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Journal articles on the topic 'OSAVI'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Rizqika Ayu, Karina, Bangun Muljo Sukojo, and Dyah Ayu Retno Mukti. "Correlation Analysis of Vegetation Index Impact on Rice Paddy Productivity Estimation using Landsat-8 and Sentinel-2A Images (Case Study: Blitar District)." IOP Conference Series: Earth and Environmental Science 1418, no. 1 (2024): 012007. https://doi.org/10.1088/1755-1315/1418/1/012007.

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Abstract Rice is consumed by most of the population in Indonesia. The generative phase, the final stage of rice growth cycle, produces raw grains that are processed into rice, forming the basis of rice production. To estimate rice paddy productivity in March 2023, vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the Optimized Soil-Adjusted Vegetation Index (OSAVI) are used. These indices are crucial as they correlate with rice paddy areas in the generative phase. Sentinel-2A imagery calculations have shown strong correlations, with NDVI at R = 0.61 and OSAVI at

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Duddu, Hema S. N., Eric N. Johnson, Christian J. Willenborg, and Steven J. Shirtliffe. "High-Throughput UAV Image-Based Method Is More Precise Than Manual Rating of Herbicide Tolerance." Plant Phenomics 2019 (September 15, 2019): 1–9. http://dx.doi.org/10.34133/2019/6036453.

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The traditional visual rating system is labor-intensive, time-consuming, and prone to human error. Unmanned aerial vehicle (UAV) imagery-based vegetation indices (VI) have potential applications in high-throughput plant phenotyping. The study objective is to determine if UAV imagery provides accurate and consistent estimations of crop injury from herbicide application and its potential as an alternative to visual ratings. The study was conducted at the Kernen Crop Research Farm, University of Saskatchewan in 2016 and 2017. Fababean (Vicia faba L.) crop tolerance to nine herbicide tank mixtures

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Gianquinto, Giorgio, Francesco Orsini, Giuseppina Pennisi, and Stefano Bona. "Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry." Sensors 19, no. 21 (2019): 4730. http://dx.doi.org/10.3390/s19214730.

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Canopy reflectance sensors are a viable technology to optimize the fertilization management of crops. In this research, canopy reflectance was measured through a passive sensor to evaluate the effects of either crop features (N fertilization, soil mulching, appearance of red fruits, and cultivars) or sampling methods (sampling size, sensor position, and hour of sampling) on the reliability of vegetation indices (VIs). Sixteen VIs were derived, including seven simple wavelength reflectance ratios (NIR/R460, NIR/R510, NIR/R560, NIR/R610, NIR/R660, NIR/R710, NIR/R760), seven normalized indices (N

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Al-Zwbaidi, Halima Ibrahim Ali. "Assessing the Status of Drought Using Remote Sensing: An empirical study in the Western areas of the Taif district in Saudi Arabia." Journal of Arts and Social Sciences [JASS] 6, no. 3 (2015): 61. http://dx.doi.org/10.24200/jass.vol6iss3pp61-74.

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This study aimed to utilize spectral indices in investigating the current drought of Taiff district in the 26 years (1984-2010). The study relies on processing and analysing of satellite data through several professional computer programs including ER Mapper, ERDAS and ArcGIS, where several spectral indices were used to evaluate the extent of the drought. The indices used in this study are OSAVI, VCI, TCI and VHI. Considering the results of the study, the indices: VIC, TCI, VHI and OSAVI which generally illustrate the deterioration in the ecosystem in the study area that can be considered now

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Al-Zwbaidi, Halima Ibrahim Ali. "Assessing the Status of Drought Using Remote Sensing: An empirical study in the Western areas of the Taif district in Saudi Arabia." Journal of Arts and Social Sciences [JASS] 6, no. 3 (2015): 61–74. http://dx.doi.org/10.53542/jass.v6i3.1099.

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This study aimed to utilize spectral indices in investigating the current drought of Taiff district in the 26 years (1984-2010). The study relies on processing and analysing of satellite data through several professional computer programs including ER Mapper, ERDAS and ArcGIS, where several spectral indices were used to evaluate the extent of the drought. The indices used in this study are OSAVI, VCI, TCI and VHI. Considering the results of the study, the indices: VIC, TCI, VHI and OSAVI which generally illustrate the deterioration in the ecosystem in the study area that can be considered now

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Wu, Bin, Wenjiang Huang, Huichun Ye, Peilei Luo, Yu Ren, and Weiping Kong. "Using Multi-Angular Hyperspectral Data to Estimate the Vertical Distribution of Leaf Chlorophyll Content in Wheat." Remote Sensing 13, no. 8 (2021): 1501. http://dx.doi.org/10.3390/rs13081501.

