Journal articles: 'Erdas software'

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Gabzdyl, Martin. "Comparison of the tree species select classification methods from aerial photo." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 56, no. 5 (2008): 279–92. http://dx.doi.org/10.11118/actaun200856050279.

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This article describes a comparison of various programs for the automatic supervised classification used for identification of forest tree species representation from the aerial photographs. These programs were represented by American software Erdas Imagine 8.4, Czech products LuciaG 4.0 and TopoL DMT 6.014. The study displays a minor production forest area with proportion of four most frequently occurring tree species – spruce, larch, oak and ash in the research area of the forest region around Bystřice pod Hostýnem, the Czech Republic. For the reason of lower quality of spectrozonal photographs it was necessary to use some corrections; such as highlighting pen techniques, namely Kernel Processor Low-Frequency and High-Frequency filters, belonging to space operations. Photographs, modified in this way, served for a construction of individual training sets, which were consequently used within individual classification methods of directed classification in each comparative software. Self-classification took place at the level of a particular tree species. Classification accuracy was determined by comparison of results and reference data from the terrain research.The outcome is, that the best classification for oak and ash was in combination with TopoL program, classification according to gravity centre and combination of solation + insolation signature of the treetop parts with an aggressive shade.On the contrary, for spruce and larch was the best classification in combination with software Erdas Imagine, classification roles of intervals mahalanobis with combination of solation signature of the treetop parts, along these tree edges with an aggressive shade.

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Pal, Shreesty, S. K. Pandey, S. K. Sharma, and Reena Nair. "Acreage estimation of mango orchards in Jabalpur district of Madhya Pradesh using Sentinel-2 imagery." Ecology, Environment and Conservation 29, no. 02 (2023): 840–44. http://dx.doi.org/10.53550/eec.2023.v29i02.050.

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An approach was made to evaluate the area and perform spatial mapping of mango orchards using satellite image obtained from Sentinel-2 for Jabalpur district of Madhya Pradesh. The image was processed using ERDAS IMAGINE software. Supervised classification was performed for acreage estimation. An area of 1217 ha was found to be occupied by mango orchards, covering 0.24% of total area of Jabalpur district. The study has distinctly exhibited the adequacy of remote sensing imagery for identification and area estimation of mango orchards.

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Shrestha, Ila. "Spatially Distribution of Quercus semecarifolia in Rasuwa District Using GIS and RS." International Journal of Applied Sciences and Biotechnology 3, no. 4 (2015): 747–49. http://dx.doi.org/10.3126/ijasbt.v3i4.13980.

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The paper is based on the case study of Rasuwa district, is a land of geographical extremes, ranging from 600 m Betrabati river to 7234 m Langtang Lirung, the highest point in the northwest. The study was carried out on the detection of Quercus semecarifolia J.E.Smith using Remote-Sensing and Geographic Information System technique. SPOT Image and ERDAS Software have used for the image processing. The program has detected the different types of ecological parameters in tropical to alpine zone and specified the plant species in the study after ground truthing.Int J Appl Sci Biotechnol, Vol 3(4): 747-749

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Ahmed, Khansa A. "Determination of Irrigated Field Units in North Al-Jazeera Irrigation Project Using Remote Sensing Data." Tikrit Journal of Engineering Sciences 21, no. 2 (2013): 68–74. http://dx.doi.org/10.25130/tjes.21.2.09.

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This paper presents the role of digital image processing (DIP) for the investigation ofeffectively and actually irrigated areas through the signature of vegetative growth; Thetechniques of digital image processing for remotely sensed images including subsetting,enhancement, stacking, and vegetation index calculation determining the real irrigated areas inNorthAl-jazeera irrigation project. Landsat ETM+ (Enhanced Thematic Mapper) images wereobtained, which captured in 7/4/1999, 3/6/2000, 13/6/2001 and 19/4/2002. ERDAS IMAGINE9.1 software was used for the purposes of digital image processing and for NormalizedDifference Vegetation Index calculation (NDVI).The study showed the planted and not plantedfield units and the level of vegetative growth from NDVI values.

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البغدادي, عبد الصاحب, حسين الموسوي, and سراء العذاري. "Estimation of land cover areas in Najaf governorate using remote sensing techniques." Kufa Journal of Arts 1, no. 14 (2012): 47–68. http://dx.doi.org/10.36317/kaj/2012/v1.i14.6288.

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In order to find out the temporal classification of the Earth's appearance for the current period, the study dealt with the analytical approach for the purpose of analyzing and displaying satellite visuals through classification, analysis and automated interpretation through software for remote sensing techniques through the (ERDAS) program, as it is an integrated program that contains supervised classification and non-directed (Classification Unsupervised) and (Global Mapper) program for the purpose of cutting satellite visuals, which consist of four satellite visuals (Landsat 7) to field visits for the purpose of ensuring the accuracy of information and identifying training areas.Then, the study area was classified according to Anderson's classification

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Mohammed, Mejbel Salih, I. Hassoon Khalid, A. Almajeed A. Alabas Mohammed, and Saify Samir. "Produce feldspar mineral map using Spectral Angle Mapper (SAM) technique by hyperspectral image analysis." Global Journal of Engineering and Technology Advances 12, no. 2 (2022): 057–64. https://doi.org/10.5281/zenodo.7180035.

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The analysis of the hyperspectral image is an important method used in mineral detection. A map of the Feldspar mineral will produced for the study area, which lies to the west of the holy province of Karbala and limited in image that download from USGS website (type hyperspectral image from EO-1 satellite) , by using Spectral Angle Mapper (SAM) technique in the Erdas software, which is based on calculating the spectral reflection curve of any point on the image and the spectral reflection curve of feldspar mineral that is available in the spectral library of the software. For the purpose of verifying the results of the image analysis, ground truth ( field work ) was used by collecting 12 soil samples and finding the spectral curve for each sample by the spectral analysis device (ASD) and the result show the match between image and ground, where produced Feldspar mineral map.

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Mohammed Mejbel Salih, Khalid I. Hassoon, Khalid I. Hassoon, Mohammed A Almajeed A Alabas, and Samir Saify. "Produce feldspar mineral map using Spectral Angle Mapper (SAM) technique by hyperspectral image analysis." Global Journal of Engineering and Technology Advances 12, no. 2 (2022): 057–64. http://dx.doi.org/10.30574/gjeta.2022.12.2.0138.

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The analysis of the hyperspectral image is an important method used in mineral detection. A map of the Feldspar mineral will produced for the study area, which lies to the west of the holy province of Karbala and limited in image that download from USGS website (type hyperspectral image from EO-1 satellite) , by using Spectral Angle Mapper (SAM) technique in the Erdas software, which is based on calculating the spectral reflection curve of any point on the image and the spectral reflection curve of feldspar mineral that is available in the spectral library of the software. For the purpose of verifying the results of the image analysis, ground truth ( field work ) was used by collecting 12 soil samples and finding the spectral curve for each sample by the spectral analysis device (ASD) and the result show the match between image and ground, where produced Feldspar mineral map.

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FERNANDES, Márcia Rodrigues de Moura, Ronie Silva JUVANHOL, Daniel Henrique Breda BINOTI, et al. "APLICAÇÃO DE CLASSIFICADORES CONVENCIONAIS E REDE NEURAL ARTIFICIAL PARA MAPEAMENTO DE UMA IMAGEM VANT." Geosciences = Geociências 36, no. 4 (2018): 785–91. http://dx.doi.org/10.5016/geociencias.v36i4.10472.

