scholarly journals Application of GIS and remote sensing to build up a map of environmental geological suitability for residential buildings on Thi Vai river basin

2019 ◽  
Vol 3 (1) ◽  
pp. 1-11
Author(s):  
Tuong Van Ngo Thi ◽  
Hoang Anh Nguyen
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Residential Buildings ◽  
Satellite Image ◽  
Landsat 8 ◽  
Environmental Capacity ◽  
Remotely Sensed Data ◽  
Construction Sites ◽  
Gis And Remote Sensing ◽  
Suitability Maps

Geological environment zonation is to divide the areas into relatively homogeneous units based on their natural factors such as hydrology, topography, geology, disasters... to create geoenvironmental units which suit a specific type of exploitation for the purpose of research or regional management. This study presents a process of integrating GIS and remotely sensed data to develop a map of environmental geological zonning for the planning of development of the efective and safety construction sites. Data used in this work include Landsat 8 satellite image classified by application of Fuzzy Logic method to build the map of land use status which includes construction sites, and the GIS data including geology, topography, engineering geology and hydrogeology. The result from this process of integration is the suitability maps of appropriate units for the development of construction sites on the Thi Vai river basin. This map shows 3 different levels of geological environmental condition for development of the construction sites. This result demonstrates the efficiency of the integration of GIS and remote sensing to build tools to assist for the environmental capacity management, for data analysis, and beyond, to identify and incorporate the influencing factors to the subjects of management or research.  

scholarly journals Mapping summer SUHI and its impact on the environment using GIS and Remote Sensing techniques: A case study on Municipality of Prishtina (Kosovo)

2021 ◽  
Vol 12 (3) ◽  
pp. 113-129
Author(s):  
Albert Berila ◽  
◽  
Florim Isufi ◽  
Keyword(s):  
Remote Sensing ◽  
Rural Areas ◽  
Urban Areas ◽  
Satellite Image ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Remote Sensing Techniques

Urban areas, compared to peripheral and rural areas, have higher temperatures which are caused by a series of unplanned activities that are undertaken by humans. Such a thing leads to the emergence of the Surface Urban Heat Island (SUHI) phenomenon. In this paper, summer SUHI is determined through the calculation of LST for the Municipality of Prishtina using GIS and Remote Sensing techniques. To make this calculation, the Landsat 8 satellite image with 0% cloud cover was used. From the calculations made it turns out that the pixels with the highest value of LST are found in those parts where the urban area appears, where there are numerous constructions with impermeable materials, as well as in those areas where there are bare surfaces. Whereas, the pixels with lower values of LST appear in those parts where there are vegetation and water bodies, making these areas fresher. The SUHI phenomenon makes the lives of citizens difficult, therefore, such information is very important for the leaders and urban planners of the city of Prishtina, so that they take a series of steps towards minimizing such an effect in order to the life of the citizens to be as healthy as possible.

Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping

2020 ◽  
Vol 38 (4A) ◽  
pp. 510-514
Author(s):  
Tay H. Shihab ◽  
Amjed N. Al-Hameedawi ◽  
Ammar M. Hamza
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Artificial Neural Network ◽  
Random Forest ◽  
Satellite Image ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Data Set ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

In this paper to make use of complementary potential in the mapping of LULC spatial data is acquired from LandSat 8 OLI sensor images are taken in 2019.  They have been rectified, enhanced and then classified according to Random forest (RF) and artificial neural network (ANN) methods. Optical remote sensing images have been used to get information on the status of LULC classification, and extraction details. The classification of both satellite image types is used to extract features and to analyse LULC of the study area. The results of the classification showed that the artificial neural network method outperforms the random forest method. The required image processing has been made for Optical Remote Sensing Data to be used in LULC mapping, include the geometric correction, Image Enhancements, The overall accuracy when using the ANN methods 0.91 and the kappa accuracy was found 0.89 for the training data set. While the overall accuracy and the kappa accuracy of the test dataset were found 0.89 and 0.87 respectively.

scholarly journals GIS and Remote Sensing Application in Water Management in Agriculture Field

2020 ◽  
Author(s):  
Sassi Mohamed Taher
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Resources ◽  
Land Surface ◽  
Remotely Sensed ◽  
Irrigated Agriculture ◽  
Accurate Information ◽  
Remotely Sensed Data ◽  
Gis And Remote Sensing ◽  
Practical Applications

This document is meant to demonstrate the potential uses of remote sensing in managing water resources for irrigated agriculture and to create awareness among potential users. Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere transfer processes can lead to a better understanding of the relationships between crop growth and water management. Remote sensing and GIS was used to map the agriculture area and for detect the change. This was very useful for mapping availability and need of water resources but the problem was concentrating in data collection and analysis because this kind of information and expertise are not available in all country in the world mainly in the developing and under developed country or third world country. However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing.

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

scholarly journals Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1430
Author(s):  
V. M. Fernández-Pacheco ◽  
C. A. López-Sánchez ◽  
E. Álvarez-Álvarez ◽  
M. J. Suárez López ◽  
L. García-Expósito ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Pollutants ◽  
Satellite Images ◽  
Satellite Image ◽  
Remote Sensing Image ◽  
Regional Studies ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat 5 Tm ◽  
Source Of Information

Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.

