scholarly journals Mapping Coastal Dune Landscape through Spectral Rao’s Q Temporal Diversity

2020 ◽  
Vol 12 (14) ◽  
pp. 2315
Author(s):  
Flavio Marzialetti ◽  
Mirko Di Febbraro ◽  
Marco Malavasi ◽  
Silvia Giulio ◽  
Alicia Teresa Rosario Acosta ◽  
...  
Keyword(s):  
Land Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Central Italy ◽  
Coastal Dunes ◽  
Water Index ◽  
Coastal Landscapes ◽  
Index 2 ◽  
Main Components ◽  
Q Index

Coastal dunes are found at the boundary between continents and seas representing unique transitional mosaics hosting highly dynamic habitats undergoing substantial seasonal changes. Here, we implemented a land cover classification approach specifically designed for coastal landscapes accounting for the within-year temporal variability of the main components of the coastal mosaic: vegetation, bare surfaces and water surfaces. Based on monthly Sentinel-2 satellite images of the year 2019, we used hierarchical clustering and a Random Forest model to produce an unsupervised land cover map of coastal dunes in a representative site of the Adriatic coast (central Italy). As classification variables, we used the within-year diversity computed through Rao’s Q index, along with three spectral indices describing the main components of the coastal mosaic (i.e., Modified Soil-adjusted Vegetation Index 2—MSAVI2, Normalized Difference Water Index 2—NDWI2 and Brightness Index 2—BI2). We identified seven land cover classes with high levels of accuracy, highlighting different covariates as the most important in differentiating them. The proposed framework proved effective in mapping a highly seasonal and heterogeneous landscape such as that of coastal dunes, highlighting Rao’s Q index as a sound base for natural cover monitoring and mapping. The applicability of the proposed framework on updated satellite images emphasizes the procedure as a reliable and replicable tool for coastal ecosystems monitoring.

scholarly journals Comparison between Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) Assessment of Vegetation Indices

2017 ◽  
Vol 1 (2) ◽  
pp. 355-366
Author(s):  
E. O. Makinde ◽  
A. D. Obigha
Keyword(s):  
Statistical Analysis ◽  
Land Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Water Index ◽  
Landsat 7 ◽  
Index 2

The Landsat system has contributed significantly to the understanding of the Earth observation for over forty years. Since May 2013, data from Landsat 8 has been available online for download, with substantial differences from its predecessors, having an extended number of spectral bands and narrower bandwidths. The objectives of this research were majorly to carry out a cross comparison analysis between vegetation indices derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) and also performed statistical analysis on the results derived from the vegetation indices. Also, this research carried out a change detection on four land cover classes present within the study area, as well as projected the land cover for year 2030. The methods applied in this research include, carrying out image classification on the Landsat imageries acquired between 1984 – 2016 to ascertain the changes in the land cover types, calculated the mean values of differenced vegetation indices derived from the four land covers between Landsat 7 ETM+ and Landsat 8 OLI. Statistical analysis involving regression and correlation analysis were also carried out on the vegetation indices derived between the two sensors, as well as scatter plot diagrams with linear regression equation and coefficients of determination (R2). The results showed no noticeable differences between Landsat 7 and Landsat 8 sensors, which demonstrates high similarities. This was observed because Global Environmental Monitoring Index (GEMI), Improved Modified Triangular Vegetation Index 2 (MTVI2), Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Leaf Area Index (LAI) and Land Surface Water Index (LSWI) had smaller standard deviations. However, Renormalized Difference Vegetation Index (RDVI), Anthocyanin Reflectance Index 1 (ARI1) and Anthocyanin Reflectance Index 2 (ARI2) performed relatively poorly because their standard deviations were high. the correlation analysis of the vegetation indices that both sensors had a very high linear correlation coefficient with R2 greater than 0.99. It was concluded from this research that Landsat 7 ETM+ and Landsat 8 OLI can be used as complimentary data.

scholarly journals Factors Involved on Tiger-Stripe Foliar Symptom Expression of Esca of Grapevine

Plants ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1041
Author(s):  
Francesco Calzarano ◽  
Giancarlo Pagnani ◽  
Michele Pisante ◽  
Mirella Bellocci ◽  
Giuseppe Cillo ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Central Italy ◽  
Growth Stages ◽  
Symptom Expression ◽  
Strong Response ◽  
Water Index ◽  
High Calcium ◽  
Calcium Magnesium ◽  
Different Growth Stages