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Este estudo teve por objetivo avaliar a eficiência de dois classificadores convencionais e uma rede neural MLP para o mapeamento do uso da terra a partir de uma imagem VANT. Foram definidas quatro classes na imagem para a classificação automática: eucalipto, pastagem, matocompetição e solo exposto. O algoritmo utilizado no simulador de redes neurais artificiais NeuroDic® 2.0 foi o resilient-propagation. Para aplicação dos classificadores convencionais MAXVER e ISODATA foi utilizado o software Erdas Imagine®11. A melhor classificação foi obtida pelo algoritmo MAXVER e o pior desempenho, com o algoritmo ISODATA. Ao final, pode-se concluir que a rede neural mostrou ser um paradigma eficiente para a classificação de imagens.

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Gupta, H. "Change detection of landcover/landuse type in Bhagwan Birsa Biological Park – Geospatial approach." Indian Journal of Forestry 28, no. 1 (2005): 101–4. http://dx.doi.org/10.54207/bsmps1000-2005-9o53t8.

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In the present study, the change monitoring of vegetation cover has been doen for the Bhagwan Birsa Biological Park of Ranchi over a period of 12 years. This involved the classification of land use using ERDAS IMAGINE software IRS LISS II data of 1991 and IRS LISS III data of 1996. The change in different class of forest in the Biological Park’s area in various periods has been analyzed critically for various reasons leading to it. The study demonstrates that Remote Sensed data can be useful for Forest/Wildlife Manager by providing them spatial information of their territory which can be analyzed in short time and at low cost, for various management purposes.

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Lumban-Gaol, Y. A., A. Murtiyoso, and B. H. Nugroho. "INVESTIGATIONS ON THE BUNDLE ADJUSTMENT RESULTS FROM SFM-BASED SOFTWARE FOR MAPPING PURPOSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 623–28. http://dx.doi.org/10.5194/isprs-archives-xlii-2-623-2018.

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Since its first inception, aerial photography has been used for topographic mapping. Large-scale aerial photography contributed to the creation of many of the topographic maps around the world. In Indonesia, a 2013 government directive on spatial management has re-stressed the need for topographic maps, with aerial photogrammetry providing the main method of acquisition. However, the large need to generate such maps is often limited by budgetary reasons. Today, SfM (Structure-from-Motion) offers quicker and less expensive solutions to this problem. However, considering the required precision for topographic missions, these solutions need to be assessed to see if they provide enough level of accuracy. In this paper, a popular SfM-based software Agisoft PhotoScan is used to perform bundle adjustment on a set of large-scale aerial images. The aim of the paper is to compare its bundle adjustment results with those generated by more classical photogrammetric software, namely Trimble Inpho and ERDAS IMAGINE. Furthermore, in order to provide more bundle adjustment statistics to be compared, the Damped Bundle Adjustment Toolbox (DBAT) was also used to reprocess the PhotoScan project. Results show that PhotoScan results are less stable than those generated by the two photogrammetric software programmes. This translates to lower accuracy, which may impact the final photogrammetric product.

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Li, Shi Wei, Ji Long Zhang, and Jian Sheng Yang. "Acquisitions of Vegetation Coverage and Cultivated Land Occupation Ratio of Taiyuan Valley Plain for Example Using CBERS-02B CCD Image." Advanced Materials Research 518-523 (May 2012): 5663–67. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5663.

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Vegetation covering situation is very important for the quality of air quality, soil and water conservation ability and soil forming in an area. By using the remote sensing image of Taiyuan Valley Plain, the application of Normalized Difference Vegetation Index (NDVI) and unsupervised classification, the vegetation coverage map which includes non-cultivated land disposition and cultivated land disposition was obtained using ERDAS Imagine software. To evaluate the accuracy of the results, 200 points were sampled randomly, the high spatial resolution remote sensing image from Google Earth was used as the reference. The overall classification accuracy is 82%, with the Kappa statistic of 0.81. By counting the totally pixel acreage, it was gotten that the vegetation coverage was 46% and the cultivated land coverage ratio was 31% in the study area.

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Kankara, I. A., and M. Ado. "GROUNDWATER POTENTIAL ASSESSMENT OF PART OF KAZAURE, NIGERIA USING ERDAS IMAGINE, PCI GEOMATICA, ARCMAP AND EXPERT CHOICE SOFTWARE." FUDMA JOURNAL OF SCIENCES 7, no. 2 (2023): 265–74. http://dx.doi.org/10.33003/fjs-2023-0702-1983.

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The possibility of utilizing groundwater as a source of water supply for public use is always attractive This research was focused to evaluate the groundwater potential of Kazaure area, Nigeria. The methodology adopted were mainly primary data in which six different thematic maps were integrated to generate the groundwater potential model (GWPM. It was produced by Weighted Linear Combination (WLC) where each class individual’s weight was multiplied by the map scores. In the research, Erdas Imagine 9.2, PCI Geomatica 10.0, ArcMap 9.3 and Expert Choice 10.0 in a GIS environment were used. Vertical electrical sounding (VES) was conducted using Ohmega resistivity meter with Schlumberger configuration. IP12win software was used in plotting the curves which revealed the resistivity, layers and thickness of the VES stations. Geological mapping was carried out using topographical map on a scale of 1:50,000Measurement of the depth to groundwater table in hand dug wells was carried out using dip meter. Water samples were collected and analyzed. Atomic Absorption Spectrometry (AAS) and X-Ray Fluorescence (XRF) were used in the analysis of water quality at the Multi-user laboratory, Chemistry Department, Ahmadu Bello University Zaria, Nigeria.

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Kouder, Noor Zubair. "Satellite image classification using proposed singular value decomposition method." Iraqi Journal of Physics (IJP) 13, no. 28 (2019): 52–67. http://dx.doi.org/10.30723/ijp.v13i28.243.

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In this work, satellite images for Razaza Lake and the surrounding areadistrict in Karbala province are classified for years 1990,1999 and2014 using two software programming (MATLAB 7.12 and ERDASimagine 2014). Proposed unsupervised and supervised method ofclassification using MATLAB software have been used; these aremean value and Singular Value Decomposition respectively. Whileunsupervised (K-Means) and supervised (Maximum likelihoodClassifier) method are utilized using ERDAS imagine, in order to getmost accurate results and then compare these results of each methodand calculate the changes that taken place in years 1999 and 2014;comparing with 1990. The results from classification indicated thatwater and hills are decreased, while vegetation, wet land and barrenland are increased for years 1999 and 2014; comparable with 1990.The classification accuracy was done by number of random pointschosen on the study area in the field work and geographical data thencompared with the classification results, the classification accuracy forthe proposed SVD method are 92.5%, 84.5% and 90% for years1990,1999,2014, respectivety, while the classification accuracies forunsupervised classification method based mean value are 92%, 87%and 91% for years 1990,1999,2014 respectivety.

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Ziboona, Abdulrazak T., Sajad Abdullah Abdul-Husseinlb, Muthanna M. Albayatic, and Student Fadhaa Turkey Dakheld. "Monitoring of Land Degradation in Alluvial Plain in Iraq by Using Geomatics Techniques." IOP Conference Series: Earth and Environmental Science 961, no. 1 (2022): 012023. http://dx.doi.org/10.1088/1755-1315/961/1/012023.

