Image based remote sensing method for modeling black-eyed beans (Vigna unguiculata) Leaf Area Index (LAI) and Crop Height (CH) over Cyprus

Papadavid, George; Fasoula, Dionysia A.; Hadjimitsis, M.; Perdikou, P. Skevi; Hadjimitsis, Diofantos

doi:10.2478/s13533-012-0112-0

Cited by 10 publications

(8 citation statements)

References 31 publications

(35 reference statements)

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“…Para os sensores HRVIR e ETM+, o índice Savi foi o que melhor estimou esta variável, com R 2 de 0,866 e 0,865, respectivamente. Papadavid et al (2013) estudaram a relação entre o IAF do feijão e o NDVI, que foi calculado com bandas referentes às do sensor ETM+ simulado de dados de radiômetro, e obtiveram R 2 superior a 0,88, que é maior que os encontrados no presente trabalho. Na estimativa da produtividade (Tabela 3 e Figura 2), o NDVI, calculado com bandas do sensor Modis, foi o índice que melhor estimou esta variável com R 2 = 0,861.…”

Section: Resultsunclassified

Índices de vegetação simulados de diferentes sensores na estimativa das variáveis biofísicas do feijoeiro

Monteiro

Filho

Xavier

et al. 2013

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar os índices de vegetação e bandas do vermelho e do infravermelho próximo, gerados a partir dos sensores HRVIR, ETM+ e Modis, nas estimativas de índice de área foliar e produtividade da cultura do feijoeiro. O experimento foi realizado em blocos ao acaso, com parcelas subdivididas, com quatro lâminas de irrigação (179,5, 256,5, 357,5 e 406,2 mm), três doses de N (0,0, 80,0 e 160,0 kg ha -1 ) e quatro repetições. As medidas de reflectância foram obtidas com o Spetron SE-590, no estádio R6 da cultura, nas 48 parcelas. Foram testados: a razão simples, o índice de vegetação por diferença normalizada, índice de vegetação ajustado ao solo e índice de vegetação realçado. Os índices de vegetação foram eficientes na estimativa do índice de área foliar (IAF) e da produtividade da cultura do feijoeiro. Os índices de vegetação e a banda do infravermelho apresentam o mesmo potencial na estimativa do IAF, quando se considera a resolução espectral dos sensores Modis, ETM+ e HRVIR.Termos de indexação: Phaseolus vulgaris, agricultura, reflectância espectral, sensoriamento remoto. Vegetation indices simulated from different sensors for the estimation of biophysical variables of common beanAbstract -The objective of this work was to evaluate the vegetation indices and red and infrared bands of the HRVIR, ETM+ and Modis sensors, in the estimations of leaf area index and grain yield of common bean. The experiment was carried out in a randomized block design, with split plots and four irrigation levels (179.5, 256.5, 357.5, and 406.2 mm), three N rates (0.0, 80.0 and 160.0 kg ha -1 ), and four replicates. The reflectance measurements were obtained through the Spectron SE-590, at R6 stage, on 48 plots. Simple ratio, normalized difference vegetation index, soil-adjusted vegetation index, and enhanced vegetation index were tested. The vegetation indices were efficient to estimate the leaf area index (LAI) and grain yield. The vegetation indices and infrared band show the same potential to estimate LAI, when considering the spectral resolution of Modis, ETM+ and HRVIR.

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Section: Resultsunclassified

Índices de vegetação simulados de diferentes sensores na estimativa das variáveis biofísicas do feijoeiro

Monteiro

Filho

Xavier

et al. 2013

Pesq. agropec. bras.

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“…Integrating such methods using GIS and satellite imagery has been widely used in literature [19] though it is new in this area. Supervised Maximum Likelihood Classification (MLC) algorithm, more suitable when each class defined has a Gaussian distribution was used in categorizing DN values in the different classes in the study area [20].…”

Section: Methodsmentioning

confidence: 99%

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

2015

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Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index values were used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

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“…Vegetation height is commonly derived from vegetation indexes (i.e., NDVI and LAI) using optical remote sensing data that may be suitable for low vegetation (for example, pastures, crops, shrubs, etc.) [80,81] or that can be derived from active remote sensing (i.e., Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR)) data sensitive to forest vertical structure [82,83]. Nevertheless, these methods are not possible for growing forests.…”

Section: Discussionmentioning

confidence: 99%

Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains

Tian

Tol

et al. 2015

Remote Sensing

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Abstract:We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z 0m ), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey's height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey's height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z 0m , and, thus, the heat roughness length (z 0h ). The obtained d, z 0m and z 0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R 2 = 0.80 and RMSE = 0.21 mm¨day´1).

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Image based remote sensing method for modeling black-eyed beans (Vigna unguiculata) Leaf Area Index (LAI) and Crop Height (CH) over Cyprus

Cited by 10 publications

References 31 publications

Índices de vegetação simulados de diferentes sensores na estimativa das variáveis biofísicas do feijoeiro

Índices de vegetação simulados de diferentes sensores na estimativa das variáveis biofísicas do feijoeiro

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains

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