ОЦЕНКА УРОВНЯ ОЗЕЛЕНЕНИЯ ГОРОДА БИРОБИДЖАНА С ПРИМЕНЕНИЕМ МУЛЬТИСПЕКТРАЛЬНЫХ ДАННЫХ

The urban greenness distribution between functional areas of a medium-size city Birobidzhan was assessed. To this end, normalized difference vegetation index (NDVI) values were calculated based on Sentinel 2 multispectral imaging. Birobidzhan is characterized by a large scatter of NDVI values (from –0.5 to +1). Areas with high levels of greenery are prevalent. They are found in different types of functional zones, but are specific mainly to natural recreational, agricultural, and individual build-up zones as well as to special areas. The spatial distribution of green infrastructure is highly contrast. The downtown part as well as the industrial and storage zones feature a combination of built-up areas with dense woody vegetation, which is often represented by fragments of preserved natural vegetation. In addition, a feature of the contrast is that low level of tree greenness is characteristic for the built-up districts of the city. Thus, in the city of Birobidzhan, ecological functions are largely performed by the natural vegetation present in the natural recreational zones on 70% of the city's area.

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Red-Green-Blue and Multispectral Imaging as Potential Tools for Estimating Growth and Nutritional Performance of Cassava under Deficit Irrigation and Potassium Fertigation

Remote Sensing ◽

10.3390/rs13040598 ◽

2021 ◽

Vol 13 (4) ◽

pp. 598

Author(s):

Daniel O. Wasonga ◽

Afrane Yaw ◽

Jouko Kleemola ◽

Laura Alakukku ◽

Pirjo S.A. Mäkelä

Keyword(s):

Water Deficit ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Multispectral Imaging ◽

High Energy ◽

Plant Performance ◽

Estimation Accuracy ◽

Management Decisions ◽

Lower Estimation ◽

Low K

Cassava has high energy value and rich nutritional content, yet its productivity in the tropics is seriously constrained by abiotic stresses such as water deficit and low potassium (K) nutrition. Systems that allow evaluation of genotypes in the field and greenhouse for nondestructive estimation of plant performance would be useful means for monitoring the health of plants for crop-management decisions. We investigated whether the red–green–blue (RGB) and multispectral images could be used to detect the previsual effects of water deficit and low K in cassava, and whether the crop quality changes due to low moisture and low K could be observed from the images. Pot experiments were conducted with cassava cuttings. The experimental design was a split-plot arranged in a completely randomized design. Treatments were three irrigation doses split into various K rates. Plant images were captured beginning 30 days after planting (DAP) and ended at 90 DAP when plants were harvested. Results show that biomass, chlorophyll, and net photosynthesis were estimated with the highest accuracy (R2 = 0.90), followed by leaf area (R2 = 0.76). Starch, energy, carotenoid, and cyanide were also estimated satisfactorily (R2 > 0.80), although cyanide showed negative regression coefficients. All mineral elements showed lower estimation accuracy (R2 = 0.14–0.48) and exhibited weak associations with the spectral indices. Use of the normalized difference vegetation index (NDVI), green area (GA), and simple ratio (SR) indices allowed better estimation of growth and key nutritional traits. Irrigation dose 30% of pot capacity enriched with 0.01 mM K reduced most index values but increased the crop senescence index (CSI). Increasing K to 16 mM over the irrigation doses resulted in high index values, but low CSI. The findings indicate that RGB and multispectral imaging can provide indirect measurements of growth and key nutritional traits in cassava. Hence, they can be used as a tool in various breeding programs to facilitate cultivar evaluation and support management decisions to avert stress, such as the decision to irrigate or apply fertilizers.

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Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Remote Sensing ◽

10.3390/rs13020323 ◽

2021 ◽

Vol 13 (2) ◽

pp. 323

Author(s):

Liang Chen ◽

Xuelei Wang ◽

Xiaobin Cai ◽

Chao Yang ◽

Xiaorong Lu

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Maximum Temperature ◽

Maximum Temperature Difference ◽

Rapid Urbanization ◽

The Impact ◽

The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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Application of Phenotyping Methods in Detection of Drought and Salinity Stress in Basil (Ocimum basilicum L.)