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Abstract Iraq faces a major environmental problem represented by severe deterioration, which threatens its food security. Many natural and human factors combine to make it, and it has dire environmental, economic, social and cultural consequences, most notably the loss of productive lands, the movement of sand dunes, severe sand and dust storms, and the resulting increase in air pollution. This study attempts to identify the development of the problem, analyze its causes and consequences, and propose a number of solutions to address it. In this article Remote Sensing techniques have been used to monitoring land degradation in ( Alluvial Plain ) of Iraq for the stage (1976 - 2021) using different sources of data such as satellite images (Landsat 1-5 MSS 1976, Landsat 5 1996 TM, Landsat8 2016 and sentinel 2 2021), also more than one software was used such as ENVI 5.3 and Erdas image 2015 to extract information from above images, Erdas imagine 2015 was use to sub set area of study, layer stack, merge resolution and classification stage, Arc GIS 10.7 use to make database and maps production), the article used supervise and unsupervised classification techniques to obtain the results, the article indicated that there is a big problem in the year 1976, this problem almost disappeared in the second station of work 1996, but it returned back after that through the results for the years 2016 and 2021. Finally, the article found a deterioration in the soil class during the stages from 2016 (988.547 Km2) to 2021(1342.398 Km2) and a decrease in the area of vegetation cover from (1931.596 Km2) in (2016) to (1632.695 Km2) in (2021).

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Dantas, Fabiane Regina da Cunha, Célia Campos Braga, Enio Pereira de Souza, and Saulo Tasso Araújo da Silva. "Determinação do albedo da superfície a partir de dados AVHRR/NOAA e T/LANDSAT-5." Revista Brasileira de Meteorologia 25, no. 1 (2010): 24–31. http://dx.doi.org/10.1590/s0102-77862010000100003.

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Este trabalho teve como objetivo estimar uma distribuição espacial do albedo da superfície para obter uma relação funcional entre o albedo dos sensores AVHRR/NOAA e TM/LANDSAT-5, sobre diferentes alvos nas proximidades de Quixeré-CE, nos anos de 2005 e 2006. As imagens foram processadas pelo software Erdas Image 8.7 utilizando o SEBAL (Surface Energy Balance Algorithm for Land). Os resultados mostraram diferenças na variabilidade espacial e temporal do albedo nos dois anos estudados, pois 2005 foi predominantemente seco enquanto que 2006 foi um ano chuvoso. A relação funcional entre os dados AVHRR e TM apresentou coeficiente de correlação (r) igual a 0,75 com erro padrão de 1,67%. Valores de albedo da superfície estimados pelo AVHRR e TM apresentaram respectivamente erros padrões de 2,44 e 3,45%, quando comparados com as observações do radiômetro CNR1.

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Uppin, Prateek, Lara Sabobeb, Engy Mikhai, and Tarig Ali. "Assessing the Evolution of Urban Areas, Vegetation, and Surface Temperature in Dubai Using Remote Sensing." E3S Web of Conferences 612 (2025): 02002. https://doi.org/10.1051/e3sconf/202561202002.

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This study uses remote sensing to assess the evolution of Dubai’s urban areas, vegetation, and surface temperature. With Dubai being one of the fastest-growing cities in the world, changes to the urban landscape occur rapidly, making it essential to analyze and plan for sustainable growth. The images were downloaded from the U.S. Geological Survey database, stacked, mosaiced on ERDAS, and clipped using ArcGIS software. The temporal assessment of urban growth and vegetation in Dubai was carried out using five Landsat images, i.e., 2000, 2013, 2016, 2019, and 2022, which provided valuable insights into the city’s environmental and developmental changes through analysis of urban areas’ density, NDVI, and LST from satellite images. The project results show an increase in urban areas over the years, changes in vegetation land, and temperature variations. This aims to improve and plan for future developments with environmental considerations.

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Turhal, Ümit Çiğdem, and Vahab Neccaroğlu. "DETERMINATION OF SURFACE ROUGHNESS PARAMETER THROUGH AERIAL IMAGES IN WIND POWER PLANT INSTALLATION." International Journal of Research -GRANTHAALAYAH 5, no. 12 (2020): 66–76. http://dx.doi.org/10.29121/granthaalayah.v5.i12.2017.474.

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The surface roughness parameter is an important parameter in the installation of a wind energy power plant and it varies depending on the dimensions and the distribution of the roughness elements on the land. Before the installation roughness maps indicate roughness of the surface has to be drawn. In today's applications, these maps are drawn approximately by WAsP software using the information obtained from the terrestrial observations belongs to experts. But this application is costly and time consuming and the assessment is based on limited land observations. In this study the surface roughness parameter is determined by digital image processing techniques from the digital images taken over aerial field. Thus it gives the opportunity to consider whole power plant surface into account with lower cost and time requirements over the traditional methods. Images used in the study are obtained from the Map General Command and MATLAB software platform is used. The study is based on the determination of the closure rates on the land by image segmentation method such as OTSU algorithm, fuzzy c-means and k-means algorithms. In order to evaluate the consistency of the results images are evaluated with ERDAS software. Obtained results showed the effectiveness of the study.

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Ümit, Çiğdem Turhal, and Neccaroğlu Vahab. "DETERMINATION OF SURFACE ROUGHNESS PARAMETER THROUGH AERIAL IMAGES IN WIND POWER PLANT INSTALLATION." International Journal of Research - Granthaalayah 5, no. 12 (2017): 66–76. https://doi.org/10.5281/zenodo.1133595.

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The surface roughness parameter is an important parameter in the installation of a wind energy power plant and it varies depending on the dimensions and the distribution of the roughness elements on the land. Before the installation roughness maps indicate roughness of the surface has to be drawn. In today's applications, these maps are drawn approximately by WAsP software using the information obtained from the terrestrial observations belongs to experts. But this application is costly and time consuming and the assessment is based on limited land observations. In this study the surface roughness parameter is determined by digital image processing techniques from the digital images taken over aerial field. Thus it gives the opportunity to consider whole power plant surface into account with lower cost and time requirements over the traditional methods. Images used in the study are obtained from the Map General Command and MATLAB software platform is used. The study is based on the determination of the closure rates on the land by image segmentation method such as OTSU algorithm, fuzzy c-means and k-means algorithms. In order to evaluate the consistency of the results images are evaluated with ERDAS software. Obtained results showed the effectiveness of the study.

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Souza, Cristiano Marcelo Pereira de, Maurício Santana Moreau, Ana Maria Souza Dos Santos Moreau, and Ednice De Oliveira Fontes. "Níveis de Degradação de Pastagens da Bacia do Rio Colônia-BA com Uso de Imagens LANDSAT 5TM (Degradation Level of Grassland of River Basin Colombia-BA Using Landsat 5 TM)." Revista Brasileira de Geografia Física 3, no. 3 (2011): 228. http://dx.doi.org/10.26848/rbgf.v3i3.232685.

