scholarly journals Remote Sensing Assessment of the Expansion of Ips typographus Attacks in the Chuprene Reserve, Western Balkan Range

Forests ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 39
Author(s):  
Georgi Georgiev ◽  
Margarita Georgieva ◽  
Stelian Dimitrov ◽  
Martin Iliev ◽  
Vladislav Trenkin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Norway Spruce ◽  
Bark Beetle ◽  
Satellite Images ◽  
Vegetation Index ◽  
Near Infrared ◽  
Ips Typographus ◽  
Infrared Range ◽  
Electromagnetic Spectrum ◽  
Spruce Stands

The Chuprene Reserve was created in 1973 to preserve the natural coniferous forests in the Western Balkan Range in Bulgaria. The first infestations by European spruce bark beetle (Ips typographus) were registered in Norway spruce (Picea abies) stands in the mid-1980s. The aim of this study is to assess the damages caused by I. typographus in the Chuprene Reserve using remote sensing techniques – unmanned aerial vehicle (UAV) images, airborne images, and satellite images of European Space Imaging (EUSI), combined with terrestrial verification. High-resolution images in four bands of the electromagnetic spectrum and in a standard RGB channel were taken in 2017 via a multispectral camera ‘Parrot Sequoia’, integrated with a specialized professional UAV system eBee ‘Flying Wing’. The health status of Norway spruce stands in the reserve was assessed with the normalized difference vegetation index, based on the digital mixing of imagery captured in the red and near infrared range. The dynamic of bark beetle attacks was studied in GIS on the basis of maps generated from photographic surveys, airborne images taken in 2011 and 2015, and satellite images from 2020. In the UAV-captured area (314.0 ha), the size of Norway spruce stands attacked by I. typographus increased from 7.6 ha (2.4%) in 2011 to 44.9 ha (14.3%) in 2020. The satellite images showed that on the entire territory of the Chuprene Reserve (1451.9 ha), I. typographus killed spruce trees on 137.4 ha, which is 9.6% of the total area.

scholarly journals Occurrence of Ips typographus (L.) after wind damage in the Kościeliska Valley of the Tatra National Park

2017 ◽  
Vol 78 (2) ◽  
pp. 113-119 ◽  
Author(s):  
Wojciech Grodzki ◽  
Wojciech Gąsienica Fronek
Keyword(s):  
Norway Spruce ◽  
Bark Beetle ◽  
National Park ◽  
Ips Typographus ◽  
Passive Protection ◽  
Protection Zone ◽  
Active Protection ◽  
Spruce Stands ◽  
Infestation Density ◽  
Tatra National Park

Abstract At the end of 2013, Norway spruce stands in the area of the Tatra National Park were severely damaged by strong storms especially in the Kościeliska Valley region. In the following spring of 2014, a survey recording the occurrence of the spruce bark beetle Ips typographus (Coleoptera, Curculionidae, Scolytinae) was initiated in order to describe the dynamics of beetle reproduction in relation to protection measures executed in wind-damaged stands. Ten research plots with 20 trees each were established in a socalled active protection zone, where the broken and fallen trees had been processed and removed in 2014, and in a passive protection zone, where no actions were taken, and the dynamics of Norway spruce mortality due to bark beetle infestation including quantitative parameters (infestation density, sex ratio of beetle populations) were examined. The entomological analyses were performed on 25 × 25 cm large bark samples taken from four (active zone) or two (passive zone) tree sections. In the first year of the survey, no infested standing trees were recorded on the plots and the colonisation of fallen and broken trees was very weak. In the second year (2015), infestations appeared in larger numbers on the plots with passive compared to active protection but the infestation density was 0.89 mating chambers per 1 dm2 regardless of the protection status. In the third year (2016), most of the remaining living spruces had been infested with a mean density of 0.82 m.ch. per 1 dm2. In 2015, the proportion of females in the beetle population was 65.8% being higher in the active (68.4%) than the passive (64.0%) protection zone, while in 2016 the proportion was 63.5% and in this case slightly higher in the passive protection zone (63.9% as compared to 63.2%). These results are in accordance with patterns observed in wind-damaged Norway spruce stands of other areas in Poland and Europe and demonstrate the usefulness of forest management procedures in mitigating I. typographus outbreaks.