Determination of Drought Threshold for Agricultural Land-use using Satellite Image Analysis Techniques

2020 ◽  
Author(s):  
Jieun Kim ◽  
Jaehyung Yu ◽  
Sang Kee Seo ◽  
Jin-Hee Baek ◽  
Byung Chil Jeon
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Near Infrared ◽  
Agricultural Land ◽  
Irrigation Management ◽  
Satellite Image ◽  
Agricultural Drought ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Eastern Area

<p>The climate change causes major problems in natural disasters such as storms and droughts and has significant impacts on agricultural activities. Especially, global warming changed crops cultivated causing changes in agricultural land-use, and droughts along with land-use change accompanied serious problems in irrigation management. Moreover, it is very problematic to detect drought impacted areas with field survey and it burdens irrigation management. In South Korea, drought in 2012 occurred in western area while 2015 drought occurred in eastern area. The drought cycle in Korea is irregular but the drought frequency has shown an increasing pattern. Remote sensing approaches has been used as a solution to detect drought areas in agricultural land-use and many approaches has been introduced for drought monitoring. This study introduces remote sensing approaches to detect agricultural drought by calculation of local threshold associated with agricultural land-use. We used Landsat-8 satellite images for drought and non-drought years, and Vegetation Health Index(VHI) was calculated using red, near-infrared, and thermal-infrared bands. The comparative analysis of VHI values for the same agricultural land-use between drought year and non-drought year derived the threshold values for each type of land-use. The results showed very effective detection of drought impacted areas showing distinctive differences in VHI value distributions between drought and non-drought years.</p>

scholarly journals CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

CERNE ◽  
2017 ◽  
Vol 23 (4) ◽  
pp. 413-422 ◽  
Author(s):  
Eduarda Martiniano de Oliveira Silveira ◽  
José Márcio de Mello ◽  
Fausto Weimar Acerbi Júnior ◽  
Aliny Aparecida dos Reis ◽  
Kieran Daniel Withey ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Heterogeneity ◽  
Spatial Resolution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landscape Heterogeneity ◽  
Landsat 8 ◽  
Remotely Sensed Data ◽  
Object Based ◽  
Geostatistical Techniques

ABSTRACT Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index) was generated in an area of Brazilian amazon tropical forest (1,000 km²). We selected samples (1 x 1 km) from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property) and range (φ-the length scale of the spatial structures of objects) parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA) approaches.

scholarly journals Monitoring Sugarcane Growth Phases Based on Satellite Image Analysis (A Case Study in Indramayu and its Surrounding, West Java, Indonesia)

2019 ◽  
Vol 26 (3) ◽  
pp. 117
Author(s):  
Tri Muji Susantoro ◽  
Ketut Wikantika ◽  
Agung Budi Harto ◽  
Deni Suwardi
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Landsat 8 ◽  
Gas Field ◽  
Research Results ◽  
The Third ◽  
Third Phase ◽  
The Impact

This study is intended to examine the growing phases and the harvest of sugarcane crops. The growing phases is analyzed with remote sensing approaches. The remote sensing data employed is Landsat 8. The vegetation indices of Normalized Difference Vegetation Index (NDVI) and Enhanced Normalized Difference Vegetation Index (ENDVI) are employed to analyze the growing phases and the harvest of sugarcane crops. Field survey was conducted in March and August 2017. The research results shows that March is the peak of the third phase (Stem elonging phase or grand growth phase), the period from May to July is the fourth phase (maturing or ripening phase), and the period from August to October is the peak of harvest. In January, the sugarcane crops begin to grow and some sugarcane crops enter the third phase again. The research results also found the sugarcane plants that do not grow well near the oil and gas field. This condition is estimated due as the impact of hydrocarbon microseepage. The benefit of this research is to identify the sugarcane growth cycle and harvest. Having knowing this, it will be easier to plan the seed development and crops transport.

scholarly journals Role of Relief and Slope in Agricultural Land Use: A Case Study in Valapattanam River Basin in Kannur District, Kerala Using GIS and Remote Sensing

2019 ◽  
pp. 1-11
Author(s):  
P. Jyothirmayi ◽  
B. Sukumar
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Land Use ◽  
River Basin ◽  
Agricultural Land ◽  
Digital Data ◽  
Agricultural Land Use ◽  
Land Use Patterns ◽  
Gis And Remote Sensing ◽  
Erdas Imagine

The land is a delineable area of the earth's surface, encompassing all attributes of the biosphere immediately above or below this surface. Physical characteristics of the land determine agricultural land use. Among them, relief and slope play an important role. Aim of this study is to establish the relationship of relief and slope with agricultural land use in Valapattanam River basin in Kannur district using GIS and Remote sensing. The Survey of India Topographic maps in 1:50000 scale was used as a base map for delineating the basin. Contours were digitized and Digital Elevation Model (DEM) was generated. Agricultural land use map was prepared using satellite digital data by the digital image processing method using ERDAS IMAGINE image processing software. Agricultural land use map was intersected with the relief and slope classes in ArcGIS software. Areas were calculated and the trend of agricultural land use patterns was studied. The study revealed that there is a strong correlation between Agricultural land use and relief and slope in the Valapattanam River basin. Most of the area under paddy, coconut, mixed crops like banana and tapioca concentrated below 20 m height in the coastal plain and valley regions of the basin. Rubber mostly cultivated between 100 and 300 meters with slopes between 3 to 12 degrees. Agriculture is limited up to 18-degree slope and 300 m height. Areas of more than 300 m height are occupied mostly by forest.

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