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 Operationalization of Remote Sensing Solutions for Sustainable Forest Management

2021 ◽  
Vol 13 (4) ◽  
pp. 572
Author(s):  
Gintautas Mozgeris ◽  
Ivan Balenović
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Natural Resources ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Development Trends ◽  
Comprehensive Information ◽  
The Status

The pre-requisite for sustainable management of natural resources is the availability of timely, cost-effective, and comprehensive information on the status and development trends of the management object [...]

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 Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data

2019 ◽  
Vol 23 (4) ◽  
pp. 265-282
Author(s):  
Rafael Andrés Calderón-Chaparro ◽  
German Vargas-Cuervo
Keyword(s):  
Remote Sensing ◽  
Soil Temperature ◽  
Field Data ◽  
Hot Springs ◽  
Landsat 8 ◽  
Geothermal Resources ◽  
Temperature Index ◽  
Landsat 7 ◽  
Geothermal Region

Geothermal resources (e.g. hot springs) are found with the help of field techniques, such as geological, geochemistry and geophysical. These techniques in some occasions are difficult to apply because of the limit access to the research area, rising operational costs and constrained spatially the exploration areas. The thermal infrared (TIR) remote sensing is an important tool for the exploration of geothermal resources, due to the low cost and high efficiency in the study of large geographic areas. The aim of this study is to use thermal imagery of satellite remote sensing and combined with geological-geophysical data, for spatial determination of exploratory prospects of hot springs in the geothermal region of Paipa, Boyacá. The images used in this study are from satellites Landsat-7 ETM+, Landsat-8 OLI/TIRS, MODIS, ALOS-PALSAR and Pléiades. Also, field data is used, such as soil temperature, surface temperature, air temperature, relative humidity, atmospheric pressure and thermal imagery of surface geothermal manifestations. The Landsat thermal bands were radiometrically calibrated, then atmospherically and surface emissivity corrected, applying single channel and split window algorithms, for Landsat-7 ETM+ and Landsat-8 TIRS, respectively. The field data helped to correct the thermal bands. And the soil temperature data are used to create a subsurface temperature map at 1-meter depth. Once primary and secondary data is had, in a geographic information system (GIS) is implemented an unweighted spatial model, which use four input indicators (satellite temperature index, soil temperature index, structural lineaments index and iso-resistivity index) to determine the areas with higher probability to find geothermal fluids. Six prospects are highlighted for hydrothermal fluid extraction, in which two of them are already known. Results allow to concluded that thermal remote sensing are useful to map geothermal anomalies in the Paipa region, and by using these anomalies plus geological-geophysical information is possible to determine exact exploration areas.

scholarly journals Integrating Landsat 7 and 8 data to improve basalt formation classification: A case study at Buon Ma Thuot region, Central Highland, Vietnam

2019 ◽  
Vol 11 (1) ◽  
pp. 901-917
Author(s):  
Ngo Van Liem ◽  
Dang Van Bao ◽  
Dang Kinh Bac ◽  
Nguyen Hieu ◽  
Do Trung Hieu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Band ◽  
Landsat 8 ◽  
Central Highland ◽  
Band Ratios ◽  
Landsat 7 ◽  
Cenozoic Basalt ◽  
Geological Map ◽  
Geological Formations

Abstract Cenozoic basalt regions contain various natural resources that can be used for socio-economic development. Different quantitative and qualitative methods have been applied to understand the geological and geomorphological characteristics of basalt formations. Nowadays the integration of remote sensing and geographic information systems (GIS) has become a powerful method to distinguish geological formations. In this paper, authors combined satellite and fieldwork data to analyze the structure and morphology of highland geological formations in order to distinguish two main volcanic eruption episodes. Based on remote sensing analysis in this study, different spectral band ratios were generated to select the best one for basalt classification. Lastly, two spectral combinations (including band ratios 4/3, 6/2, 7/4 in Landsat 8 and 3/2, 5/1, 7/3 in Landsat 7) were chosen for the Maximum Likelihood classification. The final geological map based on the integration of Landsat 7 and 8 outcomes shows precisely the boundary of the basalt formations with the accuracy up to 93.7%. This outcome contributed significantly to the correction of geological maps. In further studies, authors suggest the integration of Landsat 7 and 8 data in geological studies and natural resource and environmental management at both local and regional scales.

scholarly journals ZAB RIVER (IRAQ) SINUOSITY AND MEANDERING ANALYSIS BASED ON THE REMOTE SENSING DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 91-95
Author(s):  
B. Kalantar ◽  
M. H. Ameen ◽  
H. J. Jumaah ◽  
S. J. Jumaah ◽  
A. A. Halin
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Geographic Information Systems ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Sinuosity Index ◽  
River Region ◽  
Landsat 7 ◽  
Landsat 5 Tm ◽  
River Migration

