Joseph F Knight

Joseph F Knight
University of Minnesota Twin Cities | UMN · Department of Forest Resources

PhD

About

60
Publications
18,979
Reads
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2,321
Citations
Introduction
Dr. Joe Knight is a Professor in the Department of Forest Resources at the University of Minnesota. His research focuses on using geospatial science methods such as remote sensing and GIS to understand and quantify the impacts of land use on our environment and natural resources.
Additional affiliations
May 2002 - May 2007
United States Environmental Protection Agency
Position
  • Biologist
May 2002 - May 2007
United States Environmental Protection Agency
Position
  • Biologist
July 1997 - May 2002
North Carolina State University
Position
  • Research Associate
Education
July 1997 - May 2002
North Carolina State University
Field of study
  • Remote Sensing and Geographic Information Science

Publications

Publications (60)
Article
Full-text available
Invasive plant species are an increasing worldwide threat both ecologically and financially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unoccupied aircraft systems (UAS) are...
Article
Full-text available
Background Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists am...
Article
The objective of this project was to validate the efficacy of a miniature multispectral, single-sensor camera for detecting stress in deciduous juvenile tree foliage in a controlled environment. To that end, deciduous liners (one year old, nursery-grown transplants) representing five tree species (Celtis occidentalis L., Gleditsia triacanthos forma...
Article
Full-text available
Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer cost effective management tools that can be used to monitor wetlands over time, covering large areas like the Gr...
Article
Upon inhalation of spores from the fungus Blastomyces dermatitidis from the environment, humans and animals can develop the disease blastomycosis. Based on disease epidemiology, B. dermatitidis is known to be endemic in the United States and Canada around the Great Lakes and in the Ohio and Mississippi River Valleys but is starting to emerge in oth...
Preprint
Full-text available
Background: Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists a...
Article
Full-text available
Ash trees (Fraxinus spp.) are a prominent species in Minnesota forests, with an estimated 1.1 billion trees in the state, totaling approximately 8% of all trees. Ash trees are threatened by the invasive emerald ash borer (Agrilus planipennis Fairmaire), which typically results in close to 100% tree mortality within one to five years of infestation....
Article
Full-text available
The ability to predict spatially explicit nitrogen uptake (NUP) in maize (Zea mays L) during the early development stages provides clear value for making in-season nitrogen fertilizer applications that can improve NUP efficiency and reduce the risk of nitrogen loss to the environment. Aerial hyperspectral imaging is an attractive agronomic research...
Article
Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete coverage of soybean. Unmanned aerial vehicles (UAVs)...
Conference Paper
Tree management is becoming a big issue in a variety of societal domains. In recent years, historic wildfires and blackouts caused by failures in tree management have increased in both quantity and severity, resulting in many deaths and financial loses in the tens of billions of dollars. Many communities are also suffering from massive tree loss (e...
Article
Full-text available
Class ambiguity refers to the phenomenon whereby similar features correspond to different classes at different locations. Given heterogeneous geographic data with class ambiguity, the spatial ensemble learning (SEL) problem aims to find a decomposition of the geographic area into disjoint zones such that class ambiguity is minimized and a local cla...
Article
Building footprints are among the most predominant features in urban areas, and provide valuable information for urban planning, solar energy suitability analysis, etc. We aim to automatically and rapidly identify building footprints by leveraging deep learning techniques and the increased availability of remote sensing datasets at high spatial res...
Conference Paper
Full-text available
Given remote sensing datasets in a spatial domain, we aim to detect geospatial objects with minimum bounding rectangles (i.e., angle-aware) leveraging deep learning frameworks. Geospatial objects (e.g., buildings, vehicles, farms) provide meaningful information for a variety of societal applications, including urban planning, census, sustainable de...
Article
Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio‐environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across nort...
Article
Full-text available
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 a...
Conference Paper
Full-text available
Class ambiguity refers to the phenomenon whereby samples with similar features belong to different classes at different locations. Given heterogeneous geographic data with class ambiguity, the spatial ensemble learning (SEL) problem aims to find a decomposition of the geographic area into disjoint zones such that class ambiguity is minimized and a...
Article
Modern climate change in Alaska has resulted in widespread thawing of permafrost, increased fire activity, and extensive changes in vegetation characteristics that have significant consequences for socio-ecological systems. Despite observations of the heightened sensitivity of these systems to change, there has not been a comprehensive assessment o...
Article
Full-text available
Object-based image analysis was used to map land use in the Panxie coal mining area, East China, where long-term underground coal mines have been exploited since the 1980s. A rule-based classification approach was developed for a Pleiades image to identify the desired land use classes, and the same rule-based classification strategies, after the th...
Article
Full-text available
Fez is the most ancient of the imperial cities of Morocco. In Fez the rate of population growth has been spectacular in recent times (484 300 inhabitants in 1982 and 1 129 768 in 2014). The accelerated rate of population growth has generated a large urban sprawl in all its forms and serious environmental problems. In this research, we have analyzed...
