decreased moderately in both dry and wet seasons due to changes in nosZ gene abundance, MBC, net nitrification and SWC (decreased by 10-21 %). We conclude that reducing dry-season precipitation and increasing wet-season precipitation affect soil N transformations through altering functional microbial abundance and MBC, which are further affected by changes in EOC and NH4+ availabilities.

Current state and projection of the probable original vegetation of the São Carlos region of São Paulo State, Brazil.

PubMed

Soares, J J; da Silva, D W; Lima, M I

2003-08-01

A map of the native vegetation remaining in São Carlos County was built based on aerial images, satellite images, and field observations, and a projection of the probable original vegetation was made by checking it against soil and relief surveys. The existing vegetation is very fragmented and improverished, consisting predominantly of cerrados (savanna vegetation of various physiognomies), semideciduous and riparian forest, and regeneration areas. Araucaria angustifolia (Bertol.) Kuntze, found in patches inside the semideciduous forest beginning at a minimum altitude of 850 m, has practically disappeared. By evaluating areas on the map for different forms of vegetation, we obtained the following results for original coverage: 27% cerrado (sparsely arboreal and short-shrub savanna, and wet meadows); 16% cerradão (arboreal savanna); 55% semideciduous and riparian forests; and 2% forest with A. angustifolia. There are now 2% cerrados; 2.5% cerradão; 1% semideciduous forest and riparian forests; 1.5% regeneration areas; and 0% forest with A. angustifolia.

On the V-Line Radon Transform and Its Imaging Applications

PubMed Central

Morvidone, M.; Nguyen, M. K.; Truong, T. T.; Zaidi, H.

2010-01-01

Radon transforms defined on smooth curves are well known and extensively studied in the literature. In this paper, we consider a Radon transform defined on a discontinuous curve formed by a pair of half-lines forming the vertical letter V. If the classical two-dimensional Radon transform has served as a work horse for tomographic transmission and/or emission imaging, we show that this V-line Radon transform is the backbone of scattered radiation imaging in two dimensions. We establish its analytic inverse formula as well as a corresponding filtered back projection reconstruction procedure. These theoretical results allow the reconstruction of two-dimensional images from Compton scattered radiation collected on a one-dimensional collimated camera. We illustrate the working principles of this imaging modality by presenting numerical simulation results. PMID:20706545

Retina-like sensor image coordinates transformation and display

NASA Astrophysics Data System (ADS)

Cao, Fengmei; Cao, Nan; Bai, Tingzhu; Song, Shengyu

2015-03-01

For a new kind of retina-like senor camera, the image acquisition, coordinates transformation and interpolation need to be realized. Both of the coordinates transformation and interpolation are computed in polar coordinate due to the sensor's particular pixels distribution. The image interpolation is based on sub-pixel interpolation and its relative weights are got in polar coordinates. The hardware platform is composed of retina-like senor camera, image grabber and PC. Combined the MIL and OpenCV library, the software program is composed in VC++ on VS 2010. Experience results show that the system can realizes the real-time image acquisition, coordinate transformation and interpolation.

Environmental Fate and Aquatic Impacts of Hexzinone Applied at a High Rate for Planting Site Preparation

Treesearch

Jerry L. Michael

1998-01-01

Most environmental fate and impact concerns associated with the use of forest herbicides are related to offsite movement during and after application. The environmental fate and ecosystem impacts of forest herbicides are governed by movement and transformation in the atmosphere, above ground vegetation, soil surface, soil rooting zone, surface water, and groundwater....

Soil nitrogen mineralization and enzymatic activities in fire and fire surrogate treatments in California

Treesearch

J. R. Miesel; R. E. J. Boerner; C. N. Skinner

2011-01-01

Forest thinning and prescribed fire are management strategies used to reduce hazardous fuel loads and catastrophic wildfires in western mixed-conifer forests. We evaluated effects of thinning (Thin) and prescribed fire (Burn), alone and in combination (Thin+Burn), on N transformations and microbial enzyme activities relative to an untreated control (Control) at 1 and 3...

Improvement and extension of a radar forest backscattering model

NASA Technical Reports Server (NTRS)

Simonett, David S.; Wang, Yong

1989-01-01

Radar modeling of mangal forest stands, in the Sundarbans area of Southern Bangladesh, was developed. The modeling employs radar system parameters such as wavelength, polarization, and incidence angle, with forest data on tree height, spacing, biomass, species combinations, and water content (including slightly conductive water) both in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, five model components are proposed, which are required to explain the contributions of various forest species combinations in the attenuation and scattering of mangal vegetated nonflooded or flooded surfaces. Statistical data of simulated images (HH components only) were compared with those of SIR-B images both to refine the modeling procedures and to appropriately characterize the model output. The possibility of delineation of flooded or non-flooded boundaries is discussed.

ERTS data user investigation to develop a multistage forest sampling inventory system

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. W. (Principal Investigator); Wert, S. L.

1973-01-01

The author has identified the following significant results. A system to provide precision annotation of predetermined forest inventory sampling units on the ERTS-1 MSS images was developed. In addition, an annotation system for high altitude U2 photographs was completed. MSS bulk image accuracy is good enough to allow the use of one square mile sampling units. IMANCO image analyzer interpretation work for small scale images demonstrated the need for much additional analyses. Continuing image interpretation work for the next reporting period is concentrated on manual image interpretation work as well as digital interpretation system development using the computer compatible tapes.

Space Radar Image of Baikal Lake, Russia

NASA Image and Video Library

1999-05-01

This is an X-band black-and-white image of the forests east of the Baikal Forest in the Jablonowy Mountains of Russia. The image is centered at 52.5 degrees north latitude and 116 degrees east longitude near the mining town of Bukatschatscha. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on October 4, 1994, during the second flight of the spaceborne radar. This area is part of an international research project known as the Taiga Aerospace Investigation using Geographic Information System Applications. http://photojournal.jpl.nasa.gov/catalog/PIA01754

Floating Forests: Validation of a Citizen Science Effort to Answer Global Ecological Questions

NASA Astrophysics Data System (ADS)

Rosenthal, I.; Byrnes, J.; Cavanaugh, K. C.; Haupt, A. J.; Trouille, L.; Bell, T. W.; Rassweiler, A.; Pérez-Matus, A.; Assis, J.

2017-12-01

Researchers undertaking long term, large-scale ecological analyses face significant challenges for data collection and processing. Crowdsourcing via citizen science can provide an efficient method for analyzing large data sets. However, many scientists have raised questions about the quality of data collected by citizen scientists. Here we use Floating-Forests (http://floatingforests.org), a citizen science platform for creating a global time series of giant kelp abundance, to show that ensemble classifications of satellite data can ensure data quality. Citizen scientists view satellite images of coastlines and classify kelp forests by tracing all visible patches of kelp. Each image is classified by fifteen citizen scientists before being retired. To validate citizen science results, all fifteen classifications are converted to a raster and overlaid on a calibration dataset generated from previous studies. Results show that ensemble classifications from citizen scientists are consistently accurate when compared to calibration data. Given that all source images were acquired by Landsat satellites, we expect this consistency to hold across all regions. At present, we have over 6000 web-based citizen scientists' classifications of almost 2.5 million images of kelp forests in California and Tasmania. These results are not only useful for remote sensing of kelp forests, but also for a wide array of applications that combine citizen science with remote sensing.

United States forest disturbance trends observed with landsat time series

Treesearch

Jeffrey G. Masek; Samuel N. Goward; Robert E. Kennedy; Warren B. Cohen; Gretchen G. Moisen; Karen Schleweiss; Chengquan Huang

2013-01-01

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest...

Use of Aerial Hyperspectral Imaging For Monitoring Forest Health

Treesearch

Milton O. Smith; Nolan J. Hess; Stephen Gulick; Lori G. Eckhardt; Roger D. Menard

2004-01-01

This project evaluates the effectiveness of aerial hyperspectral digital imagery in the assessment of forest health of loblolly stands in central Alabama. The imagery covers 50 square miles, in Bibb and Hale Counties, south of Tuscaloosa, AL, which includes intensive managed forest industry sites and National Forest lands with multiple use objectives. Loblolly stands...

Analysis of forest and forest clearings in Amazonia with Landsat and Shuttle Imaging Radar-A data

NASA Technical Reports Server (NTRS)

Stone, Thomas A.; Woodwell, George M.

1987-01-01

Landsat and Shuttle Imaging Radar-A L band (23.5 cm wavelength) data from 1981 were used to analyze areas of intact tropical forest and areas recently cleared from forest for agriculture and pasture in Mato Grosso, Brazil. Portions of SIR-A Data Takes #24C and #31 film were digitized using a microdensitometer. Landsat MSS data of July 1981 were also examined. The digital values from SIR-A DT 31 were compared with the normalized difference vegetation index values (NDVI) from the Landsat data for the same sites. Contrary to expectations some cleared areas had brighter radar responses than surrounding forest. The explanation seems to be that a recently cleared forest (cut and burned during the dry season) is texturally very rough as the exposed standing and fallen boles and woody litter may function as effective corner or dihedral reflectors. Combining radar data with NDVI data may help to assess the relative age of forest clearings and determine differences in both woody and green leaf biomass of primary and secondary tropical forests.

Color image encryption based on color blend and chaos permutation in the reality-preserving multiple-parameter fractional Fourier transform domain

NASA Astrophysics Data System (ADS)

Lang, Jun

2015-03-01

In this paper, we propose a novel color image encryption method by using Color Blend (CB) and Chaos Permutation (CP) operations in the reality-preserving multiple-parameter fractional Fourier transform (RPMPFRFT) domain. The original color image is first exchanged and mixed randomly from the standard red-green-blue (RGB) color space to R‧G‧B‧ color space by rotating the color cube with a random angle matrix. Then RPMPFRFT is employed for changing the pixel values of color image, three components of the scrambled RGB color space are converted by RPMPFRFT with three different transform pairs, respectively. Comparing to the complex output transform, the RPMPFRFT transform ensures that the output is real which can save storage space of image and convenient for transmission in practical applications. To further enhance the security of the encryption system, the output of the former steps is scrambled by juxtaposition of sections of the image in the reality-preserving multiple-parameter fractional Fourier domains and the alignment of sections is determined by two coupled chaotic logistic maps. The parameters in the Color Blend, Chaos Permutation and the RPMPFRFT transform are regarded as the key in the encryption algorithm. The proposed color image encryption can also be applied to encrypt three gray images by transforming the gray images into three RGB color components of a specially constructed color image. Numerical simulations are performed to demonstrate that the proposed algorithm is feasible, secure, sensitive to keys and robust to noise attack and data loss.

Infrared and visible image fusion with spectral graph wavelet transform.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Zong, Jing-guo

2015-09-01

Infrared and visible image fusion technique is a popular topic in image analysis because it can integrate complementary information and obtain reliable and accurate description of scenes. Multiscale transform theory as a signal representation method is widely used in image fusion. In this paper, a novel infrared and visible image fusion method is proposed based on spectral graph wavelet transform (SGWT) and bilateral filter. The main novelty of this study is that SGWT is used for image fusion. On the one hand, source images are decomposed by SGWT in its transform domain. The proposed approach not only effectively preserves the details of different source images, but also excellently represents the irregular areas of the source images. On the other hand, a novel weighted average method based on bilateral filter is proposed to fuse low- and high-frequency subbands by taking advantage of spatial consistency of natural images. Experimental results demonstrate that the proposed method outperforms seven recently proposed image fusion methods in terms of both visual effect and objective evaluation metrics.

Long-term litter decomposition controlled by manganese redox cycling

PubMed Central

Keiluweit, Marco; Nico, Peter; Harmon, Mark E.; Mao, Jingdong; Pett-Ridge, Jennifer; Kleber, Markus

2015-01-01

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of litter was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn2+ provided by fresh plant litter to produce oxidative Mn3+ species at sites of active decay, with Mn eventually accumulating as insoluble Mn3+/4+ oxides. Formation of reactive Mn3+ species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn3+-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn3+ species in the litter layer. This observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant–soil system may have a profound impact on litter decomposition rates. PMID:26372954

Long-term litter decomposition controlled by manganese redox cycling.

PubMed

Keiluweit, Marco; Nico, Peter; Harmon, Mark E; Mao, Jingdong; Pett-Ridge, Jennifer; Kleber, Markus

2015-09-22

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of litter was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn(2+) provided by fresh plant litter to produce oxidative Mn(3+) species at sites of active decay, with Mn eventually accumulating as insoluble Mn(3+/4+) oxides. Formation of reactive Mn(3+) species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn(3+)-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn(3+) species in the litter layer. This observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant-soil system may have a profound impact on litter decomposition rates.

Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA

Treesearch

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

2008-01-01

We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867...

Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

Treesearch

Michael Palace; Michael Keller; Gregory P. Asner; Stephen Hagen; Bobby Braswell

2008-01-01

We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75◦ S, 48.37◦ W) in the eastern Amazon, and then compared with forest...

Staring 2-D hadamard transform spectral imager

DOEpatents

Gentry, Stephen M [Albuquerque, NM; Wehlburg, Christine M [Albuquerque, NM; Wehlburg, Joseph C [Albuquerque, NM; Smith, Mark W [Albuquerque, NM; Smith, Jody L [Albuquerque, NM

2006-02-07

A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.

Nitrogen cycling in canopy soils of tropical montane forests responds rapidly to indirect N and P fertilization.

PubMed

Matson, Amanda L; Corre, Marife D; Veldkamp, Edzo

2014-12-01

Although the canopy can play an important role in forest nutrient cycles, canopy-based processes are often overlooked in studies on nutrient deposition. In areas of nitrogen (N) and phosphorus (P) deposition, canopy soils may retain a significant proportion of atmospheric inputs, and also receive indirect enrichment through root uptake followed by throughfall or recycling of plant litter in the canopy. We measured net and gross rates of N cycling in canopy soils of tropical montane forests along an elevation gradient and assessed indirect effects of elevated nutrient inputs to the forest floor. Net N cycling rates were measured using the buried bag method. Gross N cycling rates were measured using (15) N pool dilution techniques. Measurements took place in the field, in the wet and dry season, using intact cores of canopy soil from three elevations (1000, 2000 and 3000 m). The forest floor had been fertilized biannually with moderate amounts of N and P for 4 years; treatments included control, N, P, and N + P. In control plots, gross rates of NH4 (+) transformations decreased with increasing elevation; gross rates of NO3 (-) transformations did not exhibit a clear elevation trend, but were significantly affected by season. Nutrient-addition effects were different at each elevation, but combined N + P generally increased N cycling rates at all elevations. Results showed that canopy soils could be a significant N source for epiphytes as well as contributing up to 23% of total (canopy + forest floor) mineral N production in our forests. In contrast to theories that canopy soils are decoupled from nutrient cycling in forest floor soil, N cycling in our canopy soils was sensitive to slight changes in forest floor nutrient availability. Long-term atmospheric N and P deposition may lead to increased N cycling, but also increased mineral N losses from the canopy soil system. © 2014 John Wiley & Sons Ltd.