Frontiers in Plant Science ◽

10.3389/fpls.2021.629441 ◽

2021 ◽

Vol 12 ◽

Author(s):

Boris Lazarević ◽

Zlatko Šatović ◽

Ana Nimac ◽

Monika Vidak ◽

Jerko Gunjača ◽

...

Keyword(s):

Drought Stress ◽

Salinity Stress ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Multispectral Imaging ◽

Ocimum Basilicum ◽

Phenotypic Traits ◽

Severe Drought ◽

Moderate Salinity ◽

Automated Phenotyping

Basil is one of the most widespread aromatic and medicinal plants, which is often grown in drought- and salinity-prone regions. Often co-occurrence of drought and salinity stresses in agroecosystems and similarities of symptoms which they cause on plants complicates the differentiation among them. Development of automated phenotyping techniques with integrative and simultaneous quantification of multiple morphological and physiological traits enables early detection and quantification of different stresses on a whole plant basis. In this study, we have used different phenotyping techniques including chlorophyll fluorescence imaging, multispectral imaging, and 3D multispectral scanning, aiming to quantify changes in basil phenotypic traits under early and prolonged drought and salinity stress and to determine traits which could differentiate among drought and salinity stressed basil plants. Ocimum basilicum “Genovese” was grown in a growth chamber under well-watered control [45–50% volumetric water content (VWC)], moderate salinity stress (100 mM NaCl), severe salinity stress (200 mM NaCl), moderate drought stress (25–30% VWC), and severe drought stress (15–20% VWC). Phenotypic traits were measured for 3 weeks in 7-day intervals. Automated phenotyping techniques were able to detect basil responses to early and prolonged salinity and drought stress. In addition, several phenotypic traits were able to differentiate among salinity and drought. At early stages, low anthocyanin index (ARI), chlorophyll index (CHI), and hue (HUE2D), and higher reflectance in red (RRed), reflectance in green (RGreen), and leaf inclination (LINC) indicated drought stress. At later stress stages, maximum fluorescence (Fm), HUE2D, normalized difference vegetation index (NDVI), and LINC contribute the most to the differentiation among drought and non-stressed as well as among drought and salinity stressed plants. ARI and electron transport rate (ETR) were best for differentiation of salinity stressed plants from non-stressed plants both at early and prolonged stress.

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Heat Islands in the city of San Francisco de Campeche: Detection and solution

ECORFAN Journal Republic of Paraguay ◽

10.35429/ejrop.2020.6.10.16.20 ◽

2020 ◽

pp. 16-20

Author(s):

Román Alejandro Canul-Turriza ◽

Francisco Javier Barrera-Lao ◽

Gabriela Patricia Aldana Narváez

Keyword(s):

Soil Temperature ◽

San Francisco ◽

Vegetation Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Heat Islands ◽

Mathematical Algorithm ◽

Green Areas ◽

Landsat 5 Tm ◽

The City

This paper presents the identification of heat islands in the city of San Francisco de Campeche, period 1990 - 2020 and their relationship with changes in the vegetation cover areas. To identify the heat islands in the city, 6 Landsat 5 (TM), 7 (TM) and 8 (OIL) images were obtained from the USGS database (http://earthexplorer.usgs.gov/). In geographic information software, soil temperature was calculated from a mathematical algorithm applied to thermal infrared bands 6 and 10, in addition, the Normalized Difference Vegetation Index (NDVI) was calculated, in order to find a relationship between changes in temperature and vegetation cover. It was found that the green areas have reduced their surface by more than 50% and the soil temperature has increased up to 7 ° C

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ANÁLISE DA GESTÃO OCUPACIONAL EM MONTES CLAROS – MG: Impactos do uso do solo e suas consequências na temperatura de superfície

Revista Cerrados ◽

10.22238/rc24482692v15n12017p285a311 ◽

2020 ◽

Vol 15 (01) ◽

pp. 285-311

Author(s):

Bruna Reis Pereira ◽

Mariana Barreto Mees ◽

Manoel Reinaldo Leite ◽

Raul de Magalhães Filho

Keyword(s):