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A carência de manejo adequado ao longo dos anos provocou alterações negativas na qualidade das pastagens da bacia hidrográfica do rio Colônia, caracterizada em maior parte como degradada sem capacidade de suporte das pastagens, isto traz como conseqüência a baixa produtividade, caracterizada pela redução do efetivo bovino na região e ainda aumento da erosão dos solos que provoca assoreamento e redução das áreas apropriadas para atividades agropecuárias, bem como outros fatores que agridem o geossistema da bacia. Assim este estudo objetivou analisar os níveis de degradação de pastagens, com elaboração de um mapa temático que represente tal aspecto para a bacia hidrográfica do Colônia. Foi analisado a partir de imagens de satélite Landsat 5TM, com aplicação técnicas de sensoriamento remoto nas imagens, principalmente correção atmosférica, por meio da transformação de números digitais em valores de reflectância, através do software ATCOR do Erdas Imagine 9.2, o que reduziu o efeito da atmosfera sobre os elementos da imagem e com realce das diferentes classes, e permitiu uma classificação mais acurada com distinção satisfatória entre os níveis de degradação.Palavras-chave: pastagens degradadas, sensoriamento remoto, classificação. Degradation Level of Grassland of River Basin Colombia-BA Using Landsat 5 TM ABSTRACT The lack of proper management over the years led to negative changes in pasture quality of Colonia’s river basin, as featured on most degraded, with soil without carrying capacity of pastures, this brings the consequence of low productivity, characterized by reduced cattle density in the region and increased soil erosion which causes siltation and reduction of suitable areas for agricultural activities, as well as other factors that affect the geosystem of the basin. So this study aimed to examine the levels of pasture degradation, including development of a thematic map that represents that aspect to the Colonia’s river basin. Was analyzed based on Landsat satellite images 5TM, with application techniques of remote sensing in images, mainly atmospheric correction, through the transformation of values of digital numbers reflectance, using the software ATCOR of Erdas Imagine 9.2, which reduced the effect of atmosphere on the elements of the image and highlight the different classes, and allowed a more accurate classification with satisfactory distinction between the levels of degradation. Keywords: degraded pastures, remote sensing, classification

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Chouhan, Bhanu Priya, and Monika Kannan. "Impacts of Urbanization on Land Use Pattern and Environment: A Case Study of Ajmer City, Rajasthan." Asian Review of Social Sciences 8, no. 1 (2019): 87–91. http://dx.doi.org/10.51983/arss-2019.8.1.1514.

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The world is undergoing the largest wave of urban growth in history. More than half of the world’s population now lives in towns and cities, and by 2030 this number will swell to about 5 billion. ‘Urbanization has the potential to usher in a new era of wellbeing, resource efficiency and economic growth. But due to increased population the pressure of demand also increases in urban areas’ (Drakakis-Smith, David, 1996). The loss of agricultural land to other land uses occasioned by urban growth is an issue of growing concern worldwide, particularly in the developing countries like India. This paper is an attempt to assess the impact of urbanization on land use and land cover patterns in Ajmer city. Recent trends indicate that the rural urban migration and religious significance of the place attracting thousands of tourists every year, have immensely contributed in the increasing population of city and is causing change in land use patterns. This accelerating urban sprawl has led to shrinking of the agricultural land and land holdings. Due to increased rate of urbanization, the agricultural areas have been transformed into residential and industrial areas (Retnaraj D,1994). There are several key factors which cause increase in population here such as Smart City Projects, potential for employment, higher education, more comfortable and quality housing, better health facilities, high living standard etc. Population pressure not only directly increases the demand for food, but also indirectly reduces its supply through building development, environmental degradation and marginalization of food production (Aldington T, 1997). Also, there are several issues which are associated with continuous increase in population i.e. land degradation, pollution, poverty, slums, unaffordable housing etc. Pollution, formulation of slums, transportation congestion, environmental hazards, land degradation and crime are some of the major impacts of urbanization on Ajmer city. This study involves mapping of land use patterns by analyzing data and satellite imagery taken at different time periods. The satellite images of year 2000 and 2017 are used. The change detection techniques are used with the help of Geographical Information System software like ERDAS and ArcGIS. The supervised classification of all the three satellite images is done by ERDAS software to demarcate and analyze land use change.

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Gunathilaka, M. D. K. L. "Modelling the Behavior of DVI and IPVI Vegetation Indices Using Multi-Temporal Remotely Sensed Data." International Journal of Environment, Engineering and Education 3, no. 1 (2021): 9–16. http://dx.doi.org/10.55151/ijeedu.v3i1.42.

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Remote sensing techniques are widely used to detect and analyze land cover changes due to their accuracy and cost-effectiveness. Among the various spectral indices derived from the satellite data Difference Vegetation Index (DVI) and Infrared Percentage Vegetation Index (IPVI) vegetation indices applied to model the behavior of the indices in the study of suburb ecosystem vegetation cover over twenty years. To achieve the aim of the study two objectives were formulated; detect Spatial-temporal variations in urban vegetation and how suitable the selected algorithms to study urban ecosystem vegetation. The study area is a rapidly developing area consists of several suburbs including Battaramulla, Malabe, and Kaduwela, Sri Lanka. The study used Landsat data and pre-processing, processing, geometric and atmospheric corrections were performed using ERDAS imagine mapping software and all the mappings were carried out via Arc GIS software. The results show Infrared Percentage Vegetation Index (IPVI) algorithm as the most suitable vegetation index to study suburb ecosystem vegetation than Difference Vegetation Index (DVI) in the study area. Therefore, the study recommends IPVI than DVI to study ecosystem vegetation in sub-urban areas.

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Beg, Ayad. "Assessment of land surface temperature variation over Rusafa side of Baghdad city, Iraq." MATEC Web of Conferences 162 (2018): 03032. http://dx.doi.org/10.1051/matecconf/201816203032.

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The current study is concerned with Rusafa side of Baghdad city, which extends on 362 square kilometres and is inhabited by 3738371 people. It suffers from population growth, which led to decline in municipal services and rising of land surface temperature (LST) during the summer season. The current study aims to assess the spatial and temporal variation of LST using different dated satellite images of Landsat 4, 7 and 8 at path 168 and raw 037 during July 16, 1989, April 25, 2000, April 26, 2006, and May 31, 2016. Eight analysis models which were built using ERDAS 2014 software are used to calculate the LST parameters; while the land use/land cover (LULC) types are classified using ENVI v.5.3 software. The maximum surface temperature recorded at barren lands are between 26 and 41°C, while at vegetation cover ranging from 25 to 34°C and an inverse correlation are recorded between LST and NDVI ranging from -0.5 to -0.81. The built-up area was increased by 23%, whereas open spaces and vegetation cover are decreased by 16% and 6% respectively all that consequently will make the environment of the study area prone to be warmer.

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S, Janarthanan, T. Ganesh Kumar, K. Uma, M. Arvindhan, Anandhan K, and C. Ramesh Kumar. "An Efficient Comparative Analysis of CNN-based Image Classification in the Jupyter Tool Using Multi-Stage Techniques." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 604–9. http://dx.doi.org/10.17762/ijritcc.v11i7s.7168.

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The main process of this image classification with a convolution neural network using deep learning model was performed in the programming language Python code in the Jupyter tool, mainly using the data set of IRS P-6 LISS IV from an Indian remote sensing satellite with a high resolution multi-spectral camera with around 5.8m from an 817 km altitude Delhi image. To classify the areas within the cropped image required to apply enhancement techniques, the image size was 1000 mb. To view this image file required high-end software for opening. For that, initially, ERDAS imaging software viewer was used for cropping into correct resolution pixels. based on that cropped image used for image classification with preprocessing for applying filters for enhancement. And with the convolution neural network model, required to train the sample images of the same pixels, was collected from the group of objects that were cropped. Then we needed to use image sample areas to train the model with learning rate and epoch rate to improve object detection accuracy using the Jupyter notebook tool with tensorflow and machine learning model produce the accuracy rate of 90.78%.