Classification of crops across heterogeneous agricultural landscape in Kenya using AisaEAGLE imaging spectroscopy data

NASA Astrophysics Data System (ADS)

Piiroinen, Rami; Heiskanen, Janne; Mõttus, Matti; Pellikka, Petri

2015-07-01

Land use practices are changing at a fast pace in the tropics. In sub-Saharan Africa forests, woodlands and bushlands are being transformed for agricultural use to produce food for the rapidly growing population. The objective of this study was to assess the prospects of mapping the common agricultural crops in highly heterogeneous study area in south-eastern Kenya using high spatial and spectral resolution AisaEAGLE imaging spectroscopy data. Minimum noise fraction transformation was used to pack the coherent information in smaller set of bands and the data was classified with support vector machine (SVM) algorithm. A total of 35 plant species were mapped in the field and seven most dominant ones were used as classification targets. Five of the targets were agricultural crops. The overall accuracy (OA) for the classification was 90.8%. To assess the possibility of excluding the remaining 28 plant species from the classification results, 10 different probability thresholds (PT) were tried with SVM. The impact of PT was assessed with validation polygons of all 35 mapped plant species. The results showed that while PT was increased more pixels were excluded from non-target polygons than from the polygons of the seven classification targets. This increased the OA and reduced salt-and-pepper effects in the classification results. Very high spatial resolution imagery and pixel-based classification approach worked well with small targets such as maize while there was mixing of classes on the sides of the tree crowns.

Coupling of microbial nitrogen transformations and climate in sclerophyll forest soils from the Mediterranean Region of central Chile.

PubMed

Pérez, Cecilia A; Armesto, Juan J

2018-06-01

The Mediterranean region of central Chile is experiencing extensive "mega-droughts" with detrimental effects for the environment and economy of the region. In the northern hemisphere, nitrogen (N) limitation of Mediterranean ecosystems has been explained by the decoupling between N inputs and plant uptake during the dormant season. In central Chile, soils have often been considered N-rich in comparison to other Mediterranean ecosystems of the world, yet the impacts of expected intensification of seasonal drought remain unknown. In this work, we seek to disentangle patterns of microbial N transformations and their seasonal coupling with climate in the Chilean sclerophyll forest-type. We aim to assess how water limitation affects microbial N transformations, thus addressing the impact of ongoing regional climate trends on soil N status. We studied four stands of the sclerophyll forest-type in Chile. Field measurements in surface soils showed a 67% decline of free-living diazotrophic activity (DA) and 59% decrease of net N mineralization rates during the summer rainless and dormant season, accompanied by a stimulation of in-situ denitrification rates to values 70% higher than in wetter winter. Higher rates of both free-living DA and net N mineralization found during spring, provided evidence for strong coupling of these two processes during the growing season. Overall, the experimental addition of water in the field to litter samples almost doubled DA but had no effect on denitrification rates. We conclude that coupling of microbial mediated soil N transformations during the wetter growing season explains the N enrichment of sclerophyll forest soils. Expected increases in the length and intensity of the dry period, according to climate change models, reflected in the current mega-droughts may drastically reduce biological N fixation and net N mineralization, increasing at the same time denitrification rates, thereby potentially reducing long-term soil N capital. Copyright © 2017 Elsevier B.V. All rights reserved.

Importance of riparian remnants for frog species diversity in a highly fragmented rainforest.

PubMed

Rodríguez-Mendoza, Clara; Pineda, Eduardo

2010-12-23

Tropical forests undergo continuous transformation to other land uses, resulting in landscapes typified by forest fragments surrounded by anthropogenic habitats. Small forest fragments, specifically strip-shaped remnants flanking streams (referred to as riparian remnants), can be particularly important for the maintenance and conservation of biodiversity within highly fragmented forests. We compared frog species diversity between riparian remnants, other forest fragments and cattle pastures in a tropical landscape in Los Tuxtlas, Mexico. We found similar species richness in the three habitats studied and a similar assemblage structure between riparian remnants and forest fragments, although species composition differed by 50 per cent. Frog abundance was halved in riparian remnants compared with forest fragments, but was twice that found in pastures. Our results suggest that riparian remnants play an important role in maintaining a portion of frog species diversity in a highly fragmented forest, particularly during environmentally stressful (hot and dry) periods. In this regard, however, the role of riparian remnants is complementary, rather than substitutive, with respect to the function of other forest fragments within the fragmented forest.

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

PubMed

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Nitrogen transformations following tropical forest felling and burning on a volcanic soil

NASA Technical Reports Server (NTRS)

Matson, Pamela A.; Vitousek, Peter M.; Ewel, John J.; Mazzarino, Maria Julia; Robertson, G. Philip

1987-01-01

Nitrogen transformations and loss were measured following forest clearing in a relatively fertile tropical forest site. Nitrogen mineralization, nitrification, and amounts of ammonium and nitrate increased substantially in surface soils during the 6 mo following burning, then returned to background levels. The nitrogen content of microbial biomass declined to half its original value 6 mo after clearing and remained low in the cleared sites. Plant uptake of nitrogen was substantial on cleared plots (50 g/sq m), but it accounted for only 18 percent of N-15 label added to field plots. MIcrobial immobilization of N-15 was small relative to that in a cleared temperate site, and measurements of denitrification potentials suggested that relatively little mineralized nitrogen was lost to the atmosphere. Substantial amounts of nitrogen (40-70 g/sq m) were retained as exchangeably bound nitrate deep in the soils of a cleared plot on which revegetation was prevented; this process accounted for 12 percent of the N-15 label added to field plots.

Characteristics of Forests in Western Sayani Mountains, Siberia from SAR Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Sun, Guoqing; Kharuk, V. I.; Kovacs, Katalin

1998-01-01

This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and

Space Radar Image of Prince Albert, Canada, seasonal

NASA Image and Video Library

1999-05-01

This is a comparison of images over Prince Albert, produced by NASA Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on its 20th orbit on April 10, 1994. The area is centered at 53.91 degrees north latitude and 104.69 degrees west longitude and is located 40 kilometers (25 miles) north and 30 kilometers (18.5 miles) east of the town of Prince Albert in the Saskatchewan province of Canada. The image covers the area east of Candle Lake, between the gravel highway of 120 and west of highway 106. The area imaged is near the southern limit of the boreal forest. The boreal forest of North America is a continuous vegetation belt at high latitudes stretching across the continent from the Atlantic shoreline of central Labrador and then westward across Canada to the interior mountains and central coastal plains of Alaska. The forest is also part of a larger northern hemisphere circumpolar boreal forest belt. Coniferous trees dominate the entire forest but deciduous trees are also present. During the month of April, the forest experiences seasonal changes from a frozen condition to a thawed condition. The trees are completely frozen over the winter season and the forest floor is covered by snow. As the average temperature rises in the spring, the trees are thawed and the snow melts. This transition has an impact on the rate of moisture evaporation and release of carbon dioxide into the atmosphere. In late September and early October, the boreal forest experiences a relatively different seasonal change. At this time, the leaves on deciduous trees start changing color and dropping off. The soil and trees are quite often moist due to frequent rainfall and cloud cover. The evaporation of moisture and carbon dioxide into the atmosphere also diminishes at this time. SIR-C/X-SAR is sensitive to the moisture of soil and vegetation and can sense this freeze-thaw cycle and the summer-fall seasonal transition over forested areas in particular. Optical sensors, by contrast, are blind to these regions, which are perpetually obscured by thick cloud cover. These changes were detected by comparing the April and October color composite images of L-band data in red, C-band data in green and X-band (vertically received and transmitted) in blue. The changes in intensity of each color over lakes, various forest stands and clear cuts in the two images is striking. Lakes such as Lake Heiberg, Crabtree Lake and Williams Lake, in the right middle part of the image, are frozen in April (appearing in bright blue) and melted (appearing in black) in October. The higher intensity of blue over lakes in April is due to low penetration of the X-band (vertically received and transmitted) and the radar's high sensitivity to surface features. Forest stands also exhibit major changes between the two images. The red areas in the October image are old jack pine canopies that cause higher return at L-band because of their moist condition in late summer compared to their partially frozen condition in April (in purple). Similarly, in the areas near the middle of the image, where black spruce and mixed aspen and jack pine trees dominate, the contrast between blue in October and red and green in April is an indication that the top of the canopy (needles and branches) were frozen in April and moist in October. The changes due to deforestation by logging companies or natural fires can also be detected by comparing the images. For example, the small blue area near the intersection of Harding Road and Highway 120 is the result of logging which occurred after the April data was acquired. The surface area of clear cut is approximately 4 hectares, which is calculated from the high-resolution capability of the radar images and verified by scientists participating in field work during the mission. http://photojournal.jpl.nasa.gov/catalog/PIA01732

Experimental image alignment system

NASA Technical Reports Server (NTRS)

Moyer, A. L.; Kowel, S. T.; Kornreich, P. G.

1980-01-01

A microcomputer-based instrument for image alignment with respect to a reference image is described which uses the DEFT sensor (Direct Electronic Fourier Transform) for image sensing and preprocessing. The instrument alignment algorithm which uses the two-dimensional Fourier transform as input is also described. It generates signals used to steer the stage carrying the test image into the correct orientation. This algorithm has computational advantages over algorithms which use image intensity data as input and is suitable for a microcomputer-based instrument since the two-dimensional Fourier transform is provided by the DEFT sensor.

EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.

2001-12-01

A wide variety of digital image compression transforms developed for still imaging and broadcast video transmission are unsuitable for Internet video applications due to insufficient compression ratio, poor reconstruction fidelity, or excessive computational requirements. Examples include hierarchical transforms that require all, or large portion of, a source image to reside in memory at one time, transforms that induce significant locking effect at operationally salient compression ratios, and algorithms that require large amounts of floating-point computation. The latter constraint holds especially for video compression by small mobile imaging devices for transmission to, and compression on, platforms such as palmtop computers or personal digital assistants (PDAs). As Internet video requirements for frame rate and resolution increase to produce more detailed, less discontinuous motion sequences, a new class of compression transforms will be needed, especially for small memory models and displays such as those found on PDAs. In this, the third series of papers, we discuss the EBLAST compression transform and its application to Internet communication. Leading transforms for compression of Internet video and still imagery are reviewed and analyzed, including GIF, JPEG, AWIC (wavelet-based), wavelet packets, and SPIHT, whose performance is compared with EBLAST. Performance analysis criteria include time and space complexity and quality of the decompressed image. The latter is determined by rate-distortion data obtained from a database of realistic test images. Discussion also includes issues such as robustness of the compressed format to channel noise. EBLAST has been shown to perform superiorly to JPEG and, unlike current wavelet compression transforms, supports fast implementation on embedded processors with small memory models.

Vessel segmentation in 4D arterial spin labeling magnetic resonance angiography images of the brain

NASA Astrophysics Data System (ADS)

Phellan, Renzo; Lindner, Thomas; Falcão, Alexandre X.; Forkert, Nils D.

2017-03-01

4D arterial spin labeling magnetic resonance angiography (4D ASL MRA) is a non-invasive and safe modality for cerebrovascular imaging procedures. It uses the patient's magnetically labeled blood as intrinsic contrast agent, so that no external contrast media is required. It provides important 3D structure and blood flow information but a sufficient cerebrovascular segmentation is important since it can help clinicians to analyze and diagnose vascular diseases faster, and with higher confidence as compared to simple visual rating of raw ASL MRA images. This work presents a new method for automatic cerebrovascular segmentation in 4D ASL MRA images of the brain. In this process images are denoised, corresponding image label/control image pairs of the 4D ASL MRA sequences are subtracted, and temporal intensity averaging is used to generate a static representation of the vascular system. After that, sets of vessel and background seeds are extracted and provided as input for the image foresting transform algorithm to segment the vascular system. Four 4D ASL MRA datasets of the brain arteries of healthy subjects and corresponding time-of-flight (TOF) MRA images were available for this preliminary study. For evaluation of the segmentation results of the proposed method, the cerebrovascular system was automatically segmented in the high-resolution TOF MRA images using a validated algorithm and the segmentation results were registered to the 4D ASL datasets. Corresponding segmentation pairs were compared using the Dice similarity coefficient (DSC). On average, a DSC of 0.9025 was achieved, indicating that vessels can be extracted successfully from 4D ASL MRA datasets by the proposed segmentation method.

A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform

NASA Astrophysics Data System (ADS)

Chen, Bangqian; Xiao, Xiangming; Li, Xiangping; Pan, Lianghao; Doughty, Russell; Ma, Jun; Dong, Jinwei; Qin, Yuanwei; Zhao, Bin; Wu, Zhixiang; Sun, Rui; Lan, Guoyu; Xie, Guishui; Clinton, Nicholas; Giri, Chandra

2017-09-01

Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer's accuracy greater than 95% when validated with ground reference data. In 2015, China's mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China.

Visualization of bacterial flagella dynamics in a viscous shear flow

NASA Astrophysics Data System (ADS)

Ali, Jamel; Kim, Minjun

2016-11-01

We report on the dynamics of tethered bacterial flagella in an applied viscous shear flow and analyze their behavior using image processing. Flagellin proteins were repolymerized into flagellar filaments functionalized with biotin at their proximal end, and allowed to self-assemble within a micro channel coated with streptavidin. It was observed that all attached flagellar filaments aligned with the steady shear flow of various polymeric solutions. Furthermore it was observed that many of the filaments were stretched, and at elevated flow rates began to undergo polymorphic transformations, which were initiated at one end of the flagellum. When undergoing a change to a different helical form the flagellum was observed to transform to an oppositely handed helix, as to counteract the viscous torque imparted by the shear flow. It was also observed that some flagellar filaments did not undergo polymorphic transformations, but rotated about their helical axis. The rate of this rotation appears to be a function of the applied flow rate. These results expand on previous experimental work and aid in the development of a novel platform that harnesses the autonomic response of a 'forest' of bacterial flagella for engineering applications. This work was funded by NSF Grant CMMI-1000255, KEIT MOTIE Grant No. 10052980, and with Government support under and awarded by DoD, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a.

Forest Biomass Mapping from Stereo Imagery and Radar Data

NASA Astrophysics Data System (ADS)

Sun, G.; Ni, W.; Zhang, Z.

2013-12-01

Both InSAR and lidar data provide critical information on forest vertical structure, which are critical for regional mapping of biomass. However, the regional application of these data is limited by the availability and acquisition costs. Some researchers have demonstrated potentials of stereo imagery in the estimation of forest height. Most of these researches were conducted on aerial images or spaceborne images with very high resolutions (~0.5m). Space-born stereo imagers with global coverage such as ALOS/PRISM have coarser spatial resolutions (2-3m) to achieve wider swath. The features of stereo images are directly affected by resolutions and the approaches use by most of researchers need to be adjusted for stereo imagery with lower resolutions. This study concentrated on analyzing the features of point clouds synthesized from multi-view stereo imagery over forested areas. The small footprint lidar and lidar waveform data were used as references. The triplets of ALOS/PRISM data form three pairs (forward/nadir, backward/nadir and forward/backward) of stereo images. Each pair of the stereo images can be used to generate points (pixels) with 3D coordinates. By carefully co-register these points from three pairs of stereo images, a point cloud data was generated. The height of each point above ground surface was then calculated using DEM from National Elevation Dataset, USGS as the ground surface elevation. The height data were gridded into pixel of different sizes and the histograms of the points within a pixel were analyzed. The average height of the points within a pixel was used as the height of the pixel to generate a canopy height map. The results showed that the synergy of point clouds from different views were necessary, which increased the point density so the point cloud could detect the vertical structure of sparse and unclosed forests. The top layer of multi-layered forest could be captured but the dense forest prevented the stereo imagery to see through. The canopy height map exhibited spatial patterns of roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlation with RH50 of LVIS data at 30m pixel size with a gain of 1.04, bias of 4.3m and R2 of 0.74 (Fig. 1). The canopy height map from PRISM and dual-pol PALSAR data were used together to map biomass in our study area near Howland, Maine, and the results were evaluated using biomass map generated from LVIS waveform data independently. The results showed that adding CHM from PRISM significantly improved biomass accuracy and raised the biomass saturation level of L-band SAR data in forest biomass mapping.

