Geography Commons^™

Landscape Fragmentation In Coffee Agroecological Subzones In Central Kenya: A Multiscale Remote Sensing Approach, Gladys Mosomtai, John Odindi, Elfatih M. Abdel-Rahman, Régis Babin, Pinard Fabrice, Onisimo Mutanga, Henri E.Z. Tonnang, Guillaume David, Tobias Landmann

All Peer-Reviewed Publications

Smallholder agroecological subzones (AEsZs) produce an array of crops occupying large areas throughout Africa but remain largely unmapped. We explored multisource satellite datasets to produce a seamless land-use and land-cover (LULC) and fragmentation dataset for upper midland (UM1 to UM4) AEsZs in central Kenya. Specifically, the utility of PlanetScope, Sentinel 2, and Landsat 8 images for mapping coffee-based landscape were tested using a random forest (RF) classifier. Vegetation indices, texture variables, and wavelength bands from all satellite data were used as inputs in generating four RF models. A LULC baseline map was produced that was further analyzed using FRAGSTAT to …

Effect Of Urbanization On Channel Platforms Of River Kaduna From 1962-2017, Kaduna State, Nigeria, Ali Williams Butu, Chukwudi Nnaemeka Emeribe, Dewingong Columbus Leke, Mamman Shaba Jibril

Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)

The study investigated changes in channel planforms of River Kaduna. Topographic maps were complimented with Mosaic of SPOT 5 satellite and Sentinel-2 images. Results showed that except for sinuosity index and channel length, channel width, braiding and channel migration exhibited considerable changes. These changes were evident in reduced velocity and stream energy, the type of sediment being transported, the silt materials being transported in suspension and the coarse sand and gravels being moved by lift and drag processes which are easily deposited, thus causing the channel to contract and braid. Channel migration occurred as gradual bend shifts leaving no evidence …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

Pre-Emptive Detection Of Mature Pine Drought Stress Using Multispectral Aerial Imagery, Nancy Grulke, Jason Maxfield, Phillip Riggan, Charlie Schrader-Patton

Biology Faculty Publications and Presentations

Drought, ozone (O₃), and nitrogen deposition (N) alter foliar pigments and tree crown structure that may be remotely detectable. Remote sensing tools are needed that pre-emptively identify trees susceptible to environmental stresses could inform forest managers in advance of tree mortality risk. Jeffrey pine, a component of the economically important and widespread western yellow pine in North America was investigated in the southern Sierra Nevada. Transpiration of mature trees differed by 20% between microsites with adequate (mesic (M)) vs. limited (xeric (X)) water availability as described in a previous study. In this study, in-the-crown morphological traits (needle chlorosis, …

Earth Observation And Sustainable Development Goals, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

"Planet Earth is a dynamic body, which is home to 7.8 billion people, and strong interactions exist between the human population and the Earth’s different components (land, ocean, biosphere, cryosphere and atmosphere). The impacts of such interactions are observed from the day-to-day changes in weather, solar radiation, cloudy conditions, poor visibility, rainfall and frequency of natural hazards around the globe. The dynamic nature of the Earth is evident at the ocean coast through the ocean waves, the nature of these waves varies from day-to-day and also morning to evening. For example, the heights of waves can now be predicted through …

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 …

Changing Agricultural Landscapes: An Investigation Of Dragon Fruit Production In Southern Vietnam., Laura Krauser

Electronic Theses and Dissertations

Agricultural transition represents an essential component of land-use and land-cover change in developing countries across the world, as economic and social factors pressure agriculturalists out of traditional subsistence farming into food commodity production. Modernization has altered modes of income, land ownership, and livelihood in Southeast Asia drastically in recent years. The Bình Thuận Province of southern Vietnam experienced a particularly radical transformation with the introduction of dragon fruit cultivation, which has been profoundly encouraged by outside markets in China, Australia, and Japan. This research combines remote sensing and qualitative research to examine and characterize a changing agricultural landscape in rural …