scholarly journals A Log-Ratio Vegetation Index (LRVI) for Discrimination and Classification of Remote Sensing Data

2020 ◽  
Vol 28 (1) ◽  
pp. 45-70
Author(s):  
Francisco C. Rego ◽  
Irene S.P. Cadima ◽  
Eva K. Strand
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Ground Cover ◽  
Spectral Space ◽  
Electromagnetic Spectrum ◽  
Remotely Sensed Data ◽  
Classical Statistics ◽  
Log Ratio

Discrimination and classification are integral processes for interpreting remotely sensed data. Many spectral vegetation indices have been proposed for discriminating between vegetation, soil, and other ground cover categories. Classical remote sensing show that reflectance in the red (R) and near infrared (NIR) bands of the electromagnetic spectrum have been successful in differentiating between vegetation and other ground cover classes and they are commonly used for this purpose. Here we demonstrate how Fisher’s classical statistics can be applied to develop discriminant functions for commonly used vegetation indices simply using the R and NIR bands. We derive a new vegetation index, the Log-Ratio Vegetation Index (LRVI) and demonstrate its utility in discriminating between cork oak trees and surrounding background in woodlands in Portugal. The LRVI performed better than seven previously developed vegetation indices, likely because of its linear properties in the reflectance density spectral space. The robustness and simplicity of LRVI suggests that it deserves further exploration and should be included for comparison with other vegetation indices and functions in discrimination, classification, and modelling studies. We suggest that the demonstrated approach is widely applicable to development of indices composed of other bands than R and NIR for systems or processes that correlate better with reflectance in other regions of the electromagnetic spectrum.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

scholarly journals Improving Field-Scale Wheat LAI Retrieval Based on UAV Remote-Sensing Observations and Optimized VI-LUTs

2019 ◽  
Vol 11 (20) ◽  
pp. 2456 ◽  
Author(s):  
Wanxue Zhu ◽  
Zhigang Sun ◽  
Yaohuan Huang ◽  
Jianbin Lai ◽  
Jing Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Management Practices ◽  
Near Infrared ◽  
Lookup Table ◽  
Field Scale ◽  
Area Index ◽  
Biophysical Parameter ◽  
Retrieval Accuracy

Leaf area index (LAI) is a key biophysical parameter for monitoring crop growth status, predicting crop yield, and quantifying crop variability in agronomic applications. Mapping the LAI at the field scale using multispectral cameras onboard unmanned aerial vehicles (UAVs) is a promising precision-agriculture application with specific requirements: The LAI retrieval method should be (1) robust so that crop LAI can be estimated with similar accuracy and (2) easy to use so that it can be applied to the adjustment of field management practices. In this study, three UAV remote-sensing missions (UAVs with Micasense RedEdge-M and Cubert S185 cameras) were carried out over six experimental plots from 2018 to 2019 to investigate the performance of reflectance-based lookup tables (LUTs) and vegetation index (VI)-based LUTs generated from the PROSAIL model for wheat LAI retrieval. The effects of the central wavelengths and bandwidths for the VI calculations on the LAI retrieval were further examined. We found that the VI-LUT strategy was more robust and accurate than the reflectance-LUT strategy. The differences in the LAI retrieval accuracy among the four VI-LUTs were small, although the improved modified chlorophyll absorption ratio index-lookup table (MCARI2-LUT) and normalized difference vegetation index-lookup table (NDVI-LUT) performed slightly better. We also found that both of the central wavelengths and bandwidths of the VIs had effects on the LAI retrieval. The VI-LUTs with optimized central wavelengths (red = 612 nm, near-infrared (NIR) = 756 nm) and narrow bandwidths (~4 nm) improved the wheat LAI retrieval accuracy (R2 ≥ 0.75). The results of this study provide an alternative method for retrieving crop LAI, which is robust and easy use for precision-agriculture applications and may be helpful for designing UAV multispectral cameras for agricultural monitoring.

scholarly journals Remote Sensing Landslide Recognition Based on Convolutional Neural Network