A Shearlet-based algorithm for quantum noise removal in low-dose CT images

NASA Astrophysics Data System (ADS)

Zhang, Aguan; Jiang, Huiqin; Ma, Ling; Liu, Yumin; Yang, Xiaopeng

2016-03-01

Low-dose CT (LDCT) scanning is a potential way to reduce the radiation exposure of X-ray in the population. It is necessary to improve the quality of low-dose CT images. In this paper, we propose an effective algorithm for quantum noise removal in LDCT images using shearlet transform. Because the quantum noise can be simulated by Poisson process, we first transform the quantum noise by using anscombe variance stabilizing transform (VST), producing an approximately Gaussian noise with unitary variance. Second, the non-noise shearlet coefficients are obtained by adaptive hard-threshold processing in shearlet domain. Third, we reconstruct the de-noised image using the inverse shearlet transform. Finally, an anscombe inverse transform is applied to the de-noised image, which can produce the improved image. The main contribution is to combine the anscombe VST with the shearlet transform. By this way, edge coefficients and noise coefficients can be separated from high frequency sub-bands effectively. A number of experiments are performed over some LDCT images by using the proposed method. Both quantitative and visual results show that the proposed method can effectively reduce the quantum noise while enhancing the subtle details. It has certain value in clinical application.

Forest representation of vessels in cone-beam computed tomographic angiography.

PubMed

Chen, Zikuan; Ning, Ruola

2005-01-01

Cone-beam computed tomographic angiography (CBCTA) provides a fast three-dimensional (3D) vascular imaging modality, aiming at digitally representing the spatial vascular structure in an angiographic volume. Due to the finite coverage of cone-beam scan, as well as the volume cropping in volumetric image processing, an angiographic volume may fail to contain a whole vascular tree, but rather consist of a multitude of vessel segments or subtrees. As such, it is convenient to represent multitudinal components by a forest. The vessel tracking issue then becomes component characterization/identification in the forest. The forest representation brings several conveniences for vessel tracking: (1) to sort and count the vessels in an angiographic volume, for example, according to spatial occupancy and skeleton pathlength; (2) to single out a vessel and perform in situ 3D measurement and 3D visualization in the support space; (3) to delineate individual vessels from the original angiographic volume; and (4) to cull the forest by getting rid of non-vessels and small vessels. A 3D skeletonization is used to generate component skeletons. For tree construction from skeletons, we suggest a pathlength-based procedure, which lifts the restrictions of unit-width skeleton and root determination. We experimentally demonstrate the forest representation of a dog's carotid arteries in a CBCTA system. In principle, the forest representation is useful for managing vessels in both 2D angiographic images and 3D angiographic volumes.

Transformation-aware perceptual image metric

NASA Astrophysics Data System (ADS)

Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2016-09-01

Predicting human visual perception has several applications such as compression, rendering, editing, and retargeting. Current approaches, however, ignore the fact that the human visual system compensates for geometric transformations, e.g., we see that an image and a rotated copy are identical. Instead, they will report a large, false-positive difference. At the same time, if the transformations become too strong or too spatially incoherent, comparing two images gets increasingly difficult. Between these two extrema, we propose a system to quantify the effect of transformations, not only on the perception of image differences but also on saliency and motion parallax. To this end, we first fit local homographies to a given optical flow field, and then convert this field into a field of elementary transformations, such as translation, rotation, scaling, and perspective. We conduct a perceptual experiment quantifying the increase of difficulty when compensating for elementary transformations. Transformation entropy is proposed as a measure of complexity in a flow field. This representation is then used for applications, such as comparison of nonaligned images, where transformations cause threshold elevation, detection of salient transformations, and a model of perceived motion parallax. Applications of our approach are a perceptual level-of-detail for real-time rendering and viewpoint selection based on perceived motion parallax.

Using the global positioning system to map disturbance patterns of forest harvesting machinery

Treesearch

T.P. McDonald; E.A. Carter; S.E. Taylor

2002-01-01

Abstract: A method was presented to transform sampled machine positional data obtained from a global positioning system (GPS) receiver into a two-dimensional raster map of number of passes as a function of location. The effect of three sources of error in the transformation process were investigated: path sampling rate (receiver sampling frequency);...

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Hurricane impacts on a pair of coastal forested watersheds: implications of selective hurricane damage to forest structure and streamflow dynamics

NASA Astrophysics Data System (ADS)

Jayakaran, A. D.; Williams, T. M.; Ssegane, H.; Amatya, D. M.; Song, B.; Trettin, C. C.

2014-03-01

Hurricanes are infrequent but influential disruptors of ecosystem processes in the southeastern Atlantic and Gulf coasts. Every southeastern forested wetland has the potential to be struck by a tropical cyclone. We examined the impact of Hurricane Hugo on two paired coastal South Carolina watersheds in terms of streamflow and vegetation dynamics, both before and after the hurricane's passage in 1989. The study objectives were to quantify the magnitude and timing of changes including a reversal in relative streamflow difference between two paired watersheds, and to examine the selective impacts of a hurricane on the vegetative composition of the forest. We related these impacts to their potential contribution to change watershed hydrology through altered evapotranspiration processes. Using over 30 years of monthly rainfall and streamflow data we showed that there was a significant transformation in the hydrologic character of the two watersheds - a transformation that occurred soon after the hurricane's passage. We linked the change in the rainfall-runoff relationship to a catastrophic change in forest vegetation due to selective hurricane damage. While both watersheds were located in the path of the hurricane, extant forest structure varied between the two watersheds as a function of experimental forest management techniques on the treatment watershed. We showed that the primary damage was to older pines, and to some extent larger hardwood trees. We believe that lowered vegetative water use impacted both watersheds with increased outflows on both watersheds due to loss of trees following hurricane impact. However, one watershed was able to recover to pre hurricane levels of evapotranspiration at a quicker rate due to the greater abundance of pine seedlings and saplings in that watershed.

Hurricane impacts on a pair of coastal forested watersheds: implications of selective hurricane damage to forest structure and streamflow dynamics

NASA Astrophysics Data System (ADS)

Jayakaran, A. D.; Williams, T. M.; Ssegane, H.; Amatya, D. M.; Song, B.; Trettin, C. C.

2013-09-01

Hurricanes are infrequent but influential disruptors of ecosystem processes in the southeastern Atlantic and Gulf coasts. Every southeastern forested wetland has the potential to be struck by a tropical cyclone. We examined the impact of Hurricane Hugo on two paired coastal watersheds in South Carolina in terms of stream flow and vegetation dynamics, both before and after the hurricane's passage in 1989. The study objectives were to quantify the magnitude and timing of changes including a reversal in relative streamflow-difference between two paired watersheds, and to examine the selective impacts of a hurricane on the vegetative composition of the forest. We related these impacts to their potential contribution to change watershed hydrology through altered evapotranspiration processes. Using over thirty years of monthly rainfall and streamflow data we showed that there was a significant transformation in the hydrologic character of the two watersheds - a transformation that occurred soon after the hurricane's passage. We linked the change in the rainfall-runoff relationship to a catastrophic shift in forest vegetation due to selective hurricane damage. While both watersheds were located in the path of the hurricane, extant forest structure varied between the two watersheds as a function of experimental forest management techniques on the treatment watershed. We showed that the primary damage was to older pines, and to some extent larger hardwood trees. We believe that lowered vegetative water use impacted both watersheds with increased outflows on both watersheds due to loss of trees following hurricane impact. However, one watershed was able to recover to pre hurricane levels of canopy transpiration at a quicker rate due to the greater abundance of pine seedlings and saplings in that watershed.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

A minimum spanning forest based classification method for dedicated breast CT images

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

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei, E-mail: bfei@emory.edu

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting modelmore » used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.« less

Helium Ion Microscopy: A Promising Tool for Probing Biota-Mineral Interfaces

NASA Astrophysics Data System (ADS)

Lybrand, R.; Zaharescu, D. G.; Gallery, R. E.

2017-12-01

The study of biogeochemical interfaces in soil requires powerful technologies that can enhance our ability to characterize mineral surfaces and interacting organisms at micro- to nanoscale resolutions. We aim to demonstrate potential applications of Helium Ion Microscopy in the earth and ecological sciences using, as an example, samples from a field experiment. We assessed samples deployed for one year along climatic and topographic gradients in two Critical Zone Observatories (CZOs): a desert to mixed conifer forest gradient (Catalina CZO) and a humid hardwood forest (Calhoun CZO). Sterile ground rock (basalt, quartz, and granite; 53-250 µm) was sealed into nylon mesh bags and buried in the surface soils of both CZOs. We employed helium ion and scanning electron microscopies to compare retrieved ground rock samples with sterile unreacted mineral controls in conjunction with the Environmental Molecular Sciences Laboratory at Pacific Northwest National Laboratory, USA. Our work showed early colonization of mesh bag materials by fungal and bacterial organisms from the field systems and identified morphological changes in mineral grains following exposure to the soil environment. Biological specimens observed on grain surfaces exhibited contrasting features depending on mineral type and ecosystem location, including fungal hyphae that varied in length, diameter, and surface morphologies. We also present imagery that provides evidence for incipient stages of mineral transformation at the fungal-mineral interface. Our findings demonstrate that helium ion microscopy can be successfully used to characterize grain features and biological agents of weathering in experimental field samples, representing a promising avenue for research in the biogeosciences. Future directions of this work will couple high resolution imaging with measures of aqueous and solid geochemistry, fungal morphological characterization, and microbial profiling to better understand mineral transformation along gradients of climate and topography.

Forest Biomass Mapping from Prism Triplet, Palsar and Landsat Data

NASA Astrophysics Data System (ADS)

Ranson, J.; Sun, G.; Ni, W.

2014-12-01

The loss of sensitivity at higher biomass levels is a common problem in biomass mapping using optical multi-spectral data or radar backscattering data due to the lack of information on canopy vertical structure. Studies have shown that adding implicit information of forest vertical structure improves the performance of forest biomass mapping from optical reflectance and radar backscattering data. LiDAR, InSAR and stereo imager are the data sources for obtaining forest structural information. The potential of providing information on forest vertical structure by stereoscopic imagery data has drawn attention recently due to the availability of high-resolution digital stereo imaging from space and the advances of digital stereo image processing software. The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observation Satellite (ALOS) has acquired multiple global coverage from June 2006 to April 2011 providing a good data source for regional/global forest studies. In this study, five PRISM triplets acquired on June 14, 2008, August 19 and September 5, 2009; PALSAR dual-pol images acquired on July 12, 2008 and August 30, 2009; and LANDSAT 5 TM images acquired on September 5, 2009 and the field plot data collected in 2009 and 2010 were used to map forest biomass at 50m pixel in an area of about 4000 km2in Maine, USA ( 45.2 deg N 68.6 deg W). PRISM triplets were used to generate point cloud data at 2m pixel first and then the average height of points above NED (National Elevation Dataset) within a 50m by 50m pixel was calculated. Five images were mosaicked and used as canopy height information in the biomass estimation along with the PALSAR HH, HV radar backscattering and optical reflectance vegetation indices from L-5 TM data. A small portion of this region was covered by the Land Vegetation and Ice Sensor (LVIS) in 2009. The biomass maps from the LVIS data was used to evaluate the results from combined use of PRISM, PALSAR and LANDSAT data. The results show that the canopy height index from PRISM stereo images significantly improves the biomass mapping accuracy and extends the saturation level of biomass, and results in a biomass map comparable with those generated from LVIS data.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic atlas datasets and obtain accurate results. © 2017 American Association of Physicists in Medicine.

QR code-based non-linear image encryption using Shearlet transform and spiral phase transform

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Bhaduri, Basanta; Hennelly, Bryan

2018-02-01

In this paper, we propose a new quick response (QR) code-based non-linear technique for image encryption using Shearlet transform (ST) and spiral phase transform. The input image is first converted into a QR code and then scrambled using the Arnold transform. The scrambled image is then decomposed into five coefficients using the ST and the first Shearlet coefficient, C1 is interchanged with a security key before performing the inverse ST. The output after inverse ST is then modulated with a random phase mask and further spiral phase transformed to get the final encrypted image. The first coefficient, C1 is used as a private key for decryption. The sensitivity of the security keys is analysed in terms of correlation coefficient and peak signal-to noise ratio. The robustness of the scheme is also checked against various attacks such as noise, occlusion and special attacks. Numerical simulation results are shown in support of the proposed technique and an optoelectronic set-up for encryption is also proposed.

WND-CHARM: Multi-purpose image classification using compound image transforms

PubMed Central

Orlov, Nikita; Shamir, Lior; Macura, Tomasz; Johnston, Josiah; Eckley, D. Mark; Goldberg, Ilya G.

2008-01-01

We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image. The feature values are then used to classify test images into a set of pre-defined image classes. This classifier was tested on several different problems including biological image classification and face recognition. Although we cannot make a claim of universality, our experimental results show that this classifier performs as well or better than classifiers developed specifically for these image classification tasks. Our classifier’s high performance on a variety of classification problems is attributed to (i) a large set of features extracted from images; and (ii) an effective feature selection and weighting algorithm sensitive to specific image classification problems. The algorithms are available for free download from openmicroscopy.org. PMID:18958301

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving Forest Inventory and Analysis efficiency with common land unit information

Treesearch

Greg C. Liknes; Mark D. Nelson

2009-01-01

The Forest Service, U.S. Department of Agriculture's (USDA's) Northern Research Station Forest Inventory and Analysis program (NRS-FIA) examines inventory locations on digital aerial imagery to determine if the land use at each plot location meets the FIA definition of forest and thereby becomes a field visit site. This manual image-interpretation effort...

Using computer visualizations to help understand how forests change and develop

Treesearch

Brian Orland; Cenk Ursavas

2006-01-01

Probably a first question people ask when they hear about proposed forest management actions to address fire hazard or forest health concerns is "what will the forest look like"? The recent advent of powerful computer visualization tools has provided one means of answering that question. The resultant images can be a powerful tool for communicating the...

Mapping tropical dry forest height, foliage height profiles and disturbance type and age with a time series of cloud-cleared Landsat and ALI image mosaics to characterize avian habitat

Treesearch

E.H. Helmer; Thomas S. Ruzycki; Jr. Joseph M. Wunderle; Shannon Vogesser; Bonnie Ruefenacht; Charles Kwit; Thomas J. Brandeis; David N. Ewert

2010-01-01

Remote sensing of forest vertical structure is possible with lidar data, but lidar is not widely available. Here we map tropical dry forest height (RMSE=0.9 m, R2=0.84, range 0.6–7 m), and we map foliage height profiles, with a time series of Landsat and Advanced Land Imager (ALI) imagery on the island of Eleuthera, The Bahamas, substituting time for vertical canopy...

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery. Caribbean Journal of Science. 44(2):175-198.

Treesearch

E.H. Helmer; T.A. Kennaway; D.H. Pedreros; M.L. Clark; H. Marcano-Vega; L.L. Tieszen; S.R. Schill; C.M.S. Carrington

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius...

Sources, transformations, and hydrological processes that control stream nitrate and dissolved organic matter concentrations during snowmelt in an upland forest

Treesearch

Stephen D. Sebestyen; Elizabeth W. Boyer; James B. Shanley; Carol Kendall; Daniel H. Doctor; George R. Aiken; Nobuhito Ohte

2008-01-01

We explored catchment processes that control stream nutrient concentrations at an upland forest in northeastern Vermont, USA, where inputs of nitrogen via atmospheric deposition are among the highest in the nation and affect ecosystem functioning. We traced sources of water, nitrate, and dissolved organic matter (DOM) using stream water samples collected at high...

