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491.
Alfios is the biggest river of the Peloponnese and the ninth longest river in Greece. It drains an area of almost 2575 km2 in Western Peloponnese and discharges at Kiparissiakos Gulf. Due to its extent, the Alfios basin presents complex physiography and geomorphology. During the last 50 years, major direct human activities have had an important impact on the river network shape and on the valley floor morphology. The most important human activities were the channel straightening caused by meander cut-offs in 1950, the construction of two dams: the Ladonas dam in 1955 and the Flokas dam in 1968 and the illegal in-stream gravel extraction that started in the 1960s and continues until today. As a result, the Alfios riverbed has presented very rapid vertical and horizontal (lateral) erosion and significant changes to its network shape. The drainage network follows a straighter course, the number of meanders has been reduced and the seventh order branch is deeply incised. Besides the morphological impacts to the river network shape there are also serious economic damages caused by human activity. During the winter of 1999, the Flokas dam bridge was closed for a long period due to damages at its foundation caused by the heavy rain and illegal gravel extraction. Transportation between the villages in the area became extremely difficult and time consuming and the cost of the repairs was estimated at 500 000 euros. In this study, there is an effort to map the network shape transformation for the period 1977–2000 using multitemporal and multisensor satellite images. One Landsat MSS image, three Landsat TM images, two Landsat ETM images, and one Terra ASTER image have been orthorectified and processed in order to cover the specific period. Principal Component Analysis (PCA) method and Geographical Information System (GIS) techniques have been applied to map the changes in the Alfios River channel. The drainage network straightening and the cut-off of five big meanders were detected and mapped. These changes occurred between 1986 and 2000. 相似文献
492.
Salt affected soils occupy significant areas in western and central India manifested by the arid and semiarid climate, sandy/clayey soil texture, absence of natural drainage, and inadequate infrastructure and irrigation development. These soils are productive following reclamation and appropriate management. The National Remote Sensing Agency, Hyderabad (India) published state-wise maps of salt affected soils in India on 1:250,000 scale using a legend that includes physiography, soil characteristics, and the aerial extent of the mapping units. In the analogue form, voluminous data contained in such maps were difficult to handle by users of varied backgrounds. An attempt was made to prepare a computerized database of salt affected soils for easy access, retrieval, and manipulation of spatial and attribute data useful for management of salt affected soils. The salt affected soils maps were prepared, for Rajasthan, Gujarat, Madhya Pradesh, and Maharashtra states, overlaying digitized layers of SAS polygons and the Survey of India basemap using the ILWIS (Integrated Land and Water Information System) software. GIS was used to prepare a composite (master) database of western and central India that showed the extent and distribution of salt affected soils. A relational database was prepared combining the digitized polygons with soil characteristics such as nature and degree of salinity (presence of higher concentration of neutral salts and neutral soil reaction), sodicity (presence of higher concentration of basic salts and alkaline reaction) and ground coverage. The regional and zonal databases of salt affected soils were prepared at a suitable scale overlaying agro-climatic regions agro-climatic zones. Spatial relation of salt affected soils with physiography, climate, geology, and agro-eco-sub-regions were evaluated employing map calculations in GIS. Saline soils were prevalent in Gujarat, and Rajasthan while sodic soils were dominant in Maharashtra and Madhya Pradesh. These were distributed primarily in the arid (B) plain of Rajasthan, alluvial (A) and coastal (D) plains of Gujarat, and peninsular plain (F) of Maharashtra and Madhya Pradesh. It occupied 2,596,942 ha (78%) in the western (Rajasthan and Gujarat) and 733,608 ha (22%) in the central (Madhya Pradesh and Maharashtra) regions. The SAS occupied 3.3 million ha in the western and central region constituting 50% of the total salt affected soils in India. The saline and sodic soils occupied 2,069,285 ha (62%) and 1,261,266 ha (38%), respectively. 相似文献
493.
