The Urban Morphology Of Hyderabad, India: A Historical Geographic Analysis,
2020
Western Michigan University
The Urban Morphology Of Hyderabad, India: A Historical Geographic Analysis, Kevin B. Haynes
Masters Theses
Hyderabad, India has undergone tremendous change over the last three centuries. The study seeks to understand how and why Hyderabad transitioned from a north-south urban morphological directional pattern to east-west during from 1687 to 2019. Satellite-based remote sensing will be used to measure the extent and land classifications of the city throughout the twentieth and twenty-first century using a geographic information science and historical-geographic approach. This approach provides the basis for a structured archival historical-geographic analysis. Focusing on Hyderabad, India from 1687 to 2019, the objectives of this research are to: (1) delineate and quantify the geographic extent of built-up …
Deep Learning For Land Cover Classification Using Only A Few Bands,
2020
Old Dominion University
Deep Learning For Land Cover Classification Using Only A Few Bands, Chiman Kwan, Bulent Ayhan, Bence Budavari, Yan Lu, Daniel Perez, Jiang Li, Sergio Bernabe, Antonio Plaza
Electrical & Computer Engineering Faculty Publications
There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and thus help improve the land cover classification performance. Although hyperspectral data with hundreds of channels provide detailed spectral signatures, the curse of dimensionality might lead to degradation in the land cover classification performance. Moreover, in some practical applications, hyperspectral data may not be available due to cost, data storage, or bandwidth issues, and RGB and near infrared (NIR) could be the only image bands …
Synergistic Use Of Remote Sensing And Modeling For Estimating Net Primary Productivity In The Red Sea With Vgpm, Eppley-Vgpm, And Cbpm Models Intercomparison,
2020
Chapman University
Synergistic Use Of Remote Sensing And Modeling For Estimating Net Primary Productivity In The Red Sea With Vgpm, Eppley-Vgpm, And Cbpm Models Intercomparison, Wenzhao Li, Surya Prakash Tiwari, Hesham El-Askary, Mohamed Ali Qurban, Vassilis Amiridis, K. P. Manikandan, Michael J. Garay, Olga V. Kalashnikova, Thomas C. Piechota, Daniele C. Struppa
Mathematics, Physics, and Computer Science Faculty Articles and Research
Primary productivity (PP) has been recently investigated using remote sensing-based models over quite limited geographical areas of the Red Sea. This work sheds light on how phytoplankton and primary production would react to the effects of global warming in the extreme environment of the Red Sea and, hence, illuminates how similar regions may behave in the context of climate variability. study focuses on using satellite observations to conduct an intercomparison of three net primary production (NPP) models--the vertically generalized production model (VGPM), the Eppley-VGPM, and the carbon-based production model (CbPM)--produced over the Red Sea domain for the 1998-2018 time period. …
Samsts Satellite Time Series Gap Filling Source Codes - Landsat,
2020
South Dakota State University
Samsts Satellite Time Series Gap Filling Source Codes - Landsat, Lin Yan, David P. Roy
SAMSTS Satellite Time Series Gap Filling Source Codes
- SAMSTS is open-source software (coded in C) for gap filling of Landsat multispectral time series developed by Drs. Lin Yan and David Roy.
- SAMSTS 1.1.1 release includes source codes, user manual and test data.
- The test data are year-2013 time series of Landsat 7 ETM+ and Landsat 8 OLI ARD surface reflectance products (http://landsat.usgs.gov/ard) over Kansas and Iowa. Each ARD tile is composed of 5000 x 5000 30m pixels with six bands (blue, red, green, NIR, SWIR 1, SWIR 2).
