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Haze from the forest fires blanket most parts of the landscape. The rainfall during the flight also contributed to the limited visibility.

 

Photo by Aulia Erlangga/CIFOR

 

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If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org

The Global Development Potential Indices are part of the Land Use Land Cover collection. The data set contains 13 sector-level Development Potential Indices (DPIs) for sectors related to renewable energy (concentrated solar power, photovoltaic solar, wind, hydropower), fossil fuels (coal, conventional and unconventional oil and gas), mining (metallic, non-metallic), and agriculture (crop, biofuels expansion). Each DPI is a 1-km spatially-explicit, global land suitability map that has been validated using locations of planned development as well as examined for uncertainty and sensitivity. This map displays the DPI for crops, grouped into six 6 classes ranging from very low to very high.

The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), 1998-2019, V4.GL.03 consists of annual concentrations (micrograms per cubic meter) of all composition ground-level fine particulate matter (PM2.5). This data set combines AOD retrievals from multiple satellite algorithms including NASA MODerate resolution Imaging Spectroradiometer Collection 6.1 (MODIS C6.1), Multi-angle Imaging SpectroRadiometer Version 23 (MISRv23), MODIS Multi-Angle Implementation of Atmospheric Correction Collection 6 (MAIAC C6), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Deep Blue Version 4. The GEOS-Chem chemical transport model is used to relate this total column measure of aerosol to near-surface PM2.5 concentration. Geographically Weighted Regression (GWR) is used with global ground-based measurements from the World Health Organization (WHO) database to predict and adjust for the residual PM2.5 bias per grid cell in the initial satellite-derived values. This map represents concentration of all composition ground-level fine particulate matter for the year 2009.

Anthropogenic biomes datasets describe potential natural vegetation, biomes, as transformed by sustained by human population density and land use including agriculture and urbanization. Anthropogenic biome categories (Anthromes) are defined by population density and land-use intensity. The data consists of 19 anthrome classes in six broad categories.

russellmoreton.blogspot.com

 

russellmoreton.tumblr.com

 

Collage on paper, written fragments and images from Peter Greenaway, Josef Albers and Robin Evans. Photo montage of The Physical Self (Greenaway) and Waverley Abbey UK. Visual research as part of The Waverley Project/Obscura and Reading Room.

 

On the horizon, then, at the furthest edge of the possible, it is a matter of producing the space of the human species-the collective (generic) work of the species-on the model of what used to be called "art" ; indeed, it is still so called, but art no longer has any meaning at the level of an "object" isolated by and for the individual.

 

Henri Lefebvre, Openings and Conclusions. from On Installation and Site Specificity (introduction) Erika Suderburg

Date: 2018-06-10

Sentinel-2 L1C + Modified False Colour Composite

 

Author: Monja Å ebela

 

Contains modified Copernicus Sentinel data [2018], processed by Sentinel Hub

 

Inspect in EO Browser

 

The week of November 9, the remnants of Hurricane Ida combined with a coastal storm to produce a powerful nor’easter that wreaked havoc along the mid-Atlantic coast. In the wake of the storm, the National Geodetic Survey responded, surveying impacted areas.

 

This image is an aerial photograph of a grounded barge along the Virginia coast.

 

To learn more about aerial photography, visit:

Remote Sensing Division, National Geodetic Survey

Nor’Easter November 2009 Aerial Photographs

 

(Original source: NOS Responds to November 2009 Nor'easter)

Remote Sensing Course at Chulalongkorn University

Remote Sensing Course at Chulalongkorn University

Aerial shot of the countryside in West Kalimantan, Indonesia.

 

Photo by Yayan Indriatmoko/CIFOR

 

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If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org

More than 100 U.S. Army installations worldwide use BAE Systems’ SOCET GXP® geospatial-intelligence software for active missions. The U.S. Army has procured SOCET GXP for Army-wide implementation into its Imagery Workstation baseline for operational units, establishing the software as its primary GEOINT exploitation tool. The software currently is used on the frontlines in Iraq and Afghanistan, and systems integrators working on National Geospatial-Intelligence Agency programs are using it to produce GEOINT products.

Global Croplands in 2000 map the proportion of each 5 minute (10 km) grid cell land area that is under cropland. Dark shaded areas denote higher proportion of are under cropland. Data from Moderate Imaging Spectroradiometer (MODIS) land cover product and Satellite Pour l'Observation de la Terre (SPOT) VEGETATION's Global Land Cover 2000 product were combined with UN Food and Agriculture (FAO) agricultural statistics to generate the data set.

