Social and Behavioral Sciences Commons^™

Agricultural Groundcover Update April 2024, Justin Laycock

Natural resources published reports

• In April, over 12% (1,876,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.5% (238,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

Agricultural Groundcover Update May 2024, Justin Laycock

Natural resources published reports

• In May, over 9% (1,410,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.3% (208,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%. Half of this land was in the West Midlands Ag Soil Zone.

Agricultural Groundcover Update March 2024, Justin Laycock

Natural resources published reports

• In March, over 10% (1,577,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.

• The northern grainbelt had the highest risk of wind erosion and over 20% of this farmland had inadequate groundcover.

• About 1.3% (191,000 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

Agricultural Groundcover Update February 2024, Justin Laycock

Natural resources published reports

• About 92% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in February 2024.

• Nearly 8% of the grainbelt (1,193,400 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion.

• The northern grainbelt had the highest risk of wind erosion and 16.5% of this farmland had inadequate groundcover.

• Less than 0.7% of the grainbelt had a high to very high risk of wind erosion because groundcover was less than 30%.

Agricultural Groundcover Update January 2024, Justin Laycock

Natural resources published reports

Summary

• About 94% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in January 2024.
• 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 coming months.
• Just under 6% of the grainbelt (855,000 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 14.5% of this farmland had inadequate groundcover.
• Less than 0.5% of the grainbelt had a high to very high risk of wind …

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 …

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 …

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. …

Multi-Decadal Analysis Of Remotely Sensed Vegetation Change In Berea College Forest - Seasonality Of Forest Patterns Using Remote Sensing, Jacob Foushee

The Cardinal Edge

Satellite imagery is a practical and valuable tool for monitoring vegetation condition in forests. The longevity of the USGS/NASA Landsat program along with its medium spatial resolution (30m) gives researchers the ability to make informed statements on land cover generally, and specifically on aspects such as forest conditions. The Landsat program’s nearly 50-year archive of imagery show how Earth’s surface has changed through modern development and how these developments have influenced forests. Google Earth Engine (GEE) is a cloud-based repository of satellite imagery dating as far back as the 1970s. This study utilizes Landsat 5-8 imagery from GEE to calculate …

Multi-Decadal Analysis Of Remotely Sensed Vegetation Change In Berea College Forest - Seasonality Of Forest Patterns Using Remote Sensing., Jacob Foushee

College of Arts & Sciences Senior Honors Theses

Satellite imagery is a practical and valuable tool for monitoring vegetation condition in forests. The longevity of the USGS/NASA Landsat program along with its medium spatial resolution (30m) gives researchers the ability to make informed statements on land cover generally, and specifically on aspects such as forest conditions. The Landsat program’s nearly 50-year archive of imagery show how Earth’s surface has changed through modern development and how these developments have influenced forests. Google Earth Engine (GEE) is a cloud-based repository of satellite imagery dating as far back as the 1970s. This study utilizes Landsat 5-8 imagery from GEE to calculate …

Intra-Field Nitrogen Estimation For Wheat And Corn Using Unmanned Aerial Vehicle-Based And Satellite Multispectral Imagery, Plant Biophysical Variables, Field Properties, And Machine Learning Methods, Jody Seymon Yu

Electronic Thesis and Dissertation Repository

Management of nitrogen (N) fertilizers is an important agricultural practice and field of research to increase productivity, minimize environmental impacts and the cost of production. To apply N fertilizer at the right rate, time, and place depends on the crop type, desired yield, and field conditions. The objective of this study is to use Unmanned Aerial Vehicle (UAV) multispectral imagery, PlanetScope satellite imagery, vegetation indices (VI), crop height, leaf area index (LAI), field topographic metrics, and soil properties to predict canopy nitrogen weight (g/m²) of corn and wheat fields in southwestern Ontario, Canada. Random Forests (RF) and Support …

Detection Of Change Points In Pseudo-Invariant Calibration Sites Time Series Using Multi-Sensor Satellite Imagery, Neha Khadka

Electronic Theses and Dissertations

The remote sensing community has extensively used Pseudo-Invariant Calibration Sites (PICS) to monitor the long-term in-flight radiometric calibration of Earth-observing satellites. The use of the PICS has an underlying assumption that these sites are invariant over time. However, the site’s temporal stability has not been assured in the past. This work evaluates the temporal stability of PICS by not only detecting the trend but also locating significant shifts (change points) lying behind the time series. A single time series was formed using the virtual constellation approach in which multiple sensors data were combined for each site to achieve denser temporal …