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 …

Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin

Mathematics, Physics, and Computer Science Faculty Articles and Research

Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent …

Modelling And Mapping The Intra-Urban Spatial Distribution Of Plasmodium Falciparum Parasite Rate Using Very-High-Resolution Satellite Derived Indicators, Stephanos Georganos, Oscar Brousse, Sebastien Dujardin, Catherine Linard, Daniel Casey, Marco Millones, Benoit Parmentier, Nicole P.M. Van Lipzig, Mattias Demuzere, Sabine Vanhuysse, Nicholus Mboga, Vernica Andreo, Robert W. Snow, Moritz Lennert

Geography Articles

The rapid and often uncontrolled rural–urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa’s population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of …

Remote Sensing Approaches To Predict Forest Characteristics In Northwest Montana, Ryan P. Rock

Graduate Student Theses, Dissertations, & Professional Papers

Remote sensing can be utilized by land management organizations to save money and time. Mapping vegetation using either aerial photographs or satellite imagery and the applications for forest management are of particular interest to the Montana Department of Natural Resources. In 2018, the organization began a pilot program to test the incorporation of raster analysis of remotely sensed data into their inventory program and had limited success. This analysis identified two areas of improvement: the selection method of inventory plots and the imagery used for classification and metrics. This study found that selecting inventory plots using a generalized random tessellation …

Characterizing Burn Severity Of Beetle-Killed Forest Stands Leveraging Google Earth Engine-Derived Normalized Burn Ratios, Sofronio Catalino Propios Iii

Graduate Student Theses, Dissertations, & Professional Papers

Following numerous studies, a general consensus on burn severity in forests affected by bark beetle outbreaks has not yet been achieved. The purpose of this study is to characterize burn severities in forest stands affected by mountain pine beetle (MPB) outbreaks, especially in relation to “time since outbreak”, vegetation cover, and topographic factors. This study focuses on wildfires that occurred in the northern Rocky Mountains of Idaho and Montana during the 2012 fire season within forested areas that had previously experienced prior MPB outbreaks. Remote sensing techniques were used to quantify and compare the burn severities of MPB-outbreak stands with …

Responses Of Land Surface Phenology To Wildfire Disturbances In The Western United States Forests, Jianmin Wang

Electronic Theses and Dissertations

Land surface phenology (LSP) characterizes the seasonal dynamics in the vegetation communities observed for a satellite pixel and it has been widely associated with global climate change. However, LSP and its long-term trend can be influenced by land disturbance events, which could greatly interrupt the LSP responses to climate change. Wildfire is one of the main disturbance agents in the western United States (US) forests, but its impacts on LSP have not been investigated yet. To gain a comprehensive understanding of the LSP responses to wildfires in the western US forests, this dissertation focused on three research objectives: (1) to …

Deep Learning For Overhead Imagery: Algorithms And Applications, Anthony Manuel Ortiz Cepeda

Open Access Theses & Dissertations

Remote sensing using overhead imagery has critical impact to the way we understand our environment and offers crucial information for scene understanding, climate change research, disaster response, urban planning, forest management, and many other applications. At present, deep learning is increasingly used in remote sensing, but mostly borrowing algorithms developed for natural images in the computer vision community. Specific challenges arise while applying deep learning to remote sensing. These challenges include issues related to the high dimensionality and limited labeled data, security and robustness to adversarial attacks, and model generalization. In this Thesis we focus on tackling these key challenges. …

Burning With Potential: Understanding The Relationship Between Biochar And Agriculture Of The Northern Glaciated Plains Ecoregion, Kaitlyn Abrahamson

Electronic Theses and Dissertations

Achieving global sustainable agriculture is one of the most incredible challenges of this century, yet many continue to try to solve this problem through the development of precision technologies. Biotechnologies, such as biochar, can perform like a precision technology while protecting agricultural land from soil erosion and fertility loss. The Northern Glaciated Plains ecoregion of the United States is little researched in the benefits from the use of biochar through improved soil nutrient capture and water retention, crop health improvements, and yield increases. The study plot has four sections of corn stover biochar and eight sections of control sections. This …

A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to …

An Evaluation Of Unmanned Aerial Systems And Structure-From-Motion For Fluvial Large Wood Sensing And Risk Assessment, Daniel Gerke

Masters Theses

This research aims to show Unmanned Aerial System (UAS) and Structure-from-Motion (SfM) technology can, in combination, improve on traditional large wood (LW) monitoring techniques. More temporally and economically efficient data collected at a finer spatial resolution and greater spatial extent will increase the effectiveness of management plans and risk assessment for LW by providing decision-makers with a complete picture of the river.

