Using Lidar And Normalized Difference Vegetation Index To Remotely Determine Lai And Percent Canopy Cover At Varying Scales

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Using LiDAR and Normalized Difference Vegetation Index to Remotely Determine LAI and Percent Canopy Cover at Varying Scales

Author : Alicia Marie Rutledge Griffin
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (61 download)

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Book Synopsis Using LiDAR and Normalized Difference Vegetation Index to Remotely Determine LAI and Percent Canopy Cover at Varying Scales by : Alicia Marie Rutledge Griffin

Download or read book Using LiDAR and Normalized Difference Vegetation Index to Remotely Determine LAI and Percent Canopy Cover at Varying Scales written by Alicia Marie Rutledge Griffin and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of airborne LiDAR (Light Detection and Ranging) as a direct method to evaluate forest canopy parameters is vital in addressing both forest management and ecological concerns. The overall goal of this study was to develop the use of airborne LiDAR in evaluating canopy parameters such as percent canopy cover (PCC) and leaf area index (LAI) for mixed pine and hardwood forests (primarily loblolly pine, Pinus taeda, forests) of the southeastern United States. More specific objectives were to: (1) Develop scanning LiDAR and multispectral imagery methods to estimate PCC and LAI over both hardwood and coniferous forests; (2) investigate whether a LiDAR and normalized difference vegetation index (NDVI) data fusion through linear regression improve estimates of these forest canopy characteristics; (3) generate maps of PCC and LAI for the study region, and (4) compare local scale LiDAR-derived PCC and regional scale MODIS-based PCC and investigate the relationship. Scanning LiDAR data was used to derive local scale PCC estimates, and TreeVaW, a LiDAR software application, was used to locate individual trees to derive an estimate of plot-level PCC. A canopy height model (CHM) was created from the LiDAR dataset and used to determine tree heights per plot. QuickBird multispectral imagery was used to calculate the NDVI for the study area. LiDAR- and NDVI-derived estimates of plot-level PCC and LAI were compared to field observations for 53 plots over 47 square kilometers. Linear regression analysis resulted in models explaining 84% and 78% of the variability associated with PCC and LAI, respectively. For these models to be of use in future studies, LiDAR point density must be 2.5 m. The relationship between regional scale PCC and local scale PCC was investigated by resizing the local scale LiDAR-derived PCC map to lower resolution levels, then determining a regression model relating MODIS data to the local values of PCC. The results from this comparison showed that MODIS PCC data is not very accurate at local scales. The methods discussed in this paper show great potential for improving the speed and accuracy of ecological studies and forest management.

Accuracy Assessment of Percent Canopy Cover, Cover Type, and Size Class

Author : Hans T. Schreuder
Publisher :
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4.X/5 (4 download)

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Book Synopsis Accuracy Assessment of Percent Canopy Cover, Cover Type, and Size Class by : Hans T. Schreuder

Download or read book Accuracy Assessment of Percent Canopy Cover, Cover Type, and Size Class written by Hans T. Schreuder and published by . This book was released on 2003 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Author : Francisco Javier García-Haro
Publisher : MDPI
ISBN 13 : 3039212397
Total Pages : 334 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters by : Francisco Javier García-Haro

Download or read book Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters written by Francisco Javier García-Haro and published by MDPI. This book was released on 2019-09-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Comparison of Tree Canopy Cover Derived from Lidar and Optical Imagery

Author :
Publisher :
ISBN 13 :
Total Pages : 19 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis Comparison of Tree Canopy Cover Derived from Lidar and Optical Imagery by :