Surface Temperature ◽

Urban Space ◽

Temperature Increase ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Urban Centers ◽

Human Needs ◽

Significant Temperature ◽

Landsat 5 Tm ◽

The City

O uso do solo é a atividade de uma sociedade por sobre uma superfície, este caracteriza-se conforme as individualidades conjugada aos padrões de necessidades humanas. Um dos impactos ambientais que deve ser considerado neste processo de apropriação é o comportamento térmico de superfície. Neste sentido, o presente trabalho, tendo como área de estudo o perímetro urbano de Montes Claros – MG, teve como objetivo analisar a ocupação do espaço urbano na cidade sob uma condição cronológica: 1990 a 2010. Por meio da análise de imagens de sensoriamento remoto (Landsat 5 TM) procurou-se verificar se o modelo de ocupação provocou problemas urbanos de natureza térmica. Os resultados mostraram, a partir da metodologia adotada, que regiões com decréscimo de NDVI (Índice de Vegetação por Diferença Normalizada) e grande adensamento de edificações tiveram significativos aumento de temperatura no período considerado, ratificando o problema de aumento de temperatura de superfície nos centros urbanos. Palavras-chave: Urbanização; temperatura de superfície; desenvolvimento urbano; Montes Claros. ANALYSIS OF OCCUPATIONAL MANAGEMENT IN MONTES CLAROS - MG: Impacts of land use and its consequences on surface temperature Abstract The use of the soil is the activity of a society above a surface, this is characterized according to the individualities combined with the patterns of human needs. One of the environmental impacts that must be considered in this appropriation process is the surface thermal behavior. In this sense, the present study, having as its study area the urban perimeter of Montes Claros - MG, aimed to analyze the occupation of urban space in the city under a chronological condition: 1990 to 2010. Through the analysis of remote sensing images (Landsat 5 TM), it was verified that the occupation model caused urban problems of a thermal nature. The results showed that the regions with decreasing NDVI (Normalized Difference Vegetation Index) and high density of buildings had significant temperature increase in the period considered, confirming the problem of surface temperature increase in urban centers . Keywords: Urbanization; Surface temperature; urban Development; Montes Claros. ANALYSE DES PROFESSIONNELLES GESTION MONTES CLAROS - MG: impacts de l'utilisation des terres et les conséquences de la température de surface Resumen Uso de la tierra es la actividad de una corporación sobre una superficie, este se caracteriza como individualidades combinados a los estándares de las necesidades humanas. Un impactos ambientales que deben ser considerados en este proceso de solución es la superficie comportamiento térmico. En este sentido, el presente trabajo, con el área de estudio del área urbana de Montes Claros - MG, tuvo como objetivo analizar la ocupación del espacio urbano en la ciudad bajo una condición cronológico: 1990 a 2010. Por medio del análisis de imágenes de teledetección (Landsat 5 TM) trató de verificar que el modelo de ocupación provocó problemas urbanos de la naturaleza térmica. Los resultados mostraron que a partir de la metodología utilizada, las regiones con la disminución de NDVI (índice de vegetación de diferencia normalizada) y de alta densidad de edificios tenían aumento significativo de la temperatura durante el periodo considerado, lo que confirma el problema aumento de la temperatura de superficie en los centros urbanos . Palavras chave: urbanización; temperatura de la superficie; desarrollo Urbano; Montes Claros.

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Yield, Quality and Physiological Traits of Red Beet Under Different Magnesium Nutrition and Light Intensity Levels

Agronomy ◽

10.3390/agronomy9070379 ◽

2019 ◽

Vol 9 (7) ◽

pp. 379

Author(s):

Sara D’Egidio ◽

Angelica Galieni ◽

Fabio Stagnari ◽

Giancarlo Pagnani ◽

Michele Pisante

Keyword(s):

Light Intensity ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Dry Weight ◽