Coupled hydrological and biogeochemical processes controlling variability of nitrogen species in streamflow during autumn in an upland forest

Treesearch

Stephen D. Sebestyen; James B. Shanley; Elizabeth W. Boyer; Carol Kendall; Daniel H. Doctor

2014-01-01

Autumn is a season of dynamic change in forest streams of the northeastern United States due to effects of leaf fall on both hydrology and biogeochemistry. Few studies have explored how interactions of biogeochemical transformations, various nitrogen sources, and catchment flow paths affect stream nitrogen variation during autumn. To provide more information on this...

An evaluation of supervised classifiers for indirectly detecting salt-affected areas at irrigation scheme level

NASA Astrophysics Data System (ADS)

Muller, Sybrand Jacobus; van Niekerk, Adriaan

2016-07-01

Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.

Trigonometric Transforms for Image Reconstruction

DTIC Science & Technology

1998-06-01

applying trigo - nometric transforms to image reconstruction problems. Many existing linear image reconstruc- tion techniques rely on knowledge of...ancestors. The research performed for this dissertation represents the first time the symmetric convolution-multiplication property of trigo - nometric...Fourier domain. The traditional representation of these filters will be similar to new trigo - nometric transform versions derived in later chapters

Forest Residues Bundling Project

Treesearch

U.S. Forest Service

2007-01-01

During the summer of 2003, the U.S. Forest Service conducted an evaluation of biomass bundling for forest residue extraction. This CD provides a report of the project results, a video documentary project record, and a collection of images from the project. Additional information is available at:

A Multitemporal, Multisensor Approach to Mapping the Canadian Boreal Forest

NASA Astrophysics Data System (ADS)

Reith, Ernest

The main anthropogenic source of CO2 emissions is the combustion of fossil fuels, while the clearing and burning of forests contribute significant amounts as well. Vegetation represents a major reservoir for terrestrial carbon stocks, and improving our ability to inventory vegetation will enhance our understanding of the impacts of land cover and climate change on carbon stocks and fluxes. These relationships may be an indication of a series of troubling biosphere-atmospheric feedback mechanisms that need to be better understood and modeled. Valuable land cover information can be provided to the global climate change modeling community using advanced remote sensing capabilities such as Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR). Individually and synergistically, data were successfully used to characterize the complex nature of the Canadian boreal forest land cover types. The multiple endmember spectral mixture analysis process was applied against seasonal AVIRIS data to produce species-level vegetated land cover maps of two study sites in the Canadian boreal forest: Old Black Spruce (OBS) and Old Jack Pine (OJP). The highest overall accuracy was assessed to be at least 66% accurate to the available reference map, providing evidence that high-quality, species-level land cover mapping of the Canadian boreal forest is achievable at accuracy levels greater than other previous research efforts in the region. Backscatter information from multichannel, polarimetric SAR utilizing a binary decision tree-based classification technique methodology was moderately successfully applied to AIRSAR to produce maps of the boreal land cover types at both sites, with overall accuracies at least 59%. A process, centered around noise whitening and principal component analysis features of the minimum noise fraction transform, was implemented to leverage synergies contained within spatially coregistered multitemporal and multisensor AVIRIS and AIRSAR data sets to successfully produce high-accuracy boreal forest land cover maps. Overall land cover map accuracies of 78% and 72% were assessed for OJP and OBS sites, respectively, for either seasonal or multitemporal data sets. High individual land cover accuracies appeared to be independent of site, season, or multisensor combination in the minimum-noise fraction-based approach.

Forest canopy height from Multiangle Imaging SpectroRadiometer (MISR) assessed with high resolution discrete return lidar

Treesearch

Mark Chopping; Anne Nolin; Gretchen G. Moisen; John V. Martonchik; Michael Bull

2009-01-01

In this study retrievals of forest canopy height were obtained through adjustment of a simple geometricoptical (GO) model against red band surface bidirectional reflectance estimates from NASA's Multiangle Imaging SpectroRadiometer (MISR), mapped to a 250 m grid. The soil-understory background contribution was partly isolated prior to inversion using regression...

A System for Drawing Synthetic Images of Forested Landscapes

Treesearch

Timothy P. McDonald

1997-01-01

A software package for drawing images of forested landscapes was developed. Programs included in the system convert topographic and stand polygon information output from a GIS into a form that can be read by a general-purpose ray-tracing renderer. Other programs generate definitions for surface features, mainly trees but ground surface textural properties as well. The...

Locally-constrained Boundary Regression for Segmentation of Prostate and Rectum in the Planning CT Images

PubMed Central

Shao, Yeqin; Gao, Yaozong; Wang, Qian; Yang, Xin; Shen, Dinggang

2015-01-01

Automatic and accurate segmentation of the prostate and rectum in planning CT images is a challenging task due to low image contrast, unpredictable organ (relative) position, and uncertain existence of bowel gas across different patients. Recently, regression forest was adopted for organ deformable segmentation on 2D medical images by training one landmark detector for each point on the shape model. However, it seems impractical for regression forest to guide 3D deformable segmentation as a landmark detector, due to large number of vertices in the 3D shape model as well as the difficulty in building accurate 3D vertex correspondence for each landmark detector. In this paper, we propose a novel boundary detection method by exploiting the power of regression forest for prostate and rectum segmentation. The contributions of this paper are as follows: 1) we introduce regression forest as a local boundary regressor to vote the entire boundary of a target organ, which avoids training a large number of landmark detectors and building an accurate 3D vertex correspondence for each landmark detector; 2) an auto-context model is integrated with regression forest to improve the accuracy of the boundary regression; 3) we further combine a deformable segmentation method with the proposed local boundary regressor for the final organ segmentation by integrating organ shape priors. Our method is evaluated on a planning CT image dataset with 70 images from 70 different patients. The experimental results show that our proposed boundary regression method outperforms the conventional boundary classification method in guiding the deformable model for prostate and rectum segmentations. Compared with other state-of-the-art methods, our method also shows a competitive performance. PMID:26439938

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

[Spatial domain display for interference image dataset].

PubMed

Wang, Cai-Ling; Li, Yu-Shan; Liu, Xue-Bin; Hu, Bing-Liang; Jing, Juan-Juan; Wen, Jia

2011-11-01

The requirements of imaging interferometer visualization is imminent for the user of image interpretation and information extraction. However, the conventional researches on visualization only focus on the spectral image dataset in spectral domain. Hence, the quick show of interference spectral image dataset display is one of the nodes in interference image processing. The conventional visualization of interference dataset chooses classical spectral image dataset display method after Fourier transformation. In the present paper, the problem of quick view of interferometer imager in image domain is addressed and the algorithm is proposed which simplifies the matter. The Fourier transformation is an obstacle since its computation time is very large and the complexion would be even deteriorated with the size of dataset increasing. The algorithm proposed, named interference weighted envelopes, makes the dataset divorced from transformation. The authors choose three interference weighted envelopes respectively based on the Fourier transformation, features of interference data and human visual system. After comparing the proposed with the conventional methods, the results show the huge difference in display time.

Coloured computational imaging with single-pixel detectors based on a 2D discrete cosine transform

NASA Astrophysics Data System (ADS)

Liu, Bao-Lei; Yang, Zhao-Hua; Liu, Xia; Wu, Ling-An

2017-02-01

We propose and demonstrate a computational imaging technique that uses structured illumination based on a two-dimensional discrete cosine transform to perform imaging with a single-pixel detector. A scene is illuminated by a projector with two sets of orthogonal patterns, then by applying an inverse cosine transform to the spectra obtained from the single-pixel detector a full-colour image is retrieved. This technique can retrieve an image from sub-Nyquist measurements, and the background noise is easily cancelled to give excellent image quality. Moreover, the experimental set-up is very simple.

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

PubMed

Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

Mapping the dynamics of juniper forest encroachment into grasslands during 1984-2010 based on PALSAR and Landsat images

NASA Astrophysics Data System (ADS)

Wang, J.; Xiao, X.; Qin, Y.; Dong, J.

2016-12-01

Juniper species widely encroaching into native grasslands has negatively affected the production of forage and livestock, wildlife habitats, and altered the water, carbon, nutrient and biogeochemical cycles. However, time series of juniper maps are not available across landscape, watershed and regional scales to facilitate these studies. This study examined the dynamics of juniper forest encroachment into native grasslands in Oklahoma using a pixel and phenology-based algorithm based on PALSAR mosaic data in 2010 and 10,871 Landsat 5/7 images during 1984-2010. The juniper forest maps in 2010 and five historical epochs: the late 1980s (1984-1989), early 1990s (1990-1994), late 1990s (1995-1999), early 2000s (2000-2004), and late 2000s (2005-2010) were generated. We analyzed the area dynamics at various spatial scales of state, county and geographic regions. This study found that (1) the juniper forest expanded to the northwest of Oklahoma at an annual rate of 5% during 1984-2010; (2) the geographic distribution of juniper forest has notable spatial heterogeneity, varies from one county to another; (3) the area of the juniper forest has the most significant increase in the northwestern counties, and (4) stand age analysis suggested that 65% juniper forests in Oklahoma are young with forest stand age less than 15 years. This practice at the state level demonstrated the potential to trace back the juniper encroachment into the grasslands using time series Landsat images and PALSAR data. The resultant maps can be used to support studies on the driving factors and consequences, and future estimates of the juniper forest encroachment.

[Wood transformation in dead-standing trees in the forest-tundra of Central Siberia].

PubMed

Mukhortova, L V; Kirdianov, A V; Myglan, V S; Guggenberger, G

2009-01-01

Changes in the composition of wood organic matter in dead-standing spruce and larch trees depending on the period after their death have been studied in the north of Central Siberia. The period after tree death has been estimated by means of cross-dating. The results show that changes in the composition of wood organic matter in 63% of cases are contingent on tree species. Wood decomposition in dead-standing trees is accompanied by an increase in the contents of alkali-soluble organic compounds. Lignin oxidation in larch begins approximately 80 years after tree death, whereas its transformation in spruce begins not earlier than after 100 years. In the forest-tundra of Central Siberia, the rate of wood organic matter transformation in dead-standing trees is one to two orders of magnitude lower than in fallen wood, which accounts for their role as a long-term store of carbon and mineral elements in these ecosystems.

Three-dimensional imaging of dislocation dynamics during the hydriding phase transformation

NASA Astrophysics Data System (ADS)

Ulvestad, A.; Welland, M. J.; Cha, W.; Liu, Y.; Kim, J. W.; Harder, R.; Maxey, E.; Clark, J. N.; Highland, M. J.; You, H.; Zapol, P.; Hruszkewycz, S. O.; Stephenson, G. B.

2017-05-01

Crystallographic imperfections significantly alter material properties and their response to external stimuli, including solute-induced phase transformations. Despite recent progress in imaging defects using electron and X-ray techniques, in situ three-dimensional imaging of defect dynamics remains challenging. Here, we use Bragg coherent diffractive imaging to image defects during the hydriding phase transformation of palladium nanocrystals. During constant-pressure experiments we observe that the phase transformation begins after dislocation nucleation close to the phase boundary in particles larger than 300 nm. The three-dimensional phase morphology suggests that the hydrogen-rich phase is more similar to a spherical cap on the hydrogen-poor phase than to the core-shell model commonly assumed. We substantiate this using three-dimensional phase field modelling, demonstrating how phase morphology affects the critical size for dislocation nucleation. Our results reveal how particle size and phase morphology affects transformations in the PdH system.

Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-03-01

A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

Optimized satellite image compression and reconstruction via evolution strategies

NASA Astrophysics Data System (ADS)

Babb, Brendan; Moore, Frank; Peterson, Michael

2009-05-01

This paper describes the automatic discovery, via an Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), of vectors of real-valued coefficients representing matched forward and inverse transforms that outperform the 9/7 Cohen-Daubechies-Feauveau (CDF) discrete wavelet transform (DWT) for satellite image compression and reconstruction under conditions subject to quantization error. The best transform evolved during this study reduces the mean squared error (MSE) present in reconstructed satellite images by an average of 33.78% (1.79 dB), while maintaining the average information entropy (IE) of compressed images at 99.57% in comparison to the wavelet. In addition, this evolved transform achieves 49.88% (3.00 dB) average MSE reduction when tested on 80 images from the FBI fingerprint test set, and 42.35% (2.39 dB) average MSE reduction when tested on a set of 18 digital photographs, while achieving average IE of 104.36% and 100.08%, respectively. These results indicate that our evolved transform greatly improves the quality of reconstructed images without substantial loss of compression capability over a broad range of image classes.

Evaluation of C-band SAR data from SAREX 1992: Tapajos study site

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Filho, Pedro Hernandez; Lee, David Chung Liang; Ahern, F. J.; Paivadossantosfilho, Celio; Rolodealmeida, Rionaldo

1993-01-01

As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

Single Channel Quantum Color Image Encryption Algorithm Based on HSI Model and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Gong, Li-Hua; He, Xiang-Tao; Tan, Ru-Chao; Zhou, Zhi-Hong

2018-01-01

In order to obtain high-quality color images, it is important to keep the hue component unchanged while emphasize the intensity or saturation component. As a public color model, Hue-Saturation Intensity (HSI) model is commonly used in image processing. A new single channel quantum color image encryption algorithm based on HSI model and quantum Fourier transform (QFT) is investigated, where the color components of the original color image are converted to HSI and the logistic map is employed to diffuse the relationship of pixels in color components. Subsequently, quantum Fourier transform is exploited to fulfill the encryption. The cipher-text is a combination of a gray image and a phase matrix. Simulations and theoretical analyses demonstrate that the proposed single channel quantum color image encryption scheme based on the HSI model and quantum Fourier transform is secure and effective.

Inter-image matching

NASA Technical Reports Server (NTRS)

Wolfe, R. H., Jr.; Juday, R. D.

1982-01-01

Interimage matching is the process of determining the geometric transformation required to conform spatially one image to another. In principle, the parameters of that transformation are varied until some measure of some difference between the two images is minimized or some measure of sameness (e.g., cross-correlation) is maximized. The number of such parameters to vary is faily large (six for merely an affine transformation), and it is customary to attempt an a priori transformation reducing the complexity of the residual transformation or subdivide the image into small enough match zones (control points or patches) that a simple transformation (e.g., pure translation) is applicable, yet large enough to facilitate matching. In the latter case, a complex mapping function is fit to the results (e.g., translation offsets) in all the patches. The methods reviewed have all chosen one or both of the above options, ranging from a priori along-line correction for line-dependent effects (the high-frequency correction) to a full sensor-to-geobase transformation with subsequent subdivision into a grid of match points.

Nonlinear Multiscale Transformations: From Synchronization to Error Control

DTIC Science & Technology

2001-07-01

transformation (plus the quantization step) has taken place, a lossless Lempel - Ziv compression algorithm is applied to reduce the size of the transformed... compressed data are all very close, however the visual quality of the reconstructed image is significantly better for the EC compression algorithm ...used in recent times in the first step of transform coding algorithms for image compression . Ideally, a multiscale transformation allows for an

Potential improvement for forest cover and forest degradation mapping with the forthcoming Sentinel-2 program

NASA Astrophysics Data System (ADS)

Hojas-Gascon, L.; Belward, A.; Eva, H.; Ceccherini, G.; Hagolle, O.; Garcia, J.; Cerutti, P.