Download or read book Comparison of Tree Canopy Cover Derived from Lidar and Optical Imagery written by and published by . This book was released on 2014 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Land managers requiring spatial tree canopy cover data must consider data quality and specific information needs when selecting an appropriate data source. Given the increased availability of low density lidar datasets and the recent release of the National Land Cover Database (NLCD) 2011 Tree Canopy Cover (TCC) product, land managers are faced with additional candidate data sources for obtaining spatially explicit estimates of tree canopy cover. To inform the use of various remote sensing methods and data products available to land managers, the Remote Sensing Steering Committee sponsored a project comparing canopy cover estimates derived from three different remote sensing technologies: lidar, moderate-resolution satellite imagery, and high-resolution aerial imagery. Canopy cover estimates were compared and evaluated in order to clarify their appropriate use at different spatial and temporal scales. The TCC data and tree canopy cover data derived from lidar were compared and evaluated in terms of their agreement with sample-based estimates obtained from photo-interpretation of high-resolution ortho-imagery. Canopy cover estimates from a southern pine forest were compared at plot and landscape scales. At both scales, mean canopy cover derived from lidar was not significantly different from the photo-interpreted sample estimates, while TCC values were higher. Canopy cover values from lidar agreed more strongly with the photo-interpreted canopy cover estimates (RMSE = 11.01 percent) than did TCC data (RMSE = 18.13 percent). Temporal and seasonal agreement and scale of measurement should be considered in the interpretation of these results. Recommendations and considerations for choosing appropriate canopy cover data products for a variety of management needs are presented and discussed. A supplemental evaluation of the effects of lidar point density on first order canopy structure metrics was conducted and is reported in the appendix of this report. Experimentally thinning a high-density lidar data set and comparing the derived forest structure metrics at the scale of 30 meters showed that point densities as low as 1.5 points per square meter yielded first order canopy structure estimates similar to those obtained from the high point density reference.

RELATIONSHIP BETWEEN LEAF AREA INDEX (LAI) ESTIMATED BY TERRESTRIAL LIDAR AND REMOTELY SENSED VEGETATION INDICES AS A PROXY TO FOREST CARBON SEQUESTRATION

Download RELATIONSHIP BETWEEN LEAF AREA INDEX (LAI) ESTIMATED BY TERRESTRIAL LIDAR AND REMOTELY SENSED VEGETATION INDICES AS A PROXY TO FOREST CARBON SEQUESTRATION PDF Online Free

Author : Nayani Thanuja Ilangakoon
Publisher :
ISBN 13 :
Total Pages : 62 pages
Book Rating : 4.:/5 (9 download)

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Book Synopsis RELATIONSHIP BETWEEN LEAF AREA INDEX (LAI) ESTIMATED BY TERRESTRIAL LIDAR AND REMOTELY SENSED VEGETATION INDICES AS A PROXY TO FOREST CARBON SEQUESTRATION by : Nayani Thanuja Ilangakoon

Download or read book RELATIONSHIP BETWEEN LEAF AREA INDEX (LAI) ESTIMATED BY TERRESTRIAL LIDAR AND REMOTELY SENSED VEGETATION INDICES AS A PROXY TO FOREST CARBON SEQUESTRATION written by Nayani Thanuja Ilangakoon and published by . This book was released on 2014 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leaf area index (LAI) is an important indicator of ecosystem conditions and an important key biophysical variable to many ecosystem models. The LAI in this study was measured by Leica ScanStation C 10 Terrestrial Laser Scanner (TLS) and a hand-held Li-Cor LAI-2200 Plant Canopy Analyzer for understanding differences derived from the two sensors. A total of six different LAI estimates were generated using different methods for the comparisons. The results suggested that there was a reasonable agreement (i.e., the correlations r > 0.50) considering a total of 30 plots and limited land cover types sampled. The predicted LAI from spectral vegetation indices including WDVI, DVI, NDVI, SAVI, and PVI3 which were derived from Landsat TM imagery were used to identify statistical relationships and for the development of the Bayesian inference model. The Bayesian Linear Regression (BLR) approach was used to scale up LAI estimates and to produce continuous field surfaces for the Oak Openings Region in NW Ohio. The results from the BLR provided details about the parameter uncertainties but also insight about the potential that different LAIs can be used to predict foliage that has been adjusted by removing the wooden biomass with reasonable accuracy. For instance, the modeled residuals associated with the LAI estimates from TLS orthographic projection that consider only foliage had the lowest overall model uncertainty with lowest error and residual dispersion range among the six spatial LAI estimates. The deviation from the mean LAI prediction map derived from the six estimates hinted that sparse and open areas that relate to vegetation structure were associated with the highest error. However, although in many studies TLS has been shown to hold a great potential for quantifying vegetation structure, in this study the quantified relationship between LAI and the vegetation indices did not yield any statistical relationship that needs to be further explore.

