scholarly journals VOLUMETRIC MODELING OF Pinus taeda L. FROM ORBITAL IMAGES

2022 ◽  
Vol 7 (1) ◽  
pp. 53
Author(s):  
Carla Talita Pertille ◽  
Marcos Felipe Nicoletti
Keyword(s):  
Pinus Taeda ◽  
Forest Inventory ◽  
Vegetation Index ◽  
High Spatial Resolution ◽  
Vegetation Indices ◽  
Simple Random Sampling ◽  
Sensor Data ◽  
Fixed Area ◽  
Pinus Taeda L ◽  
Sentinel 2

This work aimed to investigate the potential of image-derived indices derived from Sentinel-2/MSI images in the volumetric modeling of a stand of Pinus taeda L. located in Bom Retiro, State of Santa Catarina. For this purpose, field data derived from a forest inventory were used, by the fixed area method and simple random sampling with an allocation of 18 circular plots of 400 m². The remotely located data comprised an orbital image from the Sentinel-2/MSI sensor. From this image, 14 average vegetation indices per plot were calculated. These indices were correlated with the volume by plot (m³ 0.04 ha-1) derived from the inventory. The indices with the best correlation for volume by plot (m³ 0.04 ha-1) were the Generalized Difference Vegetation Index (GDVI) and Adjusted Soil Vegetation Index (SAVI) with 0.39 and 0.36, respectively. The best regression model completed using these VIs estimated the volume by plot with R² controls of 0.9402 and Syx of 1.44%. The use of spectral indices generated from Sentinel-2/MSI sensor data enabled the volumetric estimate of the Pinus taeda L. stand, not revealing differences between the volume accumulated by forest inventory and by orbital images. However, it is worth pointing out that new tests be carried out on other forest species and with medium to high spatial resolution sensors.

scholarly journals Biomass quantification of Pinus taeda L. from remote optical sensor data

2019 ◽  
Vol 6 (2) ◽  
Author(s):  
Carla Talita Pertille ◽  
Marcos Felipe Nicoletti ◽  
Larissa Regina Topanotti ◽  
Thiago Floriani Stepka
Keyword(s):  
Pinus Taeda ◽  
Vegetation Indices ◽  
Sensor Data ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Individual Tree ◽  
Significant Difference ◽  
Pinus Taeda L ◽  
The Individual ◽  
Sentinel 2

This research aimed to estimate the biomass of the trunk area of a Pinus taeda L. stand from vegetation indices from Landsat-8/OLI and Sentinel-2/MSI optical remote sensors. In order to obtain the biomass, a forest inventory was carried out with the installation of 33 circular plots of 400 m², in which all the individuals had the diameter at breast height (cm) and the total height (m) measured. Then, 30 trees were scaled by the Smalian method. The individual tree volume was estimated by the Meyer regression volumetric equation. The biomass was obtained through the product of the individual tree volume by the wood basic density. Subsequently, aerial biomass was obtained per plot. The processed orbital images were gathered from the Landsat-8/OLI and Sentinel-2/MSI sensors. We derived 19 vegetation indices for both images, which were correlated with the biomass per plot. The indexes with the best correlation with the biomass were considered as regression variables to develop models by the Stepwise technique (Backward and Forward). The correlation was significant among the variables and the best model was derived from the Landsat-8 data, which estimated the biomass per plot with an error of 8.75% and an adjusted coefficient of determination of 0.8173. Nevertheless, the statistical analysis revealed that there was no significant difference between the biomass estimated by the inventory and by the remotely located data.

scholarly journals Prediction of dendrometric variables by optical data in Pinus taeda L. in the south of Brazil

2021 ◽  
Vol 8 (2) ◽  
pp. 1433-1443
Author(s):  
Carla Talita Pertille ◽  
Marcos Felipe Nicoletti ◽  
Larissa Regina Topanotti ◽  
Luís Paulo Baldiserra Schorr
Keyword(s):  
Pinus Taeda ◽  
Forest Inventory ◽  
Vegetation Indices ◽  
Basal Area ◽  
Optical Data ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Pinus Taeda L ◽  
South Of Brazil ◽  
Pinus Spp