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Heterogeneity exists in the vertical distribution of the biochemical components of crops. A leaf chlorophyll deficiency occurs in the bottom- and middle-layers of crops due to nitrogen stress and leaf senescence. Some studies used multi-angular remote sensing data for estimating the vertical distribution of the leaf chlorophyll content (LCC). However, these studies performed LCC inversion of different vertical layers using a fixed view zenith angle (VZA), but rarely considered the contribution of the components of the non-target layers to the spectral response. The main goal of this work was t

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ANDRADE JUNIOR, ADERSON SOARES DE, EDSON ALVES BASTOS, CARLOS ANTONIO FERREIRA DE SOUSA, RAPHAEL AUGUSTO DAS CHAGAS NOQUELI CASARI, and BRAZ HENRIQUE NUNES RODRIGUES. "WATER STATUS EVALUATION OF MAIZE CULTIVARS USING AERIAL IMAGES." Revista Caatinga 34, no. 2 (2021): 432–42. http://dx.doi.org/10.1590/1983-21252021v34n219rc.

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ABSTRACT The objective of this study was to evaluate the water status of maize cultivars through thermal and vegetation indexes generated from multispectral aerial images obtained from an unmanned aerial vehicle (UAV), and correlate them with physiological indicators and soil water contents. The application of three water regimes based on the reference evapotranspiration (ETo) (30%, 90%, and 150% ETo) was evaluated for two maize cultivars (AG-1051 and BRS-Caatingueiro). An UAV was used to acquire thermal and multispectral images. The indexes evaluated were CWSI, CI-G, CI-RE, CIV, NDVI and OSAV

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8

Zhao, Wenhui, Jianjun Wu, Qiu Shen, Jianhua Yang, and Xinyi Han. "Exploring the Ability of Solar-Induced Chlorophyll Fluorescence for Drought Monitoring Based on an Intelligent Irrigation Control System." Remote Sensing 14, no. 23 (2022): 6157. http://dx.doi.org/10.3390/rs14236157.

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Drought is one of the most devastating disasters and a serious constraint on agricultural development. The reflectance-based vegetation indices (VIs), such as Normalized Difference Vegetation Index (NDVI), have been widely used for drought monitoring, but there is a lag in the response of VIs to the changes of photosynthesis induced by drought. Solar-induced chlorophyll fluorescence (SIF) is closely related to photosynthesis of vegetation and can capture changes induced by drought timely. This study investigated the capability of SIF for drought monitoring. An intelligent irrigation control sy

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Kong, Jiying, Zhenhai Luo, Chao Zhang, et al. "Identification of Robust Hybrid Inversion Models on the Crop Fraction of Absorbed Photosynthetically Active Radiation Using PROSAIL Model Simulated and Field Multispectral Data." Agronomy 13, no. 8 (2023): 2147. http://dx.doi.org/10.3390/agronomy13082147.

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The fraction of absorbed photosynthetically active radiation (FPAR), which represents the capability of vegetation-absorbed solar radiation to accumulate organic matter, is a crucial indicator of photosynthesis and vegetation growth status. Although a simplified semi-empirical FPAR estimation model was easily obtained using vegetation indices (VIs), the sensitivity and robustness of VIs and the optimal inversion method need to be further evaluated and developed for canola FPAR retrieval. The objective of this study was to identify the robust hybrid inversion model for estimating the winter can

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Leolini, Luisa, Marco Moriondo, Riccardo Rossi, et al. "Use of Sentinel-2 Derived Vegetation Indices for Estimating fPAR in Olive Groves." Agronomy 12, no. 7 (2022): 1540. http://dx.doi.org/10.3390/agronomy12071540.

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Olive tree cultivation is currently a dominant agriculture activity in the Mediterranean basin, where the increasing impact of climate change coupled with the inefficient management of olive groves is negatively affecting olive oil production and quality in some marginal areas. In this context, satellite imagery may help to monitor crop growth under different environmental conditions, thus providing useful information for optimizing olive grove management and final production. However, the spatial resolution of freely-available satellite products is not yet adequate to estimate plant biophysic

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Zhou, Huailin, Guangsheng Zhou, Xingyang Song, and Qijin He. "Dynamic Characteristics of Canopy and Vegetation Water Content during an Entire Maize Growing Season in Relation to Spectral-Based Indices." Remote Sensing 14, no. 3 (2022): 584. http://dx.doi.org/10.3390/rs14030584.

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A variety of spectral vegetation indices (SVIs) have been constructed to monitor crop water stress. However, their abilities to reflect dynamic canopy water content (CWC) and vegetation water content (VWC) during the growing season have not been concurrently examined, and the underlying mechanisms remain unclear, especially in relation to soil drying. In this study, a field experiment was conducted and designed with various irrigation regimes applied during two consecutive growing seasons of maize. The results showed that CWC, VWC, and the SVIs exhibited obvious trends of first increasing and

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Annala, Leevi, Eija Honkavaara, Sakari Tuominen, and Ilkka Pölönen. "Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion." Remote Sensing 12, no. 2 (2020): 283. http://dx.doi.org/10.3390/rs12020283.

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Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The

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Lyu, Hongyi, Miles Grafton, Thiagarajah Ramilan, Matthew Irwin, Hsiang-En Wei, and Eduardo Sandoval. "Using Remote and Proximal Sensing Data and Vine Vigor Parameters for Non-Destructive and Rapid Prediction of Grape Quality." Remote Sensing 15, no. 22 (2023): 5412. http://dx.doi.org/10.3390/rs15225412.