Lidar Remote Sensing Of Forest Canopy Structure

Author : Christopher Felix Hansen
Publisher :
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.:/5 (18 download)

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Book Synopsis Lidar Remote Sensing Of Forest Canopy Structure by : Christopher Felix Hansen

Download or read book Lidar Remote Sensing Of Forest Canopy Structure written by Christopher Felix Hansen and published by . This book was released on 2015 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Light detection and ranging (LiDAR) data can provide detailed information about three-dimensional forest horizontal and vertical structure that is important to forest productivity and wildlife habitat. Indeed, LiDAR data have been shown to provide accurate estimates to forest structural parameters and measures of higher trophic levels (e.g., avian abundance and diversity). However, links between forest structure and tree function have not been evaluated using LiDAR. This study was designed and scaled to assess the relationship of LiDAR to multiple aspects of forest structure and higher trophic levels (arthropod and bird populations), which included the ground-based collection of percent crown and understory closure, as well as arthropod and avian abundance and diversity data. Additional plot-based measures were added to assess the relationship of LiDAR to forest health and productivity. High-resolution discrete-return LiDAR data (flown summer of 2009) were acquired for the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA. LiDAR data were classified into four canopy structural categories: 1) high crown and high understory closure, 2) high crown and low understory closure, 3) low crown and high understory closure, and 4) low crown and low understory closure. Nearby plots from each of the four LiDAR categories were grouped into "blocks" to assess the spatial consistency of data. Ground-based measures of forest canopy structure, site, stand and individual tree measures were collected on nine 50 m-plots from each LiDAR category (36 plots total), during summer of 2012. Analysis of variance was used to assess the relationships between LiDAR and a suite of tree function measures. Our results show the novel ability of LiDAR to assess forest health and productivity at the stand and individual tree level. We found significant correspondence between LiDAR categories and our ground-based measures of tree function, including xylem increment growth, foliar nutrition, crown health, and stand mortality. Furthermore, we found consistent reductions in xylem increment growth, decreases in foliar nutrition and crown health, and increases in stand mortality related to high understory closure. This suggests that LiDAR measures can reflect competitive interactions, not just among overstory trees for light, but also interactions between overstory trees and understory vegetation for resources other than light (e.g., nutrients). High-resolution LiDAR data show promise in the assessment of forest health and productivity related to tree function.

Quantifying Forest Structure Parameters and Their Changes from LiDAR Data and Satellite Imagery in the Sierra Nevada

Author : Qin Ma
Publisher :
ISBN 13 :
Total Pages : 284 pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis Quantifying Forest Structure Parameters and Their Changes from LiDAR Data and Satellite Imagery in the Sierra Nevada by : Qin Ma

Download or read book Quantifying Forest Structure Parameters and Their Changes from LiDAR Data and Satellite Imagery in the Sierra Nevada written by Qin Ma and published by . This book was released on 2018 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sierra Nevada forests have provided many economic benefits and ecological services to people in California, and the rest of the world. Dramatic changes are occurring in the forests due to climate warming and long-term fire suppression. Accurate mapping and monitoring are increasingly important to understand and manage the forests. Light Detection and Range (LiDAR), an active remote sensing technique, can penetrate the canopy and provide three-dimensional estimates of forest structures. LiDAR-based forest structural estimation has been demonstrated to be more efficient than field measurements and more accurate than those from passive remote sensing, like satellite imagery. Research in this dissertation aims at mapping and monitoring structural changes in Sierra Nevada forests by taking the advantages of LiDAR. We first evaluated LiDAR and fine resolution imagery-derived canopy cover estimates using different algorithms and data acquisition parameters. We suggested that LiDAR data obtained at 1 point/m2 with a scan angle smaller than 12°were sufficient for accurate canopy cover estimation in the Sierra Nevada mix-conifer forests. Fine resolution imagery is suitable for canopy cover estimation in forests with median density but may over or underestimate canopy cover in extremely coarse or dense forests. Then, a new LiDAR-based strategy was proposed to quantify tree growth and competition at individual tree and forest stand levels. Using this strategy, we illustrated how tree growth in two Sierra Nevada forests responded to tree competition, original tree sizes, forest density, and topography conditions; and identified that the tree volume growth was determined by the original tree sizes and competitions, but tree height and crown area growth were mostly influenced by water and space availability. Then, we calculated the forest biomass disturbance in a Sierra Nevada forest induced by fuel treatments using bi-temporal LiDAR data and field measurements. Using these results as references, we found that Landsat imagery-derived vegetation indices were suitable for quantifying canopy cover changes and biomass disturbances in forests with median density. Large uncertainties existed in applying the vegetation indices to quantify disturbance in extremely dense forests or forests only disturbed in the understory. Last, we assessed vegetation losses caused by the American Fire in 2013 using a new LiDAR point based method. This method was able to quantify fire-induced forest structure changes in basal area and leaf area index with lower uncertainties, compared with traditional LiDAR metrics and satellite imagery-derived vegetation indices. The studies presented in this dissertation can provide guidance for forest management in the Sierra Nevada, and potentially serve as useful tools for forest structural change monitoring in the rest of the world.

