Satellite Images

Digital Surface Model (DSM) can be generated from stereo pairs of satellite or aerial images. Among the most state-of-the-art matching algorithms, Semi-Global Matching (SGM) has widely been used for generating DSM from both satellite and aerial images. This paper presents an approach to improve the accuracy of DSM generated by SGM from multi-view satellite images using a novel technique including several filters. The filters are used for deleting mismatches between very tall buildings in urban areas and removing the sea regions. The technique, in contrast to the recent multi-view matching approaches, considers some of the points generated with only a pair of images in the final DSM. The approach is implemented on five sequential high resolution images acquired by the Worldview-2 satellite. The results are locally evaluated in shape and quantitative terms in comparison with commercial software to reveal the capability of the approach to generate a reliable and dense point cloud. Experiments show that the proposed method can achieve below half-pixel accuracy.

An geologic-environmental and socio-economic evaluation of Azabache deposit in eight sectors of Sucre municipality and four sectors of Cedeño municipality, of Bolivar state, was made; chemical and petrographical analysis was made on samples from major production sites. Socio-economic aspects was known by surveys, interviews, workshop meeting and visits to each site where have operated seven production cooperative organizations and three of the ore processing. By chemical analysis it was determined the constituent elements of Azabache, aditionaly, using a petrographic microscope it was demonstrated the presence of vitrinita trace which is main mineral of representative samples studied. The characteristics of exploration, mining and ore processing activities were watched. The environmental assessment indicates the need for security measures to divers involved in operations, the need to improve techniques and quality related to manufacture of azabache. Finally it is proposing the exploration of new areas and the organizing of centers/collection-warehouses under responsability of current cooperative organizations, in order to increase incomes and socio-economic conditions, because this activity is the main livelihood for more than 100 direct jobs together to scarce agricultural and fisheries task practiced by communities in areas subject to this investigation.

The emergence of the study of fluvial dynamics of the alluvial monsoon rivers especially in India is being enriched through the application of remote sensing and GIS techniques. To study fluvial dynamics over time, channel avulsion no doubt is one of the most considerable phenomena. The study section (*75 km) in between the two confluences of the Bhagirathi River i.e., Ajay (Katwa) and Jalangi River (Nabadwip) confluence in Lower Ganga Plain of West Bengal is highly oscillatory in nature. Several satellite images and toposheets of different time periods (1955, 1973, 1990 and 2011) have been used in order to analyse the avulsive nature in this section of the river. These fluvial features (cut offs, ox-bow lakes, point bars etc.) form as a result of channel avulsion and have been identified with the help of Landsat satellite images. The decadal differences in sinuosity ratio in different parts of the studied section, channel migration rate and avulsion model explain the dynamic nature and crucial portions of high bank erosion rate of the channel in the mentioned time period. For both the reaches (R1 and R2), meander loop cut offs are dominant rather than lateral avulsion in the context of aggregate channel migration that also reflects the instability and erosional vulnerability at different meander bends.

The phenomenon of overheating in urban areas is an increasingly important issue as far as the quality of life and public health are concerned. This paper proposes a simple model, integrated with a Geographic Information System (GIS) tool, that can be used to analyze the microclimate of outdoor spaces, considering the relationship between the air temperature and the characteristics of an urban environment. The Urban Heat Island (UHI) effect was analyzed by assessing parameters that describe the urban context, such as the density of the population and of the buildings, and the urban morphology. Remote sensing data and satellite images were used to evaluate the presence of vegetation and the type of surfaces in the urban space. Through the construction of linear regression models, the main variables of influence were identified for a typical summer day. It has been found, from the results, that the UHI effect decreases proportionally with the presence of vegetation and with higher values of the albedo of urban surfaces, as well as of the altitude and the distance from the sea. The UHI effect instead increases proportionally for higher values of the canyon height-to-width ratio, the building density and the Land Surface Temperature. These models can be used to analyse the outdoor thermal comfort and the livability of an urban territory.