2015-04-01

The forthcoming European Space Agency's Sentinel-2 mission promises to provide high (10 m) resolution optical data at higher temporal frequencies (5 day revisit with two operational satellites) than previously available. CNES, the French national space agency, launched a program in 2013, 'SPOT4 take 5', to simulate such a dataflow using the SPOT HRV sensor, which has similar spectral characteristics to the Sentinel sensor, but lower (20m) spatial resolution. Such data flow enables the analysis of the satellite images using temporal analysis, an approach previously restricted to lower spatial resolution sensors. We acquired 23 such images over Tanzania for the period from February to June 2013. The data were analysed with aim of discriminating between different forest cover percentages for landscape units of 0.5 ha over a site characterised by deciduous intact and degraded forests. The SPOT data were processed by one extracting temporal vegetation indices. We assessed the impact of the high acquisition rate with respect to the current rate of one image every 16 days. Validation data, giving the percentage of forest canopy cover in each land unit were provided by very high resolution satellite data. Results show that using the full temporal series it is possible to discriminate between forest units with differences of more than 40% tree cover or more. Classification errors fell exclusively into the adjacent forest canopy cover class of 20% or less. The analyses show that forestation mapping and degradation monitoring will be substantially improved with the Sentinel-2 program.

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

Topology-Preserving Rigid Transformation of 2D Digital Images.

PubMed

Ngo, Phuc; Passat, Nicolas; Kenmochi, Yukiko; Talbot, Hugues

2014-02-01

We provide conditions under which 2D digital images preserve their topological properties under rigid transformations. We consider the two most common digital topology models, namely dual adjacency and well-composedness. This paper leads to the proposal of optimal preprocessing strategies that ensure the topological invariance of images under arbitrary rigid transformations. These results and methods are proved to be valid for various kinds of images (binary, gray-level, label), thus providing generic and efficient tools, which can be used in particular in the context of image registration and warping.

Super-Resolution for Color Imagery

DTIC Science & Technology

2017-09-01

separately; however, it requires performing the super-resolution computation 3 times. We transform images in the default red, green, blue (RGB) color space...chrominance components based on ARL’s alias-free image upsampling using Fourier-based windowing methods. A reverse transformation is performed on... Transformation from sRGB to CIELAB............................................... 3 Fig. 2 YCbCr mathematical coordinate transformation

Integrating reconstructed scatterometer and advanced very high resolution radiometer data for tropical forest inventory

NASA Astrophysics Data System (ADS)

Hardin, Perry J.; Long, David G.

1995-11-01

A scientific effort is currently underway to assess tropical forest degradation and its potential impact on Earth's climate. Because of the large continental regions involved, Advanced Very High Resolution Radiometer (AVHRR) imagery and its derivative vegetation index products with resolutions between 1 and 12 km are typically used to inventory the Earth's equatorial vegetation. Archival AVHRR imagery is also used to obtain a temporal baseline of historical forest extent. Recently however, 50-km Seasat-A Scatterometer (SASS) Ku-band imagery (acquired in 1978) has been reconstructed to approximately equals 4-km resolution, making it a supplement to AVHRR imagery for historical vegetation assessment. In order to test the utility of reconstructed Ku-band scatterometer imagery for this purpose, seasonal AVHRR vegetation index and SASS images of identical resolutions were constructed. Using the imagery, discrimination experiments involving 18 vegetation categories were conducted for a central South America study area. The results of these experiments indicate that AVHRR vegetation- index images are slightly superior to reconstructed SASS images for differentiating between equatorial vegetation classes when used alone. However, combining the scatterometer imagery with the vegetation-index images provides discrimination superior to any other combination of the data sets. Using the two data sets together, 90.3% of the test data could be correctly classified into broad classes of equatorial forest, degraded woodland/forest, woodland/savanna, and caatinga.

Combining points and lines in rectifying satellite images

NASA Astrophysics Data System (ADS)

Elaksher, Ahmed F.

2017-09-01

The quick advance in remote sensing technologies established the potential to gather accurate and reliable information about the Earth surface using high resolution satellite images. Remote sensing satellite images of less than one-meter pixel size are currently used in large-scale mapping. Rigorous photogrammetric equations are usually used to describe the relationship between the image coordinates and ground coordinates. These equations require the knowledge of the exterior and interior orientation parameters of the image that might not be available. On the other hand, the parallel projection transformation could be used to represent the mathematical relationship between the image-space and objectspace coordinate systems and provides the required accuracy for large-scale mapping using fewer ground control features. This article investigates the differences between point-based and line-based parallel projection transformation models in rectifying satellite images with different resolutions. The point-based parallel projection transformation model and its extended form are presented and the corresponding line-based forms are developed. Results showed that the RMS computed using the point- or line-based transformation models are equivalent and satisfy the requirement for large-scale mapping. The differences between the transformation parameters computed using the point- and line-based transformation models are insignificant. The results showed high correlation between the differences in the ground elevation and the RMS.

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.

Forest Disturbance Analysis with LANDSAT-8 Oli Data Related to a Parametric Wind Field: a Case Study for Typhoon Rammasun (201409)

NASA Astrophysics Data System (ADS)

Tan, C.; Fang, W.

2018-04-01

Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post- Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.

Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

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...

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...

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

Treesearch

Qingyuan Zhang; Xiangming Xiao; Bobby Braswell; Ernst Linder; Scott Ollinger; Marie-Louise Smith; Julian P. Jenkins; Fred Baret; Andrew D. Richardson; Berrien III Moore; Rakesh Minocha

2006-01-01

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface...

Scan angle calculation and image compositing for the Mexico forest mapping project

Treesearch

Zhiliang Zhu

1994-01-01

Data from the Advanced Very High Resolution Radiometer (AVHRR) were used in a cooperative project, sponsored by the U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, and the United Nations, Food and Agriculture Organization (FAO), to map Mexicos forest cover types.To provide satisfactory AVHRR data sets for the project, the sensor scan...

Super High Resolution Airborne Remote Sensing for Evaluating the Decomposition Function of Ecosystem of Temperate Forest in Japan

NASA Astrophysics Data System (ADS)

Suzuki, R.; Fadaei, H.; Ishii, R.; Nagai, S.; Okabe, K.; Yamashita, S.; Taki, H.; Honda, Y.; Kajiwara, K.

2013-12-01

Forest ecosystem is sustained by nutrients cycle among trees, floor vegetation, litter, and soil etc. One of important driving mechanisms for such nutrients cycle is the decomposition of the fallen trees by fungi, and this process would play an important function in the biogeochemical cycle of the environment. This study challenged to identify the position and size of fallen trees in a temperate forest in Japan based on super high resolution (less than 1cm) visual images taken from a camera aboard a helicopter. Field campaign was carried out on November 29, 2011 at the experimental forest (6 ha, 300m x 200m, 36° 56' 10.5'N, 140° 35' 16.5'E) in Kitaibaraki, Ibaraki, Japan. According to the census survey of the forest, deciduous broad leave trees are dominant. There was almost no leaf in the forest crown on the day of the field campaign, and that brought a high visibility of the floor from the sky. The topography of the forest site is characterized by a small valley with a river flowing north to south at its bottom. An unmanned helicopter (Yamaha RMAX G1) flew over the forest in north-south lines with a speed of 3m/s at height of 30-70m from the ground surface. The interval between adjacent two lines was 20m. A consumer grade camera (Canon EOS Kiss X5 with 55mm lens; 5184 x 3456 pixels) was fixed with the vertically looking down direction on the helicopter. The camera took forest images with 5 seconds interval. The helicopter was also equipped by a laser range finder (LRF) (SkEyesBOX MP-1). Based on the point cloud created by the LRF measurement, 1 x 1m digital elevation model (DEM) of the ground surface was established by finding the lowest point value of the point cloud in each 1 x 1m grid of the forest. The forest was covered by 211 images taken by the camera. Each image was orthorectified by using the DEM and the data of the position and orientations of the helicopter, and then they were mosaicked into one image. Fallen trees with the diameter more than 10cm were targeted for the analysis, and we confirmed that some of fallen tree was easily to identify visually, but some of them was hard to identify because the branch and trunk of trees hided fallen trees. We are going develop the automatic detection algorithm by decision tree and object-based classifications, and then validate the algorithm with in situ information.

Optimized nonorthogonal transforms for image compression.

PubMed

Guleryuz, O G; Orchard, M T

1997-01-01

The transform coding of images is analyzed from a common standpoint in order to generate a framework for the design of optimal transforms. It is argued that all transform coders are alike in the way they manipulate the data structure formed by transform coefficients. A general energy compaction measure is proposed to generate optimized transforms with desirable characteristics particularly suited to the simple transform coding operation of scalar quantization and entropy coding. It is shown that the optimal linear decoder (inverse transform) must be an optimal linear estimator, independent of the structure of the transform generating the coefficients. A formulation that sequentially optimizes the transforms is presented, and design equations and algorithms for its computation provided. The properties of the resulting transform systems are investigated. In particular, it is shown that the resulting basis are nonorthogonal and complete, producing energy compaction optimized, decorrelated transform coefficients. Quantization issues related to nonorthogonal expansion coefficients are addressed with a simple, efficient algorithm. Two implementations are discussed, and image coding examples are given. It is shown that the proposed design framework results in systems with superior energy compaction properties and excellent coding results.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Novel approach for image skeleton and distance transformation parallel algorithms

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Means, Robert W.

1994-05-01

Image Understanding is more important in medical imaging than ever, particularly where real-time automatic inspection, screening and classification systems are installed. Skeleton and distance transformations are among the common operations that extract useful information from binary images and aid in Image Understanding. The distance transformation describes the objects in an image by labeling every pixel in each object with the distance to its nearest boundary. The skeleton algorithm starts from the distance transformation and finds the set of pixels that have a locally maximum label. The distance algorithm has to scan the entire image several times depending on the object width. For each pixel, the algorithm must access the neighboring pixels and find the maximum distance from the nearest boundary. It is a computational and memory access intensive procedure. In this paper, we propose a novel parallel approach to the distance transform and skeleton algorithms using the latest VLSI high- speed convolutional chips such as HNC's ViP. The algorithm speed is dependent on the object's width and takes (k + [(k-1)/3]) * 7 milliseconds for a 512 X 512 image with k being the maximum distance of the largest object. All objects in the image will be skeletonized at the same time in parallel.

Relationship between LiDAR-derived forest canopy height and Landsat images

Treesearch

Cristina Pascual; Antonio Garcia-Abril; Warren B. Cohen; Susana Martin-Fernandez

2010-01-01

The mean and standard deviation (SD) of light detection and ranging (LiDAR)-derived canopy height are related to forest structure. However, LiDAR data typically cover a limited area and have a high economic cost compared with satellite optical imagery. Optical images may be required to extrapolate LiDAR height measurements across a broad landscape. Different spectral...

Hand pose estimation in depth image using CNN and random forest

NASA Astrophysics Data System (ADS)

Chen, Xi; Cao, Zhiguo; Xiao, Yang; Fang, Zhiwen

2018-03-01

Thanks to the availability of low cost depth cameras, like Microsoft Kinect, 3D hand pose estimation attracted special research attention in these years. Due to the large variations in hand`s viewpoint and the high dimension of hand motion, 3D hand pose estimation is still challenging. In this paper we propose a two-stage framework which joint with CNN and Random Forest to boost the performance of hand pose estimation. First, we use a standard Convolutional Neural Network (CNN) to regress the hand joints` locations. Second, using a Random Forest to refine the joints from the first stage. In the second stage, we propose a pyramid feature which merges the information flow of the CNN. Specifically, we get the rough joints` location from first stage, then rotate the convolutional feature maps (and image). After this, for each joint, we map its location to each feature map (and image) firstly, then crop features at each feature map (and image) around its location, put extracted features to Random Forest to refine at last. Experimentally, we evaluate our proposed method on ICVL dataset and get the mean error about 11mm, our method is also real-time on a desktop.

COVER Project and Earth resources research transition

NASA Technical Reports Server (NTRS)

Botkin, D. B.; Estes, J. E. (Principal Investigator)

1986-01-01

Results of research in the remote sensing of natural boreal forest vegetation (the COVER project) are summarized. The study objectives were to establish a baseline forest test site; develop transforms of LANDSAT MSS and TM data for forest composition, biomass, leaf area index, and net primary productivity; and perform tasks required for testing hypotheses regarding observed spectral responses to changes in leaf area index in aspen. In addition, the transfer and documentation of data collected in the COVER project (removed from the Johnson Space Center following the discontinuation of Earth resources research at that facility) is described.

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

PubMed

Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J; Ma, Keping

2013-01-01

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Improved forest change detection with terrain illumination corrected landsat images

USDA-ARS?s Scientific Manuscript database

An illumination correction algorithm has been developed to improve the accuracy of forest change detection from Landsat reflectance data. This algorithm is based on an empirical rotation model and was tested on the Landsat imagery pair over Cherokee National Forest, Tennessee, Uinta-Wasatch-Cache N...

Post-hurricane forest damage assessment using satellite remote sensing

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu; J.A. Stanturf

2010-01-01

This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was...

Adaptive Filtering in the Wavelet Transform Domain Via Genetic Algorithms

DTIC Science & Technology

2004-08-01

inverse transform process. 2. BACKGROUND The image processing research conducted at the AFRL/IFTA Reconfigurable Computing Laboratory has been...coefficients from the wavelet domain back into the original signal domain. In other words, the inverse transform produces the original signal x(t) from the...coefficients for an inverse wavelet transform, such that the MSE of images reconstructed by this inverse transform is significantly less than the mean squared

Rapid landscape transformation in South Island, New Zealand, following initial Polynesian settlement

PubMed Central

McWethy, David B.; Whitlock, Cathy; Wilmshurst, Janet M.; McGlone, Matt S.; Fromont, Mairie; Li, Xun; Dieffenbacher-Krall, Ann; Hobbs, William O.; Fritz, Sherilyn C.; Cook, Edward R.

2010-01-01

Humans have altered natural patterns of fire for millennia, but the impact of human-set fires is thought to have been slight in wet closed-canopy forests. In the South Island of New Zealand, Polynesians (Māori), who arrived 700–800 calibrated years (cal y) ago, and then Europeans, who settled ∼150 cal y ago, used fire as a tool for forest clearance, but the structure and environmental consequences of these fires are poorly understood. High-resolution charcoal and pollen records from 16 lakes were analyzed to reconstruct the fire and vegetation history of the last 1,000 y. Diatom, chironomid, and element concentration data were examined to identify disturbance-related limnobiotic and biogeochemical changes within burned watersheds. At most sites, several high-severity fire events occurred within the first two centuries of Māori arrival and were often accompanied by a transformation in vegetation, slope stability, and lake chemistry. Proxies of past climate suggest that human activity alone, rather than unusually dry or warm conditions, was responsible for this increased fire activity. The transformation of scrub to grassland by Europeans in the mid-19th century triggered further, sometimes severe, watershed change, through additional fires, erosion, and the introduction of nonnative plant species. Alteration of natural disturbance regimes had lasting impacts, primarily because native forests had little or no previous history of fire and little resilience to the severity of burning. Anthropogenic burning in New Zealand highlights the vulnerability of closed-canopy forests to novel disturbance regimes and suggests that similar settings may be less resilient to climate-induced changes in the future. PMID:21149690

Perceptions of social and environmental changes in a Mediterranean forest during the last 100 years: the Gavarres Massif.