Total Phenolic ◽

Storage Roots ◽

Light Reduction ◽

Red Beet ◽

Application Rates ◽

And Storage

The effects of light intensity and Magnesium (Mg) supply on quality traits, yield and macronutrient assimilation of red beet plants were studied in two greenhouse experiments (in 2017 and 2018). According to a split-plot design, we compared two photosynthetically active radiation (PAR) levels (100% PAR, Full Light, FL and 50% PAR, Light Reduction, LR) as the main factor and three Mg application rates (0, 30, and 60 kg Mg ha−1: MG_0, MG_30 and MG_60, respectively) as the secondary factor. Yield and dry matter accumulations were principally affected by Mg. In both growing seasons, storage root dry weight (DW) increased about 5-fold in MG_60 with respect to MG_0; the highest leaves DW was achieved with the “LR × MG_60” treatment. Nitrogen and Mg contents in leaves and storage roots increased as Mg availability increased; also, the highest chlorophyll content was obtained combining LR and a high Mg rate. Moreover, the reflectance-derivative Normalized Difference Vegetation Index (NDVI670) and Chlorophyll Index (CI) allowed for discriminating the Mg sub-optimal supply in red beet plants. Sucrose was found to be the most abundant sugar in both the leaves and storage organs and was affected by Mg supply. Total phenolic content and betalains in storage roots at harvest were affected by both PAR and Mg application rates. Our results highlight the potential of Mg nutrition in ensuring good yield and quality of red beet crops.

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Developing City-Wide Hurricane Impact Maps using Real-Life Data on Infrastructure, Vegetation and Weather

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120972714 ◽

2020 ◽

pp. 036119812097271

Author(s):

Mingyang Chen ◽

Alican Karaer ◽

Eren Erman Ozguven ◽

Tarek Abichou ◽

Reza Arghandeh ◽

...

Keyword(s):

Geographical Information Systems ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Real Life ◽

Google Earth ◽

Geographical Information ◽

Data Sets ◽

Hurricane Impact ◽

The City

Hurricanes affect thousands of people annually, with devastating consequences such as loss of life, vegetation and infrastructure. Vegetation losses such as downed trees and infrastructure disruptions such as toppled power lines often lead to roadway closures. These disruptions can be life threatening for the victims. Emergency officials, therefore, have been trying to find ways to alleviate such problems by identifying those locations that pose high risk in the aftermath of hurricanes. This paper proposes an integrated methodology that utilizes both Google Earth Engine (GEE) and geographical information systems (GIS). First, GEE is used to access Sentinel-2 satellite images and calculate the Normalized Difference Vegetation Index (NDVI) to investigate the vegetation change as a result of Hurricane Michael in the City of Tallahassee. Second, through the use of ArcGIS, data on wind speed, debris, roadway density and demographics are incorporated into the methodology in addition to the NDVI indices to assess the overall impact of the hurricane. As a result, city-wide hurricane impact maps are created using weighted indices created based on all these data sets. Findings indicate that the northeast side of the city was the worst affected because of the hurricane. This is a region where more seniors live, and such disruptions can lead to dramatic consequences because of the fragility of these seniors. Officials can pinpoint the identified critical locations for future improvements such as roadway geometry modification and landscaping justification.

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Generalization of Vegetation Indices for Monitoring the Terrestrial Biosphere

10.5194/egusphere-egu21-14263 ◽

2021 ◽

Author(s):

Gustau Camps-Valls ◽

Manuel Campos-Taberner ◽

Alvaro Moreno-Martinez ◽

Sophia Walther ◽

Grégory Duveiller ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Multispectral Imaging ◽

