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Book Identifying Topographic Controls of Terrestrial Vegetation Using Remote Sensing Data in a Semiarid Mountain Watershed Idaho USA

Download or read book Identifying Topographic Controls of Terrestrial Vegetation Using Remote Sensing Data in a Semiarid Mountain Watershed Idaho USA written by Ricci Loughridge and published by . This book was released on 2014 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Global climate change is a significant research focus area in contemporary Earth science. Changes in climatic patterns have already resulted in shifting energy flows with associated changes in hydrologic and ecologic systems. More specifically, changes in vegetation distribution and abundance are one of the most visible and potentially significant effects of a changing climatic regime. However, to monitor and predict future changes in vegetation, the initial conditions must be well characterized. This thesis examines the distribution of vegetation in a semiarid mountain watershed in three important ways: (1) quantifying the factors affecting the distribution of broad classes of vegetation at the hillslope scale (e.g., 30-100 m), (2) quantifying factors affecting the organization of vegetation at sub-hillslope scales, and (3) quantifying the factors influencing the distribution of vegetation water content. The first of these themes is aimed at producing a hillslope-scale classification map of 4 broad classes (sagebrush steppe, Douglas fir, ponderosa pine, and deciduous/riparian) of vegetation within Dry Creek Experimental Watershed (DCEW) at the 30 m spatial resolution using remote sensing and geospatial data, field data, and 2 supervised learning classifiers known as artificial neural network (ANN) and classification and regression tree (CART). We investigated possible drivers of vegetation distribution by partitioning 11 topographic and remote sensing inputs into the ANN and CART models. Results show that the ANN had better overall accuracy (82.3%) than the CART (77.22%); however, it is less informative of the input variables used to classify due to the complex nature of the ANN architecture. Therefore, the CART model was used to determine that 5 of the 11 predictors were significant drivers of vegetation distribution. At the sub-hillslope scale, we quantified the percent cover of specific biotic and abiotic cover types (grass, forb, shrub, bare ground, and etc.) contained within the sagebrush-steppe class: the diameter at breast height (DBH), frequency, and density for the conifer classe."--Boise State University ScholarWorks.

Book A Comprehensive Analysis of Terrestrial Surface Features Using Remote Sensing Data

Download or read book A Comprehensive Analysis of Terrestrial Surface Features Using Remote Sensing Data written by Liqun Sun and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "A Comprehensive Analysis of Terrestrial Surface Features Using Remote Sensing Data" by Liqun, Sun, 孙立群, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Using the remote sensing data, this study aims to enhance our understanding of land surface features, including ecosystem distribution in association with topographic controls and climatic controls, vegetation disturbance due to natural hazards, and surface temperature changes with consideration of the influence of urbanization. In this study, the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets from 1982 to 2006 were used to explore vegetation variation. A data mining method, Exhaustive Chi-squared Automatic Interaction Detector algorithm, was successfully applied to investigate the topographic influences on vegetation distribution in China. The study revealed that elevation is a predominant factor for controlling vegetation distribution among different topographic attributes (slope, aspect, Compound Topographic Index (CTI) and distance to the nearest river). Further, the study results indicated that solar radiation is the limited factor for plant growth in majority of the Northern Hemisphere in summer, and temperature is the main limitation for other seasons. Partial correlation coefficient (PCC) method was adopted to investigate the complex relationships of NDVI with weather variables (i.e., temperature, precipitation and solar radiation) and key climate indices (such as, El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). The study indicated that AO is the most significant index in affecting the temperatures in spring and winter in the Northern Hemisphere. This study enhanced the understanding of vegetation responds to asymmetric daytime (Tmax) and nighttime (Tmin) warming in different seasons. The result revealed that asymmetric warming of Tmax and Tmin may influence vegetation photosynthesis and respiration in the plant growth in different periods across biomes. In spring and autumn, vegetation in boreal and wet temperate regions of the Northern Hemisphere is positively correlated with Tmax and negatively correlated with Tmin, whereas, in dry regions the NDVI is always negatively correlated with Tmax and positively correlated with Tmin. In summer, the NDVI is negatively correlated with Tmax in many dry regions. In addition, this study developed a new index, Continued Vegetation Decrease Index (CVDI), to detect vegetation disturbance due to extreme natural hazards (such as, earthquake, wildfire, ice storms and so on). Using the Wenchuan earthquake occurred in Sichuan China on 12 May 2008 as an example, this study confirmed that the CVDI method can effectively identify the regions with severe vegetation damage, and it is expected that the newly-developed index can be used for detecting vegetation disturbance in other regions of the world. Finally, using the remote sensing data (land use data and surface temperature data) and weather station data, this study developed a new method to evaluate the urbanization influence on the temperature recorded at weather stations. The results revealed that the weather stations with most fast increase temperature are not in developed countries, but in developing countries. The results also imply that the global warming trend may be overestimated due to the under-estimation of urbanization influence on temperature increase. DOI: 10.5353/th_b5351026 Subjects: Remote sensing