PubMed

Rodríguez-Carreras, Roser; Ubeda, Xavier; Outeiro, Luís; Asperó, Francesc

2014-06-01

During the last century the landscape of the mid-Mediterranean mountains has undergone major transformations. The precipitous decline in the economic viability of forest products has engendered ever-thickening forests and agricultural lands have reverted to forest land cover. The related exodus of existing inhabitants since 1960 has led to new styles of occupancy: residential and touristic land uses have emerged while the primary and secondary sectors have largely disappeared. The object of the present study is to review how these transformations have developed in a specific area of north-eastern of Catalonia, known as the Gavarres Massif. The study applies a qualitative approach, based on interviews with stakeholders including active members of the local community and others who utilize or visit the area, all of whom are representatives of different social groups with a wide range of interests and points of view with regard to the massif. The information collected from the perspectives and opinions of the participants is coupled with objective data about the area. The result of this investigation is a rich variety of perceptions on landscape and social transformation and its current functional dynamics. Analyzing the information obtained allows us to understand the fact that the disappearance of the rural world is directly related to the collapse of an entire economic system that relied on the environment. In this study, two divergent points of view arise, one which supports recovering past landscapes and another which favours managing changes, conserving the existing landscape. Proposals for the current and future territorial management of Les Gavarres are presented. The diversity of opinions which emerges with regard to managing necessary changes in the massif emphasizes the importance of increased social dialogue. Copyright © 2013 Elsevier Ltd. All rights reserved.

Forest fragmentation and landscape transformation in a reindeer husbandry area in Sweden.

PubMed

Kivinen, Sonja; Berg, Anna; Moen, Jon; Ostlund, Lars; Olofsson, Johan

2012-02-01

Reindeer husbandry and forestry are two main land users in boreal forests in northern Sweden. Modern forestry has numerous negative effects on the ground-growing and arboreal lichens that are crucial winter resources for reindeer husbandry. Using digitized historical maps, we examined changes in the forest landscape structure during the past 100 years, and estimated corresponding changes in suitability of forest landscape mosaics for the reindeer winter grazing. Cover of old coniferous forests, a key habitat type of reindeer herding system, showed a strong decrease during the study period, whereas clear-cutting and young forests increased rapidly in the latter half of the 20th century. The dominance of young forests and fragmentation of old-growth forests (decreased patch sizes and increased isolation) reflect decreased amount of arboreal lichens as well as a lowered ability of the landscape to sustain long-term persistence of lichens. The results further showed that variation in ground lichen cover among sites was mainly related to soil moisture conditions, recent disturbances, such as soil scarification and prescribed burning, and possibly also to forest history. In general, the results suggest that the composition and configuration of the forest landscape mosaic has become less suitable for sustainable reindeer husbandry.

Amazon Forest maintenance as a source of environmental services.

PubMed

Fearnside, Philip M

2008-03-01

Amazonian forest produces environmental services such as maintenance of biodiversity, water cycling and carbon stocks. These services have a much greater value to human society than do the timber, beef and other products that are obtained by destroying the forest. Yet institutional mechanisms are still lacking to transform the value of the standing forest into the foundation of an economy based on maintaining rather than destroying this ecosystem. Forest management for commodities such as timber and non-timber forest products faces severe limitations and inherent contradictions unless income is supplemented based on environmental services. Amazon forest is threatened by deforestation, logging, forest fires and climate change. Measures to avoid deforestation include repression through command and control, creation of protected areas, and reformulation of infrastructure decisions and development policies. An economy primarily based on the value of environmental services is essential for long-term maintenance of the forest. Much progress has been made in the decades since I first proposed such a transition, but many issues also remain unresolved. These include theoretical issues regarding accounting procedures, improved quantification of the services and of the benefits of different policy options, and effective uses of the funds generated in ways that maintain both the forest and the human population.

Temporal and spatial variation of nitrogen transformations in nitrogen-saturated soils of a central Appalachian hardwood forest

Treesearch

Frank S. Gilliam; Bradley M. Yurish; Mary Beth Adams

2001-01-01

We studied temporal and spatial patterns of soil nitrogen (N) dynamics from 1993 to 1995 in three watersheds of Fernow Experimental Forest, W.V.: WS7 (24-year-old, untreated); WS4 (mature, untreated); and WS3 (24- year-old, treated with (NH4)2SO4 since 1989 at the rate of 35 kg N·ha–1...

Woody vegetation and soil characteristics of residential forest patches and open spaces along an urban-to-rural gradient

Treesearch

Benjamin L. Reichert; Sharon R. Jean-Philippe; Christopher Oswalt; Jennifer Franklin; Mark Radosevich

2015-01-01

As the process of urbanization advances across the country, so does the importance of urban forests, which include both trees and the soils in which they grow. Soil microbial biomass, which plays a critical role in nutrient transformation in urban ecosystems, is affected by factors such as soil type and the availability of water, carbon, and nitrogen. The aim of this...

Object-based Forest Fire Analysis for Pedrógão Grande Fire Using Landsat 8 OLI and Sentinel-2A Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2017-12-01

Forest fires are among the most important natural disasters with the damage to the natural habitat and human-life. Mapping damaged forest fires is crucial for assessing ecological effects caused by fire, monitoring land cover changes and modeling atmospheric and climatic effects of fire. In this context, satellite data provides a great advantage to users by providing a rapid process of detecting burning areas and determining the severity of fire damage. Especially, Mediterranean ecosystems countries sets the suitable conditions for the forest fires. In this study, the determination of burnt areas of forest fire in Pedrógão Grande region of Portugal occurred in June 2017 was carried out using Landsat 8 OLI and Sentinel-2A satellite images. The Pedrógão Grande fire was one of the largest fires in Portugal, more than 60 people was killed and thousands of hectares were ravaged. In this study, four pairs of pre-fire and post-fire top of atmosphere (TOA) and atmospherically corrected images were utilized. The red and near infrared (NIR) spectral bands of pre-fire and post-fire images were stacked and multiresolution segmentation algorithm was applied. In the segmentation processes, the image objects were generated with estimated optimum homogeneity criteria. Using eCognition software, rule sets have been created to distinguish unburned areas from burned areas. In constructing the rule sets, NDVI threshold values were determined pre- and post-fire and areas where vegetation loss was detected using the NDVI difference image. The results showed that both satellite images yielded successful results for burned area discrimination with a very high degree of consistency in terms of spatial overlap and total burned area (over 93%). Object based image analysis (OBIA) was found highly effective in delineation of burnt areas.

Consuming the forest in an environment of crisis: nature tourism, forest conservation and neoliberal agriculture in south India.

PubMed

Münster, Daniel; Münster, Ursula

2012-01-01

This article engages ethnographically with the neoliberalization of nature in the spheres of tourism, conservation and agriculture. Drawing on a case study of Wayanad district, Kerala, the article explores a number of themes. First, it shows how a boom in domestic nature tourism is currently transforming Wayanad into a landscape for tourist consumption. Second, it examines how tourism in Wayanad articulates with projects of neoliberalizing forest and wildlife conservation and with their contestations by subaltern groups. Third, it argues that the contemporary commodification of nature in tourism and conservation is intimately related to earlier processes of commodifying nature in agrarian capitalism. Since independence, forest land has been violently appropriated for intensive cash-cropping. Capitalist agrarian change has transformed land into a (fictitious) commodity and produced a fragile and contested frontier of agriculture and wildlife. When agrarian capitalism reached its ecological limits and entered a crisis of accumulation, farming became increasingly speculative, exploring new modes of accumulation in out-of-state ginger cultivation. In this scenario nature and wildlife tourism emerges as a new prospect for accumulation in a post-agrarian economy. The neoliberalization of nature in Wayanad, the authors argue, is a process driven less by new modes of regulation than by the agrarian crisis and new modes of speculative farming.

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

PubMed

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Discrete Fourier Transform in a Complex Vector Space

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2015-01-01

An image-based phase retrieval technique has been developed that can be used on board a space based iterative transformation system. Image-based wavefront sensing is computationally demanding due to the floating-point nature of the process. The discrete Fourier transform (DFT) calculation is presented in "diagonal" form. By diagonal we mean that a transformation of basis is introduced by an application of the similarity transform of linear algebra. The current method exploits the diagonal structure of the DFT in a special way, particularly when parts of the calculation do not have to be repeated at each iteration to converge to an acceptable solution in order to focus an image.

Measurement of forest disturbance and regrowth with Landsat and forest inventory and analysis data: anticipated benefits from forest and inventory analysis' collaboration with the national aeronautics and space administration and university partners

Treesearch

Sean Healey; Gretchen Moisen; Jeff Masek; Warren Cohen; Sam Goward; < i> et al< /i>

2007-01-01

The Forest Inventory and Analysis (FIA) program has partnered with researchers from the National Aeronautics and Space Administration, the University of Maryland, and other U.S. Department of Agriculture Forest Service units to identify disturbance patterns across the United States using FIA plot data and time series of Landsat satellite images. Spatially explicit...

Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System

Treesearch

E. H. Helmer; M. A. Lefsky; D. A. Roberts

2009-01-01

We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975–2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age...

Before-and-After LIDAR Images from 2014 King Fire in El Dorado National Forest

NASA Image and Video Library

2015-04-09

New maps of two recent California megafires that combine unique data sets from the U.S. Forest Service and NASA's Jet Propulsion Laboratory in Pasadena, California, are answering some of the urgent questions that follow a huge wildfire. These before-and-after USFS LIght Detection And Ranging (LIDAR) images from the 2014 King fire region in El Dorado National Forest, California are among new maps. They show a small section of the Rubicon River drainage basin, where fire damage was severe. Blue indicates ground level; lighter colors are higher. A road -- bordered by dense trees in the before image at left -- and part of a bridge are in the center, with the bridge appearing green. http://photojournal.jpl.nasa.gov/catalog/PIA19360

Preliminary assessment of airborne imaging spectrometer and airborne thematic mapper data acquired for forest decline areas in the Federal Republic of Germany

NASA Technical Reports Server (NTRS)

Herrmann, Karin; Ammer, Ulrich; Rock, Barrett; Paley, Helen N.

1988-01-01

This study evaluated the utility of data collected by the high-spectral resolution airborne imaging spectrometer (AIS-2, tree mode, spectral range 0.8-2.2 microns) and the broad-band Daedalus airborne thematic mapper (ATM, spectral range 0.42-13.0 micron) in assessing forest decline damage at a predominantly Scotch pine forest in the FRG. Analysis of spectral radiance values from the ATM and raw digital number values from AIS-2 showed that higher reflectance in the near infrared was characteristic of high damage (heavy chlorosis, limited needle loss) in Scotch pine canopies. A classification image of a portion of the AIS-2 flight line agreed very well with a damage assessment map produced by standard aerial photointerpretation techniques.

Using Ready-To Drone Images in Forestry Activities: Case Study of ÇINARPINAR in Kahramanmaras, Turkey

NASA Astrophysics Data System (ADS)

Gülci, S.; Akgül, M.; Akay, A. E.; Taş, İ.

2017-11-01

This short paper aims to present pros and cons of current usage of ready-to-use drone images in the field of forestry also considering flight planning and photogrammetric processes. The capabilities of DJI Phantom 4, which is the low cost drone producing by Dji company, was evaluated through sample flights in Cinarpinar Forest Enterprise Chief in Kahramanmaras in Turkey. In addition, the photogrammetric workflow of obtained images and automated flight were presented with respect to capabilities of available software. The flight plans were created by using Pix4DCapture software with android based cell phone. The results indicated that high-resolution imagery obtained by drone can provide significant data for assessment of forest resources, forest roads, and stream channels.

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.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Inverse consistent non-rigid image registration based on robust point set matching

PubMed Central

2014-01-01

Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number. The determinant of the Jacobian matrix of the deformation field is used to analyse the smoothness of the forward and backward transformations. The forward and backward transformations estimated by our algorithm are smooth for small deformation. For registration of lung slices and individual brain slices, large or small determinant of the Jacobian matrix of the deformation fields are observed. Conclusions Results indicate the improvement of the proposed algorithm in bi-directional image registration and the decrease of the inverse consistent errors of the forward and the reverse transformations between two images. PMID:25559889

Modeling small-scale variability in the composition of goshawk habitat on the Kaibab National Forest

Treesearch

Suzanne M. Joy; Robin M. Reich; Richard T. Reynolds

2000-01-01

We used field data, topographical information (elevation, slope, aspect, landform), and Landsat Thematic Mapper imagery to model forest vegetative types to a 10-m resolution on the Kaibab National Forest in northern Arizona. Forest types were identified by clustering the field data and then using a decision tree based on the spectral characteristics of a Landsat image...

From the Bronx to Birmingham: Impact of Chestnut Blight and Management Practices on Forest Health Risks in the Southern Appalachian Mountains

Treesearch

Steven W. Oak

2002-01-01

Southern Appalachian forest landscapes evoke images of the primeval forest in many people today. Indeed, most vegetation components in these forests have been present in varying mixtures and distributions for at least 58 million years (Delcourt and Delcourt 1981). However, the only thing constant about these landscapes has been change. Advancing and retreating ice...

A technique for extrapolating and validating forest cover across large regions. Calibrating AVHRR data with TM data

Treesearch

L.R. Iverson; E.A. Cook; R.L. Graham

1989-01-01

An approach to extending high-resolution forest cover information across large regions is presented and validated. Landsat Thematic Mapper (TM) data were classified into forest and nonforest for a portion of Jackson County, Illinois. The classified TM image was then used to determine the relationship between forest cover and the spectral signature of Advanced Very High...

Acceleration and novelty: community restoration speeds recovery and transforms species composition in Andean cloud forest.

PubMed

Wilson, Sarah Jane; Rhemtulla, Jeanine M

2016-01-01

Community-based tropical forest restoration projects, often promoted as a win-win solution for local communities and the environment, have increased dramatically in number in the past decade. Many such projects are underway in Andean cloud forests, which, given their extremely high biodiversity and history of extensive clearing, are understudied. This study investigates the efficacy of community-based tree-planting projects to accelerate cloud forest recovery, as compared to unassisted natural regeneration. This study takes place in northwest Andean Ecuador, where the majority of the original, highly diverse cloud forests have been cleared, in five communities that initiated tree-planting projects to restore forests in 2003. In 2011, we identified tree species along transects in planted forests (n = 5), naturally regenerating forests (n = 5), and primary forests (n = 5). We also surveyed 120 households about their restoration methods, tree preferences, and forest uses. We found that tree diversity was higher in planted than in unplanted secondary forest, but both were less diverse than primary forests. Ordination analysis showed that all three forests had distinct species compositions, although planted forests shared more species with primary forests than did unplanted forests. Planted forests also contained more animal-dispersed species in both the planted canopy and in the unplanted, regenerating understory than unplanted forests, and contained the highest proportion of species with use value for local people. While restoring forest increased biodiversity and accelerated forest recovery, restored forests may also represent novel ecosystems that are distinct from the region's previous ecosystems and, given their usefulness to people, are likely to be more common in the future.

Improved parameter extraction and classification for dynamic contrast enhanced MRI of prostate

NASA Astrophysics Data System (ADS)

Haq, Nandinee Fariah; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi

2014-03-01

Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and prognosis. The time course of the DCE images provides measures of the contrast agent uptake kinetics. Also, using pharmacokinetic modelling, one can extract parameters from the DCE-MR images that characterize the tumor vascularization and can be used to detect cancer. A requirement for calculating the pharmacokinetic DCE parameters is estimating the Arterial Input Function (AIF). One needs an accurate segmentation of the cross section of the external femoral artery to obtain the AIF. In this work we report a semi-automatic method for segmentation of the cross section of the femoral artery, using circular Hough transform, in the sequence of DCE images. We also report a machine-learning framework to combine pharmacokinetic parameters with the model-free contrast agent uptake kinetic parameters extracted from the DCE time course into a nine-dimensional feature vector. This combination of features is used with random forest and with support vector machine classi cation for cancer detection. The MR data is obtained from patients prior to radical prostatectomy. After the surgery, wholemount histopathology analysis is performed and registered to the DCE-MR images as the diagnostic reference. We show that the use of a combination of pharmacokinetic parameters and the model-free empirical parameters extracted from the time course of DCE results in improved cancer detection compared to the use of each group of features separately. We also validate the proposed method for calculation of AIF based on comparison with the manual method.