Leaf Area Index in Riparian Forests

Author : Travis Axe
Publisher :
ISBN 13 :
Total Pages : 93 pages
Book Rating : 4.:/5 (18 download)

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Book Synopsis Leaf Area Index in Riparian Forests by : Travis Axe

Download or read book Leaf Area Index in Riparian Forests written by Travis Axe and published by . This book was released on 2018 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing technology has expanded tremendously over the past few decades and has created value when integrated into environmental concepts and practices. But there is unmet potential for bolstering ecosystem services and creating additional value for society. Impediments such as the cost and complexity of the technology, and the difficulty of readily assimilating it into a decision-making process, must be overcome to facilitate broader use. This study demonstrates the capacity for an emerging and inexpensive remote sensing technology to estimate an important ecological indicator and then discusses the broader implications for societal value. First, we compare the estimation of effective leaf area index (LAI[subscript]e) of heterogeneous riparian forests between two remote sensing methodologies: discrete-return Airborne Laser Scanning (ALS) and airborne structure-from-motion (SfM). LAI[subscript]e is an indispensable component of process-based ecological research and can be associated with a variety of ecosystem services. SfM data acquisition is more frequent and inexpensive compared to ALS, but its capabilities less explored. Two point-cloud data files for each technology were evaluated using respective field-measured reference data. SfM shows promise: a combinational linear regression revealed that the distribution elevation values of upper-canopy point returns and the elevation values representing mid and max stand-level, when paired grey-level co-occurrence matrix (GLCM), can estimate LAI[subscript]E (r2 = 0.62). Although it did not perform as well as ALS, which has more data representing light attenuation behavior (r2 = 0.66), SfM as an alternative methodology for remotely sensing ecological data has demonstrated potential and warrants further investigation. Next, we discuss how remotely sensed ecological information like LAI[subscript]e can create value for society. We provide a primer on the ways in which society values the environment and how these values may be perceived and quantified, and the dynamic behavior that exists between them. We then introduce a major policy tool used in quantifying these values, benefit cost analysis, and why it is useful for framing environmental issues and how remote sensing can contribute to its outcomes. Finally, we review remote sensing applications used in increasing our understanding of society’s interaction with the environment and existing opportunities for value addition.

Measuring the Leaf Area Index and Foliage Profile of Forest Canopies Using a Group-based Lidar Instrument (Echidna)

Author : Feng Zhao
Publisher :
ISBN 13 :
Total Pages : 224 pages
Book Rating : 4.:/5 (746 download)

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Book Synopsis Measuring the Leaf Area Index and Foliage Profile of Forest Canopies Using a Group-based Lidar Instrument (Echidna) by : Feng Zhao