Book Using Remote Sensing Data Fusion Modeling to Track Seasonal Snow Cover in a Mountain Watershed

Download or read book Using Remote Sensing Data Fusion Modeling to Track Seasonal Snow Cover in a Mountain Watershed written by Allison N. Vincent and published by . This book was released on 2021 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Seasonal snowfall is the largest component of the water budget in many mountain headwater regions around the world. In addition to sustaining biological water needs in drier, lower elevation areas throughout the year, mountain snowpack also provides essential water inputs to the Critical Zone (CZ) - the outer layer of the Earth’s surface, which hosts a variety of biogeochemical processes responsible for transforming inorganic matter into forms usable for life. Water is a known driver of CZ activity, but uncertainty exists in its spatial and temporal interactions with CZ processes, particularly in the complex terrain of heterogeneous mountain areas. Increasing pressure on the CZ due to climate change and human land use needs creates an urgency to better understand the CZ system and how it may change in the future. An important variable for water driven CZ behaviors in mountain areas is the spatial extent of snow, also known as snow-covered area (SCA). SCA in mountain areas can change quickly over small scales of time and space with large impacts on the rest of the system. It has been difficult historically, however, to measure snowpack extent for large areas on very fine spatial and temporal scales due to a lack of remote sensing datasets with both of these fine scale characteristics. In this study we use the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to fill this historic knowledge gap for the East River watershed in Colorado, USA. By fusing low spatial and high temporal resolution data from MODIS (500-m, daily) with high spatial and low temporal resolution data from Landsat (30-m, 16 days), a fine resolution, 30-m daily dataset can be created. This study is one of the first to use this model with the primary intent of monitoring SCA in a mountain watershed."--Boise State University ScholarWorks.

Book Water Resources Research Catalog

Download or read book Water Resources Research Catalog written by United States. Office of Water Research and Technology and published by . This book was released on 1972 with total page 1590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beginning with vol. 9, only new and continuing but modified projects are listed. Vols. 8- should be kept as a record of continuing but unchanged projects.

Book Applications of Remote Sensing to Watershed Management

Download or read book Applications of Remote Sensing to Watershed Management written by Albert Rango and published by . This book was released on 1975 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Forest Vegetation Removal and Slope Stability in the Idaho Batholith

Download or read book Forest Vegetation Removal and Slope Stability in the Idaho Batholith written by Donald H. Gray and published by . This book was released on 1981 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Jackson, Mississippi, in 1962, there are lines that are not crossed. With the civil rights movement exploding all around them, three women start a movement of their own, forever changing a town and the way women--black and white, mothers and daughters--view one another.

