scholarly journals Sensoriamento Remoto Aplicado na Geoespacialização do Reservatório Poço da Cruz - PE e seu Entorno

2021 ◽  
Vol 14 (6) ◽  
pp. 3592
Author(s):  
Haylla Rebeka De Albuquerque Lins Leonardo ◽  
Camila Oliveira de Britto Salgueiro ◽  
Débora Natália Oliveira de Almeida ◽  
Sylvana Melo dos Santos ◽  
Leidjane Maria Maciel de Oliveira
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
Vegetation Cover ◽  
Socioeconomic Development ◽  
Temporal Variations ◽  
Rainfall Regime ◽  
Landsat 8 ◽  
Remote Sensing Technique ◽  
Low Humidity ◽  
Biophysical Indices

O Sertão Pernambucano é caracterizado por longos períodos de secas, com um regime pluviométrico inconstante e irregular, dificultando o desenvolvimento socioeconômico da região. Neste contexto a aplicação de técnica de Sensoriamento Remoto utilizando de imagens georreferenciadas destaca-se pela relevância no monitoramento e análise da variação da cobertura vegetal e do suprimento hídrico nos reservatórios da região. Este estudo objetivou-se em avaliar as variações temporais geoespacializadas do uso e ocupação do solo, vegetação e área superficial do espelho d’água do reservatório de Poço da Cruz - PE, em uma perspectiva espectro temporal utilizando imagens datadas de 2000, 2013 e 2020, aplicando os índices espectrais MNDWI, NDWI, SAVI, IAF, dos sistemas sensores TM Landsat 5 e OLI Landsat 8, e ferramentas do projeto MAPBIOMAS da coleção 5.0. A análise do MNDWI identificou o aumento na área superficial do reservatório ao longo dos anos, ressaltando que os anos de 2000 e 2013 apresentaram um maior estresse hídrico com redução dos valores do índice. Os índices NDWI, SAVI e IAF, apontaram uma cobertura vegetal escassa e seca com baixa umidade para os anos de 2000 e 2013, entretanto, observou-se o aumento do vigor vegetativo e presença de maior umidade para o ano de 2020. Condizente com os dados obtidos para o uso e ocupação do solo pelo projeto MAPBIOMAS, indicando que houve um aumento das áreas destinadas a agricultura e pastagem no entorno do reservatório entre os anos de 2000 e 2013, bem como o incremento do seu espelho d´água.   Analysis of the Temporal Variability of Water Body in the Backwoods of the Pernambuco A B S T R A C TThe Sertão Pernambucano is characterized by long periods of drought, with an unstable and irregular rainfall regime, which hinders the socioeconomic development of the region. In this context, the application of the Remote Sensing technique using georeferenced images stands out for its relevance in monitoring and analyzing the variation in vegetation cover and water supply in the region's reservoirs. This study aimed to evaluate the geospatial temporal variations of the use and occupation of the soil, vegetation and surface area of the water mirror of the Poço da Cruz reservoir - PE, in a temporal spectrum perspective using images dated from 2000, 2013 and 2020, applying the spectral indices MNDWI, NDWI, SAVI, IAF, from the TM Landsat 5 and OLI Landsat 8 sensor systems, and tools from the MapBiomas project from the 5.0 collection. The MNDWI analysis identified the increase in the surface area of the reservoir over the years, noting that the years 2000 and 2013 showed greater water stress with a reduction in the index values. The NDWI, SAVI and IAF indexes indicated a sparse and dry vegetation cover with low humidity for the years 2000 and 2013, however, there was an increase in vegetative vigor and the presence of higher humidity for the year 2020. data obtained for land use and occupation by the MapBiomas project, indicating that there was an increase in areas for agriculture and pasture around the reservoir between 2000 and 2013, as well as an increase in its water surface.Keywords: biophysical indices; water resource; remote sensing.

Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices

2021 ◽  
Vol 25 (9) ◽  
pp. 30-37
Author(s):  
N.N. Sliusar ◽  
A.P. Belousova ◽  
G.M. Batrakova ◽  
R.D. Garifzyanov ◽  
M. Huber-Humer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Google Earth ◽  
The State ◽  
Landsat 8 ◽  
The Earth

The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.

scholarly journals Temporal Influences of Vegetation Cover (C) Dynamism on MUSLE Sediment Yield Estimates: NDVI Evaluation

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2707
Author(s):  
David Gwapedza ◽  
Denis Arthur Hughes ◽  
Andrew Robert Slaughter ◽  
Sukhmani Kaur Mantel
Keyword(s):  
Sediment Yield ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Scale Validation ◽  
Spatial Scales ◽  
Temporal Variations ◽  
Early Summer ◽  
Landsat 8 ◽  
Temporal Scales ◽  
Normalised Difference Vegetation Index

Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor.

scholarly journals Changes in vegetation cover on Stara planina: Towards sustainable management of ski resorts in sensitive areas

2015 ◽  
Vol 95 (2) ◽  
pp. 25-40 ◽  
Author(s):  
Ivan Potic ◽  
Marko Joksimovic ◽  
Rajko Golic
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
High Mountain ◽  
Landsat 8 ◽  
Mountain Areas ◽  
Ski Resorts ◽  
Landsat 7 ◽  
Multispectral Analysis

Tourism is an indicator and the consequence of the development of many countries. Among the priority areas of the tourism strategy are high mountain areas with complex ecosystems. Mountain tourism in Serbia, as well as continental country is one of the leading forms of tourism through various projects stimulated by the state. In the last ten years, build up and expand the ski slopes of Stara planina in eastern Serbia, leading to various, mostly negative changes in the environment. This paper analyzes the changes in the forest areas of the site Babin Zub in years 2000 and 2013, using satellite imagery (Landsat 7 and Landsat 8) and remote sensing software. We used unsupervised multispectral analysis resolution 30 m and obtained data on forest areas. The aim is to draw attention to the change of vegetation cover and degradation of forest areas. Following to the experiences of the world's ski resorts, the paper presents the opportunities and examples of restoration of ski runs, and sustainable forest management in the studied highland area.

scholarly journals Modelling and Delineation of Hydrocarbon Micro - Seepage Prone Zones on Soil and Sediment in Ugwueme, South Eastern Nigeria with Soil Adjustment Vegetation Index (SAVI)

2020 ◽  
pp. 13-33
Author(s):  
Mfoniso Asuquo Enoh ◽  
Uzoma Chinenye Okeke ◽  
Needam Yiinu Barinua
Keyword(s):  
Remote Sensing ◽  
Image Classification ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Landsat 8 ◽  
Landsat Images ◽  
Landsat 7 ◽  
Soil And Sediment

Remote Sensing is an excellent tool in monitoring, mapping and interpreting areas, associated with hydrocarbon micro-seepage. An important technique in remote sensing known as the Soil Adjusted Vegetation Index (SAVI), adopted in many studies is often used to minimize the effect of brightness reflectance in the Normalized Difference Vegetation Index (NDVI), related with soil in areas of spare vegetation cover, and mostly in areas of arid and semi–arid regions. The study aim at analyzing the effect of hydrocarbon micro – seepage on soil and sediments in Ugwueme, Southern Eastern Nigeria, with SAVI image classification method. To achieve this aim, three cloud free Landsat images, of Landsat 7 TM 1996 and ETM+ 2006 and Landsat 8 OLI 2016 were utilized to produce different SAVI image classification maps for the study.  The SAVI image classification analysis for the study showed three classes viz Low class cover, Moderate class cover and high class cover.  The category of high SAVI density classification was observed to increase progressive from 31.95% in 1996 to 34.92% in 2006 and then to 36.77% in 2016. Moderately SAVI density classification reduced from 40.53% in 1996 to 38.77% in 2006 and then to 36.96% in 2016 while Low SAVI density classification decrease progressive from 27.51% in 1996 to 26.31% in 2006 and then increased to 28.26% in 2016. The SAVI model is categorized into three classes viz increase, decrease and unchanged. The un – changed category increased from 12.32km2 (15.06%) in 1996 to 17.17 km2 (20.96%) in 2006 and then decelerate to 13.50 km2 (16.51%) in 2016.  The decrease category changed from 39.89km2 (48.78%) in 1996 to 40.45 km2 (49.45%) in 2006 and to 51.52 km2 (63.0%) in 2016 while the increase category changed from 29.57km2 (36.16%) in 1996 to 24.18 km2 (29.58%) in 2006 and to 16.75 km2 (20.49%) in 2016. Image differencing, cross tabulation and overlay operations were some of the techniques performed in the study, to ascertain the effect of hydrocarbon micro - seepage.  The Markov chain analysis was adopted to model and predict the effect of the hydrocarbon micro - seepage for the study for 2030.  The study expound that the SAVI is an effective technique in remote sensing to identify, map and model the effect of hydrocarbon micro - seepage on soil and sediment particularly in areas characterized with low vegetation cover and bare soil cover.

scholarly journals VEGETATION COVERAGE AND IMPERVIOUS SURFACE AREA ESTIMATED BASED ON THE ESTARFM MODEL AND REMOTE SENSING MONITORING

2018 ◽  
Vol IV-3 ◽  
pp. 113-119
Author(s):  
Rongming Hu ◽  
Shu Wang ◽  
Jiao Guo ◽  
Liankun Guo
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
Temporal Resolution ◽  
Remote Sensing Data ◽  
Impervious Surface ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Spatiotemporal Resolution ◽  
Impervious Surface Area ◽  
Sensing Data

