scholarly journals Spatial analysis of heat sources in Pará state - Brazil

2020 ◽  
Vol 9 (11) ◽  
pp. e66491110387
Author(s):  
Raynon Joel Monteiro Alves ◽  
Wanderson Gonçalves Gonçalves ◽  
Janaina Pinheiro Gonçalves ◽  
Stefani Silva Raulino ◽  
Frank Bruno Baima de Sousa
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Forest Fires ◽  
Interpolation Method ◽  
Descriptive Statistics ◽  
Heat Sources ◽  
Density Map ◽  
Areas Of Concern ◽  
The One ◽  
Actual Configuration

The state of Pará has experienced a high occurrence of forest fires, which were strongly influenced by the El Niño phenomenon in 2015-2016. This study aims to analyze the conditions of heat sources in Pará, using the 2016 monthly bulletins provided by the Environment and Sustainability Secretariat. This data was analyzed through descriptive statistics. The IDW interpolation method was used to construct the density map, displaying the primary areas of concern. The results showed that the greatest detections were during the Amazonian summer, occurring during the second half of the year. Specifically, the municipalities of the Southwestern and Southeastern Para meso-regions were mainly the ones affected. Fire is used as a primary economic tool. The Southwest was the one region that presented the highest densities of hotspots. Although the results do not indicate the actual configuration of the events, because of the technical limitations of remote sensing, the information obtained in this study communicates ideas concerning prevention and action in the most affected areas. In loco studies are needed to determine precisely the causes of these occurrences.

scholarly journals TEMPORARY SERIES OF HEAT SOURCES IN MESOREGIONS OF PARAÍBA, BRAZIL

FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 181
Author(s):  
Danilo Brito Novais ◽  
Patrícia Carneiro Souto ◽  
Jacob Silva Souto ◽  
José Augusto Da Silva Santana
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Fire Management ◽  
The State ◽  
Heat Sources ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Awareness Programs ◽  
The One ◽  
And Control

The management of fire is a set of decisions directed to practices of prevention, verification and control of this agent that can modify the landscape. Remote sensing helps in understanding the phenomena that occur on the earth's surface. This work had the objective of analyzing the occurrences of heat sources recorded by satellites in the State of Paraíba (2000 – 2015). The occurrences of heat sources were selected by months of the year making it possible to visualize the frequency of heat sources in different locations. It is observable that the years with the highest number of heat sources in Paraíba were 2003, 2004 and 2009. In the six municipalities studied, 3.712 heat sources were recorded, with Cajazeiras municipality having the highest number of records (2.253 occurrences). It is concluded that the highest occurrence of heat sources inthe studied regions runs from September to December, where the Sertão Paraibano mesoregion was the one with the highest incidence of heat sources, being the most affected by fire. It is recommended, thus,the implementation of awareness programs that inform the citizens of rural and urban areas about the importance of adequate fire management in order to reduce heat sources in the region.

scholarly journals SENSORIAMENTO REMOTO NA DETECÇÃO E ANÁLISE DE FOCOS DE CALOR NA BACIA HIDROGRÁFICA DO RIO MUNIM

2020 ◽  
Vol 18 (01) ◽  
pp. 373-388
Author(s):  
Rennato Oliveira da Silva ◽  
Rhuan Oliveira da Silva ◽  
Thais de Carvalho Araújo ◽  
Carlos Augusto Alves Cardoso Silva ◽  
Ana Karla da Silva Oliveira ◽  
...  
Keyword(s):  
Public Health ◽  
Remote Sensing ◽  
Temporal Analysis ◽  
Heat Sources ◽  
Soil Monitoring ◽  
Hydrographic Basin ◽  
Palabras Clave ◽  
The One ◽  
Del Rio ◽  
Basin Area