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yu Wang ◽  
Xiaofei Wang ◽  
Junfan Jian
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Convolutional Neural Network ◽  
Large Scale ◽  
Vegetation Index ◽  
Near Infrared ◽  
Spatial Information ◽  
Spectral Characteristics ◽  
Remote Sensing Images ◽  
Landslide Event

Landslides are a type of frequent and widespread natural disaster. It is of great significance to extract location information from the landslide in time. At present, most articles still select single band or RGB bands as the feature for landslide recognition. To improve the efficiency of landslide recognition, this study proposed a remote sensing recognition method based on the convolutional neural network of the mixed spectral characteristics. Firstly, this paper tried to add NDVI (normalized difference vegetation index) and NIRS (near-infrared spectroscopy) to enhance the features. Then, remote sensing images (predisaster and postdisaster images) with same spatial information but different time series information regarding landslide are taken directly from GF-1 satellite as input images. By combining the 4 bands (red + green + blue + near-infrared) of the prelandslide remote sensing images with the 4 bands of the postlandslide images and NDVI images, images with 9 bands were obtained, and the band values reflecting the changing characteristics of the landslide were determined. Finally, a deep learning convolutional neural network (CNN) was introduced to solve the problem. The proposed method was tested and verified with remote sensing data from the 2015 large-scale landslide event in Shanxi, China, and 2016 large-scale landslide event in Fujian, China. The results showed that the accuracy of the method was high. Compared with the traditional methods, the recognition efficiency was improved, proving the effectiveness and feasibility of the method.

scholarly journals Effect of insecticide-treated trap logs and lure traps for Ips typographus(Coleoptera: Curculionidae) management on nontarget arthropods catching in Norway spruce stands

2014 ◽  
Vol 60 (No. 1) ◽  
pp. 6-11 ◽  
Author(s):  
J. Lubojacký ◽  
J. Holuša
Keyword(s):  
Czech Republic ◽  
Norway Spruce ◽  
Ips Typographus ◽  
Flight Activity ◽  
Entire Period ◽  
Pheromone Traps ◽  
Nontarget Organisms ◽  
Thanasimus Formicarius ◽  
Spruce Stands

The numbers of nontarget arthropods captured by Theysohn pheromone traps (TPTs) and insecticide-treated tripod trap logs (TRIPODs) were compared; both kinds of traps were baited with pheromone lures Pheagr IT for Ips typographus. In 2010, 15 TPTs and 15 TRIPODs were deployed (with a 10-m spacing) in a forest in the northeastern Czech Republic. The TPTs and TRIPODs were inspected weekly during the entire period of I. typographus flight activity (30 April–1 October). The TRIPODs were sprayed with Vaztak 10 SC insecticide every 7 weeks; at each spraying, the pheromone evaporators were renewed. Higher numbers of entomophagous arthropods, including the predacious beetles Thanasimus formicarius and T. femoralis, were captured by the TRIPODs than by the TPTs. The number of Thanasimus spp. captured by TRIPODs was especially high at the end of April. The efficacy of TRIPODs for the control of I. typographus could be maintained while the kill of nontarget organisms could be reduced by deploying the evaporators 1 week later (in early May rather than in late April) in relation to the recommended date of dispenser installation.  

scholarly journals Monitoring the Impact of Environmental Manipulation on Peatland Surface by Simple Remote Sensing Indices

2018 ◽  
Vol 23 ◽  
pp. 00030 ◽  
Author(s):  
Anshu Rastogi ◽  
Subhajit Bandopadhyay ◽  
Marcin Stróżecki ◽  
Radosław Juszczak
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Vegetation Index ◽  
Near Infrared ◽  
Near Infrared Reflectance ◽  
Area Index ◽  
Environmental Manipulation ◽  
Chlorophyll Index ◽  
The Impact ◽  
Remote Sensing Indices