Article
Full-text available
Long-term, large-scale underground coal mining activities in Huainan, China, have damaged the stability of the overlying rocks, resulting in large waterlogged areas. The water quality in these areas is compromised by agricultural pollutants and discharge of untreated waste. In this study, chlorophyll-a (Chl-a) concentrations were estimated in two t...
Article
Full-text available
Wetlands are dynamic in space and time, providing varying ecosystem services. Field reference data for both training and assessment of wetland inventories in the State of Minnesota are typically collected as GPS points over wide geographical areas and at infrequent intervals. This status-quo makes it difficult to keep updated maps of wetlands with...
Article
Full-text available
Comprehensive wetland inventories are an essential tool for wetland management, but developing and maintaining an inventory is expensive and technically challenging. Funding for these efforts has also been problematic. Here we describe a large-area application of a semi-automated process used to update a wetland inventory for east-central Minnesota...
Chapter
Full-text available
This chapter addresses object-based image analysis (OBIA) and other emerging methods for mapping wetlands using remotely sensed and ancillary data. This treatment includes an introduction to OBIA and decision tree techniques, a history of the development of OBIA methods in wetland mapping, and four case studies describing recent wetland mapping res...
Conference Paper
Full-text available
Given a spatial raster framework F, a set of explanatory feature maps, training and test samples with class labels on F, as well as a base classifier type, the problem of ensemble learning in raster classification aims to learn a collection of base classifiers to minimize classification errors. The problem has important societal applications such a...
Article
The Southern Ocean is one of the most rapidly changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically important krill and fish. Because sea ice loss is expected to be accompanied by declines in krill and fish predators, decoupling the effects of climate and anthropogenic changes on these predat...
Conference Paper
Full-text available
Combining historical white and black aerial photo with more recent LiDAR and high resolution imagery, this research mapped wetland with high accuracy from 1930s to 2010s in object-based image analysis approach (OBIA). This research shows good potential in combining grey level information with OBIA method to map accurate historical wetland. We found...
Conference Paper
A short-term precipitation event near Duluth, Minnesota, USA caused flooding, erosion, and deposition that impacted the natural and anthropogenic landscape. This study quantified these impacts with an object-based image analysis approach that integrated multi-temporal lidar and optical data. Flooding inundated 3% of the study area and impacted 28%...
Article
This study investigated the effectiveness of using high resolution data to map wetlands in three ecoregions in Minnesota. High resolution data included multispectral leaf-off aerial imagery and lidar elevation data. These data were integrated using an Object-Based Image Analysis (OBIA) approach. Results for each study area were compared against fie...
Article
Topography has been traditionally used as a surro-gate to model spatial patterns of water distribution and variation of hydrological conditions. In this study, we investigated the use of light detection and ranging (lidar) data to derive two Single Flow Direction (SFD) and five Multiple Flow Direction (MFD) algorithms in the application of the comp...
Article
Full-text available
Given learning samples from a raster data set, spatial decision tree learning aims to find a decision tree classifier that minimizes classification errors as well as salt-and-pepper noise. The problem has important societal applications such as land cover classification for natural resource management. However, the problem is challenging due to the...
Article
Full-text available
Given a raster spatial framework, as well as training and test sets, the spatial decision tree learning (SDTL) problem aims to minimize classification errors as well as salt-and-pepper noise. The SDTL problem is important due to many societal applications such as land cover classification in remote sensing. However, the SDTL problem is challenging...
Article
Full-text available
Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training...
Article
Full-text available
Accurate wetland maps are of critical importance for preserving the ecosystem functions provided by these valuable landscape elements. Though extensive research into wetland mapping methods using remotely sensed data exists, questions remain as to the effects of data type and classification scheme on classification accuracy when high spatial resolu...
Article
Full-text available
Given learning samples from a spatial raster dataset, the geographical classification problem aims to learn a decision tree classifier that minimizes classification errors as well as salt-n-pepper noise. The problem is important in many applications, such as land cover classification in remote sensing and lesion classification in medical diagnosis....
Data
Full-text available
Maximum parsimony trees of individual MLST loci. Download Figure S1, PDF file, 1.5 MB.
Data
Geographical distribution of culture-positive patients presenting at Mulago Hospital in Kampala, Uganda. No association between geographic location and strain genotype was observed. (A) Districts within Uganda with culture-positive patients. (B) Parishes within the Kampala district with culture-positive patients. Download Figure S2, PDF file, 1.3 M...
Data
Immune response of healthy volunteers to ex vivo stimulation with cell wall antigens. (A) Production of IL-4, IL-10, IFN-γ, and IL-8 cytokines in response to cell wall antigen from a representative clonal cluster strain within each Burst group. Antigens were standardized to a final assay concentration of 5 µg of protein per well as determined by th...
