Agricultural Groundcover Update December 2023,
2024
Department of Primary Industries and Regional Development, Western Australia
Agricultural Groundcover Update December 2023, Justin Laycock
Natural resources published reports
Summary
- About 96% of the grainbelt had adequate vegetative groundcover (more than 50%) to prevent wind erosion in December 2023.
- In the northern half of the grainbelt, a larger-than-average area has 51–60% groundcover, which is expected to decrease to below 50% over the summer.
- Just under 4% of the grainbelt (553,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. West Midlands Ag Soil Zone had the highest risk of wind erosion and 11.4% of this farmland had inadequate groundcover.
- Less than 0.5% of the grainbelt had a high to very high risk of wind erosion …
Aboveground Biomass Density Estimation Using Deep Learning: Insight From Neon Ground-Truth Data And Simulated Gedi Waveform,
2024
Michigan Technological University
Aboveground Biomass Density Estimation Using Deep Learning: Insight From Neon Ground-Truth Data And Simulated Gedi Waveform, Ashish Mahaur
Dissertations, Master's Theses and Master's Reports
Accurately estimating Aboveground Biomass Density (AGBD) is crucial for managing Earth's carbon cycle and informing climate strategies. NASA's GEDI mission advances global forest mapping, but traditional linear models often yield less reliable AGBD estimates. This study enhances AGBD estimation using deep learning models with NEON ground-truth data and simulated GEDI waveforms. We compared 1D CNNs, LSTMs, and pre-trained CNNs to traditional models. The ResNet152 model outperformed linear regression, achieving an R² of 0.68, demonstrating a 17% improvement. Our experiments also demonstrate the importance of large, diverse datasets, particularly for training deep learning models.
Investigating Flash Flood Occurrence Using Negative Binomial Models In Maryland, United States Of America,
2024
Georgia Southern University
Investigating Flash Flood Occurrence Using Negative Binomial Models In Maryland, United States Of America, Zainab O. Akinsemoyin
College of Graduate Studies: Theses & Dissertations
Globally, as extreme weather patterns intensify, flash floods have emerged as one of the most destructive and immediate environmental threats. In Maryland, flash floods are particularly concerning due to its diverse topography and increasing urban development, which exacerbates runoff and overwhelms drainage systems. The state has experienced significant flash flood events, highlighting the need for effective models to manage risks and inform mitigation strategies. While regression models such as the Negative Binomial (NB) and Zero-Inflated Negative Binomial (ZINB) are commonly used for count data analysis, their application to flash flood modeling in the USA, including regions like Maryland, remains limited …
Road Extraction On Remote Sensing Imagery: Historical Mapping Of The Brazilian Amazon,
2024
Missouri State University
Road Extraction On Remote Sensing Imagery: Historical Mapping Of The Brazilian Amazon, Jonas Paiva Botelho Jr
Graduate Theses/Dissertations
This work proposes an artificial intelligence model based on U-Net architecture to map road networks in the Brazilian Amazon. Over the years, the Amazon region has been heavily exploited, leading to increased deforestation rates, contributing to CO2 emissions, amplifying global warming, and causing a disturbance in local fauna and flora. The expansion into the forest by illegal miners, loggers, and land grabbers can be tracked down by the construction of roads, which we can refer to as the arteries of deforestation. Previous works on the matter proposed algorithms that use high-resolution imagery to map roads precisely. However, this work approach …
Regional And Landscape Scale Examination And Attribution Of Vegetation Changes To Social-Environmental System Drivers In Kazakhstan,
2024
University of South Dakota
Regional And Landscape Scale Examination And Attribution Of Vegetation Changes To Social-Environmental System Drivers In Kazakhstan, Venkatesh Kolluru
Dissertations and Theses
Kazakhstan (KZ) experienced widespread changes in ecosystem structure and function. The country is a climate and land cover/use change “hotspot” owing to political reforms, intensified grazing, and extreme climatic events. Despite their importance, there is a lack of consensus about vegetation changes, trends, and drivers in KZ. Addressing this knowledge gap is crucial for effectively managing and restoring grassland ecosystems. However, a pressing challenge is discerning anthropogenic-driven vegetation changes from climate variability and decomposing the responses to the complex human-environmental forcings. Motivated by these challenges, I employed statistical and machine learning algorithms to detect and attribute vegetation changes to social-environmental …
Lidar Remote Sensing And The Monitoring Of Brazilian Amazon Forest Structure: Tackling Issues And Finding New Possibilities,
2024
South Dakota State University
Lidar Remote Sensing And The Monitoring Of Brazilian Amazon Forest Structure: Tackling Issues And Finding New Possibilities, Pedro Valle De Carvalho E Oliveira
Electronic Theses and Dissertations
The Amazon is the largest tropical forest in the world and around 60% of it is in Brazil. The amount of carbon stored in the region uncertain, the impacts of land use and climate changes are unknown, and what drives the dynamic of the forest structure is still under a heated debate. Optical remote sensing has been used for a long time to assist the monitoring of the Brazilian Amazon. However, optical remote sensing only allows a comprehensive study from the top of the forest canopy. In contrast, lidar remote sensing of forests can produce robust information regarding the canopy …
A Tale Of Two Working Landscapes,
2024
University of Montana, Missoula
A Tale Of Two Working Landscapes, Sage C. Sutcliffe
Graduate Student Theses, Dissertations, & Professional Papers
No abstract provided.
