Relevant bibliographies by topics / Severity Index and Remote Sensing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Severity Index and Remote Sensing'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Severity Index and Remote Sensing"

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S., K. Singh, Dutta Sujay, and Dharaiya Nishith. "MAPPING OF COTTON MEALYBUG (HEMIPTERA: PSEUDOCOCCIDAE) DAMAGE IN SIRSA DISTRICT, HARYANA USING GEOSPATIAL TECHNIQUE." International Journal of Engineering Sciences & Research Technology 5, no. 3 (2016): 138–46. https://doi.org/10.5281/zenodo.47007.

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Detection of crop stress is one of the major applications of remote sensing in agriculture. Many researchers have confirmed the ability of remote sensing techniques for detection of pest/disease on cotton. Hence, this research was designed to investigate, (1) to study the spectral properties of noninfested and mealybug infested cotton crop (ii) damage assessment using remote sensing derived index. Mealybug-infested cotton crop showed significantly lower reflectance in the near infrared region and higher in the visible region of the spectrum when compared with the non-infested cotton crop. Meal
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Morgan, Penelope, Robert E. Keane, Gregory K. Dillon, et al. "Challenges of assessing fire and burn severity using field measures, remote sensing and modelling." International Journal of Wildland Fire 23, no. 8 (2014): 1045. http://dx.doi.org/10.1071/wf13058.

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Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models. We draw on diverse recent research for guidance on assessing fire effects on vegetation and soil using field methods, remote sensing and models. We suggest that instead of collapsing many diverse, complex and interacting fire effects into a single severity index, the effects of fire should
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Klinger, Rob, Randy McKinley, and Matt Brooks. "An evaluation of remotely sensed indices for quantifying burn severity in arid ecoregions." International Journal of Wildland Fire 28, no. 12 (2019): 951. http://dx.doi.org/10.1071/wf19025.

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It is sometimes assumed the sparse and low statured vegetation in arid systems would limit the effectiveness of two remote-sensing derived indices of burn severity: the difference Normalised Burn Ratio (dNBR) and relativised difference Normalised Burn Ratio (RdNBR). We compared the relationship that dNBR, RdNBR and a ground-based index of burn severity (the Composite Burn Index, CBI) had with woody cover and woody density 1 year after burning in five fires that occurred in the Mojave Desert during 2005. Data were collected within 437 plots spanning geographic and elevation gradients representa
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Ergene, E. M., F. Bektaş Balçık, and F. Balik Şanlı. "TRENDS ANALYSIS OF AGRICULTURAL DROUGHT IN CENTRAL ANATOLIAN BASIN, TURKEY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W9-2024 (March 8, 2024): 141–48. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w9-2024-141-2024.

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Abstract. Drought is a natural disaster that can have devastating economic, environmental, and social impacts on a global, national, and regional scale. Remote sensing technology is the most powerful tool to determine of drought categories and analyse drought severity, vulnerability and its trends. Because data that is temporal, quick, wide-area, and repeating can be obtained via remote sensing technologies. The calculation of drought indices with the use of remote sensing technology is crucial for assessing the severity of the drought and its evolution over time. In this study, the Central An
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Sawant, Sushant, and Shrikrishna Kukkemane. "Evaluating agricultural drought severity in Karnataka, India through integrated remote sensing indices." Ecocycles 10, no. 2 (2024): 128–43. https://doi.org/10.19040/ecocycles.v10i2.477.

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Agricultural drought significantly threatens Karnataka, India, where rain-fed agriculture is predominant. This study evaluates the spatio-temporal evolution of agricultural drought in Karnataka from 1986 to 2020 using the Advanced Drought Response Index (ADRI), which integrates the Vegetation Condition Index (VCI), Precipitation Condition Index (PCI), Soil Condition Index (SCI), and Temperature Condition Index (TCI). Data from NOAA, TerraClimate, and NASA POWER were processed using ArcGIS Pro. Key findings reveal that northern districts like Vijayapura, Chitradurga, and Gadag consistently expe
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Picotte, Joshua J., and Kevin M. Robertson. "Validation of remote sensing of burn severity in south-eastern US ecosystems." International Journal of Wildland Fire 20, no. 3 (2011): 453. http://dx.doi.org/10.1071/wf10013.

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We assessed an existing method of remote sensing of wildland fire burn severity for its applicability in south-eastern USA vegetation types. This method uses Landsat satellite imagery to calculate the Normalised Burn Ratio (NBR) of reflectance bands sensitive to fire effects, and the change in NBR from pre- to post fire (dNBR) to estimate burn severity. To ground-truth ranges of NBR and dNBR that correspond to levels of burn severity, we measured severity using the Composite Burn Index at 731 locations stratified by plant community type, season of measurement, and time since fire. Best-fit cur
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Nacheva, Lyubena. "Burn severity assessment of Rhodes island wildfire with remote sensing data." E3S Web of Conferences 638 (2025): 01011. https://doi.org/10.1051/e3sconf/202563801011.

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Forest fires are occurring more regularly and becoming more severe, which will cause significant environmental, economic, and social damage. The advanced information technologies, and especially Geographic Information Systems are contributing to dealing with this considerable world problem. This research aims to evaluate the damage and severity of the wildfire in the Greek island of Rhodes during July 2023. For this research, remote sensing images from the Landsat 8 Satellite Mission were used before and after the fire. It was calculated that the Normalized Burned Ratio index before and after
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Lei, Shuhan, Jianbiao Luo, Xiaojun Tao, and Zixuan Qiu. "Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors." Remote Sensing 13, no. 22 (2021): 4562. http://dx.doi.org/10.3390/rs13224562.

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Unmanned aerial vehicle (UAV) remote sensing technology can be used for fast and efficient monitoring of plant diseases and pests, but these techniques are qualitative expressions of plant diseases. However, the yellow leaf disease of arecanut in Hainan Province is similar to a plague, with an incidence rate of up to 90% in severely affected areas, and a qualitative expression is not conducive to the assessment of its severity and yield. Additionally, there exists a clear correlation between the damage caused by plant diseases and pests and the change in the living vegetation volume (LVV). How
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Fok, Hok, and Qing He. "Water Level Reconstruction Based on Satellite Gravimetry in the Yangtze River Basin." ISPRS International Journal of Geo-Information 7, no. 7 (2018): 286. http://dx.doi.org/10.3390/ijgi7070286.

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The monitoring of hydrological extremes requires water level measurement. Owing to the decreasing number of continuous operating hydrological stations globally, remote sensing indices have been advocated for water level reconstruction recently. Nevertheless, the feasibility of gravimetrically derived terrestrial water storage (TWS) and its corresponding index for water level reconstruction have not been investigated. This paper aims to construct a correlative relationship between observed water level and basin-averaged Gravity Recovery and Climate Experiment (GRACE) TWS and its Drought Severit
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Sobrino, Jose, Rafael Llorens, Cristina Fernández, José Fernández-Alonso, and José Vega. "Relationship between Soil Burn Severity in Forest Fires Measured In Situ and through Spectral Indices of Remote Detection." Forests 10, no. 5 (2019): 457. http://dx.doi.org/10.3390/f10050457.

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Forest fires in Galicia have become a serious environmental problem over the years. This is especially the case in the Pontevedra region, where in October 2017 large fires (>500 hectares) burned more than 15,000 Ha. In addition to the area burned being of relevance, it is also very important to know quickly and accurately the different severity degrees that soil has suffered in order to carry out an optimal restoration campaign. In this sense, the use of remote sensing with the Sentinel-2 and Landsat-8 satellites becomes a very useful resource due to the variations that appear in soil after
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Dissertations / Theses on the topic "Severity Index and Remote Sensing"

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Upadhaya, Suraj. "Use of Landsat Data to Characterize Burn Severity, Forest Structure and Invasion by Paulownia (Paulownia Tomentosa) in an Eastern Deciduous Forest, Kentucky." UKnowledge, 2015. http://uknowledge.uky.edu/forestry_etds/23.

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Landsat imagery has been used successfully to assess burn severity and monitor post-fire forest structure in a variety of ecosystems, but to date there are few documented studies on its application in the eastern deciduous forests of the eastern United States. The occurrence of a wildfire in the Daniel Boone National Forest in2010 provided a rare opportunity for research into the use of Landsat data for assessing burn severity and its ecological effects. We used differenced normalized burn ratio (∆NBR) to quantify burn severity. The ∆NBR based burn severity classification had 70% agreement wit
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Faraklioti, M. "Classification of sets of mixed pixels in remote sensing." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/844613/.

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Recently, remotely sensed multispectral data have been proved to be very useful for many applications in the field of Earth surveys. For certain applications, however, limits in the spatial resolution of satellite sensors and variation in ground surface restrict the usefulness of the available data, since the observed spectral signature of the pixels is the result of a number of surface materials found in the area of the pixel. Two mixed pixel classification techniques which have shown high correlation with vegetation coverage of single pixels are described in this thesis: the vegetation indic
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Johnson, Ryan L. "Airborne remote sensing of forest leaf area index in mountainous terrain." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ49131.pdf.

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Johnson, Ryan L., and University of Lethbridge Faculty of Arts and Science. "Airborne remote sensing of forest leaf area index in mountainous terrain." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2000, 2000. http://hdl.handle.net/10133/90.

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Leaf area index (LAI) provides forestry information that is important for regional scale ecological models and in studies of global change. This research examines the effects of mountainous terrain on the radiometric properties of multispectral CASI imagery in estimating ground-based optical measurements of LAI, obtained using the TRAC and LAI- 2000 systems. Field and image data were acquired summer 1998 in Kananaskis, Alberta, Canada. To account for the influence of terrain a new modified approach using the Li and Strahler Geometric Optical Mutual Shadowing (GOMS) model in 'multiple forward
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Sparks, Aaron, Crystal Kolden, Alan Talhelm, et al. "Spectral Indices Accurately Quantify Changes in Seedling Physiology Following Fire: Towards Mechanistic Assessments of Post-Fire Carbon Cycling." MDPI AG, 2016. http://hdl.handle.net/10150/621493.

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Fire activity, in terms of intensity, frequency, and total area burned, is expected to increase with a changing climate. A challenge for landscape-level assessment of fire effects, often termed burn severity, is that current remote sensing assessments provide very little information regarding tree/vegetation physiological performance and recovery, limiting our understanding of fire effects on ecosystem services such as carbon storage/cycling. In this paper, we evaluated whether spectral indices common in vegetation stress and burn severity assessments could accurately quantify post-fire physio
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Bowyer, P. "Estimating leaf area index in savanna vegetation using remote sensing and inverse modelling." Thesis, University of Salford, 2005. http://usir.salford.ac.uk/2234/.

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Leaf area index (LAI), defined as the one sided green leaf area per unit ground area, is a key parameter in ecosystem process models. Owing to the large area of the earth's surface that they occupy, savanna ecosystems represent the third largest terrestrial carbon sink. There is considerable uncertainty however, as to the functioning of these ecosystems, particularly as they respond to land cover changes. Consequently, ecosystem process models constitute one of the best methods available for investigating the effect this may have on terrestrial carbon cycling. If these models are to be used ov
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May, David Z. "A MULTISPECTRAL REMOTE SENSING INVESTIGATION OF LEAF AREA INDEX AT BLACK ROCK FOREST, NY." Ohio University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1157569101.

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Bayer, Andreas Paul Adolf. "Biomass forest modelling using UAV LiDAR data under fire effect." Master's thesis, ISA, 2019. http://hdl.handle.net/10400.5/21269.

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Mestrado em Engenharia Florestal e dos Recursos Naturais / Instituto Superior de Agronomia. Universidade de Lisboa<br>The main goal of the study is to analyse the possibility of quantifying the loss of biomass in burned forest stands using Light Detection and Ranging (LiDAR) data. Since wildfires are not uncommon in Mediterranean areas, it is useful to quantify the magnitude of fire damage in forests. With the use of remote sensing, it is possible to plan post-fire recovery management and to quantify the losses of biomass and carbon stock. Mata Nacional de Leiria (MNL) was chosen, because, aft
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El, Vilaly Mohamed Abd salam Mohamdy. "Drought Monitoring with Remote Sensing Based Land Surface Phenology Applications and Validation." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/301553.

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Droughts are a recurrent part of our climate, and are still considered to be one of the most complex and least understood of all natural hazards in terms of their impact on the environment. In recent years drought has become more common and more severe across the world. For more than a decade, the US southwest has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources. The focus of this work is achieving a better understanding of the impact of drought on the lands of the Hopi Tribe and Navajo Nation, situated in the Northeastern co
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McCurdy, Wyatt Conner. "Characterizing spatiotemporal variation in LAI of Virginia Pine Plantations." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/96595.

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Loblolly pine is an important managed tree species within the southeastern United States, and better understanding spatial patterns in its productivity has potential to contribute to both modeling and management of the species. Using recently-created pine management maps specific to Virginia and empirical relationships predicting pine LAI from the Landsat satellite, we conducted a statewide analysis of temporal patterns in stand-level southern pine leaf area index (LAI) following clear-cut and planting. Here, using 28 years of Landsat time-series data for 13,140 stands that were clear-cut betw
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Books on the topic "Severity Index and Remote Sensing"

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Firestone, Elaine R. SeaWiFS technical report series cumulative index: volumes 1-23. National Aeronautics and Space Administration, Goddard Space Flight Center, 1995.

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Troshichev, O. A. Space weather monitoring by ground-based means: PC index. Springer, 2012.

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Firestone, Elaine R. SeaWiFS technical report series cumulative index, volumes 1-29. National Aeronautics and Space Administration, Goddard Space Flight Center, 1996.

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Jiang, Shi. Satellite observed mesoscale convective system (MCS) propagation characteristics and a 3-12 hour heavy precipitation forecast index. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1987.

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Plummer, Stephen E. BOREAS RSS-4 1994 jack pine leaf biochemistry and modeled spectra in the SSA. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Terry, Dawson, and Goddard Space Flight Center, eds. BOREAS RSS-4 1994 jack pine leaf biochemistry and modeled spectra in the SSA. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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United States. National Aeronautics and Space Administration., ed. A remote-sensing based technique to account for sub-grid scale variability of land surface properties. National Aeronautics and Space Administration, 1995.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Book chapters on the topic "Severity Index and Remote Sensing"

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Gitas, Ioannis Z., Angela de Santis, and George H. Mitri. "Remote Sensing of Burn Severity." In Earth Observation of Wildland Fires in Mediterranean Ecosystems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01754-4_10.

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Niklaus, Markus, Christina Eisfelder, Ursula Gessner, and Stefan Dech. "Land Degradation in South Africa – A Degradation Index Derived from 10 Years of Net Primary Production Data." In Remote Sensing Time Series. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15967-6_12.

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Santra, Abhisek, Shreyashi Santra Mitra, Suman Sinha, Shidharth Routh, and Akhilesh Kumar. "Identification of Impervious Built-Up Surface Features Using ResourceSat-2 LISS-III-Based Novel Optical Built-Up Index." In Remote Sensing and GIScience. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55092-9_7.

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Cao, Chunxiang, Min Xu, Patcharin Kamsing, Sornkitja Boonprong, Peera Yomwan, and Apitach Saokarn. "Flooding Identification by Vegetation Index." In Environmental Remote Sensing in Flooding Areas. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8202-8_3.

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Patil, Krishna, Kajal Rathod, Ashwin Gujrati, and Ravindra Pawar. "Remote Sensing of Freshwater Algal Blooms: A Spectral Index Approach." In Remote Sensing for Environmental Monitoring. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-5546-5_7.

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Enenkel, Markus, Daniel Osgood, and Bristol Powell. "The Added Value of Satellite Soil Moisture for Agricultural Index Insurance." In Remote Sensing of Hydrometeorological Hazards. CRC Press, 2017. http://dx.doi.org/10.1201/9781315154947-4.

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Stathopoulos, Nikolaos, Kleomenis Kalogeropoulos, Christos Polykretis, et al. "Introducing Flood Susceptibility Index Using Remote-Sensing Data and Geographic Information Systems." In Remote Sensing of Hydrometeorological Hazards. CRC Press, 2017. http://dx.doi.org/10.1201/9781315154947-18.

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Malingreau, J. P. "The Vegetation Index and the Study of Vegetation Dynamics." In Applications of Remote Sensing to Agrometeorology. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2235-8_12.

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Hussain, Nur, Muhammad Rizwan, Mohd Shamsul Alam, and Li Suju. "Remote Sensing Applications in Landslide Susceptibility Index Mapping of Rangamati District, Bangladesh." In Re-envisioning Advances in Remote Sensing. CRC Press, 2022. http://dx.doi.org/10.1201/9781003224624-11.

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Jenice Aroma, R., and Kumudha Raimond. "A Wavelet Transform Applied Spectral Index for Effective Water Body Extraction from Moderate-Resolution Satellite Images." In Remote Sensing and Digital Image Processing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24178-0_12.

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Conference papers on the topic "Severity Index and Remote Sensing"

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Mondal, Suresh, K. Arun Prasad, K. Balasubramani, and S. Kaliraj. "Assessment of Agricultural Drought Severity in the Southern Agroclimatic Region of Tamil Nadu using Remote Sensing-Based Combined Drought Index." In 2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2024. https://doi.org/10.1109/ingarss61818.2024.10983938.

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Kasetkasem, Teerasit, Surasak Choedpasuporn, and Pudtraporn Napang. "Rice Paddy Flood Damage Severity Assessment Using Drone Images." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641579.

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Tran, Nguyen Bang, Mihai A. Tanase, Lauren T. Bennett, and Cristina Aponte. "Fire-severity classification across temperate Australian forests: random forests versus spectral index thresholding." In Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, edited by Christopher M. Neale and Antonino Maltese. SPIE, 2019. http://dx.doi.org/10.1117/12.2535616.

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Massetti, Andrea, Christoph Rudiger, Marta Yebra, and James Hilton. "The Vegetation Structure Perpendicular Index for Wildfire Severity and Forest Recovery Monitoring." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518628.

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Touati, Fatah, Nawel Benaraba, and Slimane Benyahia. "Grace-Based Observations for Near Real-Time Assessment of Groundwater Drought Severity Index." In 2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS). IEEE, 2024. http://dx.doi.org/10.1109/m2garss57310.2024.10537483.

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Zhang, Liang, Huqiang Zhang, Qiang Zhang, and Jing Wang. "Comparison of a land surface model and Palmer drought severity index in monitoring drought in China." In IGARSS 2011 - 2011 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2011. http://dx.doi.org/10.1109/igarss.2011.6049517.

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Dragozi, E., Ioannis Z. Gitas, Dimitris G. Stavrakoudis, and C. Minakou. "Burn severity estimation using GeoEye imagery, object-based image analysis (OBIA), and Composite Burn Index (CBI) measurements." In Third International Conference on Remote Sensing and Geoinformation of the Environment, edited by Diofantos G. Hadjimitsis, Kyriacos Themistocleous, Silas Michaelides, and Giorgos Papadavid. SPIE, 2015. http://dx.doi.org/10.1117/12.2193149.

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TRIFAN, Tudor, and Vera POTOPOVÁ. "2022 drought in the Danube river basin." In "Mediul şi dezvoltarea durabilă", conferinţă ştiinţifică naţională cu participare internaţională. Ion Creangă Pedagogical State University, 2024. https://doi.org/10.46727/cg.17-18-05-2024.p79-90.

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This summary presents a case study of drought conditions in the Danube River Basin, Czech Republic and Republic of Moldova in the period March - August 2022. The study uses remote sensing and climate indices to assess drought evolution. SPEI (Standardized Precipitation Evapotranspiration Index) calibrated at 3 and 12 weeks, this standardized drought severity index captures both short-term and long-term drought events. SWI (Soil Water Index) at depths of 40 and 100 centimeters, it indicates soil moisture conditions, providing information on water availability for plants. ESI (Evaporative Stress
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Madhumal, P. V. R. P., and H. G. L. N. Gunawardhana. "Evaluating the impact of drought spatial distribution on river flow dynamics using remote sensing data." In Civil Engineering Research Symposium 2024. Department of Civil Engineering, University of Moratuwa, 2024. http://dx.doi.org/10.31705/cers.2024.33.

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Drought is a complex and challenging weather-related disaster with significant economic, social, and environmental impacts. Traditional drought monitoring, which primarily relies on ground observations, often falls short due to limited spatial coverage and data scarcity. Most existing drought indices focus on a single variable, which may not adequately capture the full scope of drought conditions. To address this, integrating multiple parameters from remote sensing data presents a promising approach, providing spatially distributed and real-time information for a more accurate and comprehensiv
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Psomiadis, Emmanouil, Emmanouela Zevgoli, Marilou Avramidou, Dimitra Veropoulou, Simoni Alexiou, and Petros Mecaj. "Examining the correlation of remote sensing burn severity indices with the composite burn index method along with natural and anthropogenic features and fire frequency to analyze their impact on potential vegetation recovery: the case of the Varibobi wildfire in Athens/Greece." In Earth Resources and Environmental Remote Sensing/GIS Applications XIV, edited by Karsten Schulz, Konstantinos G. Nikolakopoulos, and Ulrich Michel. SPIE, 2023. http://dx.doi.org/10.1117/12.2679379.

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Reports on the topic "Severity Index and Remote Sensing"

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Forson, Eric Dominic, David Dotse Wemegah, Godfred Bright Hagan, et al. Data-Driven Multi-Index Overlay Gold Prospectivity Mapping Using Geophysical and Remote Sensing Datasets. Peeref, 2022. http://dx.doi.org/10.54985/peeref.2209p5617862.

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Spangenberg Kellner, Claire, Rebecca Molinari, Diane Menuz, Peter Goodwin, and Hugh Hurlow. Great Salt Lake Shorelands Preserve Water Budget, Stream Monitoring, Vegetation Mapping, and Remote Sensing Analysis. Utah Geological Survey, 2025. https://doi.org/10.34191/ri-289.

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The Great Salt Lake Shorelands Preserve (“Preserve” hereafter) includes nearly 5000 acres of wetlands, interspersed ponds and ditches, and uplands on the eastern margin of Great Salt Lake (GSL) in Davis County, Utah. The wetlands provide critical habitat for local and migratory birds on the North American Flyway and a wide range of other species, and important ecological functions including water-quality improvement and flood control. Changes in invasive vegetation, drought conditions, and land-use practices threaten the long-term water supply, water quality, and ecological health of the Prese
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Johansen, Richard A., Christina L. Saltus, Molly K. Reif, and Kaytee L. Pokrzywinski. A Review of Empirical Algorithms for the Detection and Quantification of Harmful Algal Blooms Using Satellite-Borne Remote Sensing. U.S. Army Engineer Research and Development Center, 2022. http://dx.doi.org/10.21079/11681/44523.

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Harmful Algal Blooms (HABs) continue to be a global concern, especially since predicting bloom events including the intensity, extent, and geographic location, remain difficult. However, remote sensing platforms are useful tools for monitoring HABs across space and time. The main objective of this review was to explore the scientific literature to develop a near-comprehensive list of spectrally derived empirical algorithms for satellite imagers commonly utilized for the detection and quantification HABs and water quality indicators. This review identified the 29 WorldView-2 MSI algorithms, 25
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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water
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Salazar, Lina, Marcos Agurto Adrianzen, and Luis Alvarez. Estimating the Long-term Effects of a Fruit Fly Eradication Program Using Satellite Imagery. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005056.

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This analysis applies a regression discontinuity approach combined with remote sensing data to measure the productivity impacts linked to a fruit-fly eradication program, implemented in Peru. For this purpose, satellite imagery was used to estimate a vegetation index over a 10-year span for a sample of 305 producers -155 treated and 150 controls-. The results confirmed that program participation increased agricultural productivity in the short and long terms, in a range from 12% to 49%. However, quantile regression methods suggest that most productive farmers were able to obtain greater impact
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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are ob
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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the proj
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