The objective of this work was to estimate the basal area and volume of a Pinus taeda L. settlement located in Santa Catarina, correlating data from an orbital image of the Landsat-8 / OLI sensor and forest inventory. In this sense, a forest research was carried out, with a random sampling process using the fixed area method. 20 circular parcels of 400 m² were allocated. An orbital image of the Landsat-8 / OLI sensor was used and 10 average vegetation indices per plot were calculated. These were correlated as variables of volume and basal area per plot, decorative by the forest inventory. The index with the best correlation for the volume was GNDVI with 0.47 and for a basal area, the MVI with 0.51. The adjustment of the regression models showed adjusted R² indices of 0.5639 and Syx of 13.31% for volume, and 0.5213 and 11.93% for the basal area. It was possible to estimate the volume and basal area of the stands through the spectral data, however, it is recommended that this same technique be tested in other species of the genus Pinus spp. and with high spatial resolution media.

scholarly journals Modeling of Durum Wheat Yield Based on Sentinel-2 Imagery

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1486
Author(s):  
Chris Cavalaris ◽  
Sofia Megoudi ◽  
Maria Maxouri ◽  
Konstantinos Anatolitis ◽  
Marios Sifakis ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Model Development ◽  
Wheat Yield ◽  
Growth Period ◽  
Yield Data ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Sentinel 2

In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.

scholarly journals Evaluation of a NIR camera for monitoring yield and nitrogen effect in sugarcane

2017 ◽  
Vol 35 (1) ◽  
pp. 82-91
Author(s):  
Cesar Edwin García ◽  
David Montero ◽  
Hector Alberto Chica
Keyword(s):  
Spatial Resolution ◽  
Vegetation Index ◽  
High Spatial Resolution ◽  
Early Stage ◽  
Vegetation Indices ◽  
Visible Spectrum ◽  
Crop Productivity ◽  
Spectral Information ◽  
Nitrogen Effect ◽  
Sugarcane Yield

The main objective of the research carried out in the sugar productive sector in Colombia is to improve crop productivity of sugarcane. The rise of RPAS, together with the use of multispectral cameras, which allows for high spatial resolution images and spectral information outside the visible spectrum, has generated an alternative nondestructive technological approach to monitoring crop sugarcane that must be evaluated and adapted to the specific conditions of Colombia's sugar productive sector. In this context, this paper assesses the potential of a modified camera (NIR) to discriminate three varieties of sugarcane, as well as three doses of fertilization and estimating the sugarcane yield at an early stage, for the three varieties through multiple vegetation indices. In this study, no significant differences were found by vegetation index between fertilization doses, and only significant differences between varieties were found when the fertilization was normal or high. Likewise, multiple regressions between scores derived from vegetation indices after applying PCA and productivity produced determinations of up to 56%.

scholarly journals EFICIÊNCIA DE DUAS VARIAÇÕES ESTRUTURAIS DO MÉTODO DE AMOSTRAGEM DE ÁREA FIXA EM PLANTAÇÕES DE Pinus taeda

FLORESTA ◽  
2013 ◽  
Vol 43 (4) ◽  
pp. 621
Author(s):  
João Paulo Druszcz ◽  
Nelson Yoshihiro Nakajima ◽  
Sylvio Pellico Netto ◽  
Sebastião do Amaral Machado ◽  
Nelson Carlos Rosot ◽  
...  
Keyword(s):  
Pinus Taeda ◽  
Relative Efficiency ◽  
Block Design ◽  
Basal Area ◽  
Average Diameter ◽  
Breast Height ◽  
Variable Diameter ◽  
Randomized Block Design ◽  
Fixed Area ◽  
Pinus Taeda L