In the present study, an attempt has been made to characterize the natural resources and terrain condition and prescribe suitable action items towards sustainable development of Kundeimal micro watershed using geo informatics tools like satellite remote sensing, Global Positioning System and Geographic Information System. Satellite image of WORLDVIEW-II sensor and limited ground observations have been utilized for generating the thematic layers .The spatial layers have further been integrated and analysed using different geo informatics tools in GIS platform to generate alternate sustainable land use plan and watershed based suitable soil & water conservation measures for the micro watershed. The logic used in this study to generate the site specific action plan items is based on concept of sustainability.

— Satellite image processing is one of the important research areas in the field of digital image processing and is a challenging task for the researchers. It is often required to remove noise and smooth the image to highlight certain features of interest for image analysis and extracting significant information from satellite images often termed as image enhancement. It is an important step for overall image recognition and interpretation process and is a pre processing step that serves as an important step towards the solution for image analysis. Image enhancement can be performed in spatial or frequency domains. In this paper, we focus on spatial domain enhancement techniques with respect to satellite images. Some of the important image enhancement techniques such as contrast stretching, decorrelation stretch, histogram equalization and contrast limited adaptive histogram equalization are experimented and compared for visual interpretability. Two parameters, Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) are used for performance evaluation. The techniques are tested using 20 LandSat satellite images with different illumination effects. The experimentation was carried out using soft computing tool Matlab. It was observed that for satellite images, contrast stretching gives better results as compared to other techniques.

The article attempts to supplement the existing database of archaeological sites of Afghanistan, based on the data presented in the seminal book by W. Ball, as well as on recently published materials of the Soviet-Afghan archaeological expedition (by I. T. Kruglikova). These data are considered at a new level, using methods of remote sensing and multi-scale topographic maps of the region previously difficult to access for studying. The object of the research was the area of the valley of the Murghab river and its two right tributaries: Chapnal (Qaisar) and Kurutu Arik. Through the comparison of the complex data it's become possible to increase significantly the number of firmly localized sites of different eras, as well as specify some issues of historical and geographical nature.

Coastal environments are facing constant changes over time due to their dynamic nature and geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. The focus of this paper is shoreline extraction by means of an experimental algorithm, called J-Net Dynamic. It was tested on two types of image: a very high resolution (VHR) multispectral image (WorldView-2) and a high resolution (HR) radar synthetic aperture radar (SAR) image (Sentinel-1). The extracted shorelines were compared with those manually digitized for both images independently. The results obtained with the J-Net Dynamic algorithm were also compared with common algorithms, widely used in the literature, including the WorldView water index and the Canny edge detector. The results show that the experimental algorithm is more effective than the others, as it improves shoreline extraction accuracy both in the optical and SAR images.

Rapid globalization and the interdependence of the countries have engendered tremendous inflow of human migration towards the urban spaces. With the advent of high definition satellite images, high-resolution data, computational methods such as deep neural network analysis , and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding the urban area lies in the useful classification of the urban environment that is usable for data collection, analysis, and visualization. In this paper, we propose a novel classification method that is readily usable for machine analysis and it shows the applicability of the methodology in a developing world setting. However, the state-of-the-art is mostly dominated by the classification of building structures, building types, etc., and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh where the surrounding environment is crucial for the classification. Moreover, the traditional classifications propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real-time. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently, a map was drawn. The classification is based broadly on two dimensions the state of urbanization and the architectural form of the urban environment. Consequently, the urban space is divided into four classifications: 1) highly informal area 2) moderately informal area 3) moderately formal area and 4) highly formal area. For semantic segmentation and automatic classification, Google's DeeplabV3+ model was used. The model uses the Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate a larger context. Image encompassing 70% of the urban space was used to train the model and the remaining 30% was used for testing and validation. The model can segment with 75% accuracy and 60% Mean Intersection over Union (mIoU).