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Gunathilaka, M. D. K. L. "Modelling the Behavior of DVI and IPVI Vegetation Indices Using Multi-Temporal Remotely Sensed Data." International Journal of Environment, Engineering & Education 3, no. 1 (2021): 9–16. https://doi.org/10.5281/zenodo.4718906.

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Remote sensing techniques are widely used to detect and analyze land cover changes due to their accuracy and cost-effectiveness. Among the various spectral indices derived from the satellite data Difference Vegetation Index (DVI) and Infrared Percentage Vegetation Index (IPVI) vegetation indices applied to model the behavior of the indices in the study of suburb ecosystem vegetation cover over twenty years. To achieve the aim of the study two objectives were formulated; detect Spatial-temporal variations in urban vegetation and how suitable the selected algorithms to study urban ecosystem vegetation. The study area is a rapidly developing area consists of several suburbs including Battaramulla, Malabe, and Kaduwela, Sri Lanka. The study used Landsat data and pre-processing, processing, geometric and atmospheric corrections were performed using ERDAS imagine mapping software and all the mappings were carried out via Arc GIS software. The results show Infrared Percentage Vegetation Index (IPVI) algorithm as the most suitable vegetation index to study suburb ecosystem vegetation than Difference Vegetation Index (DVI) in the study area. Therefore, the study recommends IPVI than DVI to study ecosystem vegetation in sub-urban areas. 

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Morera_Beita, Carlos, and Luis Sandoval-Murillo. "Fragmentación y conectividad de la cobertura natural a nivel cantonal en Costa Rica durante los años 2000 y 2015." Revista Geográfica de América Central 4, no. 61E (2019): 37. http://dx.doi.org/10.15359/rgac.61-4.2.

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En esta investigación se plantea la formulación de un índice de fragmentación/conectividad que valora la condición de las coberturas naturales a nivel de cantones para Costa Rica, basado en la distribución espacial, considerando las variables: superficie del cantón, la superficie de cobertura natural, el número de fragmentos y distancia de vecindad entre los fragmentos de la cobertura natural, para los años 2000 y 2015. Se utilizaron las imágenes Landsat 7 para el año 2000 y Landsat 8 para el año 2015, donde se derivaron las categorías de uso de la tierra para cada año mediante clasificación supervisada con el software ERDAS y con el ArcMap10.5, se estimaron los índices biométricos usando la ecuación de Vargas (2008), la cual para su aplicación fue modificada. Dentro de los resultados se identificó los cantones que presentan mayor o menor fragmentación y conectividad de su cobertura natural durante el periodo de estudio.

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Tang, Jie, and Yao Ji. "Prediction of Soil Erosion Loss Mass in the Coal Mining Areas of Jilin Province Based on 3S Technology and BP Neural Network." Advanced Materials Research 225-226 (April 2011): 1246–49. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.1246.

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This paper partitioned five major coal mining areas respectively in central, southern and eastern Jilin Province for case study based on current situation of exploitation and distribution of coal resources through artificial neural network(ANN) and the 3S technology to gain soil erosion loss mass. On the basis of RUSLE equation, BP neural network is fused to gain the rainfall erosion index of higher precision than those of traditional method. By extracting of indices and raster calculation on the platform of ERDAS and ArcGIS software, we made predication of soil erosion loss of the coal mining areas. After verification, the precision of rainfall erosion index is high, and thus improved the predicting accuracy of soil erosion. Comparative analysis shows that the soil erosion in central section of Jilin Province has much lower intensity, and high degree erosion occurred in the east and south mostly.

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Xia, Xu. "Environmental Quality Assessment of Tibet Based on 3S." Applied Mechanics and Materials 295-298 (February 2013): 692–95. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.692.

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TM and HJ remote images were applied to land use interpretation of Tibet on the platform of Erdas software. The spatial distribution characteristics of Tibet land use were analyzed based on Landscape Ecology theory and GIS. The Ecological Index (EI) was calculated to access Tibetan eco-environmental quality. To validate the interpretation accuracy, GPS was used in field checking. The results show: (1) the farmland area of Tibet is 0.66%t of whole area. Woodland area is 164938.29 km2( 13.71%). Grassland is 548651.10 km2 (45.60%). Water area with 84392.81 km2 is 7.01%. Urban land is 3020.20 km2 ( 0.25%). Unutilized land is 460847.68 km2 (32.765); (2) High coverage grasslands are mainly distributed in some southern Tibetan counties, such as Xigaz, Nyemo, Lhongzi, Naidong, Yatung, Gyantse and Renbu (3) among 73 counties, there are 44 counties’ environment is moderate level, 18 counties’ environment is good level. Just one county’s EI is excellent level.

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Rodrigues, Guilherme Da Silva, Ulisses Rocha de Oliveira, and Karine Bastos Leal. "Variação das dunas no Balneário Barra do Chuí, extremo sul do Brasil, entre 2005-2018." Revista Brasileira de Geografia Física 14, no. 2 (2021): 522. http://dx.doi.org/10.26848/rbgf.v14.2.p522-536.

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As dunas costeiras são feições naturais formadas a partir das praias arenosas, devido a interação do vento, areia e vegetação. No entanto, a ação humana torna-se uma variável cada vez mais relevante em sua dinâmica, ocasionando problemas ambientais. O presente trabalho tem como objetivo quantificar e caracterizar, a partir de uma série temporal de imagens orbitais no intervalo entre 2005 e 2018, a mobilidade das dunas no Balneário Barra do Chuí – RS, especificamente a variação na base das dunas frontais. O intuito é verificar processos de erosão e sedimentação na orla do balneário, bem como a variação do limite do reverso do campo de dunas, onde se encontra a área urbana edificada do balneário. A metodologia foi empregada a partir de imagens orbitais adquiridas no software Google Earth Pro® e técnicas realizadas nos softwares ArcGIS 10.3.1® e ERDAS Imagine 2013®. A variação das linhas de costa analisadas foi obtida a partir do Método do Polígono de Mudança, por meio de uma linha de controle aplicada aos limites praia-duna frontal e reverso da duna. O Balneário Barra do Chuí, no período estudado, apresentou predomínio de taxas de erosão das dunas frontais, onde depósitos pleistocênicos estão sendo diretamente trabalhados pela ação marinha. O reverso das dunas apresentou tendência de avanço em relação à retroterra. Constatou-se que em alguns locais o transporte eólico de sedimentos está soterrando algumas residências. Palavras-chave: Limite praia-duna. Reverso das Dunas. Geotecnologias. Método do Polígono de Mudança. Foredune variation in the Barra do Chui coastal settlement, southern Brazil, between 2005-2018ABSTRACT Foredunes are natural features formed from sandy beaches, due to the interaction of wind, sand, and vegetation. However, human action becomes an increasingly relevant variable in its dynamics, causing environmental problems. The present work aims to quantify and characterize, from a time series of orbital images in the interval between 2005 and 2018, the dune mobility in the Barra do Chui coastal settlement, specifically the variation in the base of the frontal dunes, in order to check erosion and sedimentation at the edge of the resort, as well as the variation of the limit of the reverse of the dune field, where the built-up area of the resort is located. The methodology was used based on orbital images acquired in the Google Earth Pro® software and techniques performed in the ArcGIS 10.3.1® and ERDAS Imagine 2013® software. The variation of the coastlines analyzed was obtained from the Change Polygon Method, through a control line applied to the frontal and reverse dune beach-dune limits. The Barra do Chui coastal settlement, in the studied period, presented a predominance of erosion rates of the frontal dunes, where Pleistocene deposits are being directly worked by the marine action. The reverse side of the dunes showed an upward trend in relation to the retrograde, in fact, in some places, wind sediment transport has already been burying some homes. Keywords: Dune-Beach Limit. Dunes Reverse. Geotechnologies. Change Polygon Method