Os incêndios são a causa da devastação de milhares de hectares de ecossistemas do planeta, gerando impactos à saúde pública, prejuízos econômicos e ambientais. O presente estudo tem como objetivo realizar uma análise temporal dos focos de calor detectados em diferentes usos e cobertura da terra mapeados entre 2008 e 2018 na Bacia Hidrográfica do Rio Munim (BHRM), leste Maranhense. Os dados utilizados no trabalho foram obtidos junto à plataforma digital do Instituto Nacional de Pesquisas Espaciais (INPE), sendo provenientes dos satélites TERRA, AQUA, GOES, NOAA, MSG-02 e ERS-2. Constatou-se um total de 74.752 ocorrências de focos de incêndios na área da bacia entre os anos de 2008 a 2018, tendo como destaque o mês de novembro o mais crítico registrando 30,33% do total de focos, seguido pelo mês de outubro com 23,03%, período em que praticamente não existe precipitação na região. Verificou-se que o ano de 2015 foi o que apresentou o maior índice de focos com 14.025 ocorrências e que o ano de 2011 foi o menos expressivo, com 2.116 ocorrências. Palavras-chave: Geotecnologias. Uso do solo. Monitoramento.   REMOTE SENSING IN THE DETECTION AND ANALYSIS OF HEAT FOCUSES IN THE HYDROGRAPHIC BASIN OF RIO MUNIM ABSTRACT  Fires are the cause of the devastation of thousands of hectares of ecosystems on the planet, generating impacts on public health, economic and environmental losses. The present study aims to perform a temporal analysis of the heat sources detected in different uses and land cover mapped between 2008 and 2018 in the hydrographic basin of the Munim River, eastern Maranhense. The data used in the study were obtained from the digital platform of the National Institute for Space Research (INPE). The number of outbreaks recorded came from the TERRA, AQUA, GOES, NOAA, MSG-02 and ERS-2 satellites. A total of 74,752 outbreaks in the basin area were found between the years 2008 to 2018, with November as the most critical month, with 30.33% of total outbreaks, followed by October with 23.03%, a period in which there is practically no rainfall in the region. It was found that the year 2015 was the one with the highest rate of outbreaks with 14,025 occurrences and that the year 2011it was the least expressive, with 2,116 occurrences. Keywords: Geotechnologies. Use of the soil. Monitoring.   SENSOR REMOTO EN LA DETECCIÓN Y ANÁLISIS DE ENFOQUES DE CALOR EN LA CUENCA HIDROGRÁFICA DE RÍO MUNIM RESUMEN  Los incendios son la causa de la devastación de miles de hectáreas de ecosistemas en el planeta, generando impactos en la salud pública, pérdidas económicas y ambientales. El presente estudio tiene como objetivo realizar un análisis temporal de las fuentes de calor detectadas en diferentes usos y la cobertura del suelo mapeada entre 2008 y 2018 en la cuenca hidrográfica del río Munim, este de Maranhense. Los datos utilizados en el estudio se obtuvieron de la plataforma digital del Instituto Nacional de Investigación Espacial (INPE). El número de brotes registrados provino de los satélites TERRA, AQUA, GOES, NOAA, MSG-02 y ERS-2. Se encontraron un total de 74,752 brotes en el área de la cuenca entre los años 2008 hasta 2018, con noviembre como el mes más crítico, con 30.33% de los brotes totales, seguido de octubre con 23.03%, un período en el que prácticamente no hay precipitaciones en la región. Se encontró que el año 2015 fue el que tuvo la mayor tasa de brotes con 14.025 ocurrencias y que el año 2011fue el menos expresivo, con 2,116 ocurrencias.  Palabras-clave: Geotecnologías. Uso del suelo. Monitoreo. 

ANALISIS KESESUAIAN LAHAN DAN EVALUASI JENIS TANAH DALAM BUDIDAYA TANAMAN TEBU UNTUK PENGEMBANGAN DAERAH KABUPATEN TEGAL

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Daru Mulyono
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Spatial Analysis ◽  
Geographical Information System ◽  
Plant Productivity ◽  
Saccharum Officinarum ◽  
Geographical Information ◽  
Sugarcane Plant ◽  
Plant Cultivation ◽  
Suitability Map

The objectives of the research were to make land suitability map for sugarcane plant (Saccharum officinarum), to give recommendation of location including area for sugarcane plant cultivation and to increase sugarcane plant productivity. The research used maps overlay and Geographical Information System (GIS) which used Arch-View Spatial Analysis version 2,0 A in Remote Sensing Laboratory, Agency for the Assessment and Application of Technology (BPPT), Jakarta. The research was carried out in Tegal Regency starting from June to October 2004.The results of the research showed that the suitable, conditionally suitable, and not suitable land for sugarcane cultivation in Tegal Regency reached to a high of 20,227 ha, 144 ha, and 81,599 ha respectively. There were six most dominant kind of soil: alluvial (32,735 ha), grumosol 5,760 ha), mediteran (17,067 ha), latosol   (18,595 ha), glei humus (596 ha), and regosol (22,721 ha).

scholarly journals Relating Spatiotemporal Patterns of Forest Fires Burned Area and Duration to Diurnal Land Surface Temperature Anomalies

2018 ◽  
Vol 10 (11) ◽  
pp. 1777 ◽  
Author(s):  
Carmine Maffei ◽  
Silvia Alfieri ◽  
Massimo Menenti
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Forest Fires ◽  
Land Surface ◽  
Fire Danger ◽  
Parametric Models ◽  
Burned Area ◽  
Informative Content