Esca of grapevine causes yield losses correlated with incidence and severity symptom expression. Factors associated with leaf symptom mechanisms are yet to be fully clarified. Therefore, in 2019 and 2020, macro and microelement analyses and leaf reflectance measurements were carried out on leaves at different growth stages in a vineyard located in Abruzzo, central Italy. Surveys were carried out on leaves of both never leaf-symptomatic vines and different categories of diseased vine shoots. Never leaf-symptomatic and diseased vines were also treated with a fertilizer mixture that proved to be able to limit the symptom expression. Results showed that untreated asymptomatic diseased vines had high calcium contents for most of the vegetative season. On the contrary, treated asymptomatic diseased vines showed higher contents of calcium, magnesium, and sodium, at berries pea-sized, before the onset of symptoms. These vines had better physiological efficiency showing higher water index (WI), normalized difference vegetation index (NDVI), and green normalized difference vegetation index (GNDVI) values, compared to untreated asymptomatic vines, at fruit set. Results confirmed the strong response of the plant to symptom expression development and the possibility of limiting this response with calcium and magnesium applications carried out before the symptom onset.

scholarly journals Utilização de Índices Físicos a partir de Imagens OLI – TIRS para o Mapeamento de Uso e Cobertura da Terra no entorno do Aeroporto Internacional do Recife/Guararapes – Gilberto Freire

2019 ◽  
Vol 12 (3) ◽  
pp. 1039
Author(s):  
Claudianne Brainer De Souza Oliveira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Land Cover Map ◽  
Area Use ◽  
Water Vegetation

Atualmente o uso de índices físicos NDVI (Normalized Difference Vegetacion Index), NDBI (Normalized Difference Built-up Index) e NDWI (Normalized Difference Water Index) vêm sendo muito utilizados como suporte para o mapeamento e monitoramento de uso e ocupação da terra. A área de estudo abrange o Aeroporto Internacional do Recife/Guararapes – Gilberto Freyre e o seu entorno, uma região na qual estão inseridos os municípios de Jaboatão dos Guararapes e Recife, ambos no Estado de Pernambuco. Utilizando imagens do satélite LANDSAT-8, sensor OLI de 18-06-2016, orbita-ponto 214-066, aplicou-se a técnica de fusão RGB-IHS para se obter uma melhor resolução espacial, logo após foram calculados os índices físicos, com o objetivo de avaliar o uso e ocupação do solo da área em questão. Como resultado final, obteve-se um mapa de uso e cobertura da terra, contendo quatro classes (solo exposto, água, vegetação e área construída), na escala de 1:50.000, no sistema de referência geodésico WGS84.  Physical indexes from OLI - TIRS images as tools for land use and coverage mapping around the airport International Recife / Guararapes - Gilberto Freire A B S T R A C TCurrently the use of NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-up Index) and NDWI (Normalized Difference Water Index) have been widely used as support for mapping and monitoring land use and occupation. The study area covers the Recife / Guararapes - Gilberto Freyre International Airport and its surroundings, a region in which the municipalities of Jaboatão dos Guararapes and Recife are located, both in the State of Pernambuco. Using images from the LANDSAT-8 satellite, OLI sensor of 06-06-2016, orbit-point 214-066, the RGB-IHS fusion technique was applied to obtain a better spatial resolution, after the physical indexes were calculated, with the objective of evaluating the land use and occupation of the area in question. As a final result, a land use and land cover map was obtained, containing four classes (exposed soil, water, vegetation and built area), in the 1: 50.000 scale, in the WGS84 geodetic reference system.Keywords: physical indexes, remote sensing, urban area, use and land cover.

scholarly journals A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 791-796
Author(s):  
S. Li ◽  
S. Zhang ◽  
D. Yang
Keyword(s):  
Land Cover ◽  
Change Detection ◽  
Vegetation Index ◽  
Morphological Features ◽  
Multi Index ◽  
Water Index ◽  
Fragmentation Index ◽  
Training Samples ◽  
Vegetation Water ◽  
New Framework