Data
Full-text available
Primers, PCR conditions, and sequence ends used for MLST analysis
Data
Full-text available
Melanin production. (A) Melanization of representative UgCl strains relative to controls on niger seed and l-DOPA media. (B) Temporal representation of strain melanization on niger seed and l-DOPA media using K-means clustering of melanin production from 12 to 48 h. Download Figure S3, PDF file, 1 MB.
Article
Full-text available
Unlabelled: In sub-Saharan Africa, cryptococcal meningitis (CM) continues to be a predominant cause of AIDS-related mortality. Understanding virulence and improving clinical treatments remain important. To characterize the role of the fungal strain genotype in clinical disease, we analyzed 140 Cryptococcus isolates from 111 Ugandans with AIDS and...
Article
Full-text available
Monitoring of water clarity trends is necessary for water resource managers. Remote sensing based methods are well suited for monitoring clarity in water bodies such as the inland lakes in Minnesota, United States. This study evaluated the potential of using imagery from NASA’s MODIS sensor to study intra-annual variations in lake clarity. MODIS re...
Article
Accurate and current wetland maps are critical tools for water resources management, however, many existing wetland maps were created by manual interpretation of one aerial image for each area of interest. As such, these maps do not inherently contain information about the intra- and interannual hydrologic cycles of wetlands, which is important for...
Article
Full-text available
Mapping impervious surfaces over regional or continental scale study areas with high spatial resolution imagery is difficult due to the cost and time involved in processing the large number of images required. This study investigated the benefits of using the coarse spatial resolution, high temporal resolution MODIS sensor to produce impervious sur...
Article
Full-text available
The monitoring of water colour parameters can provide an important diagnostic tool for the assessment of aquatic ecosystem condition. Remote sensing has long been used to effectively monitor chlorophyll concentrations in open ocean systems; however, operational monitoring in coastal and estuarine areas has been limited because of the inherent compl...
Article
Full-text available
Monitoring the locations and distributions of land-cover changes is important for establishing links between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be performance limited for applications in biologically complex systems. This stu...
Article
Full-text available
Currently available land cover data sets for large geographic regions are produced on an intermittent basis and are often dated. Ideally, annually updated data would be available to support environmental status and trends assessments and eco-system process modeling. This research examined the potential for vegetation phe-nology–based land cover cla...
Article
Full-text available
Land-cover (LC) maps derived from remotely sensed data are often presented using a minimum mapping unit (MMU) to characterize a particular landscape theme of interest. The choice of an MMU that is appropriate for the projected use of a classification is an important consideration. The objective of this experiment was to determine the effect of MMU...
Article
Full-text available
Land-cover (LC) maps derived from remotely sensed data are often presented using a minimum mapping unit (MMU) to characterize a particular landscape theme of interest. The choice of an MMU that is appropriate for the projected use of a classification is an important consideration. The objective of this experiment was to determine the effect of MMU...
Article
Keywords: distances, inter-class, spectral, thematic maps, assessment, accuracy. Thesis (Ph. D.)--North Carolina State University. Includes bibliographical references (p. 92-99). Includes vita.
Article
The goal of this research is to develop a new approach to remote sensing thematic accuracy assessment in which the spectral distances between the classes in a thematic classification are used as inputs to the error estimation process. The conceptual basis for this new approach is that the confusion of relatively spectrally different classes represe...
Article
Full-text available
A "Virtual Field Reference Database (VFRDB)" was developed using field measurement and digital imagery (camera) data collected at 999 sites in the Neuse River Basin, North Carolina. The VFmB was designed to support detailed assessments of remote-sensor-derived land-coverlland-use (LCLU) products by providing a robust database characterizing represe...
Article
Full-text available
A "Virtual Field Reference Database (VFRDB)" was developed using field measurement and digital imagery (camera) data collected at 999 sites in the Neuse River Basin, North Carolina. The V F m B was designed to support detailed assessments of remote-sensor-derived land-cover/land-use (LCLU) products by providing a robust database characterizing repr...
Conference Paper
Full-text available
The Multi-Resolution Land Characteristic (MRLC) Consortium, composed of several U.S. Government agencies, sponsored the creation of the National Land Cover Data (NLCD). This dataset provides a consistent land cover classification system for the lower forty-eight states. It is based on thirty meter spatial resolution Landsat Thematic Mapper (TM) sat...
Article
Full-text available
Thematic classifications based on remotely sensed data are frequently used in decision making for businesses, governments, and individuals. As such, it is very important to provide an estimate of the accuracy of these classifications. The standard point-for-point comparison method of accuracy assessment when using aerial photos as the reference sou...

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Projects (2)
Project
Landscape characteristics of watersheds can be important determinants of water quality and consequently fish abundance and distribution. Remotely sensed data can therefore yield insight into fish ecology where monitoring data are lacking. We are investigating patterns of cold water stream fish distribution across the Great Lakes Basin as part of a Great Lakes Restoration Initiative-funded project.