Marine environments contain substantial biological diversity, deliver vital ecosystem services, s... more Marine environments contain substantial biological diversity, deliver vital ecosystem services, supply valuable natural resources, and are a core component of our weather and climate system. However, the ocean environment is complex and ever-changing. Examining how our oceans, atmosphere, and landmasses interact would be virtually impossible without the use of a wide variety of sensors and platforms. Satellite observation sensors work in concert with in situ sensors (e.g., buoys and high-frequency radars), research vessels and ships of opportunity, aircraft, gliders (unmanned underwater robots), autonomous undersea vehicles (AUVs), drifters, animal telemetry, and tripod LiDAR to provide cohesive information regarding deep ocean, coastal, and shelf areas in order to understand the complexity, function, and structure of these systems.
Each day, millions of individual images and observations collect an enormous variety of informati... more Each day, millions of individual images and observations collect an enormous variety of information about the Earth’s surface and subsurface. This routine surveillance enables the monitoring and modeling of ecosystem health, detecting seismic activity, identifying surface vegetation, promoting sustainable agriculture, and characterizing the physical and social vulnerability of human settlements.
The use of remote sensing perhaps goes all the way back to prehistoric times when the early man s... more The use of remote sensing perhaps goes all the way back to prehistoric times when the early man stood on a platform in front of his cave and glanced at the surrounding landscape (late Robert N. Colwell, UC Berkeley). These humans were remotely sensing the features in the landscape to determine the best places to gather food and water and how to avoid becoming a food for the other inhabitants of the landscape. The term “photography” is derived from two Greek words meaning “light” (phos) and “writing” (graphein) (late John E. Estes, UC Santa Barbara). All cameras and sensors utilize the same concept of light entering a camera or a sensor and being recorded on a film or on a digital media.
ABSTRACT We describe a process for developing an index of biotic integrity (IBI) for resident fis... more ABSTRACT We describe a process for developing an index of biotic integrity (IBI) for resident fish communities in an ecoregion that exhibits low natural species richness. From 1990 to 2006, fish community samples were collected by the North Carolina Division of Water Quality (NCDWQ) at 36 sample sites in the Cape Fear, Lumber, and Yadkin river basins within the Sandhills region of North Carolina. The NCDWQ does not currently have an IBI capable of distinguishing significant differences between reference and non-reference streams. To develop a more robust method of measuring responses to anthropogenic disturbance, we delineated contributing watersheds for each of the 36 sample sites using a geographic information system, hydrologic modeling, and 20-foot-resolution digital elevation models derived from light-detection and ranging data. The 2001 National Land Cover Database (NLCD) and in situ habitat data were used to determine various land-use/land-cover and hydrologic variables within each watershed. These variables were then used to select the sites with absolute minimal anthropogenic impacts. We used the Kruskal-Wallis test to identify 11 fish-community metrics, 2 chemical metrics, and 9 individual species that were significantly different between reference and non-reference sites. Of the final 15 metrics, only 3 exhibited higher values in reference streams. Our results demonstrate that the abundance and richness of the Sandhills fish fauna are greater in areas more highly impacted by anthropogenic activities. By automating the process by which reference sites are chosen, we were able to produce a multi-metric IBI that reflects the varying levels of anthropogenic impacts on wadeable streams in the Sandhills.
Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems... more Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/À30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.
The Haw River provides drinking water to nearly one million people living in and around the citie... more The Haw River provides drinking water to nearly one million people living in and around the cities of Greensboro, Burlington, Chapel Hill, Cary, and Durham, and is home to a variety of fish and wildlife, including blue heron, bald eagle, beaver, deer, otter, largemouth and smallmouth bass, bowfin, crappie, carp, bluegill, and the endangered Cape Fear shiner and an assortment of rare freshwater mussel species.
Digital image processing, post-processing, and data integration techniques as applied to airborne... more Digital image processing, post-processing, and data integration techniques as applied to airborne and satellite remotely sensed data for the purpose of extracting useful Earth resources information will be discussed in this chapter. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: • Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems • The most widely accepted indices and land use/land cover classification schemes • Post-processing techniques such as filtering and change detection • Accuracy assessment and validation of results • Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes
ABSTRACT The main objective of this chapter is to focus on the digital image processing, post-pro... more ABSTRACT The main objective of this chapter is to focus on the digital image processing, post-processing, and data integration techniques as applied to remotely sensed data for the purpose of extracting useful earth resources information. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems The most widely accepted indices and land use/land cover classification schemes Post-processing techniques such as filtering and change detection Accuracy assessment and validation of results Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes
ABSTRACT The main objective of this chapter is to focus on the digital preprocessing and data red... more ABSTRACT The main objective of this chapter is to focus on the digital preprocessing and data reduction techniques as applied to remotely sensed data for the purpose of extracting useful Earth resources information. The image processing and post-processing tools are described in the next chapter. The concepts discussed in this chapter include: Image acquisition considerations including currently available remotely sensed data Image characteristics in terms of spatial, spectral, radiometric, and temporal resolutions Preprocessing techniques such as geometric distortion removals, atmospheric correction algorithms, image registration, enhancement, masking, and data transformations Data reduction, fusion, and integration techniques International policies governing acquisition and distribution of remotely sensed data
Page 1. Chapter 4 Using Remote Sensing for Terrestrial Applications Every day, literally millions... more Page 1. Chapter 4 Using Remote Sensing for Terrestrial Applications Every day, literally millions of individual images and observations are collected, allowing the ability to examine, monitor, and model ecosystem health, assess ...