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Yuan, Debao, Ximin Cui, Yahui Qiu, Xueyun Gu, and Li Zhang. "Accuracy Analysis on the Automatic Registration of Multi-Source Remote Sensing Images Based on the Software of ERDAS Imagine." Advances in Remote Sensing 02, no. 02 (2013): 140–48. http://dx.doi.org/10.4236/ars.2013.22018.

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Journal, Baghdad Science. "Geomorphological Mapping of Razzaza–Habbaria Area using Remote Sensing Techniques." Baghdad Science Journal 13, no. 1 (2018): 155–66. http://dx.doi.org/10.21123/bsj.13.1.155-166.

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Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razzaza Lake shows the different geomorphologic units and the land use maps that were delineated from Landsat ETM+ Image. Digital Image unsupervised classification was adopted to delineate the different classes by applying ERDAS 8.4 software. According to this classification five classes were selected and delineated in different colors.

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Dr. Parveen. "An Analysis of crop rotation practice by the farmers of North-western Haryana: Using geospatial technology." Universal Research Reports 11, no. 4 (2024): 57–63. http://dx.doi.org/10.36676/urr.v11.i4.1310.

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Crop rotation studies that include comprehensive temporal and spatial data are essential for sustainable agricultural management, crop monitoring, and addressing food security concerns. Insufficient agricultural information is a significant barrier to effective policy-making and research aimed at ensuring food security. A study was carried out in northwestern Haryana to map crop rotation using satellite-based remote sensing data, combined with other spatial and non-spatial collateral data. The main data sources utilized were Landsat-5 and Sentinel-2, which were analyzed using digital image processing techniques in ERDAS Imagine and ArcGIS software. An interactive supervised classification method was applied to evaluate the data. Crop rotation maps were created for the periods 1990-1991 and 2021-2022. The findings indicated that the cotton-mustard cropping area comprised 19.85% of the total geographical area in 1990-1991, while the rice-wheat cropping area accounted for 31.46% in 2021-2022. This indicates that cotton-mustard was the predominant crop rotation in 1990-1991, whereas rice-wheat became the primary

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Appanna, B., and Y. Sujatha. "Land use and Land cover analysis of Tungabhadra River Basin, Kurnool District of Andhra Pradesh using remote sensing and GIS." Indian Journal of Spatial Science 15(2), Summer (2024): 43–48. https://doi.org/10.5281/zenodo.12507596.

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The present study aims to determine the land use/land cover features of the Tungabhadra River basin of Kurnool District, Andhra Pradesh, for 2023 using remote sensing and GIS Technologies. The study used the Survey of India topographic maps 57E/1 to 57E/16 and 57I/1 to 57I/5 and the remote sensing data of LISS III, 2023 processing in Arc GIS 10.3 and ERDAS software. Understanding existing land use and land cover in a region is crucial for maximizing land efficiency. It allows informed decision-making in urban planning, agriculture, conservation, and resource management. Accurate knowledge empowers stakeholders to optimize land utilization for sustainable development. The analysis reveals that the study area contains components such as Agricultural land, Built- up areas, Forests, Wasteland, Water bodies, and Transportation. Most of the study area is occupied by agricultural land 77.03%, followed by Wastelands 10.68%, Forest land 4.58%, Water bodies 3.90%, Built-up land 3.53%, and Transportation 0.28%.

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Voitechovič, Mažena, and Birutė Ruzgienė. "A COMPARISON ANALYSIS OF DIFFERENT PHOTOGRAMMETRIC SOFTCOPIES FOR GEODATA PRODUCTION." Geodesy and cartography 40, no. 4 (2014): 175–80. http://dx.doi.org/10.3846/20296991.2014.987459.

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Up-to-date mapping technologies for geodata production are widely applicable in Remote Sensing and Photogrammetry Communities. Therefore, the education in Remote Sensing and photogrammetric methods becomes very important using different image processing software for the terrain mapping purposes, spatial data modelling, etc. The use of new methods, technologies and professional widely-known systems demonstrates the desire to increase mapping capability. Despite that, digital didactics photogrammetric systems might be used (particularly in education process) simultaneously, this way getting more efficiency results. The objective of the research is to analyse some aspects of the use of digital photogrammetric softcopies, applied for terrain mapping: professional IMAGE ERDAS with LPS, LISA and Didactics Digital Photogrammetric Systems (DDPS). The experimental investigations lead to contiguity of this different software in consideration of the following criteria: accuracy, flexibility and time. The digital terrain models and orthophoto maps, created using two technologies, are almost the same due to time required for separate image processing steps. However, full workflow on DDPS requires about 2.5 times less time than on LPS. The photogrammetric measurement results demonstrate that there are some differences in accuracy due to stereoscopic measurements. When processing the images, the defined value of accuracy estimators meets the requirements for topographic mapping; however, DEM needs a separate study.

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Oliveira, Jose Diorgenes Alves, Biancca Correia De Medeiros, Jhon Lennon Bezerra Da Silva, et al. "Space-temporal evaluation of biophysical parameters in the High Ipanema watershed by remote sensing." Journal of Hyperspectral Remote Sensing 7, no. 6 (2018): 357. http://dx.doi.org/10.29150/jhrs.v7.6.p357-366.

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The High Ipanema watershed is located in a semiarid region and because of this, becomes more vulnerable and susceptible to the effects of environmental changes and the degradation process, it has serious economic and socio-environmental implications. In recent years with the advancement of remote sensing based on satellite imagery or other platforms, it has become possible to monitor different and large areas of the various biomes in the world. The objective of this study was to identify changes in the vegetation cover conditions in the Alto Ipanema watershed, using spectral analyzes of Landsat-8 OLI / TIRS satellite images, using remote sensing techniques. Landsat-8 OLI / TIRS satellite images were obtained from the United States Geological Survey – USGS, on 10/12/2013, 14/01/2015 and 12/08/2016, where they were processed from ERDAS IMAGINE® Software, version 9.1. The thematic maps of biophysical parameters were processed by ArcGis® 10.2.2 Software. With the biophysical parameters analyzed, it was found that the northwest portion of the watershed presents a considerable area of exposed soils with indication of a high degree of susceptibility to degradation and that the biophysical parameters evaluated by the SEBAL algorithm are efficient in understanding the dynamics of spatial and temporal areas of semiarid environments.