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The traditional method for determining wine grape total soluble solid (TSS) is destructive laboratory analysis, which is time consuming and expensive. In this study, we explore the potential of using different predictor variables from various advanced techniques to predict the grape TSS in a non-destructive and rapid way. Calculating Pearson’s correlation coefficient between the vegetation indices (VIs) obtained from UAV multispectral imagery and grape TSS resulted in a strong correlation between OSAVI and grape TSS with a coefficient of 0.64. Additionally, seven machine learning models includ

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14

Steven, Michael D. "The Sensitivity of the OSAVI Vegetation Index to Observational Parameters." Remote Sensing of Environment 63, no. 1 (1998): 49–60. http://dx.doi.org/10.1016/s0034-4257(97)00114-4.

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Rendulić Jelušić, Ivana, Branka Šakić Bobić, Zoran Grgić, et al. "Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt." Agriculture 12, no. 6 (2022): 852. http://dx.doi.org/10.3390/agriculture12060852.

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The practical application of grape quality zoning and selective harvesting in small vineyards (<1 ha) has not yet gained much importance worldwide. However, winegrowers with small vineyards are looking for ways to improve wine quality and maximise profit. Therefore, the aim of this study was to identify the most predictive vegetation index for grape quality zoning among three vegetation indices—NDVI, NDRE, and OSAVI—at three grapevine growth stages for the efficient use in small vineyards for the selective harvesting and production of different wine types from the same vineyard. Multispectr

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16

Hayati, Dwi, and Sri Yulianto Joko Prasetyo. "Prediksi Spasial Wilayah Resiko Tanah Longsor Di Jawa Tengah Berdasarkan SAVI, OSAVI, DVI, NDVI Menggunakan Krigging." Indonesian Journal of Computing and Modeling 1, no. 2 (2018): 80–86. http://dx.doi.org/10.24246/j.icm.2018.v1.i2.p80-86.

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Landslides are the process of moving rock periods (soil) due to gravity. On the spatial prediction of landslide occurrence in the District in Central Java based on vegetation index using kriging. The vegetation index is the amount of green vegetation values obtained from the processing of digital signal data of the brightness value of several satellite sensor data channels. Some of the vegetation index algorithms used are SAVI (Soil Adjusted Vegetation Index), OSAVI (Optimized Soil Adjusted Vegetation Index), DVI (Difference Vegetation Index), NDVI (Normalized Difference Vegetation Index). Kri

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Azmi, Rahajeng Aulia, Lalu Muhamad Jaelani, and Lena Sumargana. "Pemanfaatan Data Citra Satelit Sentinel-2 untuk Estimasi Kandungan Nitrogen Pada Tanaman Jagung (Studi Kasus : Desa Jadi, Kecamatan Semanding, Kabupaten Tuban)." GEOID 19, no. 3 (2024): 529–42. https://doi.org/10.12962/geoid.v19i3.1910.

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Jagung (Zea mays L.) adalah tanaman semusim dengan beberapa varietas, termasuk NK 6172 (Perkasa), NK 212 (Wirosableng), dan NK 7328 (Sumo). Identifikasi varietas jagung dilakukan menggunakan metode Linear Spectral Unmixing yang menghasilkan peta sebaran varietas, dimana NK 6172 (Perkasa) mendominasi dengan 80,97%, diikuti oleh NK 7328 (Sumo) dengan 15,15%, dan NK 212 (Wirosableng) dengan 3,48%. Untuk mengidentifikasi fase pertumbuhan jagung ditentukan menggunakan citra MODIS dan algoritma NDVI serta NDWI. Pada penelitian ini lahan jagung diklasifikasikan dengan metode Support Vector Machine da

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Anggraini, N., A. A. M. A. P. Suardana, M. R. Nandika, et al. "Mangrove damage based on canopy density derived on SPOT 6 at Ngurah Rai forest park, Bali." IOP Conference Series: Earth and Environmental Science 1224, no. 1 (2023): 012017. http://dx.doi.org/10.1088/1755-1315/1224/1/012017.

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Abstract The Indonesian government has launched a mangrove rehabilitation program of 600,000 ha in 2021-2024. This program needs information about mangrove forest damage obtained quickly and accurately. Remote sensing technology is a solution to the availability of the required speed of information. Mangrove damage information can be obtained from the canopy density derived from the vegetation index. This study aims to detect mangrove damage based on the density level derived from the vegetation index. The data used are SPOT 6 satellite imagery recorded in 2020 with the research location in Ng

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Suszek, Grazieli, Eduardo Godoy de Souza, Miguel Angel Uribe-Opazo, Lúcia Helena Pereira Nóbrega, and Márcia Regina Siqueira Konopazki. "INFLUÊNCIA DA DIREÇÃO DA SEMEADURA E DA HORA DO DIA EM ÍNDICES DE VEGETAÇÃO." REVISTA ENGENHARIA NA AGRICULTURA - REVENG 18, no. 5 (2010): 405–12. http://dx.doi.org/10.13083/reveng.v18i5.250.