Download or read book Measuring the Leaf Area Index and Foliage Profile of Forest Canopies Using a Group-based Lidar Instrument (Echidna) written by Feng Zhao and published by . This book was released on 2011 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Effective leaf area index (LAI) retrievals from a ground-based, upward-scanning, under-canopy, full waveform, near-infrared (1064 nm) lidar, the Echidna Validation Instrument (EVI), agree with those obtained from both hemispherical photography and the Li-Cor LAI-2000 Plant Canopy Analyzer. A newly proposed approach for clumping index retrieval based on the three dimensional structure of gaps also produced clumping index measurements that were consistent with those of gap-size distribution theory using hemispherical photography, documenting the ability of the EVI to characterize the clumping of forest foliage at the stand scale. These results are based on trials at 28 plots within six hardwood and conifer stands at Harvard Forest, Massachusetts, Bartlett Experimental Forest, New Hampshire, and Howland Experimental Forest, Maine, from July 2007, and on additional 30 plots within six conifer stands in Sierra National Forest, California, from July 2008. These stands vary in tree heights, stocking densities, and local surface topography. In addition to LAI, foliage profiles (leaf area with height), can be estimated from the EVI. These are difficult to retrieve from hemispherical photos or LAI-2000 measurements, but are easily derived from EVI observations of gap probability with zenith angle. The foliage profiles retrieved were consistent with stand structure as observed in the field and match well with those obtained from Lidar Vegetation Imaging Sensor (LVIS) airborne large-footprint lidar system. Tree heights as determined from the foliage profiles retrieved by the EVI are also close to heights determined using the LVIS. LAI and foliage profile (leaf area with height) are key biophysical parameters for assessing plant productivity, and for understanding atmosphere-vegetation exchange processes such as photosynthesis, evaporation and transpiration, and carbon flux. The accuracies of many modeling studies using LAI as a key input depend heavily on the accuracies of ground-truth LAI estimates. The Echidna Validation Instrument is the first realization of the Echidna® lidar concept, devised by Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), for measuring forest structure using full-waveform, ground-based, scanning lidar.

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Author : Hongliang Fang
Publisher :
ISBN 13 : 9783039212408
Total Pages : 1 pages
Book Rating : 4.2/5 (124 download)

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Book Synopsis Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters by : Hongliang Fang

Download or read book Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters written by Hongliang Fang and published by . This book was released on 2019 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Vertical Decomposition of Forest Structure Using LiDAR Remote Sensing

Author : Hamish Asmath
Publisher :
ISBN 13 : 9780494163474
Total Pages : 204 pages
Book Rating : 4.1/5 (634 download)

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Book Synopsis Vertical Decomposition of Forest Structure Using LiDAR Remote Sensing by : Hamish Asmath

Download or read book Vertical Decomposition of Forest Structure Using LiDAR Remote Sensing written by Hamish Asmath and published by . This book was released on 2006 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vertical LiDAR profiles that measure the vertical organization of the canopy structure were created and used to classify the study area based upon reference profiles developed from selected silvicultural practices present in the Turkey Lakes Watershed. A previous method of estimating LAI from LiDAR data uses the vegetation returns to calculate the mean vegetation height. A new method of estimating LAI based upon the area under the vertical LiDAR profile was developed that is more accurate than the mean vegetation height approach. A procedure was developed to vertically distribute the LAI throughout the forest canopy using the estimated LAI and the LiDAR vertical profile. The result was a vertical LAI profile for each pixel. This allowed for the calculation of LAI at a specified height, and the height a specified LAI occurs. Vertical decomposition of LAI was performed at the plot level (20 x 20 m) and the canopy level (5 x 5 m).

LiDAR and WorldView-2 Satellite Data for Leaf Area Index Estimation in the Boreal Forest

Author : Graham Wesley Pope
Publisher :
ISBN 13 :
Total Pages : 184 pages
Book Rating : 4.:/5 (815 download)

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Book Synopsis LiDAR and WorldView-2 Satellite Data for Leaf Area Index Estimation in the Boreal Forest by : Graham Wesley Pope