Book Integrating Remote Sensing and Field Observations to Investigate the Impacts of Vegetation Dynamics on Emergent Ecological and Hydrological Processes at the Watershed Scale

Download or read book Integrating Remote Sensing and Field Observations to Investigate the Impacts of Vegetation Dynamics on Emergent Ecological and Hydrological Processes at the Watershed Scale written by Mahsa Khodaee and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large-scale forest dynamics, mostly driven by climate change and disturbance activities, have great implications for forest biodiversity, and ecosystem structures and services. Therefore, monitoring these changes over space and time is critical to improve our understanding of forest responses to climate change and disturbance activities. In this dissertation, remote sensing data were employed in statistical and machine learning (ML) approaches to characterize forest disturbances (infestation and fire) and long-term phenological changes at the eastern United States. Further, vegetation phenological information were integrated with field measurements of meteorological parameters to evaluate hydrologic alterations of forested watersheds. More specifically, three objectives are the focus of this dissertation: (1) developing an accurate approach to characterize the spectral-temporal trajectory of forest disturbances using long-term satellite observations, (2) evaluating the impacts of both vegetation and snowpack seasonal dynamics on emergent watershed-scale hydrologic behavior over vernal and autumnal transition periods, and (3) mapping fire-induced changes in forested landscapes using the combined approach of remote sensing and ML techniques.In the first chapter, using time series analysis of remote sensing imagery, we evaluated the performance of well-known spectral indices in capturing vegetation dynamics following the two major disturbances, fire and hemlock woolly adelgid (HWA; Adelges tsugae Annad) infestation. Our results suggested that the overall performance of Normalized Difference Vegetation Index (NDVI) was the most accurate in detecting disturbances intensity, temporal dynamics, and recovery patterns. Results obtained from our second chapter demonstrated that the lengthened growing season and declined winter snowpack can significantly alter the low-frequency seasonal streamflow distributions by changing the seasonality of evapotranspiration. Our findings also suggested that with continuous declines in winter snowfall, the effect of snowpack dynamics on identifying the seasonal streamflow regimes has weakened, while vegetation phenology has exerted more dominant control. In the third study of this dissertation, we evaluated the performance of four ML classification techniques in estimating fire severity, using spectral indices, topographic parameters, and surface temperature (ST) variables from remote sensing data. We found that Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models had high predictive capability to detect fire severity in regions with mixes of low to medium fire disturbances. Results also indicated that spectral indices, especially Normalized Burn Ratio (NBR) and Tasseled Cap Wetness index (TCW), elevation, aspect and growing season ST had higher relative contributions to fire severity prediction than other variables.

Book Monitoring Vegetation Greenness with Satellite Data

Download or read book Monitoring Vegetation Greenness with Satellite Data written by Robert E. Burgan and published by . This book was released on 1993 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Guidelines for the Use of Digital Imagery for Vegetation Mapping

Download or read book Guidelines for the Use of Digital Imagery for Vegetation Mapping written by Henry Lachowski and published by DIANE Publishing. This book was released on 1996-09 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: A basic reference for those considering digital imagery, particularly satellite imagery for vegetation mapping. Contents: using remote sensing and GIS for mapping vegetation; remote sensors and remotely sensed data; determining appropriate uses for satellite imagery; defining the classification scheme; collecting reference data; assessing accuracy; creating polygons; project management; the basic tour; and case studies. Important terms and ideas are introduced while showing the progression of key activities in the classification and mapping process.

Book Integrating Remote Sensing and Ecosystem Models for Terrestrial Vegetation Analysis

Download or read book Integrating Remote Sensing and Ecosystem Models for Terrestrial Vegetation Analysis written by Gong Zhang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Terrestrial vegetation plays an important role in global carbon cycling and climate change by assimilating carbon into biomass during the growing season and releasing it due to natural or anthropogenic disturbances. Remote sensing and ecosystem models can help us extend our studies of vegetation phenology, aboveground biomass, and disturbances from field sites to regional or global scales. Nonetheless, remote sensing-derived variables may differ in fundamental and important ways from ground measurements. With the growth of remote sensing as a key tool in geoscience research, comparisons to ground data and inter-comparisons among satellite products are needed. Here I conduct three separate but related analyses and show promising comparisons of key ecosystem states and processes derived from remote sensing and theoretical modeling to those observed on the ground. First, I show that the Moderate Resolution Imaging Spectroradiometer (MODIS) greenup product is significantly correlated with the earliest ground phenology event for North America. Spring greenup indices from different satellites demonstrate similar variability along latitudes, but the number of ground phenology observations in summer, fall, and winter is too limited to interpret the remote sensing-derived phenology products. Second, I estimate aboveground biomass (AGB) for California and show that it agrees with inventory-based regional biomass assessments. In this approach, I present a new remote sensing-based approach for mapping live forest AGB based on a simple parametric model that combines high-resolution estimates of Leaf Area Index derived from Landsat and canopy maximum height from the space-borne Geoscience Laser Altimeter System (GLAS) sensor. Third, I built a theoretical model to estimate stand age in primary forests by coupling a carbon accumulation function to the probability density of disturbance occurrences, and then ran the model with satellite-derived AGB and net primary production. The validated remote sensing data, integrated with ecosystem models, are particularly useful for large-region vegetation research in areas with sparse field measurements, and will help us to explore the long-term vegetation dynamics.