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A necessidade de nitrogênio (N) apresenta grande variabilidade espacial dentro de uma mesma área. A aplicação da real necessidade de N pode aumentar o rendimento, reduzir a aplicação desnecessária e o fluxo para os lençóis freáticos. A medida da reflectância espectral e conseqüente cálculo de índices de vegetação são considerados promissoras abordagens não destrutivas e sem contato para o sensoriamento instantâneo da deficiência de N em milho. Neste trabalho procurou-se estudar a influência da direção da semeadura e da hora do dia nos índices de vegetação no milho. As linhas de semeadura foram

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Neves, Sabrina Oliveira, Paula de Aguiar Silva, Gildriano Soares de Oliveira, Jackson Paulo Silva Souza, and Érica Pereira Cardozo. "Correlação entre a Produtividade do Milho e os Índices de Vegetação Utilizando Imagens do Sentinel 2." Revista de Gestão e Secretariado 16, no. 4 (2025): e4811. https://doi.org/10.7769/gesec.v16i4.4811.

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Este estudo analisou a correlação entre a produtividade do milho e os índices de vegetação NDVI, NDRE e OSAVI, utilizando imagens multiespectrais do satélite Sentinel-2. A pesquisa foi conduzida em uma propriedade agrícola no Triângulo Mineiro ao longo das safras de 2020 e 2021, abrangendo uma área de 277 hectares distribuída em cinco pivôs de irrigação. Os índices de vegetação foram calculados a partir das bandas espectrais do Sentinel-2 e analisados estatisticamente por meio de modelos de regressão para avaliar sua relação com a produtividade do milho. Os resultados indicaram uma forte corre

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Pavlova, Anna I. "APPLICATION OF VEGETATION INDECES FOR DOGITAL SOIL MAPPING BASED ON SENTINEL-2 SPACE IMAGES." Siberian Journal of Life Sciences and Agriculture 13, no. 6 (2021): 119–31. http://dx.doi.org/10.12731/2658-6649-2021-13-6-119-131.

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At present, the works devoted to the creation of digital soil maps using geographic information systems (GIS) and remote sensing (RS) data are relevant. In the work the analysis of vegetation indices (VI) for soil mapping was carried out, the maps of vegetation indices were created: Normalized Difference Vegetation Index (NDVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Soil-Adjusted Vegetation Index (SAVI), Tranformed Soil-Adjusted Vegetation Index (TSAVI), Enhanced Vegetation Index2 (EVI2) for the territory of ZAO Mirny farm of Kochenevsky District using Sentinel-2 A satellite image

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Zhao, Yan, Andries B. Potgieter, Miao Zhang, Bingfang Wu, and Graeme L. Hammer. "Predicting Wheat Yield at the Field Scale by Combining High-Resolution Sentinel-2 Satellite Imagery and Crop Modelling." Remote Sensing 12, no. 6 (2020): 1024. http://dx.doi.org/10.3390/rs12061024.

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Accurate prediction of crop yield at the field scale is critical to addressing crop production challenges and reducing the impacts of climate variability and change. Recently released Sentinel-2 (S2) satellite data with a return cycle of five days and a high resolution at 13 spectral bands allows close observation of crop phenology and crop physiological attributes at field scale during crop growth. Here, we test the potential for indices derived from S2 data to estimate dryland wheat yields at the field scale and the potential for enhanced predictability by incorporating a modelled crop water

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Khairunnisa, Dita, Mochtar Lutfi Rayes, and Christanti Agustina. "PEMANFAATAN INDEKS VEGETASI UNTUK ESTIMASI KANDUNGAN KALIUM PADA TANAMAN NANAS (Ananas comosus) MENGGUNAKAN UAV (Unmanned Aerial Vehicle) DI PT. GREAT GIANT PINEAPPLE, LAMPUNG." Jurnal Tanah dan Sumberdaya Lahan 8, no. 1 (2020): 91–99. http://dx.doi.org/10.21776/ub.jtsl.2021.008.1.12.

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PT Great Giant Pineapple (PT. GGP) is the largest pineapple production company in Indonesia. One of the nutrients that pineapple plants really need is potassium (K). K plays a key role in carbohydrate metabolism and transport of photosynthates from source to sink. Remote sensing technology has been developed to estimate nutrient status, one of which is using an Unmanned Aerial Vehicle (UAV). This study aims to estimate the K nutrient content in pineapple plants using vegetation indexes in the form of NDVI (Normalyzed Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index), and OSAV

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Liu, Shenzhou, Wenzhi Zeng, Lifeng Wu, et al. "Simulating the Leaf Area Index of Rice from Multispectral Images." Remote Sensing 13, no. 18 (2021): 3663. http://dx.doi.org/10.3390/rs13183663.