Este estudo foi conduzido em três diferentes condições de plantações de Pinus taeda L., sem desbastes, com 10, 9 e 7 anos de idade, 2.000 árvores por hectare e diferentes inclinações no terreno, localizados no Estado do Paraná. O objetivo foi avaliar a eficiência do inventário florestal, utilizando-se a amostragem de área fixa com a estrutura de parcela circular (PC) e conglomerado em cruz (CC), através da análise do comportamento quanto às precisões e eficiências relativas nas estimativas das seguintes variáveis: diâmetro médio (cm), número de árvores por ha, área basal (m2/ha) e volume total (m3/ha). Para isso, utilizou-se o delineamento em blocos casualizados com 40 unidades amostrais para a PC e 10 unidades para o CC, sendo este composto por 4 subunidades circulares. Concluiu-se que, para as variáveis diâmetro médio (cm), número de árvores (N/ha), área basal (m2/ha) e volume total (m3/ha), indica-se a utilização do método de área fixa com PC, tendo em vista a maior eficiência no levantamento dessas variáveis.Palavras-chave: Eficiência relativa; precisão; reflorestamento. AbstractStructural efficiency of two variations of method of sampling of fixed area in plantations of Pinus taeda. This study was carried out in three different stands of Pinus taeda L., unthinned and aged 10, 9 and 7 years. The stands have 2.000 trees per hectare and are located in Parana State. The aim was to evaluate the efficiency of inventories using circular plot (PC) and cross cluster (CC) by analyses of behavior towards accuracies and relative efficiencies for estimation of the following variables: average diameter at breast height, number of trees, basal area and total volume per hectare. For this study, it was taken a sample of 40 units to the PC structure and 10 units for the CC structure, which is composed of four circular subunits, and it was used the randomized block design. It was concluded that for the variable diameter (cm), number of trees (ha), basal area (m2/ha) and total volume (m3/ha) it is indicated the use of PC, since its greater efficiency in the survey of these variables.Keywords: Relative efficiency; accuracy; reforestation.

scholarly journals Land Cover and Forest Type Classification by Values of Vegetation Indices and Forest Structure of Tropical Lowland Forests in Central Vietnam

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Hung Nguyen Trong ◽  
The Dung Nguyen ◽  
Martin Kappas
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Forest Type ◽  
Vegetation Indices ◽  
Landsat 8 ◽  
Tropical Lowland ◽  
Central Vietnam ◽  
Lowland Forests ◽  
Type Classification ◽  
Sentinel 2

This paper aims to (i) optimize the application of multiple bands of satellite images for land cover classification by using random forest algorithms and (ii) assess correlations and regression of vegetation indices of a better-performed land cover classification image with vertical and horizontal structures of tropical lowland forests in Central Vietnam. In this study, we used Sentinel-2 and Landsat-8 to classify seven land cover classes of which three forest types were substratified as undisturbed, low disturbed, and disturbed forests where forest inventory of 90 plots, as ground-truth, was randomly sampled to measure forest tree parameters. A total of 3226 training points were sampled on seven land cover types. The performance of Landsat-8 showed out-of-bag error of 31.6%, overall accuracy of 68%, kappa of 67.5%, while Sentinel-2 showed out-of-bag error of 14.3% and overall accuracy of 85.7% and kappa of 83%. Ten vegetation indices of the better-performed image were extracted to find out (i) the correlation and regression of horizontal and vertical structures of trees and (ii) assess the variation values between ground-truthing plots and training sample plots in three forest types. The result of the t test on vegetation indices showed that six out of ten vegetation indices were significant at p<0.05. Seven vegetation indices had a correlation with the horizontal structure, but four vegetation indices, namely, Enhanced Vegetation Index, Perpendicular Vegetation Index, Difference Vegetation Index, and Transformed Normalized Difference Vegetation Index, had better correlations r = 0.66, 0.65, 0.65, 0.63 and regression results were of R2 = 0.44, 0.43, 0.43, and 0.40, respectively. The correlations of tree height were r = 0.46, 0.43, 0.43, and 0.49 and its regressions were of R2 = 0.21, 0.19, 0.18, and 0.24, respectively. The results show the possibility of using random forest algorithm with Sentinel-2 in forest type classification in line with vegetation indices application.