Multidecadal Analysis Of Beach Loss At The Major Offshore Sea Turtle Nesting Islands In The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Rejoice Thomas, Hesham El-Askary, Sachi Perera, Ace Vincent B. Flandez, Abdullajid U. Basali, Joselito Francis A. Alcaria, Jinoy Gopalan, Surya Prakash Tiwari, Mubarak Al-Jedani, Perdana K. Prihartato, Ronald A. Loughlan, Ali Qasem, Mohamed A. Qurban, Wail Falath, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Undocumented historical losses of sea turtle nesting beaches worldwide could overestimate the successes of conservation measures and misrepresent the actual status of the sea turtle population. In addition, the suitability of many sea turtle nesting sites continues to decline even without in-depth scientific studies of the extent of losses and impacts to the population. In this study, multidecadal changes in the outlines and area of Jana and Karan islands, major sea turtle nesting sites in the Arabian Gulf, were compared using available Kodak aerographic images, USGS EROS Declassified satellite imagery, and ESRI satellite images. A decrease of 5.1% and 1.7% …

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

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 …

Hyperspectral Reflectance Signature Protocol For Predicting Subsurface Bottom Reflectance In Water: In-Situ And Analytical Methods, Charles R. Bostater, Tyler A. Rotkiske, Taylor Scott Oney

Ocean Engineering and Marine Sciences Faculty Publications

In-situ measurement of bottom reflectance signatures and bottom features in water are used to test an analytical based irradiance model protocol. Comparisons between predicted and measured bottom reflectance signatures are obtained using measured hyperspectral remote sensing reflectance signatures, water depth and water column constituent concentrations. Analytical solutions and algorithms are used to generate synthetic signatures of different bottom types. The analytical methodology used to simulated bottom reflectance contains offset and bias that can be corrected using spectral window based corrections. Example results are demonstrated for application to coral species, submerged aquatic vegetation and a sand bottom type. Spectral windows are …

Land Cover Land Use Change And Soil Organic Carbon Under Climate Variability In The Semi-Arid West African Sahel (1960-2050), Amadou M. Dieye

Electronic Theses and Dissertations

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project LCLU change is of considerable interest for mitigation and adaptation measures in response to climate change. A combination of remote sensing analyses, qualitative social survey techniques, and biogeochemical modeling was used to study the relationships between climate change, LCLU change and soil organic carbon in the …

Grid: A Methodology Integrating Witness Testimony And Satellite Imagery Analysis For Documenting Alleged Mass Atrocities, Brittany L. Card, Isaac L. Baker

Genocide Studies and Prevention: An International Journal

Aim: This article documents the development and initial use case of the GRID (Ground Reporting through Imagery Delivery) methodology by the Harvard Humanitarian Initiative (HHI). GRID was created to support corroboration of witness testimony of mass atrocity related-events using satellite imagery analysis. A repeating analytic limitation of employing imagery for this purpose is that differences in the geographic knowledge of a witness and an imagery analyst can limit or impede corroboration.

Methods: The primary method used in this article is a case study of HHI’s development and use of GRID. The GRID methodology was designed during HHI’s work with the …

Ice Sheet Record Of Recent Sea-Ice Behavior And Polynya Variability In The Amundsen Sea, West Antarctica, Alison S. Criscitiello, Sarah B. Das, Matthew J. Evans, Karen E. Frey, Howard Conway, Ian Joughin, Brooke Medley, Eric J. Steig

Geography

[1] Our understanding of past sea-ice variability is limited by the short length of satellite and instrumental records. Proxy records can extend these observations but require further development and validation. We compare methanesulfonic acid (MSA) and chloride (Cl-) concentrations from a new firn core from coastal West Antarctica with satellite-derived observations of regional sea-ice concentration (SIC) in the Amundsen Sea (AS) to evaluate spatial and temporal correlations from 2002-2010. The high accumulation rate (∼39 g·cm-2·yr-1) provides monthly resolved records of MSA and Cl-, allowing detailed investigation of how regional SIC is recorded in the ice-sheet stratigraphy. Over the period 2002-2010 …

Spatial And Interannual Variability Of Dissolved Organic Matter In The Kolyma River, East Siberia, Observed Using Satellite Imagery, Claire G. Griffin, Karen E. Frey, John Rogan, Robert M. Holmes

Geography

The Kolyma River basin in northeastern Siberia, the sixth largest river basin draining to the Arctic Ocean, contains vast reserves of carbon in Pleistocene-aged permafrost soils. Permafrost degradation, as a result of climate change, may cause shifts in riverine biogeochemistry as this old source of organic matter is exposed. Satellite remote sensing offers an opportunity to complement and extrapolate field sampling of dissolved organic matter in this expansive and remote region. We develop empirically based algorithms that estimate chromophoric dissolved organic matter (CDOM) and dissolved organic carbon (DOC) in the Kolyma River and its major tributaries in the vicinity of …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …