Landsat 7 – ETM+ (15m) Satellite Image of the Yukon Delta September 22, 2002 Click on image to view in high resolution (Image credit: NASA)
The Yukon River one of the largest river deltas in the world originates in British Columbia, Canada, and flows through Yukon Territory before entering Alaska. In southwestern Alaska, the Yukon Delta spreads out in a vast tundra plain, where the Yukon and Kuskokwim Rivers meander toward the Bering Sea. Looking a little like branching and overlapping blood vessels, the rivers and streams flow through circuitous channels toward the sea, passing and feeding a multitude of coastal ponds and lakes.
The Yukon Delta is an important habitat for waterfowl and migratory birds, and most of the protected refuge is less than 100 feet (30 meters) above sea level and is currently (2010) protected as part of the Yukon Delta National Wildlife Refuge. Over such low-lying, mostly treeless terrain, the rivers can change course frequently and carve new channels to find the fastest route toward the sea.....
Our eyes perceive a leaf as green because wavelengths in the green region of the spectrum are reflected by pigments in the leaf, while the other visible wavelengths are absorbed. In addition, the components in plants reflect, transmit, and absorb different portions of the near-infrared radiation that we cannot see. Reflected near-infrared radiation can be sensed by satellites, allowing scientists to study vegetation from space. Healthy vegetation absorbs blue- and red-light energy to fuel photosynthesis and create chlorophyll. A plant with more chlorophyll will reflect more near-infrared energy than an unhealthy plant. Thus, analyzing a plants spectrum of both absorption and reflection in visible and in infrared wavelengths can provide information about the plants' health and productivity.
With the help of satellite images fifth and sixth grade students at Mr. Tim Blum’s geography class (photo below) at the UW Lab School got a birds-eye view of how humans have impacted or modified their environments (31 January 2011). Images acquired by satellites decades apart showed cleared forests, irrigated crop fields in the middle of the deserts, altered landscapes (new roads and water bodies), and urban growth......
California Council on Science and TechnologyInter-institutional Water Management Project Receives Partnership AwardCalifornia Council on Science and Technology"The project uses a satellite based, remote sensing platform to help refine irrigation...
USDA scientists conduct ongoing research at the USDA Agricultural Research Service’s (ARS) Jornada Experimental Range in southern New Mexico...
At Jornada Experimental Range in southern New Mexico, ongoing research is aimed at determining the utility of UAS for rangeland mapping and monitoring and developing an operational UAS-based remote sensing programme for ecological applications.
USDA scientists Al Rango and Andrea Laliberte are leading a team to conduct ongoing research at the USDA Agricultural Research Service’s (ARS) Jornada Experimental Range in southern New Mexico. The goal of this research is to determine the utility of UAS for rangeland mapping and monitoring and to develop an operational UAS-based remote sensing program for ecological applications. Over the last five years, they have developed workflows for acquisition, processing, and analysis of fine-detail UAS imagery and for relating remotely sensed information to ground-based measurements......
In 2006, amongst denied claims of human rights violations, researchers Dr. Chris Lavers, Chris Bishop, Anne Lavers, and Samuel Lavers, used GeoEye Foundation imagery to study demolition patterns and prove that widespread human rights abuses had indeed taken place in Porta Farm, Zimbabwe, where an entire community was destroyed....
The FP7 project EBONE (European Biodiversity Observation Network) will have its final meeting on 12 and 13 March in Brussels that is opened by DG Research and Innovation director Manuela Soares. The project, coordinated by Alterra, part of Wageningen UR, has set major steps in harmonisation of biodiversity observation in Europe. It has had its focus on habitat information and linking field observations with remote sensing. Results are being applied already in other on-going projects and in national approaches in Switzerland and Israel.
He said Risat-1 is the first such satellite being built by India and is a bit complex compared to other remote sensing/earth observation satellites built and sent up earlier. According to ISRO officials, Risat-1 at 1850 kg is the ...
At the end of summer, 2012, the South Atlantic Ocean held several icebergs. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra satellite captured this true-color image of three large icebergs floating south of the South Sandwich Islands on March 7, 2012. These three icebergs were likely calved off the coast of Antarctica, and are floating on the currents of the Southern Atlantic Ocean, drifting northwest towards South America.
Speckles of bright white can be seen on the deep blue ocean water near the large icebergs. This is likely light reflecting off of several smaller icebergs in the area.
It's been a year since the huge earthquake and tsunami struck Japan, and Google has released fresh imagery to show the recovery made by Japan over the past 12 months.
The new imagery was captured during the past month, and covers almost the entire northeastern coastline of Japan from Hachinohe down to Hitachi City. As you can see from some of the snapshots below, the improvements made to the country in the past year are quite remarkable.
On the one year anniversary of the Japanese earthquake and tsunami, we have updated Google Maps with the latest satellite imagery of the affected areas.