scholarly journals Spatial and Temporal Monitoring of Pasture Ecological Quality: Sentinel-2-Based Estimation of Crude Protein and Neutral Detergent Fiber Contents

2019 ◽  
Vol 11 (7) ◽  
pp. 799 ◽  
Author(s):  
Rachel Lugassi ◽  
Eli Zaady ◽  
Naftaly Goldshleger ◽  
Maxim Shoshany ◽  
Alexandra Chudnovsky
Keyword(s):  
Crude Protein ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Neutral Detergent Fiber ◽  
Ecological Quality ◽  
Spatial And Temporal Patterns ◽  
Validation Data ◽  
Calibration And Validation ◽  
Sentinel 2

Frequent, region-wide monitoring of changes in pasture quality due to human disturbances or climatic conditions is impossible by field measurements or traditional ecological surveying methods. Remote sensing imagery offers distinctive advantages for monitoring spatial and temporal patterns. The chemical parameters that are widely used as indicators of ecological quality are crude protein (CP) content and neutral detergent fiber (NDF) content. In this study, we investigated the relationship between CP, NDF, and reflectance in the visible–near-infrared–shortwave infrared (VIS–NIR–SWIR) spectral range, using field, laboratory measurements, and satellite imagery (Sentinel-2). Statistical models were developed using different calibration and validation data sample sets: (1) a mix of laboratory and field measurements (e.g., fresh and dry vegetation) and (2) random selection. In addition, we used three vegetation indices (Normalized Difference Vegetative Index (NDVI), Soil-adjusted Vegetation Index (SAVI) and Wide Dynamic Range Vegetation Index (WDRVI)) as proxies to CP and NDF estimation. The best models found for predicting CP and NDF contents were based on reflectance measurements (R2 = 0.71, RMSEP = 2.1% for CP; and R2 = 0.78, RMSEP = 5.5% for NDF). These models contained fresh and dry vegetation samples in calibration and validation data sets. Random sample selection in a model generated similar accuracy estimations. Our results also indicate that vegetation indices provide poor accuracy. Eight Sentinel-2 images (December 2015–April 2017) were examined in order to better understand the variability of vegetation quality over spatial and temporal scales. The spatial and temporal patterns of CP and NDF contents exhibit strong seasonal dependence, influenced by climatological (precipitation) and topographical (northern vs. southern hillslopes) conditions. The total CP/NDF content increases/decrease (respectively) from December to March, when the concentrations reach their maximum/minimum values, followed by a decline/incline that begins in April, reaching minimum values in July.

Forest inventory estimation with mapped plots

2004 ◽  
Vol 34 (2) ◽  
pp. 493-497 ◽  
Author(s):  
Paul C Van Deusen
Keyword(s):  
Forest Inventory ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Mean Squared Errors ◽  
Additional Work ◽  
Fixed Area ◽  
Plot Design

Procedures are developed for estimating means and variances with a mapped-plot design. The focus is on fixed-area plots, and simulations are used to validate the proposed estimators. The mapped-plot estimators for means and variances are compared with simple random sampling estimators that utilize only full plots. As expected, the mapped-plot estimates have smaller mean squared errors than the simple random sampling estimates. The theory for fixed-area plots is easy to apply, although additional work is required to map plots in the field. Corresponding theory for variable plots is developed but not tested with simulations. The difficulty of applying these methods to variable plots is greater, but not prohibitive.

scholarly journals Application of multispectral sensors and unmanned aerial system in Stara Planina region