Download or read book LiDAR and WorldView-2 Satellite Data for Leaf Area Index Estimation in the Boreal Forest written by Graham Wesley Pope and published by . This book was released on 2012 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leaf Area Index (LAI) is an important input variable for forest ecosystem modeling as it is a factor in predicting productivity and biomass, two key aspects of forest health. Current in situ methods of determining LAI are sometimes destructive and generally very time consuming. Other LAI derivation methods, mainly satellite-based in nature, do not provide sufficient spatial resolution or the precision required by forest managers. This thesis focused on estimating LAI from: i) height and density metrics derived from Light Detection and Ranging (LiDAR); ii) spectral vegetation indices (SVIs), in particular the Normalized Difference Vegetation Index (NDVI); and iii) a combination of these two remote sensing technologies. In situ measurements of LAI were calculated from digital hemispherical photographs (DHPs) and remotely sensed variables were derived from low density LiDAR and high resolution WorldView-2 data. Multiple Linear Regression (MLR) models were created using these variables, allowing forest-wide prediction surfaces to be created. Results from these analyses demonstrated: i) moderate explanatory power (i.e., R2 = 0.54) for LiDAR models incorporating metrics that have proven to be related to canopy structure; ii) no relationship when using SVIs; and iii) no significant improvement of LiDAR models when combining them with SVI variables. The results suggest that LiDAR models in boreal forest environments provide satisfactory estimations of LAI, even with low ranges of LAI for model calibration. On the other hand, it was anticipated that traditional SVI relationships to LAI would be present with WorldView-2 data, a result that is not easily explained. Models derived from low point density LiDAR in a mixedwood boreal environment seem to offer a reliable method of estimating LAI at a high spatial resolution for decision makers in the forestry community.

Seasonal LAI in Slash Pine Estimated with LANDSAT TM

Author :
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (317 download)

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Book Synopsis Seasonal LAI in Slash Pine Estimated with LANDSAT TM by :

Download or read book Seasonal LAI in Slash Pine Estimated with LANDSAT TM written by and published by . This book was released on 1990 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Monitoring Seasonal Changes Using NOAA-AVHRR Normalized Difference Vegetation Index Data

Author : Asaph Anyamba
Publisher :
ISBN 13 :
Total Pages : 230 pages
Book Rating : 4.:/5 (29 download)

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Book Synopsis Monitoring Seasonal Changes Using NOAA-AVHRR Normalized Difference Vegetation Index Data by : Asaph Anyamba

Download or read book Monitoring Seasonal Changes Using NOAA-AVHRR Normalized Difference Vegetation Index Data written by Asaph Anyamba and published by . This book was released on 1992 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multi-scale Mapping and Accuracy Assessment of Leaf Area Index for Vegetation Study in Southern Illinois

Author : Kushendra Narayan Shah
Publisher :
ISBN 13 :
Total Pages : 186 pages
Book Rating : 4.:/5 (884 download)

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Book Synopsis Multi-scale Mapping and Accuracy Assessment of Leaf Area Index for Vegetation Study in Southern Illinois by : Kushendra Narayan Shah

Download or read book Multi-scale Mapping and Accuracy Assessment of Leaf Area Index for Vegetation Study in Southern Illinois written by Kushendra Narayan Shah and published by . This book was released on 2013 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing interest of modeling global carbon cycling during the past two decades has driven this research to map leaf area index (LAI) at multiple spatial resolutions by combining LAI field observations with various sensor images at local, regional, and global scale. This is due to its important role in process based models that are used to predict carbon sequestration of terrestrial ecosystems. Although a substantial research has been conducted, there are still many challenges in this area. One of the challenges is that various images with spatial resolutions varying from few meters to several hundred meters and even to 1 km have been used. However, a method that can be used to collect LAI field measurements and further conduct multiple spatial resolution mapping and accuracy assessment of LAI is not available. In this study, a pilot study in a complex landscape located in the Southern Illinois was carried out to map LAI by combining field observations and remotely sensed images. Multi-scale mapping and accuracy assessment of LAI using aerial photo, Landsat TM and MODIS images were explored by developing a multi-scale sampling design. The results showed that the sampling design could be used to collect LAI observations to create LAI products at various spatial resolutions and further conduct accuracy assessment. It was also found that the TM derived LAI maps at the original and aggregated spatial resolutions successfully characterized the heterogeneous landscape and captured the spatial variability of LAI and were more accurate than those from the aerial photo and MODIS. The aerial photo derived models led to not only over- and under-estimation, but also pixilated maps of LAI. The MODIS derived LAI maps had an acceptable accuracy at various spatial resolutions and are applicable to mapping LAI at regional and global scale. Thus, this study overcame some of the significant gaps in this field.