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

scholarly journals EMPREGO DO SENSORIAMENTO REMOTO E SISTEMA DE INFORMAÇÃO GEOGRÁFICA NA AVALIAÇÃO DA FRAGILIDADE AMBIENTAL DA BACIA HIDROGRÁFICA DO RIBEIRÃO SÃO PEDRO, SANTA RITA DO PARDO/MS

2020 ◽  
Vol 16 (02) ◽  
pp. 31-50
Author(s):  
Angélica Estigarribia São Miguel ◽  
Rafael Brugnolli Medeiros ◽  
Weslen Manari Gomes
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
River Basin ◽  
Vegetation Cover ◽  
Digital Terrain Model ◽  
Landsat 8 ◽  
Terrain Model ◽  
Gis Environment ◽  
Del Rio ◽  
Two Stages

A fragilidade ambiental diz respeito à fragilidade do ambiente em função de qualquer tipo de dano causado pela dinâmica ambiental, seja de forma natural e/ou antrópica, sendo relacionada com a erosão do solo e assoreamento dos rios. O objetivo desta pesquisa foi realizar uma análise da fragilidade ambiental da bacia hidrográfica do ribeirão São Pedro, no município de Santa Rita do Pardo/MS, analisando suas características físicas e o uso da terra e cobertura vegetal. Para tanto, a metodologia consiste em duas etapas: a primeira delas na avaliação das precipitações buscando algumas estações meteorológicas no entorno da bacia hidrográfica, trabalhando em ambiente SIG ArcGis 10. A segunda diz respeito ao manuseio das informações sobre áreas prioritárias e solos, buscou-se dados do SISLA/IMASUL, a declividade, trabalhou-se com o modelo digital de terreno SRTM e para o uso da terra e cobertura vegetal a utilização das imagens de satélite Landsat 8. Com isso, a interpolação dessas informações foi embasada na proposta metodológica de Ross (1994) para a fragilidade ambiental. As classes de fragilidade obtidas são a categoria baixa que se mostrou dominante na bacia, sendo presentes em matas nativas e pastagens, a categoria média e alta, que juntas apresentaram 39,56% da área total da bacia foram encontradas em locais com alto declive, concluindo assim que a bacia hidrográfica necessita da análise de suas características, onde qualquer mudança em um de seus elementos pode alterar a fragilidade do local, prejudicando assim, seus recursos naturais. Palavras-chave: Fragilidade ambiental. Sensoriamento Remoto. Uso da terra e cobertura vegetal.   EMPLOYMENT OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM IN EVALUATION OF ENVIRONMENTAL FRAGILITY OF HYDROGRAPHIC BASIN SÃO PEDRO, SANTA RITA DO PARDO/MS ABSTRACT The environmental fragility refers to the fragility of the environment due to any kind of damage caused by the environmental dynamics, either naturally or anthropically, and is related to soil erosion and silting of rivers. The objective of this research was to analyze the environmental fragility of the São Pedro river basin, in the municipality of Santa Rita do Pardo / MS, analyzing its physical characteristics and the use of land and vegetation cover. To do so, the methodology consists of two stages: the first one in the evaluation of precipitation by searching for some meteorological stations around the watershed, working in ArcGis 10 GIS environment. The second one concerns the handling of information on priority areas and soils, if data from the SISLA / IMASUL, the slope was worked with the SRTM digital terrain model and for the land use and vegetation cover the use of Landsat 8 satellite images. With this, the interpolation of this information was based on the methodological proposal of Ross (1994) for environmental fragility. The fragility classes obtained are the low category that was dominant in the basin, being present in native forests and pastures, the medium and high category, which together presented 39.56% of the total area of ​​the basin were found in places with high slope, thus concluding that the river basin needs the analysis of its characteristics, where any change in one of its elements can alter the fragility of the place, thus damaging its natural resources. Key Words: Environmental fragility. Remote Sensing. Land use and vegetation cover.   EMPLEO DEL SENSORIAMIENTO REMOTO Y SISTEMA DE INFORMACIÓN GEOGRÁFICA EN LA EVALUACIÓN DE LA FRAGILIDAD AMBIENTAL DE LA BACIA HIDROGRÁFICA DEL RIBEIRÃO SÃO PEDRO, SANTA RITA DO PARDO/MS RESUMEN La fragilidad ambiental se refiere a la fragilidad del ambiente en función de cualquier tipo de daño causado por la dinámica ambiental, sea de forma natural y / o antrópica, estando relacionada con la erosión del suelo y la sedimentación de los ríos. El objetivo de esta investigación fue realizar un análisis de la fragilidad ambiental de la cuenca hidrográfica del río San Pedro, en el municipio de Santa Rita do Pardo / MS, analizando sus características físicas y el uso de la tierra y cobertura vegetal. Para ello, la metodología consiste en dos etapas: la primera de ellas en la evaluación de las precipitaciones buscando algunas estaciones meteorológicas en el entorno de la cuenca hidrográfica, trabajando en ambiente SIG ArcGis 10. La segunda se refiere al manejo de las informaciones sobre áreas prioritarias y suelos, si los datos del SISLA / IMASUL, la declividad, se trabajó con el modelo digital de terreno SRTM y para el uso de la tierra y cobertura vegetal la utilización de las imágenes de satélite Landsat 8. Con ello, la interpolación de esas informaciones se basó en la propuesta metodológica de Ross (1994) para la fragilidad ambiental. Las clases de fragilidad obtenidas son la categoría baja que se mostró dominante en la cuenca, siendo presentes en bosques nativos y pastos, la categoría media y alta, que juntas presentaron el 39,56% del área total de la cuenca se encontraron en locales con alto declive, concluyendo así que la cuenca hidrográfica necesita el análisis de sus características, donde cualquier cambio en uno de sus elementos puede alterar la fragilidad del local, perjudicando así sus recursos naturales. Palabras clave: Fragilidad ambiental. Detección remota. Uso de la tierra y cobertura vegetal.