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Accurate estimation of the leaf area index (LAI) is essential for crop growth simulations and agricultural management. This study conducted a field experiment with rice and measured the LAI in different rice growth periods. The multispectral bands (B) including red edge (RE, 730 nm ± 16 nm), near-infrared (NIR, 840 nm ± 26 nm), green (560 nm ± 16 nm), red (650 nm ± 16 nm), blue (450 nm ± 16 nm), and visible light (RGB) were also obtained by an unmanned aerial vehicle (UAV) with multispectral sensors (DJI-P4M, SZ DJI Technology Co., Ltd.). Based on the bands, five vegetation indexes (VI) includ

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Qin, Minghao, Ruren Li, Huichun Ye, Chaojia Nie, and Yue Zhang. "Study on the Extraction of Maize Phenological Stages Based on Multiple Spectral Index Time-Series Curves." Agriculture 14, no. 11 (2024): 2052. http://dx.doi.org/10.3390/agriculture14112052.

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The advent of precision agriculture has highlighted the necessity for the careful determination of crop phenology at increasingly smaller scales. Although remote sensing technology is extensively employed for the monitoring of crop growth, the acquisition of high-precision phenological data continues to present a significant challenge. This study, conducted in Youyi County, Shuangyashan City, Heilongjiang Province, China, employed time-series spectral index data derived from Sentinel-2 remote sensing images to investigate methodologies for the extraction of pivotal phenological phases during t

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Bian, Jiang, Zhitao Zhang, Junying Chen, et al. "Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery." Remote Sensing 11, no. 3 (2019): 267. http://dx.doi.org/10.3390/rs11030267.

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Irrigation water management and real-time monitoring of crop water stress status can enhance agricultural water use efficiency, crop yield, and crop quality. The aim of this study was to simplify the calculation of the crop water stress index (CWSI) and improve its diagnostic accuracy. Simplified CWSI (CWSIsi) was used to diagnose water stress for cotton that has received four different irrigation treatments (no stress, mild stress, moderate stress, and severe stress) at the flowering and boll stage. High resolution thermal infrared and multispectral images were taken using an Unmanned Aerial

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Binte Mostafiz, Rubaiya, Ryozo Noguchi, and Tofael Ahamed. "Agricultural Land Suitability Assessment Using Satellite Remote Sensing-Derived Soil-Vegetation Indices." Land 10, no. 2 (2021): 223. http://dx.doi.org/10.3390/land10020223.

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Satellite remote sensing technologies have a high potential in applications for evaluating land conditions and can facilitate optimized planning for agricultural sectors. However, misinformed land selection decisions limit crop yields and increase production-related costs to farmers. Therefore, the purpose of this research was to develop a land suitability assessment system using satellite remote sensing-derived soil-vegetation indicators. A multicriteria decision analysis was conducted by integrating weighted linear combinations and fuzzy multicriteria analyses in a GIS platform for suitabili

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Bai, Xueyuan, Yingqiang Song, Ruiyang Yu, et al. "Hyperspectral Estimation of Apple Canopy Chlorophyll Content Using an Ensemble Learning Approach." Applied Engineering in Agriculture 37, no. 3 (2021): 505–11. http://dx.doi.org/10.13031/aea.13935.

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HighlightsMonitored the canopy chlorophyll content of apple trees using hyperspectral reflectance information.Constructed support vector machine combination regression model (C-SVR) based on five-fold cross validation and support vector machine regression approach.Compared estimation accuracy of ensemble learning models (C-SVR, RF), machine learning models (SVR, ANN), and PLSR models for apple canopy chlorophyll content.Abstract. Rapidly and effective monitoring of the canopy chlorophyll content (CCC) of apple trees is of great significance for crop stress monitoring in precision agriculture.

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Wang, Xiaoxuan, Guosheng Cai, Xiaoping Lu, Zenan Yang, Xiangjun Zhang, and Qinggang Zhang. "Inversion of Wheat Leaf Area Index by Multivariate Red-Edge Spectral Vegetation Index." Sustainability 14, no. 23 (2022): 15875. http://dx.doi.org/10.3390/su142315875.

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Leaf area index (LAI) is an important parameter that determines the growth status of winter wheat and impacts the ecological and physical processes of plants in ecosystems. The problem of spectral saturation of winter wheat LAI at the booting stage was easily caused by the inversion of the univariate red-edge spectral vegetation index constructed by the red-edge band. In this paper, a new method that the univariate red-edge spectral vegetation index constructed in the red-edge band is used to invert the spectral saturation of the winter wheat LAI. The multivariable red-edge spectral vegetation

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Victor, Aghimien Ehimwenma. "Above-ground carbon stock estimation using pleiades satellite imagery of the secondary forest ecosystem in Ibadan, Nigeria." Forestry Research and Engineering: International Journal 3, no. 2 (2019): 46–54. http://dx.doi.org/10.15406/freij.2019.03.00077.

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Secondary forest ecosystem contributes to global climate change mitigation through carbon sequestration. Above-Ground Biomass (AGB) is the major component for monitoring and estimating Carbon Stocks (CS) and fluxes in tropical forests. However, information on Above-Ground Carbon Stock (AGCS) for the International Institute of Tropical Agriculture (IITA), which hosts relics of the undisturbed secondary forest ecosystem in south-western Nigeria, has not been documented. Therefore, AGCS of the secondary forest ecosystem was estimated using remote sensing techniques. Pleiades satellite data were u

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Jełowicki, Łukasz, Konrad Sosnowicz, Wojciech Ostrowski, Katarzyna Osińska-Skotak, and Krzysztof Bakuła. "Evaluation of Rapeseed Winter Crop Damage Using UAV-Based Multispectral Imagery." Remote Sensing 12, no. 16 (2020): 2618. http://dx.doi.org/10.3390/rs12162618.

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This research is related to the exploitation of multispectral imagery from an unmanned aerial vehicle (UAV) in the assessment of damage to rapeseed after winter. Such damage is one of a few cases for which reimbursement may be claimed in agricultural insurance. Since direct measurements are difficult in such a case, mainly because of large, unreachable areas, it is therefore important to be able to use remote sensing in the assessment of the plant surface affected by frost damage. In this experiment, UAV images were taken using a Sequoia multispectral camera that collected data in four spectra

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Mouadili, Omar, and Abdelkader Sbai. "The role of GIS and remote sensing in tracking vegetation cover in the Tlagh and El-Abed Basins (Northeastern Morocco) from 1986 to 2018." E3S Web of Conferences 607 (2025): 04020. https://doi.org/10.1051/e3sconf/202560704020.

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The Tlagh and El-Abed basins in the Taourirt-Guercif corridor are known for their diverse plant cover, especially in species naturally present for generations, termed 'inherited species'. However, this diversity needs to be more evenly distributed. Vegetation degradation is concentrated in the piedmonts and reliefs of both basins, attributed to topography, lithology, soil type, and climate. These formations, categorized into various types, all exhibit severe degradation due to persistent drought. Plant cover has decreased over time due to species disappearance or emergence of new formations ad

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Fern, Rachel R., Elliott A. Foxley, Andrea Bruno, and Michael L. Morrison. "Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland." Ecological Indicators 94 (November 2018): 16–21. http://dx.doi.org/10.1016/j.ecolind.2018.06.029.

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Mohd Salleh, M. R., Z. Ismail, S. A. Mohd Ariff, et al. "SPATIAL PREDICTION MODELS FOR LANDSLIDE ACTIVITY MAPPING USING VEGETATION ANOMALIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 441–49. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-441-2019.

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Abstract. An area that located in Kundasang which in Ranau district in Sabah, Malaysia that lies along the bank of Kundasang valley was chosen for comparing the reliability of frequency ratio (FR) and weight of evidence (WoE) methods for landslide activity probability mapping by using related vegetation anomalies indicator. The locations of 47 and 189 of active and dormant landslides respectively were identified using 4 raster layers (topographic openness, hillshade, colour composite and high resolution orthophoto). Each landslide activites were randomly divided into two groups as training (70

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Jelev, Georgi, Petar Dimitrov, and Eugenia Roumenina. "Within-Field Mapping of Winter Wheat Biophysical Variables Using Multispectral Images from UAV." Aerospace Research in Bulgaria 34 (2022): 13–28. http://dx.doi.org/10.3897/arb.v34.e02.

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The paper presents the results from a study aiming to map the dynamic of biophysical variables of winter wheat crops in different phenological growth stages (PGSs) using multispectral camera data acquired by Unmanned Aerial Vehicle (UAV). The studied biophysical variables are Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and fraction of vegetation cover (fCover). During agricultural year 2016/2017, 4 field campaigns (FCs) were carried out in 6 farmer-managed fields sown with two winter wheat varieties. During the FCs, 8 UAV flight missions were accompl

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H. R., Ragini, Manoj Kanti Debnath, Pradip Basak, and Deb Sankar Gupta. "Relationship between Above-ground Biomass and Different Vegetation Indices of Tea Plantation of Alipurduar District, West Bengal, India." International Journal of Environment and Climate Change 14, no. 9 (2024): 149–58. http://dx.doi.org/10.9734/ijecc/2024/v14i94400.

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This study investigates the relationship between above-ground biomass (AGB) and various vegetation indices in the tea plantations of Alipurduar District, West Bengal, India. The research was conducted in three major tea estates: Kumargram, Sankos and Newlands, using stratified random sampling across 36 plots. Field measurements of trees, shrubs and herbs were taken and AGB was estimated using allometric equations. Sentinel-2 satellite data was utilized to derive vegetation indices such as NDVI, GNDVI, SAVI, MSAVI, EVI-1, EVI-2, NDVIRE, RDVI, DVI, OSAVI and ARVI. The study found significant var

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Podlasova, Ekaterina Yu, and Antonina A. Novikova. "Analysis of chlorophyll content in spring barley leaves using hyperspectral imaging and spectrophotometry." Animal Husbandry and Fodder Production 107, no. 4 (2025): 337–46. https://doi.org/10.33284/2658-3135-107-4-337.

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The article presents the results of research on the search for universal vegetation indices on spring barley plants grown on a hydroponic system in a closed climate chamber. Using a spectrophotometer, the concentrations of chlorophyll in the leaves of spring barley during the tillering phase ranged in chlorophyll Cl a from 0.17 to 0.35 mg/cm2, chlorophyll Cl b from 0.11 to 0.31 mg/cm2, chlorophyll Cl a+b from 0.11 to 0.25 mg/cm2 and carotenoids (Car) from 0.11 to 0.19 mg/cm2. To quantify the chlorophyll content, several vegetation indices were derived, calculated on the basis of the reflection

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Hu, B., W. M. Jung, J. Liu, and J. Shang. "RETRIEVAL OF LEAF AREA INDEX AND LEAF CHLOROPHYLL CONTENT FROM HYPERSPECTRAL DATA USING DEEP LEARNING NETWORKS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 397–404. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-397-2022.

