scholarly journals Fenômenos geofísicos, captados a partir de sensores orbitais: estimativa de temperatura na superfície de Garanhuns-PE / Geophysical phenomena, obtained from orbital sensors: estimation of temperature on the surface in Garanhuns-PE

2015 ◽  
Vol 26 (45) ◽  
pp. 95
Author(s):  
Felippe Pessoa De Melo ◽  
Rosemeri Melo e Souza ◽  
Maria Betânia Moreira Amador
Keyword(s):  
Remote Sensing ◽  
Thermal Behavior ◽  
Working Conditions ◽  
Temporal Analysis ◽  
Mitigation Measures ◽  
Anthropogenic Effects ◽  
Thematic Mapping ◽  
Multi Temporal ◽  
Vector Base ◽  
Anthropogenic Processes

<p>A presente pesquisa teve como finalidade realizar uma análise multitemporal, da termodinâmica da superfície de Garanhuns-PE. Para tanto, utilizou-se as geotecnologias do Sensoriamento Remoto e Sistemas de Informações Geográficas (SIG). Juntamente com as imagens oriundas do satélite Landsat 5, sensor TM, banda 6, referentes aos anos de 1987, 2001 e 2010. Disponibilizadas pelo Instituto Nacional de Pesquisas Espaciais (INPE). A base vetorial, foi disponibilizada pelo Instituto Brasileiro de Geografia e Estatística (IBGE). Sendo assim, foi possível confeccionar um banco de dados georreferenciados e geocronológicos, o qual, viabilizou o mapeamento temático. Possibilitando, compreender o comportamento térmico dos alvos no transcorrer do tempo. Dados esses que são de suma importância para traçar medidas de mitigação dos efeitos antropogênicos na paisagem. Logo, ficou evidenciado que a maximização das médias termais no transcorrer das décadas, foram reciprocas aos processos antropogênicos</p><p> </p><p><strong>Palavras–chave:</strong> termodinâmica, geotecnologias, mapeamento temático, mitigação.</p><p> </p><p><strong>Abstract </strong></p><p>This research aimed to realize a multi-temporal analysis, the surface of thermodynamics in Garanhuns-PE. For this, it used the geotechnologies of Remote Sensing and Geographic Information Systems (GIS). Along with the images coming from the Landsat 5 satellite, TM sensor, band 6, referring to the years 1987, 2001 and 2010. Disclosed by the National Institute for Space Research (INPE). The vector base, was available by the Brazilian Institute of Geography and Statistics (IBGE). Thus, it was possible to confection a georeferenced database and geochronological, which, enabled the thematic mapping. Making it possible to understand the thermal behavior of the targets in the course of time. These data are of paramount importance to draw mitigation measures of the anthropogenic effects in the landscape. Soon, it was evident that the maximization of the hot medium in the course of decades, were reciprocal to anthropogenic processes.<strong> </strong></p><p><strong>Keywords</strong>: garbage collectors, recycling, working conditions, Association.</p><p> </p>

scholarly journals Remote Sensing in Predicting Development Patterns of Built-up Land

2021 ◽  
Vol 2 (2) ◽  
pp. 56-64
Author(s):  
Iqbal Eko Noviandi ◽  
Ramadhan Alvien Hanif ◽  
Hasanah Rahma Nur ◽  
Nandi
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Population Growth Rate ◽  
Landsat Imagery ◽  
Temporal Analysis ◽  
West Java ◽  
Development Patterns ◽  
Human Needs ◽  
Multi Temporal ◽  
Total Growth

Indonesia is a developing country whose construction and development are centered on the island of Java, especially in West Java Province. Sukabumi City is one of the areas in West Java. The development of urban areas is expanding due to various human needs to carry out the construction of buildings. Remote sensing that can be used to store developments with multi-temporal analysis with materials is Landsat imagery from 2001 to 2020. The method used is the Normalized Difference Built-up Index (NDBI). The purpose of this study is to map the development of the built-up land from year to year and predict the following years. The results of the research on the significant changes in built-up land occurred between 2013-2020, while from 2001 to 2013 there was not much change. Based on the research results, the total growth of built-up land was 1.539% per year with a population growth rate of 1.4% per year. The results of the analysis show that the area of ​​land built in Sukabumi City in 2028 is 186,7194 km2 or has increased by 21,2808 km2 since 2020.

scholarly journals Análise espaço-temporal das mudanças no uso e cobertura do solo no município de São Thomé das Letras / Spatio-temporal land use land and cover changes analysis in the São Thomé das Letras municipality

2015 ◽  
Vol 26 (45) ◽  
pp. 79
Author(s):  
Nayara Lage Silva ◽  
Bráulio Magalhães Fonseca
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Temporal Analysis ◽  
Minas Gerais ◽  
Time Range ◽  
Land Change ◽  
Land Change Modeler ◽  
Rupestrian Fields ◽  
Multi Temporal