Contemporary practices are too inefficient in time and labor for large-scale monitoring of fluvial LW with anything more than the most general management or risk assessment in mind. The paradigm of river research, the river continuum concept (RCC), …

Satellite-Based Decadal Change Assessments Of Pan-Arctic Environments, Liza K. Jenkins, Tom Barry, Karl R. Bosse, William S. Currie, Tom Christensen, Sara Longan, Robert A. Shuchman, Danielle Tanzer, Jason J. Taylor

United States National Park Service: Publications

Remote sensing can advance the work of the Circumpolar Biodiversity Monitoring Program through monitoring of satellite-derived terrestrial and marine physical and ecological variables. Standardized data facilitate an unbiased comparison across variables and environments. Using MODIS standard products of land surface temperature, percent snow-covered area, NDVI, EVI, phenology, burned area, marine chlorophyll, CDOM, sea surface temperature, and marine primary productivity, significant trends were observed in almost all variables between 2000 and 2017. Analysis of seasonal data revealed significant breakpoints in temporal trends. Within the terrestrial environment, data showed significant increasing trends in land surface temperature and NDVI. In the marine environment, …

Quantifying Four Decades Of Arid-Region Agricultural Development In Arequipa, Peru Using Landsat, Zachary S. Brecheisen, Nicholas Hamp-Adams, Edwin Bocardo Delgado, Martin Villalta Soto, Timothy Filley, Darrell G. Schulze

Purdue GIS Day

The Arequipa Nexus Institute for Food, Energy and the Environment (Nexus Institute) is located in Southwestern Peru, generally bounded by the city of Arequipa to the east, the Majes River to the west, the Pacific Ocean to the south, and the Andes mountains to the north. Though agriculture has been practiced in parts of this cool desert region (MAT~15°C, MAP

The Importance Of Landscape Position Information And Elevation Uncertainty For Barrier Island Habitat Mapping And Modeling, Nicholas Matthew Enwright

LSU Doctoral Dissertations

Barrier islands provide important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. As a result, natural resource managers are concerned with monitoring changes to these islands and modeling future states of these environments. Landscape position, such as elevation and distance from shore, influences habitat coverage on barrier islands by regulating exposure to abiotic factors, including waves, tides, and salt spray. Geographers commonly use aerial topographic lidar data for extracting landscape position information. However, researchers rarely consider lidar elevation uncertainty when using automated processes for extracting elevation-dependent habitats from lidar data. …

Mapping Soil Moisture From Remotely Sensed And In-Situ Data With Statistical Methods, Yaping Xu

LSU Doctoral Dissertations

Soil moisture is an important factor for accurate prediction of agricultural productivity and rainfall runoff with hydrological models. Remote sensing satellites such as Soil Moisture Active Passive (SMAP) offer synoptic views of soil moisture distribution at a regional-to-global scale. To use the soil moisture product from these satellites, however, requires a downscaling of the data from an usually large instantaneous field of view (i.e. 36 km) to the watershed analysis scales ranging from 30 m to 1 km. In addition, validation of the soil moisture products using the ground station observations without an upscaling treatment would lead to cross-level fallacy. …

Spatial And Temporal Variability Of Inherent And Apparent Optical Properties In Western Lake Erie: Implications For Water Quality Remote Sensing, Michael Sayers, Karl Bosse, Robert Shuchman, Steven A. Ruberg, Gary L. Fahnenstiel, George Leshkevich, Et Al.