Background and Objectives: Low flows are the most important parameters for the qualitative and quantitative hydrological analysis of the catchments and have a significant role in the planning and water resource management. Several factors are involved in low flow trend, including, land use and vegetation that directly and indirectly affected by the interference of humans. Low flow data, within a watershed is used for a wide range of activities including: drought planning, investigation of ecosystem status, planning water demand, water pollution issues, development projects in the field of power generation and environmental studies. Low flows from various aspects have been investigated. Some of these cases can be pointed to research Riggs (1990), Warner (2003) and McMahon and Nathan (1991). They were used a linear correlation and multivariate regression methods to estimate low flows. For prediction and investigation of the effect of land cover variation on flow parameters, several studies have been done, including research of Zhao, (2010) and Wei and Zhang (2010). The impact of land use and climate change on the hydrology of Alabama coastal basins by Ruoyu, et al was evaluated by hydrological modeling. Direct and indirect effects of human in land use changing and its role on water resources have studied by some researcher. Including: Kashaigili, (2008) and Delgado et al (2010) the aim of this study was to investigate the role of land use change on a number of low flow indices in Taleghan catchment.

Materials and methods: In this research, by using topographical maps with the scale of 1:250000 and 1:50000 and Positioning the Galinak gauging stations in Taleghan river, the study area was Determined. Then using aerial photographs with the scale of1:20000 and TM and ETM satellite images of 1366 and 1381, land use map in the four-level of rangeland, dry land farming, irrigated and rock outcrop were prepared. Then land use change was calculated. Base flow index using daily data and based on, one parameter recursive digital filter algorithm were extracted by HydroOffice, 2012. Low flow indices with 3, 7, 15, 30 and 60 days duration using daily data were extracted. Then relationship between low flow indices and land use in the period of study were investigated. In this research, land use changes in the basin using the interpretation of aerial photographs and satellite imagery in three intervals of the years 1349, 1366 and 1381 were investigated. Base flow index using daily data and one parameter recursive digital filter algorithm were extracted. Low flow indices with 3, 7, 15, 30 and 60 days duration using daily data were extracted. Then relationship between low flow indices and land use in the period of study were investigated.

Results: The results showed that all of the low flow indices in the first period of study have experienced a steep upward trend. This trend in the second period during the years 1349 to 1366 also shows an increasing trend but with little slope. In the period 1366- 1381 all indices, including base flow index and other low flow indices a minimal decline have experienced. Increasing rangeland coverage of 81 with respect to 49 was in accordance with the increasing of indices in the period studied.

Conclusion: Land use Changes due to direct and indirect human intervention has a direct impact on the trend of low flow indices.Conformity of vegetation cover trend in 49 to 81 years with trend of low flow indices, indicating a positive role of rangeland on increasing the low flow indices. So rangeland protection to ensure, base flow continuity in the research area, is essential.

Remote sensing data and image classification algorithms can be very useful in the identification of beach patterns and therefore can be used as inputs in beach classification models. In this work, one aerial photograph, one IKONOS-2 image and one FORMOSAT-2 image were applied to a part of the northwest coast of Portugal. Several image processing algorithms were employed and compared: pixel-based approach, object-based approach, Principal Components Analysis (PCA), Artificial Neural Network (ANN) and Decision Trees (DT). The ANN and DT algorithms employed conduced to better results than the traditional classification methodologies (pixel-based, object-based and PCA), allowed a more accurate identification of rip currents. Regarding the data used, the high spatial resolution of aerial photograph allows for the better discrimination of different micro patterns. The FORMOSAT-2 image presents a lower spatial resolution, which did not allow for the identification of small microforms. Concluding, the conjugation of better spatial and spectral resolution of IKONOS-2 data and the data mining algorithms seems to be the better approach to accurately identify
beach patterns through remotely sensed data.

There are many ways to encode, represent, and compress satellite images. Today, with the huge technological advance, algorithms are used to perform many calculations to compress and decompress a satellite image. The future of the compression can take place only through mathematical algorithms, and the progress of mathematical research undoubtedly will lead to an advance in image and file compression. In this paper, we propose a hybrid DPCM-DCT predictive coding and discrete cosine transform DCT and, run-length encoding (RLE) for satellite image compression.