Development of a High-Throughput Microwave Imaging System for Concealed Weapons Detection

DTIC Science & Technology

2016-07-15

hardware. Index Terms—Microwave imaging, multistatic radar, Fast Fourier Transform (FFT). I. INTRODUCTION Near-field microwave imaging is a non-ionizing...configuration, but its computational demands are extreme. Fast Fourier Transform (FFT) imaging has long been used to efficiently construct images sampled with...Simulated image of 25 point scatterers imaged at range 1.5m, with array layout depicted in Fig. 3. Left: image formed with Equation (5) ( Fourier

Development Of Polarimetric Decomposition Techniques For Indian Forest Resource Assessment Using Radar Imaging Satellite (Risat-1) Images

NASA Astrophysics Data System (ADS)

Sridhar, J.

2015-12-01

The focus of this work is to examine polarimetric decomposition techniques primarily focussed on Pauli decomposition and Sphere Di-Plane Helix (SDH) decomposition for forest resource assessment. The data processing methods adopted are Pre-processing (Geometric correction and Radiometric calibration), Speckle Reduction, Image Decomposition and Image Classification. Initially to classify forest regions, unsupervised classification was applied to determine different unknown classes. It was observed K-means clustering method gave better results in comparison with ISO Data method.Using the algorithm developed for Radar Tools, the code for decomposition and classification techniques were applied in Interactive Data Language (IDL) and was applied to RISAT-1 image of Mysore-Mandya region of Karnataka, India. This region is chosen for studying forest vegetation and consists of agricultural lands, water and hilly regions. Polarimetric SAR data possess a high potential for classification of earth surface.After applying the decomposition techniques, classification was done by selecting region of interests andpost-classification the over-all accuracy was observed to be higher in the SDH decomposed image, as it operates on individual pixels on a coherent basis and utilises the complete intrinsic coherent nature of polarimetric SAR data. Thereby, making SDH decomposition particularly suited for analysis of high-resolution SAR data. The Pauli Decomposition represents all the polarimetric information in a single SAR image however interpretation of the resulting image is difficult. The SDH decomposition technique seems to produce better results and interpretation as compared to Pauli Decomposition however more quantification and further analysis are being done in this area of research. The comparison of Polarimetric decomposition techniques and evolutionary classification techniques will be the scope of this work.

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

Range and Panoramic Image Fusion Into a Textured Range Image for Culture Heritage Documentation

NASA Astrophysics Data System (ADS)

Bila, Z.; Reznicek, J.; Pavelka, K.

2013-07-01

This paper deals with a fusion of range and panoramic images, where the range image is acquired by a 3D laser scanner and the panoramic image is acquired with a digital still camera mounted on a panoramic head and tripod. The fused resulting dataset, called "textured range image", provides more reliable information about the investigated object for conservators and historians, than using both datasets separately. A simple example of fusion of a range and panoramic images, both obtained in St. Francis Xavier Church in town Opařany, is given here. Firstly, we describe the process of data acquisition, then the processing of both datasets into a proper format for following fusion and the process of fusion. The process of fusion can be divided into a two main parts: transformation and remapping. In the first, transformation, part, both images are related by matching similar features detected on both images with a proper detector, which results in transformation matrix enabling transformation of the range image onto a panoramic image. Then, the range data are remapped from the range image space into a panoramic image space and stored as an additional "range" channel. The process of image fusion is validated by comparing similar features extracted on both datasets.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

GF-3 SAR Image Despeckling Based on the Improved Non-Local Means Using Non-Subsampled Shearlet Transform

NASA Astrophysics Data System (ADS)

Shi, R.; Sun, Z.

2018-04-01

GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously. Recently, Shearlet is applied to the image processing with its best sparse representation. A new Shearlet-transform-based method is proposed in this paper based on the improved non-local means. Firstly, the logarithmic operation and the non-subsampled Shearlet transformation are applied to the GF-3 SAR image. Secondly, in order to solve the problems that the image details are smoothed overly and the weight distribution is affected by the speckle, a new non-local means is used for the transformed high frequency coefficient. Thirdly, the Shearlet reconstruction is carried out. Finally, the final filtered image is obtained by an exponential operation. Experimental results demonstrate that, compared with other despeckling methods, the proposed method can suppress the speckle effectively in homogeneous regions and has better capability of edge preserving.

Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, Qian; Yao, Shaowen; Zhou, Dongming; Nie, Rencan; Lee, Shin-Jye; He, Kangjian

2018-01-01

In order to promote the performance of infrared and visual image fusion and provide better visual effects, this paper proposes a hybrid fusion method for infrared and visual image by the combination of discrete stationary wavelet transform (DSWT), discrete cosine transform (DCT) and local spatial frequency (LSF). The proposed method has three key processing steps. Firstly, DSWT is employed to decompose the important features of the source image into a series of sub-images with different levels and spatial frequencies. Secondly, DCT is used to separate the significant details of the sub-images according to the energy of different frequencies. Thirdly, LSF is applied to enhance the regional features of DCT coefficients, and it can be helpful and useful for image feature extraction. Some frequently-used image fusion methods and evaluation metrics are employed to evaluate the validity of the proposed method. The experiments indicate that the proposed method can achieve good fusion effect, and it is more efficient than other conventional image fusion methods.

Comparative performance evaluation of transform coding in image pre-processing

NASA Astrophysics Data System (ADS)

Menon, Vignesh V.; NB, Harikrishnan; Narayanan, Gayathri; CK, Niveditha

2017-07-01

We are in the midst of a communication transmute which drives the development as largely as dissemination of pioneering communication systems with ever-increasing fidelity and resolution. Distinguishable researches have been appreciative in image processing techniques crazed by a growing thirst for faster and easier encoding, storage and transmission of visual information. In this paper, the researchers intend to throw light on many techniques which could be worn at the transmitter-end in order to ease the transmission and reconstruction of the images. The researchers investigate the performance of different image transform coding schemes used in pre-processing, their comparison, and effectiveness, the necessary and sufficient conditions, properties and complexity in implementation. Whimsical by prior advancements in image processing techniques, the researchers compare various contemporary image pre-processing frameworks- Compressed Sensing, Singular Value Decomposition, Integer Wavelet Transform on performance. The paper exposes the potential of Integer Wavelet transform to be an efficient pre-processing scheme.

Isotropic scalar image visualization of vector differential image data using the inverse Riesz transform.

PubMed

Larkin, Kieran G; Fletcher, Peter A

2014-03-01

X-ray Talbot moiré interferometers can now simultaneously generate two differential phase images of a specimen. The conventional approach to integrating differential phase is unstable and often leads to images with loss of visible detail. We propose a new reconstruction method based on the inverse Riesz transform. The Riesz approach is stable and the final image retains visibility of high resolution detail without directional bias. The outline Riesz theory is developed and an experimentally acquired X-ray differential phase data set is presented for qualitative visual appraisal. The inverse Riesz phase image is compared with two alternatives: the integrated (quantitative) phase and the modulus of the gradient of the phase. The inverse Riesz transform has the computational advantages of a unitary linear operator, and is implemented directly as a complex multiplication in the Fourier domain also known as the spiral phase transform.

Isotropic scalar image visualization of vector differential image data using the inverse Riesz transform

PubMed Central

Larkin, Kieran G.; Fletcher, Peter A.

2014-01-01

X-ray Talbot moiré interferometers can now simultaneously generate two differential phase images of a specimen. The conventional approach to integrating differential phase is unstable and often leads to images with loss of visible detail. We propose a new reconstruction method based on the inverse Riesz transform. The Riesz approach is stable and the final image retains visibility of high resolution detail without directional bias. The outline Riesz theory is developed and an experimentally acquired X-ray differential phase data set is presented for qualitative visual appraisal. The inverse Riesz phase image is compared with two alternatives: the integrated (quantitative) phase and the modulus of the gradient of the phase. The inverse Riesz transform has the computational advantages of a unitary linear operator, and is implemented directly as a complex multiplication in the Fourier domain also known as the spiral phase transform. PMID:24688823

Forest abovegroundbiomass mapping using spaceborne stereo imagery acquired by Chinese ZY-3

NASA Astrophysics Data System (ADS)

Sun, G.; Ni, W.; Zhang, Z.; Xiong, C.

2015-12-01

Besides LiDAR data, another valuable type of data which is also directly sensitive to forest vertical structures and more suitable for regional mapping of forest biomass is the stereo imagery or photogrammetry. Photogrammetry is the traditional technique for deriving terrain elevation. The elevation of the top of a tree canopy can be directly measured from stereo imagery but winter images are required to get the elevation of ground surface because stereo images are acquired by optical sensors which cannot penetrate dense forest canopies with leaf-on condition. Several spaceborne stereoscopic systems with higher spatial resolutions have been launched in the past several years. For example the Chinese satellite Zi Yuan 3 (ZY-3) specifically designed for the collection of stereo imagery with a resolution of 3.6 m for forward and backward views and 2.1 m for the nadir view was launched on January 9, 2012. Our previous studies have demonstrated that the spaceborne stereo imagery acquired in summer has good performance on the description of forest structures. The ground surface elevation could be extracted from spaceborne stereo imagery acquired in winter. This study mainly focused on assessing the mapping of forest biomass through the combination of spaceborne stereo imagery acquired in summer and those in winter. The test sites of this study located at Daxing AnlingMountains areas as shown in Fig.1. The Daxing Anling site is on the south border of boreal forest belonging to frigid-temperate zone coniferous forest vegetation The dominant tree species is Dhurian larch (Larix gmelinii). 10 scenes of ZY-3 stereo images are used in this study. 5 scenes were acquired on March 14,2012 while the other 5 scenes were acquired on September 7, 2012. Their spatial coverage is shown in Fig.2-a. Fig.2-b is the mosaic of nadir images acquired on 09/07/2012 while Fig.2-c is thecorresponding digital surface model (DSM) derived from stereo images acquired on 09/07/2012. Fig.2-d is the difference between the DSM derived from stereo imagery acquired on 09/07/2012 and the digital elevation model (DEM) from stereo imagery acquired on 03/14/2012.The detailed analysis will be given in the final report.

Enhanced image fusion using directional contrast rules in fuzzy transform domain.

PubMed

Nandal, Amita; Rosales, Hamurabi Gamboa

2016-01-01

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.

Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

PubMed

Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet

2010-01-01

Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

PubMed

Varga, Timothy A; Asner, Gregory P

2008-04-01

Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.

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.

Devil's vortex Fresnel lens phase masks on an asymmetric cryptosystem based on phase-truncation in gyrator wavelet transform domain

NASA Astrophysics Data System (ADS)

Singh, Hukum

2016-06-01

An asymmetric scheme has been proposed for optical double images encryption in the gyrator wavelet transform (GWT) domain. Grayscale and binary images are encrypted separately using double random phase encoding (DRPE) in the GWT domain. Phase masks based on devil's vortex Fresnel Lens (DVFLs) and random phase masks (RPMs) are jointly used in spatial as well as in the Fourier plane. The images to be encrypted are first gyrator transformed and then single-level discrete wavelet transformed (DWT) to decompose LL , HL , LH and HH matrices of approximation, horizontal, vertical and diagonal coefficients. The resulting coefficients from the DWT are multiplied by other RPMs and the results are applied to inverse discrete wavelet transform (IDWT) for obtaining the encrypted images. The images are recovered from their corresponding encrypted images by using the correct parameters of the GWT, DVFL and its digital implementation has been performed using MATLAB 7.6.0 (R2008a). The mother wavelet family, DVFL and gyrator transform orders associated with the GWT are extra keys that cause difficulty to an attacker. Thus, the scheme is more secure as compared to conventional techniques. The efficacy of the proposed scheme is verified by computing mean-squared-error (MSE) between recovered and the original images. The sensitivity of the proposed scheme is verified with encryption parameters and noise attacks.

Seasonal Course of Boreal Forest Reflectance

NASA Astrophysics Data System (ADS)

Rautiainen, M.; Heiskanen, J.; Mottus, M.; Eigemeier, E.; Majasalmi, T.; Vesanto, V.; Stenberg, P.

2011-12-01

According to the IPCC 2007 report, northern ecosystems are especially likely to be affected by climate change. Therefore, understanding the seasonal dynamics of boreal ecosystems and linking their phenological phases to satellite reflectance data is crucial for the efficient monitoring and modeling of northern hemisphere vegetation dynamics and productivity trends in the future. The seasonal reflectance course of a boreal forest is a result of the temporal cycle in optical properties of both the tree canopy and understory layers. Seasonal reflectance changes of the two layers are explained by the complex combination of changes in biochemistry and geometrical structure of different plant species as well as seasonal and diurnal variation in solar illumination. Analyzing the role of each of the contributing factors can only be achieved by linking radiative transfer modeling to empirical reflectance data sets. The aim of our project is to identify the seasonal reflectance changes and their driving factors in boreal forests from optical satellite images using new forest reflectance modeling techniques based on the spectral invariants theory. We have measured an extensive ground reference database on the seasonal changes of structural and optical properties of tree canopy and understory layers for a boreal forest site in central Finland in 2010. The database is complemented by a concurrent time series of Hyperion and SPOT satellite images. We use the empirical ground reference database as input to forest reflectance simulations and validate our simulation results using the empirical reflectance data obtained from satellite images. Based on our simulation results, we quantify 1) the driving factors influencing the seasonal reflectance courses of a boreal forest, and 2) the relative contribution of the understory and tree-level layers to forest reflectance as the growing season proceeds.

Migrants, markets, and the transformation of natural resources management: galax harvesting in Western North Carolina

Treesearch

Marla R. Emery; Clare Ginger; Jim Chamberlain

2007-01-01

Latinos are present in increasing numbers in U.S. forests as consumers and producers. This change is transforming the physical and social spaces of natural resources management. For example, extended families from Mexico and Central America seek picnic areas where many people can spend a day preparing food and socializing, a need not met by the typical arrangement of...

Chemical and physical transformations of organic aerosol from the photo-oxidation of open biomass burning emissions in an environmental chamber

Treesearch

C. J. Hennigan; M. A. Miracolo; G. J. Engelhart; A. A. May; A. A. Presto; T. Lee; A. P. Sullivan; G. R. McMeeking; H. Coe; C. E. Wold; W.-M. Hao; J. B. Gilman; W. C. Kuster; J. de Gouw; B. A. Schichtel; J. L. Collett; S. M. Kreidenweis; A. L. Robinson

2011-01-01

Smog chamber experiments were conducted to investigate the chemical and physical transformations of organic aerosol (OA) during photo-oxidation of open biomass burning emissions. The experiments were carried out at the US Forest Service Fire Science Laboratory as part of the third Fire Lab at Missoula Experiment (FLAME III). We investigated emissions from 12 different...

Soil gross nitrogen transformations in responses to land use conversion in a subtropical karst region.