Michigan Tech Publications, Part 1

Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP …

Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell

Michigan Tech Publications, Part 1

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 …

Satellite Monitoring Of Harmful Algal Blooms In The Western Basin Of Lake Erie: A 20-Year Time-Series, Michael Sayers, Amanda Grimm, Robert Shuchman, Karl Bosse, Gary L. Fahnenstiel, Steven A. Ruberg, George A. Leshkevich

Michigan Tech Publications, Part 1

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m3) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the …

Detecting Coastal Marsh Change From Aerial Imagery Using Spectral And Textural Methods: Pascagoula River Estuary, Mississippi, 1955-2014, Margaret Claire Bell Waldron

Master's Theses

As sea level rise accelerates, coastal marsh ecosystems are increasingly vulnerable. Vertical accretion rates must exceed or keep pace with rates of sea level rise to prevent transition to open water or inland migration of marsh vegetation. While some marsh systems along the northern Gulf of Mexico coast have remained stable, others, e.g., the marshes of the Louisiana Gulf Coast, have experienced high rates of conversion to open water. This study examined the historical extent of intertidal marsh at the mouth of the Pascagoula River in Jackson County, Mississippi to determine whether marsh extent changed during the period 1955-2014 and …

Using Remotely Sensed Imagery To Examine Changing Urban Land Cover Across Time And Topography: A Study Of Nepal’S Kathmandu Valley, Rajesh Sigdel

Masters Theses

The Kathmandu Valley, located in Nepal, is the most rapidly growing demographic region in the country. With this demographic transformation, urban land is also expanding within the valley. It is important to understand the rate and extent of urban land cover change for effective land use planning. This study analyzed the urban land cover change in the Kathmandu Valley in 1990, 2006, and 2018 using remote sensing. It also analyzed the shift in the urban topography of the valley during the same period. Landsat 5 and Landsat 8 were used to study the transformation of urban land cover in the …

The Use Of High And Medium Resolution Imagery To Detect Agricultural Land Cover In Chinese Cities: A Case Study Of Nanjing 2000 To 2015, Erik Breidinger

Masters Theses

According to McGee and Ginsburg’s desakota hypothesis, rapidly growing Asian cities differ from large Western cities in their land cover/land use (LC/LU) as they retain a significant portion of agricultural land and labor despite rapid urbanization. However, significant amounts of agricultural production within desakotas takes place in plastic greenhouses, causing a unique problem when calculating LC/LU estimates via traditional remote sensing techniques. While greenhouses appear equivalent to developed land spectrally, their purpose is entirely agricultural. This study provides an improved method of calculating greenhouse land-cover as agricultural land-use using Jiangning District in the city of Nanjing as the study area …

The Effects Of Deforestation On Carbon Storage In Khabarovsk Krai, Russia, Rowan E. Cole

Masters Theses

With over one-fifth of the planet’s forested area, Russia has become a major source of round wood and wood products. In 2003, the Russian government established an energy policy aimed at reducing the negative impacts of industry on the environment and improving the nation’s environments as a whole. This study analyzes deforestation and logging activities in the forests along the Amur River in Khabarovsk Krai in the Russian Far East to determine the effectiveness of Russian government policy in achieving the goals put forward in the 2003 energy policy. Changes in land-use and land-cover will be assessed using 500-meter resolution …

Lidar Predictive Modeling Of Kalapuya Mound Sites In The Calapooia Watershed, Oregon, Tia Rachelle Cody

Dissertations and Theses

Archaeologists grapple with the problematic nature of archaeological discovery. Certain types of sites are difficult to see even in the best environmental conditions (e.g., low-density lithic scatters) and performing traditional archaeological survey is challenging in some environments, such as the dense temperate rain forests of the Pacific Northwest. Archaeologists need another method of survey to assess large areas and overcome environmental and archaeological barriers to site discovery in regions like the Pacific Northwest. LiDAR (light detection and ranging) technology, a method for digitally clearing away swaths of vegetation and surveying the landscape, is one possible solution to some of these …

Impact Of Deadly Dust Storms (May 2018) On Air Quality, Meteorological, And Atmospheric Parameters Over The Northern Parts Of India, Sudipta Sarkar, Akshansa Chauhan, Rajesh Kumar, Ramesh P. Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and …