2020 ◽  
pp. 175-186
Author(s):  
Nenad Šurjanac ◽  
Marija Milosavljević ◽  
Mara Tabaković-Tošić ◽  
Miroslava Marković
Keyword(s):  
Vegetation Index ◽  
Physiological Activity ◽  
Vegetation Indices ◽  
Ground Truth ◽  
Sensor Data ◽  
Spectral Signature ◽  
Unmanned Aerial System ◽  
Positive Ratio ◽  
Pest Infestation ◽  
Leaf Mining

In the area of Stara Planina mountain, a multispectral survey of forest vegetation was performed. Data acquisition was done with unmanned aerial system DJI Phantom 4 Pro, equipped with integrated RGB 20Mpix sensor, and MicaSense RedEdge M, 5-channel narrowband multispectral sensor. Data was collected in the form of images, and 4 composite orthomosaics were produced-broadband visible RGB, narrowband visible RGB, and with vegetation indices applied NDVI and NDRE. RGB orthomosaic showed no significant changes in canopies apart from the variability of levels of green. Orthomosaics with vegetation indices applied showed changes in the level of physiological activities of leaves. NDVI map showed the negative changes of the top of the canopies, while NDRE map showed more dramatic changes within the canopy as well. Besides the map, 5 polygons with different NDRE values were selected and their respective spectral signature graphs were produced. The areas with the lowest NDRE values had the highest reflectance values in all wavelengths, while the absorption of light is much higher in physiologically active vegetation. Values of NDRE lower than 0.479 were inspected from the ground. This kind of ground-truth provided evidence that the areas coded in red were with lower physiological activity due to the infestation by beech leaf-mining weevil Orchestes fagi L. Another interesting finding was that both NDVI and NDRE values were higher in the areas not directly exposed to the sunlight. The areas shaded by surrounding canopies received only diffuse light but it showed a more positive ratio between absorbed and reflected wavelength which could be characteristic of the Fagus Sylvatica species. The findings in this study showed a strong correlation between low values NDRE vegetation index and negative changes deep within the canopy of high vegetation, which can serve as an indicator of pest infestation in forestry.

scholarly journals The Efficiency of Sampling Methods for Dendrometric Estimates of Thinned Stands of Pinus taeda L. in Santa Catarina, Brazil

2019 ◽  
Vol 11 (17) ◽  
pp. 218
Author(s):  
Klerysson Julio Farias ◽  
Thiago Floriani Stepka ◽  
Marcos Felipe Nicoletti ◽  
Luis Paulo Baldissera Schorr ◽  
Geedre Adriano Borsoi ◽  
...  
Keyword(s):  
Pinus Taeda ◽  
Relative Error ◽  
Relative Efficiency ◽  
Sampling Methods ◽  
Alternative Methods ◽  
Santa Catarina ◽  
Area Method ◽  
Fixed Area ◽  
Pinus Taeda L ◽  
Installation Time

This study aimed to compare the efficiency of the sampling methods: Fixed Area, Bitterlich, Prodan and Modified Prodan to estimate the commercial volume and other dendrometric estimators for a 34 years old of Pinus taeda L. stands located in Campo Belo do Sul, Santa Catarina, Brazil. It were distributed a total of 10 sample units of the following methods: Fixed Area with 200, 400 and 500 m&sup2; of area, Bitterlich, Prodan and Modified Prodan were distributed, both with 6, 7, 8, 9 and 10 trees. In addition to collecting dendrometric data, the installation time of the sample units was timed, whereby the relative efficiency for each method was calculated. The comparison between the harvest volumes and the volumes estimated by the methods was performed by the Skott Knott test, and the results that did not differ statistically were weighted by the parameters of relative error, relative efficiency and proximity to harvest. All variations of the Modified Prodan and Prodan methods had sample insufficiency. The number of trees per hectare presented higher values for the 200 m&sup2; Fixed Area method and lower values for Prodan with 10 trees. Prodan with 6 trees got the shortest time. The Bitterlich method obtained sample adequancy at 10% error and presented the best result. Among the alternative methods to Fixed Area, Modified Prodan with 7 trees can be indicated for pilot inventory. However, when more precise results are needed, the Bitterlich method is indicated.

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