Exploring the Relationships Between Vegetation Measurements and Temperature in Residential Areas by Integrating LIDAR and Remotely Sensed Imagery

Download Exploring the Relationships Between Vegetation Measurements and Temperature in Residential Areas by Integrating LIDAR and Remotely Sensed Imagery PDF Online Free

Author : Matthew A Clemonds
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (857 download)

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Book Synopsis Exploring the Relationships Between Vegetation Measurements and Temperature in Residential Areas by Integrating LIDAR and Remotely Sensed Imagery by : Matthew A Clemonds

Download or read book Exploring the Relationships Between Vegetation Measurements and Temperature in Residential Areas by Integrating LIDAR and Remotely Sensed Imagery written by Matthew A Clemonds and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Population growth and urban sprawl have contributed to the formation of significant urban heat island phenomena in Houston, Texas, the fourth largest city in theUnited States. The population growth in Houston was 25.8% between 1990 and 2000 nearly double the national average. The demand for information concerning the effects of urban and suburban development is growing. Houston is currently the only major US city lacking any kind of comprehensive city zoning ordinances. The Normalized Difference Vegetation Index (NDVI) has been used as a surrogate variable to estimate land surface temperatures at higher spatial resolutions, given the fact that a high-resolution remotely sensed NDVI can be created almost effortlessly and remotely sensed thermal data at higher resolutions is much more difficult to obtain. This has allowed researchers to study urban heat island dynamics at amicro-scale. However, this study suggests that a vegetation index alone might not be the best surrogate variable for providing information regarding the independent effects and level of contribution that tree canopy, grass, and low-lying plants have on surface temperatures in residential neighborhoods. This research combines LIDAR (Light Detection and Ranging) feature height data and high-resolution infrared aerial photos to measure the characteristics of the micro-structure of residential areas (residential structure), derives various descriptive vegetation measurement statistics, and correlates the spatial distribution of surface temperature to the type and amount of vegetation covering residential areas. Regression analysis is used to quantify the independent influence that different residential-structures have on surface temperature. In regard to implementing changes at a neighborhood level, the descriptive statistics derived for residential-structure at a micro-scale may provide useful information to decision-makers and may reveal a guide for future developers concerned with mitigating the negative effects of urban heat island phenomena.

Evaluating Forest Volume Estimation at Barksdale Air Force Base Using Lidar and Multispectral Imagery

Author : Richard Edward Brooks
Publisher :
ISBN 13 :
Total Pages : 168 pages
Book Rating : 4.:/5 (859 download)

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Book Synopsis Evaluating Forest Volume Estimation at Barksdale Air Force Base Using Lidar and Multispectral Imagery by : Richard Edward Brooks

Download or read book Evaluating Forest Volume Estimation at Barksdale Air Force Base Using Lidar and Multispectral Imagery written by Richard Edward Brooks and published by . This book was released on 2009 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating timber volume from a field perspective, with field plots occasionally falling within remote and inaccessible areas, can be a costly and timely endeavor. Remote sensing, with its ability to record information at both the local and regional scale, offers an alternative to traditional field based measurements. Studies have shown that remotely sensed vegetation biomass indices (e.g. NDVI) derived from mid-spatial resolution digital imagery (e.g. Landsat TM, 30-meters), after being corrected for atmospheric effects, topographical differences and shadow, were highly correlated with timber volume. With the recent advent of high spatial resolution digital imagery from the IKONOS and QuickBird satellites providing more textural information about a forest canopy, with spatial resolutions of 4 meters and 2.44 meters for multispectral data respectively, the opportunity to assess forest volume from a distance at a much finer scale has increased. Additionally Lidar (light detection and ranging) is a relatively new remote sensing technology that can accurately estimate the 3-dimensional structure of forest vegetation which is related to forest volume and offers an alternative to ground based measurement of remotely sensed multispectral data.