Book Bibliography of Agriculture

Download or read book Bibliography of Agriculture written by and published by . This book was released on 1983 with total page 2330 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book A Mathematical Transformation of Multi angular Remote Sensing Data for the Study of Vegetation Change

Download or read book A Mathematical Transformation of Multi angular Remote Sensing Data for the Study of Vegetation Change written by Robert G. Friedel and published by . This book was released on 2007 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vegetation change is an important factor affecting the global carbon cycle, land-atmosphere interaction, and terrestrial ecology. The study of vegetation change on a global scale can be used to evaluate the impact of global climate change on terrestrial ecosystems. Satellite remote sensing can monitor vegetation change at the global scale, providing continuous samples of radiation reflected by vegetated surfaces with a temporal resolution of days. The MISR instrument offers the potential to sample the specular anisotropy of the Earth from up to 9 angles. Characterization of the specular anisotropy of vegetated surfaces on a global scale will provide information on the physical characteristics of vegetation affecting anisotropy not available from nadir-view only remote sensing. The objective of this study is to develop a Principal Components Analysis (PCA) transformation of multi-angular measurements of the Earth?s surface acquired by the MISR instrument, to examine the feasibility of quantifying the structural characteristics of different vegetation communities at a global scale. This transformation will be applied to a time-series analysis of the Kalmioposis Wilderness in the Siskiyou National Forest in Southwestern Oregon to better understand the changes in spectral and angular reflectance of a forest stand during re-growth after a stand-replacing disturbance. A sample encompassing a full phenologic cycle, of the red bands only from MISR cameras Ca ? Cf, at scaled surface reflectance, provided the template on which PCA was performed. The sample of MISR data was created using imagery collected from 2001 ? 2005 to provide a wide variety of vegetation and soils reflectance over a phenologic cycle. Sample data was rotated to the principal components as the new axes using the coefficients of rotation from an un-standardized PCA. Samples were evaluated at various latitudes, differing topography, and varying vegetation density and land cover to determine the properties of the scene controlling the range and magnitude of the principal components. Principal component 1 was found to have high negative correlation to NDVI. Principal component 2 was found to have high positive correlation to both the solar zenith angle and the relative azimuth angle between the MISR sensor and the path of incident radiation. Principal component 3 could not be correlated to any available metric, although evidence suggests that component 3 may carry useful information. The PCA transformation proved useful at relating the changes in vegetation after a fire at the Biscuit Complex. The changes in the BRDF as sampled by MISR were expressed through the principal components, but these changes could not be directly related to changing structural characteristics of the vegetation. The goal of assessing structural characteristics of vegetation through the PCA transformation to a single metric of vegetation structure was unsuccessful. The PCA transformation of the MISR sample successfully yielded a transformation where different classes of vegetation occupied distinct and unique regions of PCA space. The first two principal components were successfully correlated to measurable and definable metrics of vegetation and solar illumination. The third principal component, for which a correlation could not be found, was suggestive of carrying unique information and merits further investigation. The transformation of multi-angular red band reflectance as presented in this study may prove to be a valuable method of estimating biomass at a global scale. With principal components correlated to measures of biomass in NDVI and to the shadowing of the ground through the angle of solar illumination, the PCA relates characteristics of vegetated scenes in a minimum of bands.