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

scholarly journals Pemodelan Hujan Netto Berdasarkan Tutupan Lahan untuk Analisa Debit Aliran Rendah

2019 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Adhi Yanuar Avianta ◽  
Rispiningtati Rispiningtati ◽  
Lily Montarcih Limantara ◽  
Ery Suhartanto
Keyword(s):  
Land Cover ◽  
Field Study ◽  
Land Cover Change ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Interception ◽  
Volume Balance ◽  
Discharge Modeling

This research intends to investigate the land cover change and to obtain the canopy interception in the Lesti sub-watershed, and to produce the rainfall-discharge modeling as the function of net rainfall factor. The methodology consisted of identifying the land cover based on the Normalized Difference Vegetation Index (NDVI) classification of digital satellite images Landsat TM 7 and TM 8, carrying out the field study to obtain the canopy interception used a volume balance approach. The interception rate of Lesti sub-watershed are 5 – 7 % in everage of rainfall, the net-rainfall models of Lesti sub-watershed are Pnetto= P - (-1E07P² + 0.059P +0.260) for land clasification II and Pnetto = P – (-1E07P² + 0.199P + 0.16) for land clasification III, it used as the input on the rainfall-discharge modeling of F.J. Mock, the result showed that the use of net-rainfall on the rainfall-discharge modeling of F.J. Mock increased the accuracy of generated discharge which is strongly influenced by the proportional of land classification.

scholarly journals USE AN OPEN SOURCE CHANGE MATTERS SITE TO MEASURE THE VEGETATION INDEX IN THE WESTERN PLATEAU OF ANBAR IN IRAQ

2020 ◽  
Vol 46 (1) ◽  
pp. 34-40
Author(s):  
Ahmed Alkubaisi
Keyword(s):  
Land Cover ◽  
Open Source ◽  
Satellite Images ◽  
Vegetation Index ◽  
Digital Technologies ◽  
Large Data ◽  
Land Cover Changes ◽  
Living Organisms ◽  
Many Sources ◽  
Extract Information

As a result of the development of geo-technologies, in recent years, software has emerged that has provided the possibility of deriving information. The most important of these are geographic information systems (GIS), which are many sources in satellite data from multi-spectral satellites, The source via the Internet is one of the most important modern means of providing large data that varied between maps and satellite images (LANDSAT-SPOT-NASA). The study of land cover changes is one of the most important subjects of interest to the sciences and in particular the geographical research related to the environment and its effects on humans and living organisms. In the current research, the data of interactive open source maps were adopted, which provided the possibility of analysis. Using the Change Matters esri, it is one of the most efficient locations for detection of land cover changes by dealing with visuals for different periods of time. The study also reviewed some of the open source websites dealing with GIS to indicate their importance and role in the analysis and production of maps. The research aims to employ open-source digital technologies via the web to extract information about land cover changes.

scholarly journals NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades

2020 ◽  
Vol 12 (9) ◽  
pp. 1468 ◽  
Author(s):  
Loránd Szabó ◽  
Balázs Deák ◽  
Tibor Bíró ◽  
Gareth J. Dyke ◽  
Szilárd Szabó
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Risk Index ◽  
Open Water ◽  
Ecological Processes ◽  
Water Basin ◽  
Water Index ◽  
Water Characteristics ◽  
Normalized Difference Water Index

Observing wetland areas and monitoring changes are crucial to understand hydrological and ecological processes. Sedimentation-induced vegetation spread is a typical process in the succession of lakes endangering these habitats. We aimed to survey the tendencies of vegetation spread of a Hungarian lake using satellite images, and to develop a method to identify the areas of risk. Accordingly, we performed a 33-year long vegetation spread monitoring survey. We used the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI) to assess vegetation and open water characteristics of the basins. We used these spectral indices to evaluate sedimentation risk of water basins combined with the fact that the most abundant plant species of the basins was the water caltrop (Trapa natans) indicating shallow water. We proposed a 12-scale Level of Sedimentation Risk Index (LoSRI) composed from vegetation cover data derived from satellite images to determine sedimentation risk within any given water basin. We validated our results with average water basin water depth values, which showed an r = 0.6 (p < 0.05) correlation. We also pointed on the most endangered locations of these sedimentation-threatened areas, which can provide crucial information for management planning of water directorates and management organizations.

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.

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