A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment,
2024
Old Dominion University
A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic
Electrical & Computer Engineering Faculty Publications
This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.
Trends Of Autumn Phenology In Response To Environmental And Meteorological Variables,
2023
Western Michigan University
Trends Of Autumn Phenology In Response To Environmental And Meteorological Variables, Meagan Renee Maguire
Masters Theses
Previous studies have identified that changes in plant phenology are most likely induced by climate variability. One such change is the end of season (EOS) for deciduous forests in the United States. In essence, the EOS represents the end of plant productivity for a given year; the phase in which plant dormancy is reached. However, our wealth of knowledge on plant phenology largely overlooks the phases that occur in autumn, especially the EOS, with many previous studies focusing on spring phenology. This study uses remote sensing MODIS aerial imagery data and historical meteorological data to analyze any relationships that may …
Sc-Fuse: A Feature Fusion Approach For Unpaved Road Detection From Remotely Sensed Images,
2023
University of Nebraska-Lincoln
Sc-Fuse: A Feature Fusion Approach For Unpaved Road Detection From Remotely Sensed Images, Aniruddh Saxena
School of Computing: Dissertations, Theses, and Student Research
Road network extraction from remote sensing imagery is crucial for numerous applications, ranging from autonomous navigation to urban and rural planning. A particularly challenging aspect is the detection of unpaved roads, often underrepresented in research and data. These roads display variability in texture, width, shape, and surroundings, making their detection quite complex. This thesis addresses these challenges by creating a specialized dataset and introducing the SC-Fuse model.
Our custom dataset comprises high resolution remote sensing imagery which primarily targets unpaved roads of the American Midwest. To capture the diverse seasonal variation and their impact, the dataset includes images from different …
Agricultural Groundcover Update November 2023,
2023
Department of Primary Industries and Regional Development, Western Australia
Agricultural Groundcover Update November 2023, Justin Laycock
Natural resources published reports
Summary
- About 98% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in November 2023. This amount of groundcover is normal for the middle of harvest.
- In the northern half of the grainbelt, a larger-than-average area had 51–60% groundcover, which is expected to decrease to below 50% over summer.
- Just over 2% of the grainbelt (324,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. Mullewa to Morawa Ag Soil Zone had the highest risk of wind erosion and 9.7% of this farmland had inadequate groundcover.
- Less than 0.5% of the …
Optimizing Remote Sensing Approaches For Dryland Carbon Flux Estimation,
2023
University of Texas at El Paso
Optimizing Remote Sensing Approaches For Dryland Carbon Flux Estimation, Kamal Nyaupane
Open Access Theses & Dissertations
Dryland ecosystems account for 40% of the global land surface area and play a vital role in the global carbon cycle. Gross Primary Productivity (GPP) is crucial for carbon exchange between ecosystems and the atmosphere, serving as a fundamental determinant of the carbon balance. However, precise modeling of GPP in terrestrial ecosystems, especially drylands, remains a complex challenge. This research utilizes a decade long spectral reflectance dataset acquired with a robotic tram system to estimate GPP using Random Forest model. The research exceled in capturing the complex spatio-temporal dynamics of the study site. Notably, the RF model exhibited best performance …
Unraveling Water Quality Issues In The Colorado River Basin: Utilizing Remote Sensing Satellite Images, Statistical, And Machine Learning For Improved Monitoring,
2023
University of Nevada, Las Vegas
Unraveling Water Quality Issues In The Colorado River Basin: Utilizing Remote Sensing Satellite Images, Statistical, And Machine Learning For Improved Monitoring, Godson Ebenezer Adjovu
UNLV Theses, Dissertations, Professional Papers, and Capstones
This research was aimed at exploring innovative and cost-effective tools in understanding the spatiotemporal variability of water quality parameters in the Colorado River Basin (CRB), which includes the Colorado River and major reservoirs and lakes in the USA including Lake Mead. The river which arises in the state of Colorado and empties into the Republic of Mexico at the Gulf of California, is a source of water to seven US states and the Republic of Mexico and provides water to about 40 million people and million acres of farmlands in seven states in the western US and the Republic of …
Urban Flood And Its Correlation With Built-Up Area In Semarang, Indonesia,
2023
University of Indonesia
Urban Flood And Its Correlation With Built-Up Area In Semarang, Indonesia, Risty Khoirunisa, Bambang Darmo Yuwono
Smart City
The expansion of urban areas is closely related to environmental problems such as changes in land use, flooding, and land subsidence. Semarang is a city with reasonably rapid development and a high land change experiencing floods and land subsidence. This paper will discuss land transformation caused by urban growth and its implications. It uses a combination of geospatial techniques and cloud computing Google Earth Engine (GEE) to carry out mapping over a large area without being constrained by computer capabilities. This study found that the built-up area in 2010 occupied 36.27% of the city, and it went up to 59.79% …
Agricultural Groundcover Update October 2023,
2023
Department of Primary Industries and Regional Development, Western Australia
Agricultural Groundcover Update October 2023, Justin Laycock
Natural resources published reports
Summary
- About 98% of the grainbelt had adequate vegetative groundcover (more than 50%) to prevent wind erosion in October 2023. This amount of groundcover is normal at the end of spring and pre-harvest in most areas.