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Keniya, B. J., V. J. Zinzala, R. R. Sisodiya, and A. V. Patel. "Assessment of Soil Nutrient Dynamics in Sugarcane Cultivation Areas of Navsari District: Implications for Sustainable Agriculture." Asian Journal of Soil Science and Plant Nutrition 10, no. 3 (2024): 519–32. http://dx.doi.org/10.9734/ajsspn/2024/v10i3364.

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Sentinel 2 satellite data from the year 2021 were acquired from the Copernicus site to identify the sugarcane producing area in the Navsari district. Hybrid classification approach i.e., supervised and unsupervised with ground truth data were applied using ERDAS IMAGINE software. After image classification, 2.5 km x 2.5 km grid was prepared in Q-GIS software which along with classified sugarcane area were overlapped for site identification. Then, random soil surface and sub-surface samples were collected with reference from grid of intensive sugarcane growing area. The available nitrogen, phosphorus, potassium, DTPA-Fe, DTPA-Mn, DTPA-Zn and DTPA-Cu of surface soil ranged from 132.19 to 428.65 kg ha-1, 18.48 to 107.32 kg ha-1, 202.34 to 359.39 kg ha-1, 0.97 to 29.90 ppm, 1.10 to 29.63 ppm, 0.20 to 6.89 ppm and 1.02 to 11.69 ppm while sub-surface soil varied from 101.91 to 388.62 kg ha-1, 10.16 to 99.57 kg ha-1, 138.66 to 323.35 kg ha-1, 0.35 to 24.97 ppm, 0.20 to 29.08 ppm, 0.05 to 3.64 ppm and 0.21 to 8.07 ppm respectively. The soils of sugarcane growing area of Navsari district showed low OC, available N and S while other nutrients were normal in range for sugarcane cultivation.

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Agone, Vikram. "Change Detection of Land Use/Land Cover by Using Remote Sensing and GIS." Journal of Remote Sensing and Earth Science 1, no. 1 (2015): 15–20. https://doi.org/10.5281/zenodo.11942573.

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Land use and land cover are important components in understanding the interactions of human activities with the environment and for land evaluation purposes; thus, it is necessary to be able to simulate changes. The present paper attempted to detect the detection of land use during 1989–2015 on the basis of remote sensing data and GIS software with the help of ArcGIS 10.2, ERDAS 2011 software, and remote sensing data. The base map of land use and land cover was prepared with the help of Landsat 5TM in 1989 and Landsat 8 in 2015. It is found that considerable changes in land use and land cover have been detected from 1989 to 2015 on the Landsat imagery. The present study examines land use in a micro-scale natural region of a mesowatershed like the Waghur Basin. Among the various parameters of the land uses, the following five classes have been considered in this study:. Land under agriculture, land under forest, land under built-up area, bare land, and land under water bodies. The results of the work show a rapid growth in water bodies, settlements, and agricultural land while a rapid decrease in forest and bare land between 1989 and 2015. 

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Francisco, Paulo Roberto Megna, Iede de Brito Chaves, Lucia Helena Garofalo Chaves, Ziany Neiva Brandão, Eduardo Rodrigues Viana de Lima, and Bernardo Barbosa da Silva. "Mapeamento da Vulnerabilidade das Terras da Bacia Hidrográfica do Rio Taperoá (Mapping the Vulnerability of the Land of River Basin Taperoá)." Revista Brasileira de Geografia Física 6, no. 2 (2013): 271–86. http://dx.doi.org/10.26848/rbgf.v6.2.p271-286.

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A inadequação do uso e do manejo das terras tem degradado os solos, acelerando o impacto das atividades humanas sobre o meio ambiente, particularmente nas regiões semiáridas do Nordeste brasileiro. Partindo do pressuposto de que a erosão do solo é o efeito mais marcante da degradação ambiental, e que a cobertura vegetal e a declividade do terreno são os fatores determinantes do processo erosivo, este trabalho teve como objetivo mapear a vulnerabilidade das terras da bacia hidrográfica do rio Taperoá através do índice de vegetação por diferença normalizada e do índice de biomassa da vegetação lenhosa utilizando imagens de satélite. Foi utilizado o software ERDAS para gerar a imagem-índice e o SPRING para gerar o mapa de vegetação, declividade e vulnerabilidade. Concluiu-se que a boa correlação entre os índices possibilitou o mapeamento da vegetação de caatinga. O cruzamento do mapa de declividade e de vegetação permitiu diagnosticar a vulnerabilidade da bacia. Constata-se que 28,66% da área total da bacia estão com maior vulnerabilidade. Estima-se que 61,98% da área da bacia estejam em processo avançado de degradação. A B S T R A C T Inadequate use and land management has degraded soils, accelerating the impact of human activities on the environment, particularly in the semiarid regions of northeastern Brazil. Assuming that soil erosion is the most striking effect of environmental degradation, and the vegetation cover and land slope factors are important determinants of the erosion process, this study aimed to map the vulnerability of watershed land river Taperoá. It was used vegetation index (NDVI) satellite images to estimate the degree of vegetation cover, expressed by the biomass index of woody vegetation (IBVL) and SRTM database to generate the slope map. With ERDAS software was generated the index image and with SPRING program maps of vegetation, slope and vulnerability. The results show that the simplified model for estimating risk of erosion (vegetation and slope) presents results consistent with field observations and studies that link the main area mapped as high and very high vulnerability, such as area very severe and severe degree desertification Cariri Paraiba. In general, due to the occurrence of flat and smooth relief in 87% of the area, the basin has a low and very low degree of vulnerability in 61.1% of its land. Keywords: Semiarid, vegetation index, remote sensing

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Arif Maullana, Danang, and Arief Darmawan. "Perubahan Penutupan Lahan Di Taman Nasional Way Kambas." Jurnal Sylva Lestari 2, no. 1 (2014): 87. http://dx.doi.org/10.23960/jsl1287-94.

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Land cover changes in Way Kambas National Park (TNWK) changes rapidly. Data on changes in land cover in 1996, 2002 and 2010 in TNWKanalyzed by using remote sensing and Geographic Information Systems (GIS). Analysis also includes changes in land cover in each zoning park management.The research was conducted in June-September 2012 at the Way Kambas National Park. Data collected in the form of Landsat ETM + and TM (1996, 2002, and 2010), field verification points, and attribute data in the form of zoning. Spatial data processed with ERDAS imagine software version 8.5 and Arc View version 3.3, while the data is processed by descriptive attributes and analyzed qualitatively. Land cover types in the Way Kambas National Park is divided into 9 classes of forest, wetland forests, wetlands, shrubs, reeds, open land, water bodies, lading, and no data (cloud and cloud shadow). The largest land cover on the forest zone and the intensive use of coarse grass while special conservation zone and the core zone has the largest forest cover in the form of forest. Keyword : GIS, land cover, Way Kambas National Park

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Jahan, Zartab, Faiza Sarwar, Isma Younes, Rakhshanda Sadaf, and Adeel Ahmad. "Assessment of Smog Pattern and its Effects on Visibility in Lahore Using Remote Sensing and GIS." International Journal of Economic and Environmental Geology 10, no. 2 (2019): 55–59. http://dx.doi.org/10.46660/ijeeg.vol10.iss2.2019.263.