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Abstract. This study aimed to exploit the use of deep learning networks in the retrieval of the biophysical and biochemical parameters of vegetation canopies. Convolutional Neural Network (CNN), network with only fully connected layers, referred as dense network (DNN), and Autoencoder (AE) were investigated to retrieve leaf area index (LAI) and leaf chlorophyll content. Hyperspectral data simulated by the coupled PROSPECT and SAIL model were used for training and validation. The real CASI hyperspectral data in 50 spectral channels ranging from 522.4 nm to 894.2 nm collected over three agricult

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Soubry, I., P. Patias, and V. Tsioukas. "Monitoring vineyards with UAV and multi-sensors for the assessment of water stress and grape maturity." Journal of Unmanned Vehicle Systems 5, no. 2 (2017): 37–50. http://dx.doi.org/10.1139/juvs-2016-0024.

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This paper deals with the monitoring of vineyards for the assessment of water stress and grape maturity using an unmanned aerial vehicle (UAV) equipped with multispectral/infrared and red-green-blue (RGB) cameras. The study area is the Gerovassiliou winery in the region of Epanomi, Greece, cultivated with the local grape variety of Malagouzia. Fifteen flights were conducted with a fixed-wing UAV during the months of April to August 2015 with a mean interval of 2 weeks. The flight images were photogrammetrically processed for the production of orthoimages and then used to extract indices for th

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Bagheri, Nikrooz, Hojjat Ahmadi, Seyed Kazem Alavipanah, and Mahmoud Omid. "Multispectral remote sensing for site-specific nitrogen fertilizer management." Pesquisa Agropecuária Brasileira 48, no. 10 (2013): 1394–401. http://dx.doi.org/10.1590/s0100-204x2013001000011.

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The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-a

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Strzępek, Krzysztof, Mateusz Salach, Bartosz Trybus, Karol Siwiec, Bartosz Pawłowicz, and Andrzej Paszkiewicz. "Quantitative and Qualitative Analysis of Agricultural Fields Based on Aerial Multispectral Images Using Neural Networks." Sensors 23, no. 22 (2023): 9251. http://dx.doi.org/10.3390/s23229251.

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This article presents an integrated system that uses the capabilities of unmanned aerial vehicles (UAVs) to perform a comprehensive crop analysis, combining qualitative and quantitative evaluations for efficient agricultural management. A convolutional neural network-based model, Detectron2, serves as the foundation for detecting and segmenting objects of interest in acquired aerial images. This model was trained on a dataset prepared using the COCO format, which features a variety of annotated objects. The system architecture comprises a frontend and a backend component. The frontend facilita

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Tavares, Cássio Jardim, Walter Quadros Ribeiro Junior, Maria Lucrécia Gerosa Ramos, et al. "Water Stress Alters Physiological, Spectral, and Agronomic Indexes of Wheat Genotypes." Plants 12, no. 20 (2023): 3571. http://dx.doi.org/10.3390/plants12203571.

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Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, specifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irrigation system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 0

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Bai, Xiaohui, Changzhi Yang, Lei Fang, et al. "Identification of Salt Marsh Vegetation in the Yellow River Delta Using UAV Multispectral Imagery and Deep Learning." Drones 9, no. 4 (2025): 235. https://doi.org/10.3390/drones9040235.

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Salt marsh ecosystems play a critical role in coastal protection, carbon sequestration, and biodiversity preservation. However, they are increasingly threatened by climate change and anthropogenic activities, necessitating precise vegetation mapping for effective conservation. This study investigated the effectiveness of spectral features and machine learning models in separating typical salt marsh vegetation types in the Yellow River Delta using uncrewed aerial vehicle (UAV)-derived multispectral imagery. The results revealed that the Normalized Difference Vegetation Index (NDVI), Green Norma

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TROFYMENKO, Petro, Оlha TOMCHENKO, Rostyslav PORALO, Vitalii ZATSERKOVNYI, and Іryna STAKHIV. "REMOTE IDENTIFICATION OF MICROSEDIMENTAL RELIEF FORMS AND SOIL SECTIONS OF AGROLANDSCAPES OF THE FORESTS OF UKRAINE WITH SIGNS OF HYDROMORPHISM." Visnyk of Taras Shevchenko National University of Kyiv. Geology, no. 1 (104) (2024): 98–106. http://dx.doi.org/10.17721/1728-2713.104.12.