<p>O mapeamento do uso e cobertura do solo por meio da utilização de dados de sensoriamento remoto e técnicas de processamento digital de imagens tem se difundindo globalmente por permitir uma análise espacial e dinâmica das tipologias de uso e cobertura. A mineração é uma das atividades transformadoras do meio que mais causa impactos aos ambientes naturais, mesmo que de maneira concentrada, devido ao fator de rigidez locacional da atividade. É uma atividade que demanda controle ambiental em todo processo para reduzir os impactos negativos e garantir o equilíbrio dos processos ambientais. Neste contexto o trabalho objetivou:  1 - realizar uma análise multitemporal da cobertura do solo no município de São Thomé das Letras, no estado de Minas Gerais; 2 - quantificar e espacializar as alterações no período determinado entre 1984 a 2011.  Buscou-se visualizar o comportamento da atividade de mineração desde seu início até os dias atuais, e consequentemente, observar a dinamicidade das mudanças ocorridas na cobertura do solo das outras classes mapeadas. Para o mapeamento do uso e cobertura do solo foi utilizado o programa SPRING/INPE e para a análise temporal/espacial de mudanças utilizou-se o modelo <em>Land Change Modeler</em> acoplado ao programa IDRISI. A partir da análise dos resultados foi possível quantificar e espacializar o avanço da mineração sob o campo rupestre/afloramento rochoso; a perda substancial da vegetação densa no intervalo do período analisado; o crescimento exponencial da ocupação urbana; e o surgimento da atividade reflorestamento.</p><p><strong>Palavras-chave:</strong> Análise multitemporal. Uso e Cobertura do Solo. <span lang="EN-US">Mineração. Sensoriamento Remoto.</span></p><p> </p><p><strong><span lang="EN-US">Abstract</span></strong></p><p><span lang="EN-US">The land use and land cover mapping using remote sensing data and techniques of digital image processing has been widely used by enabling a dynamic spatial analysis of  land use and land cover types. Mining is a human activity that transforms the landscape and is one of the most impactful for natural environments, even in a concentrated way, due to locational rigidity factor of activity. It is an activity that requires environmental control throughout the process to reduce the negative impacts and ensure a balance of environmental processes. In that context the study aimed to: 1 - conduct a multi-temporal analysis of land use and land cover in São Thomé das Letras municipality, in Minas Gerais State, Brazil; 2- quantify and map changes from 1984 to 2011 in the </span><span lang="EN-US">area studied. We attempted to visualize the behavior of mining activity from its inception to the present day, and therefore observe the dynamics of change in land use and land cover of other mapped classes. To map land use and land cover was used SPRING/INPE software and to analyze the changes used the Land Change Modeler model, coupled to the IDRISI software. From the analysis of the results was possible to quantify and spatialize the advancement of mining under the outcrop and Rupestrian Fields; occurred substantial loss of dense vegetation in the analyzed time range; the exponential growth of urban occupation; and the emergence of reforestation activity.</span></p><p> </p><p><strong><span lang="EN-US">Keywords: </span></strong><span lang="EN-US">Multi-temporal analysis. Land Use and Land Cover. Mining. Remote sensing.</span></p>

scholarly journals DISTRICT-WISE CHANGE ANALYSIS OF LAND USE-LAND COVER IN DELHI TERRITORY USING REMOTE SENSING & GIS

2017 ◽  
Vol 10 (2) ◽  
pp. 201-213
Author(s):  
Surya Prakash Pattanayak ◽  
Sumant Kumar Diwakar
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
High Growth ◽  
Temporal Analysis ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Multi Temporal

Digital change detection is the process that helps in determining the changes associated with Land use and Land cover properties with reference to geo-referenced multi-temporal remote sensing data. It helps in identifying change between two or more dates that is uncharacterized of normal variation. This work is an attempt to assess the district-wise changes in land use/land cover in Delhi, India. The study made use of LISS -III imageries of 2008 and 2012 year. The images were classified using Maximum Likelihood classification method. The output can be useful in many applications such as Land use changes, habitat fragmentation, rate of deforestation, urban sprawl and other cumulative changes through spatial and temporal analysis. The study shows that Delhi land cover from 2008 to 2012 a major rapid changes in the landscape as there is high growth in the fallow and built up area. Agriculture land and forest area has reduced marginally and water body is showing almost stagnant condition over time.

scholarly journals Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China

2019 ◽  
Vol 11 (18) ◽  
pp. 2088 ◽  
Author(s):  
Yuankang Xiong ◽  
Qingling Zhang ◽  
Xi Chen ◽  
Anming Bao ◽  
Jieyun Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Crop Production ◽  
Large Scale ◽  
General Pattern ◽  
Temporal Analysis ◽  
Classification And Regression Tree ◽  
Plastic Mulch ◽  
Temporal And Spatial Distribution ◽  
Plastic Mulching ◽  
Multi Temporal

Plastic mulching has been widely practiced in crop cultivation worldwide due to its potential to significantly increase crop production. However, it also has a great impact on the regional climate and ecological environment. More importantly, it often leads to unexpected soil pollution due to fine plastic residuals. Therefore, accurately and timely monitoring of the temporal and spatial distribution of plastic mulch practice in large areas is of great interest to assess its impacts. However, existing plastic-mulched farmland (PMF) detecting efforts are limited to either small areas with high-resolution images or coarse resolution images of large areas. In this study, we examined the potential of cloud computing and multi-temporal, multi-sensor satellite images for detecting PMF in large areas. We first built the plastic-mulched farmland mapping algorithm (PFMA) rules through analyzing its spectral, temporal, and auxiliary features in remote sensing imagery with the classification and regression tree (CART). We then applied the PFMA in the dry region of Xinjiang, China, where a water resource is very scarce and thus plastic mulch has been intensively used and its usage is expected to increase significantly in the near future. The experimental results demonstrated that the PFMA reached an overall accuracy of 92.2% with a producer’s accuracy of 97.6% and a user’s accuracy of 86.7%, and the F-score was 0.914 for the PMF class. We further monitored and analyzed the dynamics of plastic mulch practiced in Xinjiang by applying the PFMA to the years 2000, 2005, 2010, and 2015. The general pattern of plastic mulch usage dynamic in Xinjiang during the period from 2000 to 2015 was well captured by our multi-temporal analysis.

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