The behaviour of nature depends on the different components of climates. Among these, temperature and rainfall are two of the most important components which are known to change plant productivity. Peatlands are among the most valuable ecosystems on the Earth, which is due to its high biodiversity, huge soil carbon storage, and its sensitivity to different environmental factors. With the rapid growth in industrialization, the climate change is becoming a big concern. Therefore, this work is focused on the behaviour of Sphagnum peatland in Poland, subjected to environment manipulation. Here it has been shown how a simple reflectance based technique can be used to assess the impact of climate change on peatland. The experimental setup consists of four plots with two kind of manipulations (control, warming, reduced precipitation, and a combination of warming and reduced precipitation). Reflectance data were measured twice in August 2017 under a clear sky. Vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), near-infrared reflectance of vegetation (NIRv), MERIS terrestrial chlorophyll index (MTCI), Green chlorophyll index (CIgreen), Simple Ration (SR), and Water Band Index (WBI) were calculated to trace the impact of environmental manipulation on the plant community. Leaf Area Index of vascular plants was also measured for the purpose to correlate it with different VIs. The observation predicts that the global warming of 1°C may cause a significant change in peatland behaviour which can be tracked and monitored by simple remote sensing indices.

scholarly journals Separation of soil and canopy reflectance signatures of Mid German agricultural soils

2011 ◽  
Vol 51 (No, 7) ◽  
pp. 296-303 ◽  
Author(s):  
T. Behrens ◽  
K. Gregor ◽  
W. Diepenbrock
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Near Infrared ◽  
Field Experiments ◽  
Agricultural Soils ◽  
Soil Reflectance

Remote sensing can provide visual indications of crop growth during production season. In past, spectral optical estimations were well performed in the ability to be correlated with crop and soil properties but were not consistent within the whole production season. To better quantify vegetation properties gathered via remote sensing, models of soil reflectance under changing moisture conditions are needed. Signatures of reflected radiation were acquired for several Mid German agricultural soils in laboratory and field experiments. Results were evaluated at near-infrared spectral region at the wavelength of 850 nm. The selected soils represented different soil colors and brightness values reflecting a broad range of soil properties. At the wavelength of 850 nm soil reflectance ranged between 10% (black peat) and 74% (white quartz sand). The reflectance of topsoils varied from 21% to 32%. An interrelation was found between soil brightness rating values and spectral optical reflectance values in form of a linear regression. Increases of soil water content from 0% to 25% decreased signatures of soil reflectance at 850 nm of two different soil types about 40%. The interrelation of soil reflectance and soil moisture revealed a non-linear exponential function. Using knowledge of the individual signature of soil reflectance as well as the soil water content at the measurement, soil reflectance could be predicted. As a result, a clear separation is established between soil reflectance and reflectance of the vegetation cover if the vegetation index is known.

scholarly journals Merocoenoses of cambioxylophagous insect fauna of Norway spruce (Picea abies [L.] Karst.) with focus on bark beetles (Coleoptera: Scolytidae) and types of tree damage in different gradation conditions

2010 ◽  
Vol 56 (No. 10) ◽  
pp. 474-484 ◽  
Author(s):  
E. Kula ◽  
W. Ząbecki
Keyword(s):  
Picea Abies ◽  
Norway Spruce ◽  
Bark Beetles ◽  
Fungal Pathogens ◽  
Ips Typographus ◽  
Insect Fauna ◽  
Spruce Bark ◽  
Standing Trees ◽  
Spruce Stands ◽  
Endemic Population

Research on merocoenoses of cambioxylophagous insect fauna of Norway spruce (Picea abies [L.] Karst.) was carried out in spruce stands of different age in the area with an endemic population (Moravian-Silesian Beskids, Czech Republic) and in the area with an epidemic population (Beskid Żywiecki, Poland) of the eight-toothed spruce bark beetle Ips typographus (L.). The structure of merocoenoses was characterized separately for standing trees attacked by bark beetles, trees struck by lightning, trees affected by fungal pathogens and wind-felling and trees in the form of snags and fragments. The occurrence of cambioxylophagous insects, mostly bark beetles (Coleoptera: Scolytidae), was compared between the study areas with emphasis on dominant facultative primary bark beetles and types of damage to spruce trees.  

scholarly journals Acute Drought Is an Important Driver of Bark Beetle Infestation in Austrian Norway Spruce Stands

2019 ◽  
Vol 2 ◽  
Author(s):  
Sigrid Netherer ◽  
Bernd Panassiti ◽  
Josef Pennerstorfer ◽  
Bradley Matthews
Keyword(s):  
Norway Spruce ◽  
Bark Beetle ◽  
Spruce Stands
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