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Background. Agricultural lands play a key role in ensuring the food security of the population and the development of the country's economy. However, excessive wetting poses a significant threat to these lands, as a result of which the conditions for the formation of soils with signs of glaciation and low fertility are formed within the lower relief elements, which significantly reduces their potential. In order to highlight the problems of geospatial identification of micro-recessed landforms (MRLF) on agricultural lands, the article uses spectral indices based on the data of RSE. Methods. 6

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Al-Quraishi, Ayad, Hawar Razvanchy, and Heman Gaznayee. "A Comparative Study for Performance of Five Landsat-based Vegetation Indices: Their Relations to Some Ecological and Terrain Variables." Journal of Geoinformatics & Environmental Research 1, no. 1 (2020): 20–37. http://dx.doi.org/10.38094/jgier119.

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Spectral vegetation indices and their relations to some ecological and terrain variables in the Iraqi Kurdistan Region (IKR) is the main objective of this study. A mosaic of two Landsat-7 ETM+ images was utilized to produce five spectral vegetation indices, and Terra ASTER Digital Elevation Model (DEM) dataset were employed. The Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Optimized Soil Adjusted Vegetation Index (OSAVI), Tasseled Cap Greenness, Land Surface Temperature (LST) were utilized for this study. The results of the current study revealed that M

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M. M. LUNAGARIA, B. I. KARANDE, K. I. PATEL, and VYAS PANDEY. "Determination of optimal narrow bands for vegetation indices to discriminate nitrogen status in wheat crop." Journal of Agrometeorology 17, no. 1 (2015): 23–29. http://dx.doi.org/10.54386/jam.v17i1.971.

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Nitrogen stress sensors are based on reflectance measurement controlled by the chlorophyll content. Reflectance of canopy is spectral dependent and more sensitive narrow spectral band can be exploited for reflectance measurement sensors.The experiments for present study were conducted in split plot design on two widely grown wheat (Triticumaestivum L.) cultivars (GW 496 and LOK 1) during rabi seasons of three consecutive years 2007-08 to 2009-10 at Anand. The two cultivars viz; GW 496 and LOK 1 were taken as the main treatments and five nitrogen fertilizer application rates 120, 90, 60, 30 and

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Le Saint, Théo, Jean Nabucet, Sidonie Lefebvre, Jean-Philippe Gastellu-Etchegorry, Laurence Hubert-Moy, and Karine Adeline. "Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones." Remote Sensing 16, no. 23 (2024): 4402. http://dx.doi.org/10.3390/rs16234402.

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Urban trees contribute to urban well-being but face challenging environments that can reduce their lifespan and increase young tree mortality. Although many studies have used remote sensing data to monitor the functional status of trees in rural areas, few have done so in urban areas to assess the health or estimate the biomass of large green areas. This study assessed the suitability of using Sentinel-2 images to characterize two urban tree functional traits—leaf chlorophyll content (Cab) and leaf area density (LAD)—in isolated trees and tree rows. Simulated Sentinel-2 images were generated u

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Červená, L., L. Kupková, and R. Suchá. "FIELD SPECTROSCOPY FOR VEGETATION EVALUATION ALONG THE NUTRIENT AND ELEVATION GRADIENT ABOVE THE TREE LINE IN THE KRKONOŠE MOUNTAINS NATIONAL PARK." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 211–14. http://dx.doi.org/10.5194/isprs-archives-xli-b6-211-2016.

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This paper examines the relations between vegetation spectra measured in the field along the nutrient and elevation gradient in the most valuable parts of The Krkonoše Mountains tundra and selected parameters describing vegetation state and condition (fAPAR, plant cover and average vegetation height). The main goal was to find relations and indices based on spectral measurements that could be used for vegetation evaluation and classification in practice and management. The vegetation parameters and spectral properties were also compared for two datasets – one acquired in July and second in Aug

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Zhang, Aiwu, Shaoxing Hu, Xizhen Zhang, et al. "A Handheld Grassland Vegetation Monitoring System Based on Multispectral Imaging." Agriculture 11, no. 12 (2021): 1262. http://dx.doi.org/10.3390/agriculture11121262.

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Monitoring grassland vegetation growth is of vital importance to scientific grazing and grassland management. People expect to be able to use a portable device, like a mobile phone, to monitor grassland vegetation growth at any time. In this paper, we propose a handheld grassland vegetation monitoring system to achieve the goal of monitoring grassland vegetation growth. The system includes two parts: the hardware unit is a hand-held multispectral imaging tool named ASQ-Discover based on a smartphone, which has six bands (wavelengths)—including three visible bands (450 nm, 550 nm, 650 nm), a re

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Melillos, George, Athos Agapiou, Silas Michaelides, and Diofantos G. Hadjimitsis. "Monitoring military landscapes and detection of underground man-made critical infrastructures in Cyprus using Earth Observation." Advances in Geosciences 45 (November 21, 2018): 335–42. http://dx.doi.org/10.5194/adgeo-45-335-2018.

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Abstract. This paper aims to explore the importance of monitoring military landscapes in Cyprus using Earth Observation. The rising availability of remote sensing data provides adequate opportunities for monitoring military landscapes and detecting underground military man-made structures. In order to study possible differences in the spectral signatures of vegetation so as to be used for the systematic monitoring of military landscapes that comprise underground military structures, field spectroscopy has been used. The detection of underground and ground military structures based on remote se

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