scholarly journals STUDY OF INFLUENCE OF THE FAULT ZONES ON VEGETATION COVER OF STATE TERRITORY OF THE NATURE SANCTUARY "DOLINSKY" (SAKHALIN ISLAND) USING EARTH’S REMOTE SENSING DATA

2021 ◽  
Vol 26 (5) ◽  
pp. 75-85
Author(s):  
Olesya V. Kuptsova ◽  
◽  
Inna I. Lobishcheva ◽  
Alexey A. Verhoturov ◽  
Vyacheslav A. Melkiy ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Plant Communities ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Fault Zones ◽  
Sakhalin Island ◽  
The State ◽  
Likelihood Method ◽  
Landsat 8 ◽  
Sensing Data

Fault zones on the territory of Nature Sanctuary “Dolinsky” (Sakhalin Island), which are characterized by high geodynamic activity, are generally well distinguished when analyzing satellite imagery materials. In any territory, it is not difficult to identify the various plant communities that occupy it, as well as to determine their state by the content of phytomass determined by the vegetation index NDVI. The aim of the study is to test the validity of the hypothesis about the formation of abundant vegetation cover within the fault zones by analyzing the state of various plant communities by the volume of phytomass. Methods: decryption and analysis of Earth remote sensing data from Sentinel, Landsat and SRTM generation, geoinformation mapping on the ArcGIS platform. Results. In the course of the study, the state of the Nature Sanctuary “Dolinsky” analyzed by Landsat-8, Sentinel-2A satellite sur-veys, as well as SRTM data. Fault zones identified using the software systems ArcGIS, QGIS, and PyLEFA by lineament analysis, vegetation was classified by the maximum likelihood method, and its condition was determined by the values of the NDVI index, which reflects the content of phytomass in the study area. As result of the work carried out, an increase in phytomass revealed, and, consequently, good conditions for the growth of plant communities confined to the zones of distribution of faults of the earth's crust, and the reliability of the working hypothesis confirmed.

scholarly journals A Satellite-based Remote Sensing Technique for Surface Water Quality Estimation

2019 ◽  
Vol 9 (2) ◽  
pp. 3965-3970 ◽  
Author(s):  
M. V. Japitana ◽  
M. E. C. Burce
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Input Image ◽  
Landsat 8 ◽  
Band Ratio ◽  
Remote Sensing Technique

Remote sensing provides a synoptic view of the earth surface that can provide spatial and temporal trends necessary for comprehensive water quality (WQ) monitoring and assessment. This study explores the applicability of Landsat 8 and regression analysis in developing models for estimating WQ parameters such as pH, dissolved oxygen (DO), total dissolved solids (TDS), total suspended solids (TSS), biological oxygen demand (BOD), turbidity, and conductivity. The input image was radiometrically-calibrated using fast line-of-sight atmospheric analysis (FLAASH) and then atmospherically corrected to obtain surface reflectance (SR) bands using FLAASH and dark object subtraction (DOS) for comparison. SR bands derived using FLAASH and DOS, water indices, band ratio, and principal component analysis (PCA) images were utilized as input data. Feature vectors were then collected from the input bands and subsequently regressed together with the WQ data. Forward regression results yielded significant high R2 values for all WQ parameters except TSS and conductivity which had only 60.1% and 67.7% respectively. Results also showed that the regression models of pH, BOD, TSS, TDS, DO, and conductivity are highly significant to SR bands derived using DOS. Furthermore, the results of this study showed the promising potential of using RS-based WQ models in performing periodic WQ monitoring and assessment.

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