Spectral Band ◽

Vegetation Indices ◽

Observation Data ◽

Terrestrial Biosphere ◽

Time Resolved ◽

Area Index ◽

Nonlinear Generalization

Vegetation indices are the most widely used tool in remote sensing and multispectral imaging applications. This paper introduces a nonlinear generalization of the broad family of vegetation indices based on spectral band differences and ratios. The presented indices exploit all higher-order relations of the involved spectral channels, are easy to derive and use, and give some insight on problem complexity. The framework is illustrated to generalize the widely adopted Normalized Difference Vegetation Index (NDVI). Its nonlinear generalization named, kernel NDVI (kNDVI), largely improves performance over NDVI and the recent NIRv in monitoring key vegetation parameters, showing much higher correlation with independent products, such as the MODIS leaf area index (LAI), flux tower gross primary productivity (GPP), and GOME-2 sun-induced fluorescence. The family of indices constitutes a valuable choice for many applications that require spatially explicit and time-resolved analysis of Earth observation data. Reference: "A Unified Vegetation Index for Quantifying the Terrestrial Biosphere", Gustau Camps-Valls, Manuel Campos-Taberner, &#193;lvaro Moreno-Mart&#305;&#769;nez, Sophia Walther, Gr&#233;gory Duveiller, Alessandro Cescatti, Miguel Mahecha, Jordi Mu&#241;oz-Mar&#305;&#769;, Francisco Javier Garc&#305;&#769;a-Haro, Luis Guanter, John Gamon, Martin Jung, Markus Reichstein, Steven W. Running. Science Advances, in press, 2021

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Standardized Green View Index and Quantification of Different Metrics of Urban Green Vegetation

Sustainability ◽

10.3390/su12187434 ◽

2020 ◽

Vol 12 (18) ◽

pp. 7434 ◽

Cited By ~ 2

Author(s):

Yusuke Kumakoshi ◽

Sau Yee Chan ◽

Hideki Koizumi ◽

Xiaojiang Li ◽

Yuji Yoshimura

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Urban Landscapes ◽

Site Location ◽

Urban Green ◽

Urban Greenery ◽

Geographical Scale ◽

Green Vegetation ◽

Block Level ◽

The City

Urban greenery is considered an important factor in sustainable development and people’s quality of life in the city. To account for urban green vegetation, Green View Index (GVI), which captures the visibility of greenery at street level, has been used. However, as GVI is point-based estimation, when aggregated at an area-level by mean or median, it is sensitive to the location of sampled sites, overweighing the values of densely located sites. To make estimation at area-level more robust, this study aims to (1) propose an improved indicator of greenery visibility (standardized GVI; sGVI), and (2) quantify the relation between sGVI and other green metrics. Experiment on an hypothetical setting confirmed that bias from site location can be mitigated by sGVI. Furthermore, comparing sGVI and Normalized Difference Vegetation Index (NDVI) at the city block level in Yokohama city, Japan, we found that sGVI captures the presence of vegetation better in the city center, whereas NDVI is better at capturing vegetation in parks and forests, principally due to the different viewpoints (eye-level perception and top-down eyesight). These tools provide a foundation for accessing the effect of vegetation in urban landscapes in a more robust matter, enabling comparison on any arbitrary geographical scale.

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Spatiotemporal Assessment of Vegetation Indices and Land Cover for Erbil City and Its Surrounding Using Modis Imageries

Journal of Environmental Geography ◽

10.1515/jengeo-2017-0004 ◽

2017 ◽

Vol 10 (1-2) ◽

pp. 31-39 ◽

Cited By ~ 6

Author(s):

Shwan O. Hussein ◽

Ferenc Kovács ◽

Zalán Tobak

Keyword(s):

Land Cover ◽

Urban Areas ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Vegetation Indices ◽

Natural Vegetation ◽

Visual Interpretation ◽

Surrounding Areas ◽

The Impact

Abstract The rate of global urbanization is exponentially increasing and reducing areas of natural vegetation. Remote sensing can determine spatiotemporal changes in vegetation and urban land cover. The aim of this work is to assess spatiotemporal variations of two vegetation indices (VI), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), in addition land cover in and around Erbil city area between the years 2000 and 2015. MODIS satellite imagery and GIS techniques were used to determine the impact of urbanization on the surrounding quasi-natural vegetation cover. Annual mean vegetation indices were used to determine the presence of a spatiotemporal trend, including a visual interpretation of time-series MODIS VI imagery. Dynamics of vegetation gain or loss were also evaluated through the study of land cover type changes, to determine the impact of increasing urbanization on the surrounding areas of the city. Monthly rainfall, humidity and temperature changes over the 15-year-period were also considered to enhance the understanding of vegetation change dynamics. There was no evidence of correlation between any climate variable compared to the vegetation indices. Based on NDVI and EVI MODIS imagery the spatial distribution of urban areas in Erbil and the bare around it has expanded. Consequently, the vegetation area has been cleared and replaced over the past 15 years by urban growth.

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