PubMed

Li, Dejun; Liu, Jing; Chen, Hao; Zheng, Liang; Wang, Kelin

2018-04-15

Gross nitrogen (N) transformations can provide important information for assessing indigenous soil N supply capacity and soil nitrate leaching potential. The current study aimed to assess the variation of gross N transformations in response to conversion of maize-soybean fields to sugarcane, mulberry, and forage grass fields in a subtropical karst region of southwest China. Mature forests were included for comparison. Gross rates of N mineralization (GNM) were highest in the forests, intermediate in the maize-soybean and forage grass fields, and lowest in the sugarcane and mulberry fields, suggesting capacity of indigenous soil N supply derived from organic N mineralization was lowered after conversion to sugarcane and mulberry fields. The relative high indigenous soil N supply capacity in the maize-soybean fields was obtained at the cost of soil organic N depletion. Gross nitrification (GN) rates were highest in the forests, intermediate in the forage grass fields and lowest in the other three agricultural land use types. The nitrate retention capacity (24.1 ± 2.0% on average) was similar among the five land use types, implying that nitrate leaching potential was not changed after land use conversion. Microbial biomass N exerted significant direct effects on the rates of N mineralization, nitrification, ammonium immobilization and nitrate immobilization. Soil organic carbon, total N and exchangeable magnesium had significant indirect effects on these N transformation rates. Our findings suggest that forage grass cultivation instead of other agricultural land uses should be recommended from the perspective of increasing indigenous soil N supply while not depleting soil organic N pool. Copyright © 2018 Elsevier Ltd. All rights reserved.

Onboard image compression schemes for modular airborne imaging spectrometer (MAIS) based on wavelet transform

NASA Astrophysics Data System (ADS)

Zhu, Zhenyu; Wang, Jianyu

1996-11-01

In this paper, two compression schemes are presented to meet the urgent needs of compressing the huge volume and high data rate of imaging spectrometer images. According to the multidimensional feature of the images and the high fidelity requirement of the reconstruction, both schemes were devised to exploit the high redundancy in both spatial and spectral dimension based on the mature wavelet transform technology. Wavelet transform was applied here in two ways: First, with the spatial wavelet transform and the spectral DPCM decorrelation, a ratio up to 84.3 with PSNR > 48db's near-lossless result was attained. This is based ont he fact that the edge structure among all the spectral bands are similar while WT has higher resolution in high frequency components. Secondly, with the wavelet's high efficiency in processing the 'wideband transient' signals, it was used to transform the raw nonstationary signals in the spectral dimension. A good result was also attained.

A new method of Quickbird own image fusion

NASA Astrophysics Data System (ADS)

Han, Ying; Jiang, Hong; Zhang, Xiuying

2009-10-01

With the rapid development of remote sensing technology, the means of accessing to remote sensing data become increasingly abundant, thus the same area can form a large number of multi-temporal, different resolution image sequence. At present, the fusion methods are mainly: HPF, IHS transform method, PCA method, Brovey, Mallat algorithm and wavelet transform and so on. There exists a serious distortion of the spectrums in the IHS transform, Mallat algorithm omits low-frequency information of the high spatial resolution images, the integration results of which has obvious blocking effects. Wavelet multi-scale decomposition for different sizes, the directions, details and the edges can have achieved very good results, but different fusion rules and algorithms can achieve different effects. This article takes the Quickbird own image fusion as an example, basing on wavelet transform and HVS, wavelet transform and IHS integration. The result shows that the former better. This paper introduces the correlation coefficient, the relative average spectral error index and usual index to evaluate the quality of image.

Detailed forest formation mapping in the land cover map series for the Caribbean islands

NASA Astrophysics Data System (ADS)

Helmer, E. H.; Schill, S.; Pedreros, D. H.; Tieszen, L. L.; Kennaway, T.; Cushing, M.; Ruzycki, T.

2006-12-01

Forest formation and land cover maps for several Caribbean islands were developed from Landsat ETM+ imagery as part of a multi-organizational project. The spatially explicit data on forest formation types will permit more refined estimates of some forest attributes. The woody vegetation classification scheme relates closely to that of Areces-Malea et al. (1), who classify Caribbean vegetation according to standards of the US Federal Geographic Data Committee (FGDC, 1997), with modifications similar to those in Helmer et al. (2). For several of the islands, we developed image mosaics that filled cloudy parts of scenes with data from other scene dates after using regression tree normalization (3). The regression tree procedure permitted us to develop mosaics for wet and drought seasons for a few of the islands. The resulting multiseason imagery facilitated separation between classes such as seasonal evergreen forest, semi-deciduous forest (including semi-evergreen forest), and drought deciduous forest or woodland formations. We used decision tree classification methods to classify the Landsat image mosaics to detailed forest formations and land cover for Puerto Rico (4), St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines and Grenada. The decision trees classified a stack of raster layers for each mapping area that included the Landsat image bands and various ancillary raster data layers. For Puerto Rico, for example, the ancillary data included climate parameters (5). For some islands, the ancillary data included topographic derivatives such as aspect, slope and slope position, SRTM (6) or other topographic data. Mapping forest formations with decision tree classifiers, ancillary geospatial data, and cloud-free image mosaics, accurately distinguished spectrally similar forest formations, without the aid of ecological zone maps, on the islands where the approach was used. The approach resulted in maps of forest formations with comparable or better detail than when IKONOS or Landsat imagery was hand-digitized, as it was for the Dominican Republic (7) and Barbados. 1. T. Kennaway, E. H. Helmer. (Intl Inst of Tropical Forestry, USDA Forest Service, Río Piedras, Puerto Rico, 2006). 2. A. Areces-Mallea et al. (The Nature Conservancy, 1999). 3. E. H. Helmer, O. Ramos, T. Lopez, M. Quiñones, W. Diaz, Carib J Sci 38, 165-183 (2002). 4. C. Daly, E. H. Helmer, M. Quiñones, Int J Climatology 23, 1359-1381 (2003). 5. T. G. Farr, M. Kobrick, Eos Transactions 81, 583-585 (2000). 6. E. H. Helmer, B. Ruefenacht, Photogrammetric Eng Rem Sens 71, 1079-1089 (2005). 7. S. Hernández, M. Pérez. (Secretaría de Estado de Medio Ambiente y Recursos Naturales de la República Dominicana, Santo Domingo, Dominican Republic, 2005).

Earth Observations taken by the Expedition 15 Crew

NASA Image and Video Library

2007-08-13

ISS015-E-22269 (13 Aug. 2007) --- The crew aboard the International Space Station provided this image of the wide-spread forest fires in the Payette National Forest, Central Idaho within the Salmon River Mountains. North is toward the left of the image. The Salmon River is the feature in the bottom central part of the frame. Lake Cascade is seen at the lower right.

Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer

Treesearch

Mark Chopping; Gretchen G. Moisen; Lihong Su; Andrea Laliberte; Albert Rango; John V. Martonchik; Debra P. C. Peters

2008-01-01

A rapid canopy reflectance model inversion experiment was performed using multi-angle reflectance data from the NASA Multi-angle Imaging Spectro-Radiometer (MISR) on the Earth Observing System Terra satellite, with the goal of obtaining measures of forest fractional crown cover, mean canopy height, and aboveground woody biomass for large parts of south-eastern Arizona...

Atmospheric deposition in coniferous and deciduous tree stands in Poland

NASA Astrophysics Data System (ADS)

Kowalska, Anna; Astel, Aleksander; Boczoń, Andrzej; Polkowska, Żaneta

2016-05-01

The objective of this study was to assess the transformation of precipitation in terms of quantity and chemical composition following contact with the crown layer in tree stands with varied species composition, to investigate the effect of four predominant forest-forming species (pine, spruce, beech, and oak) on the amount and composition of precipitation reaching forest soils, and to determine the sources of pollution in atmospheric precipitation in forest areas in Poland. The amount and chemical composition (pH, electric conductivity, alkalinity, and chloride, nitrate, sulfate, phosphate, ammonium, calcium, magnesium, sodium, potassium, iron aluminum, manganese, zinc, copper, total nitrogen, and dissolved organic carbon contents) of atmospheric (bulk, BP) and throughfall (TF) precipitation were studied from January to December 2010 on twelve forest monitoring plots representative of Polish conditions. The study results provided the basis for the determination of the fluxes of pollutants in the forest areas of Poland and allowed the comparison of such fluxes with values provided in the literature for European forest areas. The transformation of precipitation in the canopy was compared for different tree stands. The fluxes of substances in an open field and under canopy were influenced by the location of the plot, including the regional meteorological conditions (precipitation amounts), vicinity of the sea (effect of marine aerosols), and local level of anthropogenic pollution. Differences between the plots were higher in TF than in BP. The impact of the vegetation cover on the chemical composition of precipitation depended on the region of the country and dominant species in a given tree stand. Coniferous species tended to cause acidification of precipitation, whereas deciduous species increased the pH of TF. Pine and oak stands enriched precipitation with components that leached from the canopy (potassium, manganese, magnesium) to a higher degree than spruce and beech stands.

Optimal Landsat transforms for forest applications

NASA Technical Reports Server (NTRS)

Logan, T. L.; Strahler, A. H.

1983-01-01

Eleven transformations of data from four Landsat MSS channels were investigated to find if any of the transforms accentuated the separability of natural vegetation classes in regions of varying topographical relief. Attention was given to the divergence analysis and classification accuracy of information content of the eleven transforms and four channels. A useful scaling function was observed with the second eigenvector being the denominator in the divergence values obtained. The second eigenvector was found to reduce the effects of shadowing and differential illumination of vegetation signatures, thereby enhancing the divergence values. The highest accuracies in crop identification were provided by the averages of channels 4, 6, and 7 divided by the second eigenvector.

Long-term litter decomposition controlled by manganese redox cycling

DOE PAGES

Keiluweit, Marco; Nico, Peter S.; Harmon, Mark; ...

2015-09-08

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of littermore » was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn 2+ provided by fresh plant litter to produce oxidative Mn 3+ species at sites of active decay, with Mn eventually accumulating as insoluble Mn 3+/4+ oxides. Formation of reactive Mn 3+ species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn 3+-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn 3+ species in the litter layer. As a result, this observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant–soil system may have a profound impact on litter decomposition rates.« less

Analyzing Land Use Changes in the Metropolitan Jilin City of Northeastern China Using Remote Sensing and GIS.

PubMed

Hu, Dan; Yang, Guodong; Wu, Qiong; Li, Hongqing; Liu, Xusheng; Niu, Xuefeng; Wang, Zhiheng; Wang, Qiong

2008-09-03

Remote sensing and GIS have been widely employed to study temporal and spatial urban land use changes in southern and southeastern China. However, few studies have been conducted in northeastern regions. This study analyzed land use change and spatial patterns of urban expansion in the metropolitan area of Jilin City, located on the extension of Changbai Mountain, based on aerial photos from 1989 and 2005 Spot images. The results indicated that urban land and transportation land increased dramatically (by 94.04% and 211.20%, respectively); isolated industrial and mining land decreased moderately (by 29.54%); rural residential land increased moderately (by 26.48%); dry land and paddy fields increased slightly (by 15.68% and 11.78%, respectively); forest and orchards decreased slightly (by 5.27% and 4.61%, respectively); grasslands and unused land decreased dramatically (by 99.12% and 86.04%, respectively). Sloped dry land (more than 4 degrees) was mainly distributed on the land below 10 degrees with an east, southeastern and south sunny direction aspect, and most sloped dry land transformed to forest was located on an east aspect lower than 12 degrees, while forest changed to dry land were mainly distributed on east and south aspects lower than 10 degrees. A spatial dependency analysis of land use change showed that the increased urban land was a logarithmic function of distance to the Songhua River. This study also provided some data with spatial details about the uneven land development in the upstream areas of Songhua River basin.

Discrete Cosine Transform Image Coding With Sliding Block Codes

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Pearlman, William A.

1989-11-01

A transform trellis coding scheme for images is presented. A two dimensional discrete cosine transform is applied to the image followed by a search on a trellis structured code. This code is a sliding block code that utilizes a constrained size reproduction alphabet. The image is divided into blocks by the transform coding. The non-stationarity of the image is counteracted by grouping these blocks in clusters through a clustering algorithm, and then encoding the clusters separately. Mandela ordered sequences are formed from each cluster i.e identically indexed coefficients from each block are grouped together to form one dimensional sequences. A separate search ensues on each of these Mandela ordered sequences. Padding sequences are used to improve the trellis search fidelity. The padding sequences absorb the error caused by the building up of the trellis to full size. The simulations were carried out on a 256x256 image ('LENA'). The results are comparable to any existing scheme. The visual quality of the image is enhanced considerably by the padding and clustering.

Visual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1992-01-01

Topics discussed in these proceedings include nonlinear processing and communications; feature extraction and recognition; image gathering, interpolation, and restoration; image coding; and wavelet transform. Papers are presented on noise reduction for signals from nonlinear systems; driving nonlinear systems with chaotic signals; edge detection and image segmentation of space scenes using fractal analyses; a vision system for telerobotic operation; a fidelity analysis of image gathering, interpolation, and restoration; restoration of images degraded by motion; and information, entropy, and fidelity in visual communication. Attention is also given to image coding methods and their assessment, hybrid JPEG/recursive block coding of images, modified wavelets that accommodate causality, modified wavelet transform for unbiased frequency representation, and continuous wavelet transform of one-dimensional signals by Fourier filtering.

Space Radar Image of Manaus, Brazil

NASA Image and Video Library

1999-01-27

These two images were created using data from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). On the left is a false-color image of Manaus, Brazil acquired April 12, 1994, onboard space shuttle Endeavour. In the center of this image is the Solimoes River just west of Manaus before it combines with the Rio Negro to form the Amazon River. The scene is around 8 by 8 kilometers (5 by 5 miles) with north toward the top. The radar image was produced in L-band where red areas correspond to high backscatter at HH polarization, while green areas exhibit high backscatter at HV polarization. Blue areas show low backscatter at VV polarization. The image on the right is a classification map showing the extent of flooding beneath the forest canopy. The classification map was developed by SIR-C/X-SAR science team members at the University of California,Santa Barbara. The map uses the L-HH, L-HV, and L-VV images to classify the radar image into six categories: Red flooded forest Green unflooded tropical rain forest Blue open water, Amazon river Yellow unflooded fields, some floating grasses Gray flooded shrubs Black floating and flooded grasses Data like these help scientists evaluate flood damage on a global scale. Floods are highly episodic and much of the area inundated is often tree-covered. http://photojournal.jpl.nasa.gov/catalog/PIA01712

Colour space influence for vegetation image classification application to Caribbean forest and agriculture

NASA Astrophysics Data System (ADS)

Abadi, M.; Grandchamp, E.

2008-10-01

This paper deals with a comparison of different colour space in order to improve high resolution images classification. The background of this study is the measure of the agriculture impact on the environment in islander context. Biodiversity is particularly sensitive and relevant in such areas and the follow-up of the forest front is a way to ensure its preservation. Very high resolution satellite images are used such as QuickBird and IKONOS scenes. In order to segment the images into forest and agriculture areas, we characterize both ground covers with colour and texture features. A classical unsupervised classifier is then used to obtain labelled areas. As features are computed on coloured images, we can wonder if the colour space choice is relevant. This study has been made considering more than fourteen colour spaces (RGB, YUV, Lab, YIQ, YCrCs, XYZ, CMY, LMS, HSL, KLT, IHS, I1I2I3, HSV, HSI, etc.) and shows the visual and quantitative superiority of IHS on all others. For conciseness reasons, results only show RGB, I1I2I3 and IHS colour spaces.