- Major Software functionality:
- Automatic gap filling of Landsat multispectral time series caused by clouds, shadows, SLC-off (for Landsat-7 …
When Nature Invades: Resident Perceptions Of The Austerity-Driven "Rewilding" Of An Urban Park In Rock Island, Illinois,
2020
Augustana College, Rock Island Illinois
When Nature Invades: Resident Perceptions Of The Austerity-Driven "Rewilding" Of An Urban Park In Rock Island, Illinois, Christian S. B. Elliott
Anthropology: Student Scholarship & Creative Works
In an era of rapid urbanization, changing climate, and increasing political division, parks represent increasingly important places for urban residents to interact with and feel connected to the natural environment and receive a number of mental and physical health benefits. Unfortunately, in an age of austerity politics, parks and recreation departments in Midwest Rust Belt cities often lack adequate funding to maintain such public spaces. Recently, the business-minded Rock Island, Illinois Department of Parks and Recreation has implemented a creative cost-saving management solution: “naturalizing” sections of its city parks. This interdisciplinary study uses a mixed methods approach to discover how …
A View From Above: Alternative Perspectives On Smallholder Livelihoods And Agrobiodiversity Conservation In Northern Ecuador,
2020
The University of Southern Mississippi
A View From Above: Alternative Perspectives On Smallholder Livelihoods And Agrobiodiversity Conservation In Northern Ecuador, Chris Hair
Dissertations
Food security and deintensification of agriculture are serious concerns in Latin America. Agriculture, especially at small-scale subsistence levels, is hard work, and comes with some economic and physical risk. Transitions from traditional multi-cropping to mono-cropping systems introduce two particular risks that are new to most smallholders: (1) the loss of agricultural diversity and (2) the potential for widespread failure when focusing on the cultivation of a single crop. This research explores how Small Unmanned Aerial Systems (sUAS), or drones, can be used for rapid inventories of crop diversity and to enhance crop management techniques on small-scale farms. In the community …
How Much Variation In Land Surface Phenology Can Climate Oscillation Modes Explain At The Scale Of Mountain Pastures In Kyrgyzstan?,
2020
South Dakota State University
How Much Variation In Land Surface Phenology Can Climate Oscillation Modes Explain At The Scale Of Mountain Pastures In Kyrgyzstan?, Monika A. Tomaszewska, Geoffrey M. Henebry
NASA Land-Cover Land-Use Change Data Sets
Climate oscillation modes can shape weather across the globe due to atmospheric teleconnections. We built on the findings of a recent study to assess whether the impacts of teleconnections are detectable and significant in the early season dynamics of highland pastures across five rayons in Kyrgyzstan. Specifically, since land surface phenology (LSP) has already shown to be influenced by snow cover seasonality and terrain, we investigated here how much more explanatory and predictive power information about climatic oscillation modes might add to explain variation in LSP. We focused on seasonal values of five climate oscillation indices that influence vegetation dynamics …
An Evaluation Of Unmanned Aircraft Systems' Ability To Assess Stripe Rust In Large Wheat Breeding Nursies,
2020
University of Arkansas, Fayetteville
An Evaluation Of Unmanned Aircraft Systems' Ability To Assess Stripe Rust In Large Wheat Breeding Nursies, Jamison T. Murry
Graduate Theses and Dissertations
Stripe Rust (Puccinia striiformis f. sp. tritici) is a foliar disease that significantly impacts global wheat production, and resistant cultivars provide the most efficient method of control. High-throughput phenotyping using unmanned aircraft systems (UAS) offers a potentially more efficient method for field-based phenotyping compared to visual assessment. Here we tested the ability of remote sensing to predict stripe rust severity in a diverse population of 594 soft red winter wheat lines, planted in single-rows, and evaluated them by visually rating stripe rust intensity and remotely using the dark green color index (DGCI), normalized difference vegetation index (NDVI) and blue NDVI. …
Characterizing The Impacts Of The Invasive Hemlock Woolly Adelgid On The Forest Structure Of New England,
2020
University of Massachusetts Boston
Characterizing The Impacts Of The Invasive Hemlock Woolly Adelgid On The Forest Structure Of New England, Peter Brehm Boucher
Graduate Doctoral Dissertations
Climate change is raising winter temperatures in the Northeastern United States, both expanding the range of an invasive pest, the hemlock woolly adelgid (HWA; Adelges tsugae), and threatening the survival of its host species, eastern hemlock (Tsuga canadensis). As a foundation species, hemlock trees underlie a distinct network of ecological, biogeochemical, and structural systems that will likely disappear as the HWA infestation spreads northward. Remote sensing can offer new perspectives on this regional transition, recording the progressive loss of an ecological foundation species and the transition of evergreen hemlock forest to mixed deciduous forest over the course of the infestation. …
Changes In Land Use Land Cover (Lulc), Surface Water Quality And Modelling Surface Discharge In Beaver Creek Watershed, Northeast Tennessee And Southwest Virginia,
2020
East Tennessee State University
Changes In Land Use Land Cover (Lulc), Surface Water Quality And Modelling Surface Discharge In Beaver Creek Watershed, Northeast Tennessee And Southwest Virginia, Tosin James
Electronic Theses and Dissertations
Beaver Creek is an impaired streams that is not supporting its designated use for recreation due to Escherichia coli (E.coli), and sediment. To address this problem, this thesis was divided into two studies.