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In recent times, many parts of the world are experiencing drastic levels of air pollution, which includessmog, the mixture of fog and smoke, polluted air formed by human activities like burning of coal, excessive use ofvehicles and many others. During November 2016, Lahore city also experienced the smog due to increased level of airpollutants. In earlier studies, very limited research work has been done related to smog, therefore, this research is aimedto study the pattern of smog in Lahore and its impact on visibility through remote sensing and GIS. Satellite images ofMODIS and Landsat OLI, of November, 2016 is used to study the pattern of smog, whereas the visibility data wasacquired from Pakistan Meteorological Department (PMD). For the processing and analysis of data ERDAS IMAGINE14 and ArcGIS 10.1 software were used. The findings of this research reveal that the dense smog cover on 2nd, 3rd,and 4th November 2016 leads to the considerable reduction in visibility. As on 2nd November’16, it was only 111.6meters (m) while during bright days it was recorded more than 300 m or 400 m.

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Jahan, Zartab, Faiza Sarwar, Isma Younes, Rakhshanda Sadaf, and Adeel Ahmad. "Assessment of Smog Pattern and its Effects on Visibility in Lahore Using Remote Sensing and GIS." International Journal of Economic and Environmental Geology 10, no. 2 (2019): 55–59. http://dx.doi.org/10.46660/ojs.v10i2.263.

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In recent times, many parts of the world are experiencing drastic levels of air pollution, which includessmog, the mixture of fog and smoke, polluted air formed by human activities like burning of coal, excessive use ofvehicles and many others. During November 2016, Lahore city also experienced the smog due to increased level of airpollutants. In earlier studies, very limited research work has been done related to smog, therefore, this research is aimedto study the pattern of smog in Lahore and its impact on visibility through remote sensing and GIS. Satellite images ofMODIS and Landsat OLI, of November, 2016 is used to study the pattern of smog, whereas the visibility data wasacquired from Pakistan Meteorological Department (PMD). For the processing and analysis of data ERDAS IMAGINE14 and ArcGIS 10.1 software were used. The findings of this research reveal that the dense smog cover on 2nd, 3rd,and 4th November 2016 leads to the considerable reduction in visibility. As on 2nd November’16, it was only 111.6meters (m) while during bright days it was recorded more than 300 m or 400 m.

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47

Araujo, Taciana Lima, and Frederico Tejo Di Pace. "Valores Instantâneos da Temperatura da Superfície Terrestre na Cidade de Maceió-AL Utilizando Imagens do Satélite TM/Landsat 5." Revista Brasileira de Geografia Física 2, no. 3 (2010): 104. http://dx.doi.org/10.26848/rbgf.v3i2.232658.

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O trabalho proposto estima, mediante dados de imagens multiespectrais do Landsat 5-TM, a temperatura da superfície terrestre da cidade de Maceió, relacionando-os com a malha urbana. Maceió nos últimos 30 anos teve seu crescimento areal intensificado, o que resulta na substituição de áreas verdes por uma zona urbana edificada, alterando o relevo, impermeabilizando o solo, e em consequência, a diminuição da participação do fluxo de calor no solo do balanço de energia na superfície e o aumento do fluxo de calor sensível, responsável pela sensação térmica sentida. Portanto, mudanças locais causadas por edificações e ocupações inadequadas provocaram alterações no conforto urbano. As imagens utilizadas são compostas por sete bandas espectrais, referentes aos dias 11 de junho de 1990, 21 de setembro de 1998 e 03 de setembro de 2003. Os cálculos foram realizados com a utilização do software ERDAS 8.5. A temperatura da superfície terrestre estimada foi maior para o ano de 1998 sendo de 26,96°C seu valor médio e para os anos de 1990 e 2003 foi praticamente a mesma, sendo de 24,19°C e 24,90°C, respectivamente.

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Mohammed, D., M. M. Maina, I. Audu, I. Y. Tudun Wada, and N. K. Nasir. "Remote sensing techniques in mapping spatial variability of salinity in Kano River Irrigation Project (KRIP), Nigeria." Nigerian Journal of Technology 40, no. 4 (2021): 732–39. http://dx.doi.org/10.4314/njt.v40i4.20.

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   Salinity has become a major issue in most large scale irrigation schemes, assessing the extent of the spread has become daunting and laborious. Remote sensing techniques were used to map salinity and develop models for extracting and identifying salinity in soils. Sentinel-2B optical imaging satellite with 13 spectral bands and 10 m spatial resolution was used. SNAP Desktop, ERDAS Imagine, and ArcGIS 10.6 software were used as the main GIS packages for building models and running functions such as input, output, analysis, and processing. Stepwise Multiple Linear Regression (MLR) techniques were carried out for the assessment of the spatial distribution of ECe and to predict salinity level at different locations of the Kano River Irrigation Project (KRIP). Four models were developed, however, due to the lower Variance Inflation Factor (VIF), model 2 which is a combination of salinity Index and band 3 (Green band) was used in delineating the spatial extent of the salinity. Close monitoring of the salt development and application of reversal measures were recommended.  

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Hanjagi, Aishwarya S., Shahnin Irfan, P. Surendra, and Ashok D. Hanjagi. "Land use Land cover changes in Mandya taluk using GIS and remote sensing." Geo Eye 8, no. 1 (2019): 1–4. http://dx.doi.org/10.53989/bu.ge.v8i1.1.

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Land and water are the most keys and pivotal factors for the progress of any region or locality. Land use and land cover transformation have turned out to be a dynamic factor in recent strategies for dealing with natural resources and monitoring environmental changes. The research aimed to analyze and monitor land use/land cover changes in Mandya taluk of Karnataka by using an integrated approach of remote sensing and geographical information system The Mandy taluk satellite data were collected for the years of 1995, 2005, and 2018 and were classified by using a maximum likelihood algorithm, nonparametric parallelepiped classifier in ERDAS Imagine software. Multi-spectral pixels of the study area were classified and mapped into four broad land cover classes i.e., Waterbody, Open space, Agriculture area, and urban or built-up land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. Significant shifts from some classes to others were also observed. The accuracy assessment was computed using user, producer, overall, and Kappa (Khat/K) statistics. Keywords: Land use/Land Cover, GIS, and remote sensing

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Mayi, Yomto, Joanica Delicia Jyrwa, and Santanu K. Patnaik. "Monitoring of Land use/ land cover changes of Daying Ering Wildlife Sanctuary, Arunachal Pradesh, India, using Remote Sensing and Geographic Information System." Journal of Applied and Natural Science 15, no. 2 (2023): 713–19. http://dx.doi.org/10.31018/jans.v15i2.4602.

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The advent of geospatial technology plays a vital role in identifying environmental problems and provides solutions to good decision-making. In India, much of wildlife research and management occurs in protected areas. Therefore, it is imperative to study the landscape dynamics of such areas. The present study aimed to investigate the spatio-temporal of land use/land cover (LULC) changes that occurred in Daying Ering wildlife sanctuary, East Siang District, Arunachal Pradesh, for 10 years (2012-2022). The LULC were categorized into vegetation, water body, marsh, riverbed, and grassland. Supervised classification was used with the maximum likelihood algorithm in ERDAS 15.0 software. Post-assessment of the study area images revealed that there had been some major land changes whereby grassland has decreased by 25.10 %, an increase in the river bed (16.73%), and an increase in the water body (16.16%). The findings of the present study call for attention from researchers, environmentalists, policymakers, government officials and local villagers to study the consequences of LULC changes on vulnerable species and form mitigation/management measures accordingly.

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Journal articles on the topic 'Erdas software'

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