The main objective of this research was to develop a new concept and approach to extract knowledge from satellite imageries for near real-time drought monitoring. The near real-time data downloaded from the Atlantic Bird satellite were used to produce the drought spatial distribution. Our results showed that approximately 40% of the observed areas exhibited negative deviation. In this study, the possibility of using the near real-time spatio-temporal Meteosat Second Generation (MSG) data for drought monitoring in food insecure areas of Ethiopia was tested, and promising results were obtained. The output of this research is expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-affected areas.

The ability to organize and retrieve visual information such as images is becoming a crucial problem for specialists, because processing visual information requires perceptual abilities not yet known to exist in computational form. Therefore the ability to retrieve visual information is a complex problem. The main retrieval pattern include the features of an image such as colour, and shape. The algorithms used to calculate the similarity between extracted feature with an image database, that utilizes colour features of the images as the basis of comparison and retrieval. An object-oriented definition also involves prescribing a set of pertinent features or pixels as well as a method such as a classification algorithm with the appropriate training data. A low resolution satellite image of a rural scenario has been selected for the analysis. The entire image scene is divided into four equal quadrants. The Content-based retrieval of image features have been carried out for the selected two quadrants I and II. The color classification of the image in two quadrants clearly indicates that there are four important features that are common to the images 1 The features identified include, Natural Vegetation, Water Bodies, Land, and Housing associated with the image. Further using the L*a*b color spectral distribution and histogram techniques an estimation of the different features identified in the image has been made for all the four quadrants. The results are presented in the paper.

In the present study a suitable methodology is developed for estimating crop area by integrating remote sensing and GIS based on land survey approach. Area frame surveys are common ap-proaches to gather land cover data. In contrast to mapping approaches, area frame sampling is a statistical method. Based on the visual observation of sample geo-referenced points, area estimates are computed and used as a valid generalization without studying the entire area under investiga-tion. The approach has also the important advan-tage of not involving/disturbing the land owners and the farmers. The survey concerning the esti-mation of yield for the major crop will be carried out by cutting small samples in the field. The sample covers the whole Nile valley and the delta, the ob-served area is about 35000 km² and the distance from South to North is about 1000 km. Digital to-pographic maps 1:5000 and SPOT5 satellite Im-ages was used, 2,5m resolution, Ortho-rectified (DTM). The survey used the WG...

In the present study a suitable methodology is developed for estimating crop area by integrating remote sensing and GIS based on land survey approach. Area frame surveys are common ap-proaches to gather land cover data. In contrast to mapping approaches, area frame sampling is a statistical method. Based on the visual observation of sample geo-referenced points, area estimates are computed and used as a valid generalization without studying the entire area under investiga-tion. The approach has also the important advan-tage of not involving/disturbing the land owners and the farmers. The survey concerning the esti-mation of yield for the major crop will be carried out by cutting small samples in the field. The sample covers the whole Nile valley and the delta, the ob-served area is about 35000 km² and the distance from South to North is about 1000 km. Digital to-pographic maps 1:5000 and SPOT5 satellite Im-ages was used, 2,5m resolution, Ortho-rectified (DTM). The survey used the WG...