The first study explored changes in Land Use Land Cover (LULC), and its impact on surface water quality. Changes in E.coli load between 1997-2001 and 2014-2018 were analyzed. Also, Landsat data of 2001, and 2018 were examined in Terrset 18.31. Mann-Whitney test only showed a significant reduction in E.coli for one site. Negative correlation was established between E.coli load, and Developed LULC, Forest LULC, and …
Archaeological, Geophysical, And Geospatial Analysis At David Crockett Birthplace State Park, In Upper East Tennessee,
2020
East Tennessee State University
Archaeological, Geophysical, And Geospatial Analysis At David Crockett Birthplace State Park, In Upper East Tennessee, Reagan Cornett
Electronic Theses and Dissertations
A geophysical survey was conducted at David Crockett Birthplace State Park (40GN205, 40GN12) using ground-penetrating radar (GPR) and magnetometry. The data indicated multiple levels of occupation that were investigated by Phase II and Phase III archaeological excavations. New cultural components were discovered, including the remnants of a Protohistoric Native American structure containing European glass trade beads and Middle Woodland artifacts that suggest trade with Hopewell groups from Ohio. A circular Archaic hearth was uncovered at one meter below surface and similar deep anomalies were seen in the GPR data at this level. A semi-automated object-based image analysis (OBIA) was implemented …
Earth Observation And Cloud Computing In Support Of Two Sustainable Development Goals For The River Nile Watershed Countries,
2020
Chapman University
Earth Observation And Cloud Computing In Support Of Two Sustainable Development Goals For The River Nile Watershed Countries, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa
Mathematics, Physics, and Computer Science Faculty Articles and Research
In September 2015, the members of United Nations adopted the 2030 Agenda for Sustainable Development with universal applicability of 17 Sustainable Development Goals (SDGs) and 169 targets. The SDGs are consequential for the development of the countries in the Nile watershed, which are affected by water scarcity and experiencing rapid urbanization associated with population growth. Earth Observation (EO) has become an important tool to monitor the progress and implementation of specific SDG targets through its wide accessibility and global coverage. In addition, the advancement of algorithms and tools deployed in cloud computing platforms provide an equal opportunity to use EO …
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach.,
2020
Louisiana State University and Agricultural and Mechanical College
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach., Bienvenu Sedin Massamba
LSU Master's Theses
The Antarctic surface snowmelt is prone to the polar climate and is common in its coastal regions. With about 90 percent of the planet's glaciers, if all of the Antarctica glaciers melted, sea levels will rise about 58 meters around the planet. The development of an effective automated ice-sheet snowmelt monitoring system is therefore crucial.
Microwave remote sensing instruments, on the one hand, are very sensitive to snowmelt and can see day and night through clouds, allowing us to distinguish melting from dry snow and to better understand when, where, and for how long melting has taken place. On the …
Learning Set Representations For Lwir In-Scene Atmospheric Compensation,
2020
Air Force Institute of Technology
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Faculty Publications
Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …
Land Surface Phenology In The Highland Pastures Of Montane Central Asia: Interactions With Snow Cover Seasonality And Terrain Characteristics,
2020
South Dakota State University
Land Surface Phenology In The Highland Pastures Of Montane Central Asia: Interactions With Snow Cover Seasonality And Terrain Characteristics, Monika A. Tomaszewska, Lan H. Nguyen, Geoffrey Henebry
NASA Land-Cover Land-Use Change Data Sets
Many studies have shown that high elevation environments are among very sensitive to climatic changes and where impacts are exacerbated. Across Central Asia, which is especially vulnerable to climate change due to aridity, the ability of global climate projections to capture the complex dynamics of mountainous environments is particularly limited. Over montane Central Asia, agropastoralism constitutes a major portion of the rural economy. Extensive herbaceous vegetation forms the basis of rural economies in Kyrgyzstan. Here we focus on snow cover seasonality and the effects of terrain on phenology in highland pastures using remote sensing data for 2001–2017. First, we describe …
Mapping Kenyan Grassland Heights Across Large Spatial Scales With Combined Optical And Radar Satellite Imagery,
2020
Michigan State University
Mapping Kenyan Grassland Heights Across Large Spatial Scales With Combined Optical And Radar Satellite Imagery, Olivia S. B. Spagnuolo, Julie C. Jarvey, Michael Battaglia, Zachary Laubach, Mary Ellen Miller, Kay E. Holekamp, Laura Bourgeau-Chavez