Forest fires are a major source of ecosystem disturbance. Vegetation reacts to meteorological factors contributing to fire danger by reducing stomatal conductance, thus leading to an increase of canopy temperature. The latter can be detected by remote sensing measurements in the thermal infrared as a deviation of observed land surface temperature (LST) from climatological values, that is as an LST anomaly. A relationship is thus expected between LST anomalies and forest fires burned area and duration. These two characteristics are indeed controlled by a large variety of both static and dynamic factors related to topography, land cover, climate, weather (including those affecting LST) and anthropic activity. To investigate the predicting capability of remote sensing measurements, rather than constructing a comprehensive model, it would be relevant to determine whether anomalies of LST affect the probability distributions of burned area and fire duration. This research approached the outlined knowledge gap through the analysis of a dataset of forest fires in Campania (Italy) covering years 2003–2011 against estimates of LST anomaly. An LST climatology was first computed from time series of daily Aqua-MODIS LST data (product MYD11A1, collection 6) over the longest available sequence of complete annual datasets (2003–2017), through the Harmonic Analysis of Time Series (HANTS) algorithm. HANTS was also used to create individual annual models of LST data, to minimize the effect of varying observation geometry and cloud contamination on LST estimates while retaining its seasonal variation. LST anomalies where thus quantified as the difference between LST annual models and LST climatology. Fire data were intersected with LST anomaly maps to associate each fire with the LST anomaly value observed at its position on the day previous to the event. Further to this step, the closest probability distribution function describing burned area and fire duration were identified against a selection of parametric models through the maximization of the Anderson-Darling goodness-of-fit. Parameters of the identified distributions conditional to LST anomaly where then determined along their confidence intervals. Results show that in the study area log-transformed burned area is described by a normal distribution, whereas log-transformed fire duration is closer to a generalized extreme value (GEV) distribution. The parameters of these distributions conditional to LST anomaly show clear trends with increasing LST anomaly; significance of this observation was verified through a likelihood ratio test. This confirmed that LST anomaly is a covariate of both burned area and fire duration. As a consequence, it was observed that conditional probabilities of extreme events appear to increase with increasing positive deviations of LST from its climatology values. This confirms the stated hypothesis that LST anomalies affect forest fires burned area and duration and highlights the informative content of time series of LST with respect to fire danger.

scholarly journals Retrieved Optical Thickness for Analyzing The Aerosol and Cloud Properties Using Lidar Remote Sensing

2012 ◽  
Vol 13 (1) ◽  
pp. 7
Author(s):  
Syamsir Dewang
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Reference Data ◽  
Single Scattering ◽  
Lidar Data ◽  
Night Time ◽  
Cloud Properties ◽  
Tropical Area ◽  
Signal Simulation ◽  
The One

The lidar remote sensing is the one important application to observe the aerosol and cloud of the atmosphere. Themicropulse lidar (MPL) return signals were studied in the tropical area. In this investigation, the single scatteringis analyzed by the physical properties of aerosol and cloud. The signal simulation of the single scattering predictsthe maximum optical thickness by saturation. It was observed that saturation optical thickness from the lidarsignal depends on the variation of extinction coefficient. This simulation is compared by the optical thicknessestimation from the lidar data. The MPL data (at wavelength of 523 nm) was determined, and the sky radiometer (atwavelength 500 nm) was used as reference data. The maximum optical thickness of lidar was 2.6 at night time,and the maximum optical depth of lidar and sky radiometer data on the same day were 2.25 and 1.7, respectively.

scholarly journals The contribution of remote sensing in hydraulics and hydrology, analysis and evaluation of digital terrain model for flood risk mapping

2018 ◽  
Vol 39 (1) ◽  
pp. 17-26
Author(s):  
Faiza hassainia Bouzahar ◽  
Lahbaci Ouerdachi ◽  
Mahdi Keblouti ◽  
Akram Seddiki
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Flood Risk ◽  
Digital Terrain Model ◽  
Risk Map ◽  
Terrain Model ◽  
Digital Terrain ◽  
Wetland Biodiversity ◽  
Adopted Model ◽  
Flood Risk Map

AbstractThe study of flood risk involves the knowledge of the spatial variability in the characteristics of the vegetation cover, terrain, climate and changes induced by the intervention of humans in watersheds. The increased needs of the actors in land management mean that static maps no longer meet the requirements of scientists and decision-makers. Access is needed to the data, methods and tools to produce complex maps in response to the different stages of risk evaluation and response. The availability of very high spatial resolution remote sensing data (VHSR) and digital terrain model (DTM) make it possible to detect objects close to human size and, therefore, is of interest for studying anthropogenic activities. The development of new methods and knowledge using detailed spatial data, coupled with the use of GIS, naturally becomes beneficial to the risks analysis. Indeed, the extraction of information from specific processes, such as vegetation indices, can be used as variables such as water heights, flow velocities, flow rates and submersion to predict the potential consequences of a flood. The functionalities of GIS for cartographic overlay and multi-criteria spatial analysis make it possible to identify the flood zones according to the level of risk from the flood, thus making it a useful decision-making tool.This study was carried out on the territory of watersheds in the Annaba region, East of Algeria. The choice was guided by the availability of data (satellites images, maps, hydrology, etc.) and hydrological specificities (proximity to an urban area). The adopted model is divided into two parts. The first part is to establish a methodology for the preservation of wetland biodiversity and the protection of urban areas against floods. Thanks to the multi-criteria spatial analysis and the functionalities of the GIS, we established a flood risk map for the watershed defined above. The result was satisfactory compared with the field reality. The second part of the model consisted of the integration of cadastral information with the flood risk map obtained in the first part of our research.The primary objective of this mapping is to contribute to the development of flood risk management plans (in the sense of risk reduction). The mapping stage also provides quantitative elements to more accurately assess the vulnerability of a territory.

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