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrat... more the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
In the previous chapters, we have discussed how the scientific community, government agencies, no... more In the previous chapters, we have discussed how the scientific community, government agencies, nongovernmental organizations (NGOs), private industry, and the general public use the wealth of information provided by airborne and satellite remote sensing data. We have presented specific examples of its cost-effective and timely use in a wide range of disciplines including engineering, forestry, geology, public health, archaeology, humanitarian aid, natural resources, and geography. Finally, we explored the linkages between remote sensing, geographical information systems, and spatial modeling. It is this continued fusion of remote sensing and big data science where the future of remote sensing lies.
Submerged Aquatic Vegetation (SAV) is an important component in any estuarine ecosystem. As such,... more Submerged Aquatic Vegetation (SAV) is an important component in any estuarine ecosystem. As such, it is regulated by federal and state agencies as a jurisdictional resource, where impacts to SAV are compensated through mitigation. Historically, traditional detection methodologies have been proven to be ineffective or inappropriate for SAV mitigation over very large areas. These tasks are further complicated in that the location and density of SAV can change from year to year depending on variances in weather and water quality. Satellite remote sensing holds great promise for providing a labor and cost-effective means of monitoring and quantifying SAV distribution. For this analysis, sensor specific models based on multinomial logit procedures proved to be the best approach for predicting SAV presence or absence. No models could be developed for low distribution occurrence categories due to a low ratio of events to non-events. Statistical automated selection methods were developed to...
Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often includ... more Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often including large quantities of redundant points. Because of these large memory requirements, practitioners often use decimation to reduce the number of points used to create models. This paper introduces a novel approach to improve decimation, thereby reducing the total count of ground points in a Lidar dataset while retaining more accuracy than Random Decimation. This reduction improves efficiency of downstream processes while maintaining output quality nearer to the undecimated dataset. Points are selected for retention based on their discrete curvature values computed from the mesh geometry of the TIN model of the points. Points with higher curvature values are preferred for retention in the resulting point cloud. We call this technique Curvature Weighted Decimation (CWD). We implement CWD in a new free, open-source software tool, CogoDN, which is also introduced in this paper. We evaluate t...
Marine environments contain substantial biological diversity, deliver vital ecosystem services, s... more Marine environments contain substantial biological diversity, deliver vital ecosystem services, supply valuable natural resources, and are a core component of our weather and climate system. However, the ocean environment is complex and ever-changing. Examining how our oceans, atmosphere, and landmasses interact would be virtually impossible without the use of a wide variety of sensors and platforms. Satellite observation sensors work in concert with in situ sensors (e.g., buoys and high-frequency radars), research vessels and ships of opportunity, aircraft, gliders (unmanned underwater robots), autonomous undersea vehicles (AUVs), drifters, animal telemetry, and tripod LiDAR to provide cohesive information regarding deep ocean, coastal, and shelf areas in order to understand the complexity, function, and structure of these systems.
Each day, millions of individual images and observations collect an enormous variety of informati... more Each day, millions of individual images and observations collect an enormous variety of information about the Earth’s surface and subsurface. This routine surveillance enables the monitoring and modeling of ecosystem health, detecting seismic activity, identifying surface vegetation, promoting sustainable agriculture, and characterizing the physical and social vulnerability of human settlements.
The use of remote sensing perhaps goes all the way back to prehistoric times when the early man s... more The use of remote sensing perhaps goes all the way back to prehistoric times when the early man stood on a platform in front of his cave and glanced at the surrounding landscape (late Robert N. Colwell, UC Berkeley). These humans were remotely sensing the features in the landscape to determine the best places to gather food and water and how to avoid becoming a food for the other inhabitants of the landscape. The term “photography” is derived from two Greek words meaning “light” (phos) and “writing” (graphein) (late John E. Estes, UC Santa Barbara). All cameras and sensors utilize the same concept of light entering a camera or a sensor and being recorded on a film or on a digital media.
ABSTRACT We describe a process for developing an index of biotic integrity (IBI) for resident fis... more ABSTRACT We describe a process for developing an index of biotic integrity (IBI) for resident fish communities in an ecoregion that exhibits low natural species richness. From 1990 to 2006, fish community samples were collected by the North Carolina Division of Water Quality (NCDWQ) at 36 sample sites in the Cape Fear, Lumber, and Yadkin river basins within the Sandhills region of North Carolina. The NCDWQ does not currently have an IBI capable of distinguishing significant differences between reference and non-reference streams. To develop a more robust method of measuring responses to anthropogenic disturbance, we delineated contributing watersheds for each of the 36 sample sites using a geographic information system, hydrologic modeling, and 20-foot-resolution digital elevation models derived from light-detection and ranging data. The 2001 National Land Cover Database (NLCD) and in situ habitat data were used to determine various land-use/land-cover and hydrologic variables within each watershed. These variables were then used to select the sites with absolute minimal anthropogenic impacts. We used the Kruskal-Wallis test to identify 11 fish-community metrics, 2 chemical metrics, and 9 individual species that were significantly different between reference and non-reference sites. Of the final 15 metrics, only 3 exhibited higher values in reference streams. Our results demonstrate that the abundance and richness of the Sandhills fish fauna are greater in areas more highly impacted by anthropogenic activities. By automating the process by which reference sites are chosen, we were able to produce a multi-metric IBI that reflects the varying levels of anthropogenic impacts on wadeable streams in the Sandhills.
Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems... more Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/À30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.
The Haw River provides drinking water to nearly one million people living in and around the citie... more The Haw River provides drinking water to nearly one million people living in and around the cities of Greensboro, Burlington, Chapel Hill, Cary, and Durham, and is home to a variety of fish and wildlife, including blue heron, bald eagle, beaver, deer, otter, largemouth and smallmouth bass, bowfin, crappie, carp, bluegill, and the endangered Cape Fear shiner and an assortment of rare freshwater mussel species.
Digital image processing, post-processing, and data integration techniques as applied to airborne... more Digital image processing, post-processing, and data integration techniques as applied to airborne and satellite remotely sensed data for the purpose of extracting useful Earth resources information will be discussed in this chapter. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: • Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems • The most widely accepted indices and land use/land cover classification schemes • Post-processing techniques such as filtering and change detection • Accuracy assessment and validation of results • Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes
ABSTRACT The main objective of this chapter is to focus on the digital image processing, post-pro... more ABSTRACT The main objective of this chapter is to focus on the digital image processing, post-processing, and data integration techniques as applied to remotely sensed data for the purpose of extracting useful earth resources information. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems The most widely accepted indices and land use/land cover classification schemes Post-processing techniques such as filtering and change detection Accuracy assessment and validation of results Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes
ABSTRACT The main objective of this chapter is to focus on the digital preprocessing and data red... more ABSTRACT The main objective of this chapter is to focus on the digital preprocessing and data reduction techniques as applied to remotely sensed data for the purpose of extracting useful Earth resources information. The image processing and post-processing tools are described in the next chapter. The concepts discussed in this chapter include: Image acquisition considerations including currently available remotely sensed data Image characteristics in terms of spatial, spectral, radiometric, and temporal resolutions Preprocessing techniques such as geometric distortion removals, atmospheric correction algorithms, image registration, enhancement, masking, and data transformations Data reduction, fusion, and integration techniques International policies governing acquisition and distribution of remotely sensed data
Page 1. Chapter 4 Using Remote Sensing for Terrestrial Applications Every day, literally millions... more Page 1. Chapter 4 Using Remote Sensing for Terrestrial Applications Every day, literally millions of individual images and observations are collected, allowing the ability to examine, monitor, and model ecosystem health, assess ...
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrat... more the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
In the previous chapters, we have discussed how the scientific community, government agencies, no... more In the previous chapters, we have discussed how the scientific community, government agencies, nongovernmental organizations (NGOs), private industry, and the general public use the wealth of information provided by airborne and satellite remote sensing data. We have presented specific examples of its cost-effective and timely use in a wide range of disciplines including engineering, forestry, geology, public health, archaeology, humanitarian aid, natural resources, and geography. Finally, we explored the linkages between remote sensing, geographical information systems, and spatial modeling. It is this continued fusion of remote sensing and big data science where the future of remote sensing lies.
Submerged Aquatic Vegetation (SAV) is an important component in any estuarine ecosystem. As such,... more Submerged Aquatic Vegetation (SAV) is an important component in any estuarine ecosystem. As such, it is regulated by federal and state agencies as a jurisdictional resource, where impacts to SAV are compensated through mitigation. Historically, traditional detection methodologies have been proven to be ineffective or inappropriate for SAV mitigation over very large areas. These tasks are further complicated in that the location and density of SAV can change from year to year depending on variances in weather and water quality. Satellite remote sensing holds great promise for providing a labor and cost-effective means of monitoring and quantifying SAV distribution. For this analysis, sensor specific models based on multinomial logit procedures proved to be the best approach for predicting SAV presence or absence. No models could be developed for low distribution occurrence categories due to a low ratio of events to non-events. Statistical automated selection methods were developed to...
Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often includ... more Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often including large quantities of redundant points. Because of these large memory requirements, practitioners often use decimation to reduce the number of points used to create models. This paper introduces a novel approach to improve decimation, thereby reducing the total count of ground points in a Lidar dataset while retaining more accuracy than Random Decimation. This reduction improves efficiency of downstream processes while maintaining output quality nearer to the undecimated dataset. Points are selected for retention based on their discrete curvature values computed from the mesh geometry of the TIN model of the points. Points with higher curvature values are preferred for retention in the resulting point cloud. We call this technique Curvature Weighted Decimation (CWD). We implement CWD in a new free, open-source software tool, CogoDN, which is also introduced in this paper. We evaluate t...
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