Abstract. This work studies the meandering and change of paths along the Zab River in Iraq. Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 (2-sets) images were acquired from the years 1989, 1999, 2015 and 2019, respectively, which were used together with Remote sensing and Geographic Information Systems (GIS) techniques to study the changes. To determine the river/stream shape, the Sinuosity Index was calculated to classify Zab River segments into either the straight, sinuous or meandering class. Our findings via image analysis show coarse river migration and that most river segments fall into the two classes of sinuous and meander. In addition, it seems that the east bank of the Zab River region of the basin has extremely shifted where the river passes near the Kirkuk governorate.

scholarly journals Remote Sensing Application for Exploring Land Use and Land Cover Dynamics in and Around Chatra Wetland, English Bazar, West Bengal

2021 ◽  
Vol 9 (1) ◽  
pp. 15-27
Author(s):  
Saleha Jamal ◽  
Md Ashif Ali
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
United States Geological Survey ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Erdas Imagine ◽  
Landsat 7 ◽  
Vegetation Water

Wetlands are often called as biological “supermarket” and “kidneys of the landscape” due to their multiple functions, including water purification, water storage, processing of carbon and other nutrients, stabilization of shorelines and support of aquatic lives. Unfortunately, although being dynamic and productive ecosystem, these wetlands have been affected by human induced land use changes. India is losing wetlands at the rate of 2 to 3 per cent each year due to over-population, direct deforestation, urban encroachment, over fishing, irrigation and agriculture etc (Prasher, 2018). The present study tries to investigate the nature and degree of land use/land cover transformation, their causes and resultant effects on Chatra Wetland. To fulfil the purpose of the study, GIS and remote sensing techniques have been employed. Satellite imageries have been used from United States Geological Survey (USGS) Landsat 7 Enhanced Thematic Mapper plus and Landsat 8 Operational Land Imager for the year 2003 and 2018. Cloud free imageries of 2003 and 2018 have been downloaded from USGS (https://glovis.usgs.gov/) for the month of March and April respectively. Image processing, supervised classificationhas been done in ArcGis 10.5 and ERDAS IMAGINE 14. The study reveals that the settlement hasincreased by about 90.43 per cent in the last 15 years around the Chatra wetland within the bufferzone of 2 Sq km. Similarly agriculture, vegetation, water body, swamp and wasteland witnessed asignificant decrease by 5.94 per cent, 57.69 per cent, 26.64 per cent 4.52 per cent and 55.27 per centrespectively from 2003 to 2018.

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.

scholarly journals Effect of Reduced Anthropogenic Activities on Water Quality in Lake Vembanad, India

2021 ◽  
Vol 13 (9) ◽  
pp. 1631
Author(s):  
Gemma Kulk ◽  
Grinson George ◽  
Anas Abdulaziz ◽  
Nandini Menon ◽  
Varunan Theenathayalan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Sustainable Development ◽  
Sustainable Management ◽  
Marine Pollution ◽  
Anthropogenic Activities ◽  
Landsat 8 ◽  
Anthropogenic Pressures ◽  
Socioeconomic Impacts ◽  
Agriculture Industry

The United Nation’s Sustainable Development Goal Life Below Water (SDG-14) aims to “conserve and sustainably use the oceans, seas, and marine resources for sustainable development”. Within SDG-14, targets 14.1 and 14.2 deal with marine pollution and the adverse impacts of human activities on aquatic systems. Here, we present a remote-sensing-based analysis of short-term changes in the Vembanad-Kol wetland system in the southwest of India. The region has experienced high levels of anthropogenic pressures, including from agriculture, industry, and tourism, leading to adverse ecological and socioeconomic impacts with consequences not only for achieving the targets set out in SDG-14, but also those related to water quality (SDG-6) and health (SDG-3). To move towards the sustainable management of coastal and aquatic ecosystems such as Lake Vembanad, it is important to understand how both natural and anthropogenic processes affect water quality. In 2020, a unique opportunity arose to study water quality in Lake Vembanad during a period when anthropogenic pressures were reduced due to a nationwide lockdown in response to the global pandemic caused by SARS-CoV-2 (25 March–31 May 2020). Using Sentinel-2 and Landsat-8 multi-spectral remote sensing and in situ observations to analyse changes in five different water quality indicators, we show that water quality improved in large areas of Lake Vembanad during the lockdown in 2020, especially in the more central and southern regions, as evidenced by a decrease in total suspended matter, turbidity, and the absorption by coloured dissolved organic matter, all leading to clearer waters as indicated by the Forel-Ule classification of water colour. Further analysis of longer term trends (2013–2020) showed that water quality has been improving over time in the more northern regions of Lake Vembanad independent of the lockdown. The improvement in water quality during the lockdown in April–May 2020 illustrates the importance of addressing anthropogenic activities for the sustainable management of coastal ecosystems and water resources.

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