The Fengyun-4A (FY-4A) is a relatively new geostationary satellite launched by the National Satellite Meteorological Center of China in 2016. With its Advanced Geosynchronous Radiation Imager (AGRI) instrument, FY-4A was able to provide a Fire and Hotspot product (FHS). This study explored the use of the FHS product in detecting wildfires and was compared to the similar fire detection product of the Visible Infrared Imaging Radiometer Suite (VIIRS) with the goal of assessing its effectiveness in the early detection and monitoring of wildfires. The FY-4A FHS and the VIIRS fire detection products have spatial resolutions of 2 km and 375 m, and temporal resolutions of 15 minutes and 12 hours, respectively. The results of the comparative study showed that the FY-4A FHS product generated false negative results for detecting wildfires smaller than 20 pixels of VIIRS data (~2.82 km 2), at less than 4 MW of radiative power, and brightness temperature lower than 330 K. The FY-4A FHS product was also shown to be 50% accurate (1 correct and 1 false negative out of 2 samples) in detecting large wildfires (>2.5 km 2) with high radiative power (>4 MW) and high brightness temperature (>330 K). Lower accuracy may also be attributed to the presence of clouds that tend to obscure satellite images leading to an even lower accuracy of wildfire detection. For future studies, it is recommended that a comparison of the FY-4A FHS product be made with a more similar instrument, for example, the Advanced Himawari Imager 8/9 (AHI 8/9). It is also recommended to improve the fire and hotspot algorithm by incorporating a Normalized Brightness Temperature Difference Index (NBTDI) or by incorporating diurnal temperature cycle modelling for the older FY-2G data. Lastly, if available, a more reliable accuracy assessment can be done using FHS products of higher spatial resolution (at least 500 m).

Coastal environments are facing constant changes over time due to their dynamic nature and geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. The focus of this paper is shoreline extraction by means of an experimental algorithm, called J-Net Dynamic (Semeion Research Center of Sciences of Communication, Rome, Italy). It was tested on two types of image: a very high resolution (VHR) multispectral image (WorldView-2) and a high resolution (HR) radar synthetic aperture radar (SAR) image (Sentinel-1). The extracted shorelines were compared with those manually digitized for both images independently. The results obtained with the J-Net Dynamic algorithm were also compared with common algorithms, widely used in the literature, including the WorldView water index and the Canny edge detector. The results show tha...

Environmental mapping is a necessary tool for the geoscience research in the university classes of geography, GIS cartography and mapping. However, GIS methods of processing remote sensing data are often being discussed, and the optimal approaches are disputed. This work reports innovative approach of the processing Landsat TM satellite image in ILWIS GIS software using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described below. The results demonstrate successful application of the innovative approach of technical satellite image processing for the studies of the environment. The presented methods can be used by students of geography.

This study intends to map and detect the space distribution of gold mining dynamics in the Tapajós region, in the Legal Amazon, and to characterize the forest covering change in an area of 57.014 km². We use Landsat satellite images (TM-Thematic Mapper), with 1-5 and 7 bands, in the range of 1992-2003. The results showed that Remote Sensing was a robust tool to detect and map the gold mining activities. Using the automatic classification for decision tree method, the Spectral Mixture Analysis (SMA) and Normalized Difference Fraction Index (NDFI) were combined and the data showed an important resulted: gold mining can be mapped using the methodology proposed in this study. Palavras-chave: decision tree, gold mining, satellite images, árvore de decisão, garimpos, imagens de satélite.

La isla Alejandro Selkirk, perteneciente al archipiélago de Juan Fernández, está localizada a 33,18° S y  79,99° W, alcanzando una altura máxima de 1,6 Km. sobre el nivel del mar. Esta región se encuentra fuertemente influenciada por la presencia del anticiclón subtropical del Pacífico Suroriental, que contribuye  a la generación de una  inversión térmica cuasi permanente en la isla y  al desarrollo de nubes estratocúmulos que quedarían bajo esta capa de inversión; además de presentar vientos promedios que van desde los 3,5 a 9 m/s, variando según la estación. Los vórtices atmosféricos o de Von Karman son remolinos que se crean cuando la atmósfera se comporta como un fluido turbulento (número de Reynolds entre 80 y 200)  que interactúa con un obstáculo,  en este caso el relieve de una isla.  Primeramente se determinaron las condiciones necesarias para la generación de vórtices de Von Karman  en la atmósfera que rodea una isla oceánica genérica. Se encontró que la isla Alejandro Selkirk cumple con estas condiciones, sin embargo, el estudio de  imágenes satelitales (Landsat 7) entre los años 1999 y 2001 sólo presentan una única imagen que muestra la ocurrencia de estos vórtices. Finalmente, se analizó el día en que ocurrió este fenómeno y se comparó el periodo en que no ocurrió, con el propósito de identificar otras condiciones necesarias o suficientes pare su formación.