As you can see in the photo below, the new imagery covers the Northeastern coast from Hachinohe in Aomori Prefecture down to Hitachi City in Ibaraki Prefecture. This high-resolution imagery from GeoEye was taken in February and March and provides a telling view of what the affected areas look like a year into recovery.
O objetivo deste trabalho foi identificar embarcações em imagens de radar obtidas pela aeronave R-99 da Força Aérea Brasileira. Dados de amplitude, obtidas na banda L e nas polarizações HH, HV, VH e VV da região de Porto de Tubarão, ES, foram processados por meio de diferentes tipos de realces, filtros, classificadores e transformadores espectrais. As imagens com maior potencial para identificar embarcações foram ainda analisadas para diferenciar embarcações militares de mercantes, considerando-se os cinco elementos de interpretação (forma, tamanho, sombra, tonalidade e fatores associados, isto é, o contexto em que as embarcações se encontram nas imagens) e as cinco fases de interpretação de imagens (detecção, reconhecimento, análise, dedução e classificação). A combinação de processamentos mais favoráveis foi o realce com contraste 50-200, seguido de filtro abertura ou erosão e classificador SVM (Support Vector Machine) ou transformação SCI (Synthetic Color Image). Foi possível discriminar embarcações nas fases de detecção e reconhecimento, enquanto a diferenciação entre embarcações mercantes e militares foi obtida nas fases de análise e dedução. No nível de classificação, não foi possível definir o tipo de embarcação militar (e.g., fragata ou contratorpedeiro) ou o tipo de embarcação mercante (e.g., petroleiro ou graneleiro).
In a previous blog entry, we discussed how you can use Landsat image services in ArcMap to see the change over time. In this blog entry, we dive further into Landsat image services and describe how you can create thematic land cover maps which can then be used for analyses, such as land cover change detection.
The image classification process involves conversion of multi-band raster imagery into a single-band raster with a number of categorical classes that relate to different types of land cover.
There are two primary ways to classify a multi-band raster image; supervised and unsupervised classification. Using the supervised classification method, an image is classified using spectral signatures (i.e., reflectance values) obtained from training samples (polygons that represent distinct sample areas of the different land cover types to be classified). These samples are collected by you, the image analyst, to classify the image. With the unsupervised classification method, the software finds the spectral classes (or clusters) in the multi-band image without the analyst’s intervention, thus being unsupervised. Once the clusters are found, you then need to identify what the cluster represents (e.g., water, bare earth, dry soil, etc…)
In this blog entry, we explain how to use the Landsat image services with supervised classification method to create a land cover map. If you want to follow along, you can download the zip file we created for you to try this out yourself.....
The first global high-resolution map of the boundary between Earth’s crust and mantle – the Moho – has been produced based on data from ESA’s GOCE gravity satellite. Understanding the Moho will offer new clues into the dynamics of Earth’s interior.
Digging deep into 3D at USFSpar Point GroupFor example, Egypt's National Authority for Remote Sensing and Space Sciences does a lot of aerial remote sensing, “but they haven't really gotten into terrestrial work, so we were there to showcase some ...
“Floodplain forests play a crucial role in the storage of organic carbon (Corg). However, modeling of carbon stocks in these dynamic ecosystems remains inherently difficult. Here, we present the spatial estimation of Corg stocks in riparian woody vegetation and soils (to a depth of 1 m) in a Central European floodplain using very high spatial resolution remote sensing data and auxiliary geodata. The research area is the Danube Floodplain National Park in Austria, one of the last remaining wetlands with near-natural vegetation in Central Europe. Different vegetation types within the floodplain show distinct capacities to store Corg. We used remote sensing to distinguish the following vegetation types: meadow, reed bed and hardwood, softwood, and cottonwood forests. Spectral and knowledge-based classification was performed with object-based image analysis. Additional knowledge rules included distances to the river, object area, and slope information.
Filiado ao International Charter “Space and Major Disasters”, o Instituto Nacional de Pesquisas Espaciais (INPE) recebe especialistas das agências espaciais europeia, inglesa e canadense que representam esse consórcio de instituições para fornecimento de dados de satélites em situação de catástrofe.
De 5 a 7 de abril, a comitiva do International Charter tem a oportunidade de conhecer os projetos de satélites e as instalações do Laboratório de Integração e Testes (LIT) e do Centro de Rastreio e Controle (CRC), em São José dos Campos, e do Centro de Previsão do Tempo e Estudos Climáticos (CPTEC) e do Centro de Dados de Sensoriamento Remoto (CDSR), em Cachoeira Paulista.
O objetivo do International Charter é fornecer um sistema unificado de recepção e disseminação de dados de satélite para usuários autorizados em localidades que foram afetadas por desastres naturais.
“Os dados devem ser distribuídos com o compromisso de ajudar a mitigar os efeitos que esses desastres naturais ou tecnológicos possam causar para a vida humana e em suas propriedades”, comenta Ivan Barbosa, chefe da Divisão de Geração de Imagens do INPE.
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