Remote classification of land-use/land-cover (LULC) types in Brazil's Cerrado ecoregion is necessary because knowledge of Cerrado LULC is incomplete, sources of inaccuracy are unknown, and high-resolution data are required for the validation of moderate-resolution LULC maps. The aim of this research is to discriminate between Cerrado and agriculture using high-resolution Landsat 7 ETM+ imagery for the western region of Bahia state in northeastern Brazil. The Maximum Likelihood Classification (MLC) and Spectral Angle Mapper (SAM) algorithms were applied to a ~3000 km2 subset, yielding comparable classification accuracies. The panchromatic band was reserved for validation. User's and producer's accuracies were highest for non-irrigated agriculture (~94%) but lower for Cerrado Lato Sensu (89%). Classification errors likely resulted from spatial and spectral characteristics of particular classes (e.g. riparian forest and burned) and overestimation of other classes (e.g. Eucalyptus and water). Manual misinterpretation of validation data may have also led to lower reported classification accuracies. 相似文献
494.
A global inventory of coral reef stressors based on satellite observed nighttime lights 总被引:1,自引:0,他引:1
In this article, we present a satellite-based approach to gather information about the threat to coral reefs worldwide. Three chosen reef stressors – development, gas flaring and heavily lit fishing boat activity – are analysed using nighttime lights data derived from the Defense Meteorological Satellite Program (DMSP) produced at the National Oceanic & Atmospheric Administration, National Geophysical Data Center (NOAA/NGDC). Nighttime lights represent a direct threat to coral reef ecosystems and are an excellent proxy measure for associated human-caused stressors. A lights proximity index (LPI) is calculated, measuring the distance of coral reef sites to each of the stressors and incorporating the stressor's intensity. Colourized maps visualize the results on a global scale. Area rankings clarify the effects of artificial night lighting on coral reefs on a regional scale. The results should be very useful for reef managers and for state administrations to implement coral reef conservation projects and for the scientific world to conduct further research. 相似文献
495.
Michael A. O'Neal 《国际地球制图》2013,28(4):315-325
Climatic interpretations of recent glacier fluctuations rely on ice-extent chronologies developed from lichenometric ages of Holocene landforms. However, lichenometry requires time- and resource-consuming field surveys, which limit our understanding of glacier chronologies, especially in remote locations. This study presents a rapid, coarse, a priori approach to predicting new field sites where lichenometry can be applied. Geologic, geographic, climatic, and landcover data were used in spatial and supervised classification analyses to identify areas in the Cascade Range of Washington and northern Oregon with similar environmental conditions to those where lichenometric dating techniques had previously been applied. These results focus the attention of researchers to only 1100 km2, or 3%, of the broader Cascade Range study area. Though this study concentrates on the utility of lichenometry for dating recent glacier activity in the Cascade Range, the screening method presented is easily translatable to a variety of geomorphic and environmental applications. 相似文献
496.
497.
498.
Xiaodong Zhang Ho Jin Kim Clinton Streeter David A. Claypool Ramesh Sivanpillai Santhosh Seelan 《国际地球制图》2013,28(7):537-551
Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ~2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management. 相似文献
499.
Effective and efficient monitoring of oil spills that originate from ships, offshore platforms and any accidents are of immense importance from the viewpoint of public safety and environmental protection. Detection of spilled oil is also essential to estimate the potential spread and drift from the source to the nearby coastal areas. In this regard, utilization of SAR data for the detection and monitoring of oil spills has received considerable attention in recent times, due to their wide area coverage, day-night and all-weather capabilities. In this paper, two oil spills incidents along the coast of Mumbai, India are investigated; (1) The 2010 oil spill that occurred after the MV MSC Chitra and MV Khalijia-3 collided and (2) the oil spill caused due to sinking of MV RAK carrier in 2011. Two simple and relatively quick approaches for oil spill detection have been applied to VV polarized Radarsat-2 imagery of the incidents and a comparison is made of the results obtained. The first approach utilizes the oil spill detection tool of Sentinel Application Platform (SNAP) and the second explores texture analysis using Grey Level co-occurrence matrix (GLCM). The results of the study show that texture analysis proves to be an efficient method for oil spill detection as compared to the SNAP oil spill detection tool. Nevertheless, both the proposed methodologies are useful for detection of oil spills and for subsequent utilization of the results, timely and cost effectively, for the calibration and validation of numerical models that predict oil spill dispersion trajectories. 相似文献
500.
AbstractShoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments. 相似文献