- There was a larger than average area with 51–60% groundcover, and groundcover in these areas is expected to reduce over summer to below 50%.
- About 2% of the grainbelt (293,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. Mullewa to Morawa Ag Soil Zone had the highest risk of wind erosion and 8% of this farmland had inadequate groundcover. …
Complex Impacts Of Wars On Global Sustainable Development In A Metacoupled World,
2023
The University of Hong Kong
Complex Impacts Of Wars On Global Sustainable Development In A Metacoupled World, Qutu Jiang, Zhenci Xu, Yuanzheng Cui, Jianguo Liu
I-GUIDE Forum
Wars and armed conflicts have had profound impacts on local and global sustainable development in an interconnected world. However, evidence on the impacts of wars is fragmented and little attention has been paid to the impacts on the 17 UN’s Sustainable Development Goals (SDGs), a unifying framework for achieving global sustainable development. This perspective synthesizes the scattered information to provide a holistic analysis and highlight the applications of remote sensing in assessing the impacts of wars on global sustainable development in a metacoupling world. Wars have complex impacts on all 17 SDGs, which cascade beyond conflict zones and spillover to …
The Challenge Of Misclassification Error In The European Union’S Deforestation Regulation,
2023
Lafayette College
The Challenge Of Misclassification Error In The European Union’S Deforestation Regulation, Caleb T. Gallemore
I-GUIDE Forum
The European Union’s Regulation 2023/1115, which requires firms to undertake significant due diligence efforts to minimize the import of deforestation-linked commodities into the Union, relies heavily on cutting-edge geospatial technologies. While several studies of zero-deforestation supply chain efforts have pointed to the political and logistical challenges such initiatives face, there has been less consideration of the role that the measurement errors that are unavoidable in geospatial technologies might affect emerging zero-deforestation governance systems. Using information on misclassification error rates for forest areas from 20 recent validation studies of global land-cover datasets, I simulate the misclassification risks we might expect from …
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach,
2023
University of Minnesota - Twin Cities
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022,
2023
Indian Institute of Technology Guwahati
Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Karakoram Himalayas are vulnerable to glacial lake outburst floods (GLOFs), which cause catastrophic floods in the surrounding areas. The increasing natural and anthropogenic activities, especially in the Indo-Gangetic Plains at the southern flank of the towering Himalayas, could be the cause of climate change affecting the frequency of the natural hazards in the Himalayas. In the present study, a detailed analysis of the Shisper Lake breach of 7 May 2022 is carried out using satellite remote sensing. A decreasing trend in the glacial mass balance is observed between 2017 and 2021; in this period, frequent GLOF episodes occurred. A pronounced …
Analysis Of Normalized Difference Vegetation Index Change Of The West Bank, Palestine, Using Multitemporal Satellite Remote Sensing Data,
2023
1Department Of Geography & Geomatics, Faculty of Economics and Social Sciences, An-Najah National University, Nablus, Palestine
Analysis Of Normalized Difference Vegetation Index Change Of The West Bank, Palestine, Using Multitemporal Satellite Remote Sensing Data, Ahmed Ghodieh
An-Najah University Journal for Research - B (Humanities)
The West Bank is characterized by the diversity of its climate despite its small area. It includes four climatic regions:- a humid, semi-humid, arid, and semi-arid climate. This in turn affected the geographical distribution of vegetation cover seasonally and over the years. This study investigated changes in the West Bank, Palestine vegetation cover using multitemporal Landsat data. Four images were selected for this purpose – two corresponding to 2001 and the other two corresponding to 2021. Seasonal change of the Normalized Difference Vegetation Index (NDVI) was investigated for the acquired images. ArcGIS 10.8 software was used for image processing and …