Michigan Tech Publications, Part 1
Grassland monitoring can be challenging because it is time-consuming and expensive to measure grass condition at large spatial scales. Remote sensing offers a time- and cost-effective method for mapping and monitoring grassland condition at both large spatial extents and fine temporal resolutions. Combinations of remotely sensed optical and radar imagery are particularly promising because together they can measure differences in moisture, structure, and reflectance among land cover types. We combined multi-date radar (PALSAR-2 and Sentinel-1) and optical (Sentinel-2) imagery with field data and visual interpretation of aerial imagery to classify land cover in the Masai Mara National Reserve, Kenya using …
Unveiling Shadows: How To Optimize Shadow Detection In Hsi Through Combination Of Lidar And Histogram Thresholding,
2020
University of Northern Iowa
Unveiling Shadows: How To Optimize Shadow Detection In Hsi Through Combination Of Lidar And Histogram Thresholding, Maritza Salinas
Research in the Capitol
From “multi-” to “hyper-” spectral, remote sensing capacities have improved tremendously in how we measure Earth’s unique signatures. Unfortunately, shadow detection and correction remain an issue in most images, especially those with high spatial resolution. Shadows result when direct sun light is obstructed and the spectral reflectance values for pixels in those regions decrease. Many successful approaches exist to correct this blue skew to shorter wavelengths, but it can be daunting to truly assess which approach to employ since each require different levels of priori knowledge. This research attempts to generate and cross-validate shadow masks using popular GIS software.The goal …
Changes In Atmospheric, Meteorological, And Ocean Parameters Associated With The 12 January 2020 Taal Volcanic Eruption,
2020
China Earthquake Administration
Changes In Atmospheric, Meteorological, And Ocean Parameters Associated With The 12 January 2020 Taal Volcanic Eruption, Feng Jing, Akshansa Chauhan, Ramesh P. Singh, Prasanjit Dash
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The Taal volcano erupted on 12 January 2020, the first time since 1977. About 35 mild earthquakes (magnitude greater than 4.0) were observed on 12 January 2020 induced from the eruption. In the present paper, we analyzed optical properties of volcanic aerosols, volcanic gas emission, ocean parameters using multi-satellite sensors, namely, MODIS (Moderate Resolution Imaging Spectroradiometer), AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) and ground observations, namely, Argo, and AERONET (AErosol RObotic NETwork) data. Our detailed analysis shows pronounced changes in all the parameters, which mainly occurred in the western and south-western regions because the …
Is It Possible To Discern Striga Weed (Striga Hermonthica) Infestation Levels In Maize Agro-Ecological Systems Using In-Situ Spectroscopy?,
2020
International Centre of Insect Physiology and Ecology Nairobi
Is It Possible To Discern Striga Weed (Striga Hermonthica) Infestation Levels In Maize Agro-Ecological Systems Using In-Situ Spectroscopy?, Bester Tawona Mudereri, Timothy Dube, Saliou Niassy, Emily Kimathi, Tobias Landmann, Zeyaur Khan, Elfatih M. Abdel-Rahman
All Peer-Reviewed Publications
The invasion by Striga in most cereal crop fields in Africa has posed a significant threat to food security and has caused substantial socioeconomic losses. Hyperspectral remote sensing is an effective means to discriminate plant species, providing possibilities to track such weed invasions and improve precision agriculture. However, essential baseline information using remotely sensed data is missing, specifically for the Striga weed in Africa. In this study, we investigated the spectral uniqueness of Striga compared to other co-occurring maize crops and weeds. We used the in-situ FieldSpec® Handheld 2™ analytical spectral device (ASD), hyperspectral data and their respective narrow-band indices …
Predicting The Spatial Suitability Distribution Of Moringa Oleifera Cultivation Using Analytical Hierarchical Process Modelling,
2020
University of KwaZulu-Natal
Predicting The Spatial Suitability Distribution Of Moringa Oleifera Cultivation Using Analytical Hierarchical Process Modelling, T. Tshabalala, B. Ncube, H. P. Moyo, E. M. Abdel-Rahman, O. Mutanga, A. R. Ndhlala
All Peer-Reviewed Publications
Moringa oleifera Lam, often grows well under cultivation in the tropics and sub-tropics. It does well in sandy to clayey soils and tolerates low rainfall. The plant is well-known for its nutritional and medicinal properties, hence it is fast gaining popularity in South Africa and the rest of the world. The objective of this study was to predict the suitable areas for cultivating M. oleifera in South Africa using climate and edaphic variables that significantly affect its growth and development. We used an Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) weight function to assign suitability weights to criteria …