Forest monitoring requires more automated systems to analyse the large amount of remote sensing data. A new method of change detection is proposed for identifying forest land cover change using high spatial resolution satellite images. Combining the advantages of image segmentation, image differencing and stochastic analysis of the multispectral signal, this OB-Reflectance method is object-based and statistically driven. From a multidate image, a single segmentation using region-merging technique delineates multidate objects characterised by their reflectance differences statistics. Objects considered as outliers from multitemporal point of view are successfully discriminated thanks to a statistical procedure, i.e., the iterative trimming. Based on a chi-square test of hypothesis, abnormal values of reflectance differences statistics are identified and the corresponding objects are labelled as change. The object-based method performances were assessed using two sources of reference ...

On-board image compression has been a growing trend in most recent satellite missions. Since majority of satellite applications deal with imagery; compression of images due to limited on-board data storage mediums has become a necessity. The idea of treating satellite imageries as fractals and then encoding them provides an efficient way of conserving bandwidth and per-bit storage costs. Fractal encoding is characterized by slow encoding times which somehow had hindered its popularity in spite of its impressive compression ratio scaling many orders as compared to JPEG. In order to circumvent this handicap, Fractal compression is implemented using powerful GPUs (Graphical Processor Units) that are capable of reaching astronomical computing speeds of around 900 GFLOPS (Quadro Graphic Cards from Nvidia TM) with internal memory bandwidth ranging to 100 GB/s. This astounding parallel capability is probed to be used on board systems, providing much needed boost for image compression. As t...

Coastal environments are facing constant changes over time due to their dynamic nature and geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. The focus of this paper is shoreline extraction by means of an experimental algorithm, called J-Net Dynamic (Semeion Research Center of Sciences of Communication, Rome, Italy). It was tested on two types of image: a very high resolution (VHR) multispectral image (WorldView-2) and a high resolution (HR) radar synthetic aperture radar (SAR) image (Sentinel-1). The extracted shorelines were compared with those manually digitized for both images independently. The results obtained with the J-Net Dynamic algorithm were also compared with common algorithms, widely used in the literature, including the WorldView water index and the Canny edge detector. The results show tha...

Knowledge of a territory is an essential element in any future planning action and in appropriate territorial and environmental requalification action planning. The current large-scale availability of satellite data, thanks to very high resolution images, provides professional users in the environmental, urban planning, engineering, and territorial government sectors, in general, with large amounts of useful data with which to monitor the territory and cultural heritage. Italy is experiencing environmental emergencies, and coastal erosion is one of the greatest threats, not only to the Italian heritage and economy, but also to human life. The aim of this paper is to find a rapid way of identifying the instantaneous shoreline. This possibility could help government institutions such as regions, civil protection, etc., to analyze large areas of land quickly. The focus is on instantaneous shoreline extraction in Ortona (CH, Italy), without considering tides, using WorldView-2 satellite...

The study area is focused on the coastal city of Taipei. The environmental changes of the city were detected by geospatial analysis of the satellite images. The areas occupied by different landscape types were calculated and analysed. It was detected that various districts were developing with different rate and intensity due to the complex factors of both human and ecological origin. The results showed intensive urban development, decline of green areas, increase of urban spaces since 1990. Область исследования сосредоточена на прибрежном городе Тайбэй (Тайвань, Китай). Экологические изменения города были обнаружены с помощью геопространственного анализа спутниковых снимков. Площади, занимаемые различными типами ландшафта, были проанализированы. Было обнаружено, что разные части города развиваются с разной скоростью и интенсивностью из-за сложного сочетания антропогенных и природных факторов. Результаты показали процессы интенсивной урбанизации, деградацию зеленых ареалов, увеличение площадей застроенных территорий с 1990 года.