Aerial view of the landscape around Halimun Salak National Park, West Java, Indonesia.

 

Photo by Kate Evans/CIFOR

 

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If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org

Reference: APAAME_20221103_RHB-0324

Photographer: Robert Bewley

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Global Croplands in 2000 map the proportion of each 5 minute (10 km) grid cell land area that is under cropland. Dark shaded areas denote higher proportion of are under cropland. Data from Moderate Imaging Spectroradiometer (MODIS) land cover product and Satellite Pour l'Observation de la Terre (SPOT) VEGETATION's Global Land Cover 2000 product were combined with UN Food and Agriculture (FAO) agricultural statistics to generate the data set.

Satellite: Sentinel-1. SAR (Radar de Apertura Sintética).

 

El embalse de La Serena se localiza en la provincia de Badajoz (Extremadura, España) sobre el río Zújar. Se trata de la segunda mayor bolsa de agua de la península ibérica, y de la tercera de Europa.​ Es además el embalse español de mayor superficie​ de lámina de agua. (es.wikipedia.org/wiki/Embalse_de_La_Serena)

 

Capacidad total: 3219 hm³

Cuenca: río Guadiana

Inauguración: 1990

 

A diferencia de los sensores ópticos, que registran la luz del sol reflejada en la superficie terrestres, los sensores de radar como el del satélite Sentinel-1 emiten sus propias ondas y registran el reflejo de estas procedente de la superficie. Tienen la gran ventaja de funcionar de noche y de atravesar las nubes.

 

Esta imagen ha sido procesada con el navegador EO Browser (apps.sentinel-hub.com/eo-browser) de Sentinel Hub. Sentinel Hub es un motor de procesamiento de datos satelitales, dentro del programa de observación de la Tierra Copernicus (copernicus.eu) de la Unión Europea, operado por la empresa Sinergise. EO Browser es gratuito y fácil de usar. El norte siempre está arriba.

 

This image has been processed using the EO Browser (apps.sentinel-hub.com/eo-browser) by Sentinel Hub. Sentinel Hub is a satellite data processing engine, within the European Union's Earth observation programme Copernicus (copernicus.eu), operated by the Sinergise company. EO Browser is free and easy to use. North is always up.

Reference: APAAME_20221110_SAlK-0708

Photographer: Sufyan Al Karaimeh

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Global Croplands in 2000 map the proportion of each 5 minute (10 km) grid cell land area that is under cropland. Dark shaded areas denote higher proportion of are under cropland. Data from Moderate Imaging Spectroradiometer (MODIS) land cover product and Satellite Pour l'Observation de la Terre (SPOT) VEGETATION's Global Land Cover 2000 product were combined with UN Food and Agriculture (FAO) agricultural statistics to generate the data set.

Landscape of the South Yazd Province, Iran

Date: 2019-12-01

Sentinel-2 L2A + Custom Script

 

Author: Monja Å ebela

 

Contains modified Copernicus Sentinel data [2021], processed by Sentinel Hub

 

Inspect in EO Browser

Remote Sensing Course at Chulalongkorn University

Remote Sensing Course at Chulalongkorn University

Reference: APAAME_20221110_SAlK-0712

Photographer: Sufyan Al Karaimeh

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Photo by Kate Evans/CIFOR

 

Find out more:

landscapes.org

Twitter: @GLForum and #GLFCOP19

Facebook.com/GlobalLandscapesForum

 

cifor.org

 

blog.cifor.org

 

If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org

I work with orbital remote sensing over six years and every time I've the opportunity to travel by plane I analyse the surface like an satellite, searching for patterns between crops, grasslands, natural vegetation, urban organization and infrastruture.

Haze from the forest fires blanket most parts of the landscape. The rainfall during the flight also contributed to the limited visibility.

 

Photo by Aulia Erlangga/CIFOR

 

cifor.org

 

blog.cifor.org

 

If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org

Remote Sensing Course at Chulalongkorn University

Of the mason's who built them, we can say that they both designed as they drew, and drew as they designed. But their designing, like their drawing, was a process of work, not a project of the mind.

  

Tim Ingold 'Making'

Reference: APAAME_20221110_SAlK-0711

Photographer: Sufyan Al Karaimeh

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Reference: APAAME_20221121_FB-0416

Photographer: Firas Bqa'in

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Copernicus Sentinel 2 2022-12-04

Reference: APAAME_20221121_RHB-0258

Photographer: Robert Bewley

Credit: APAAME

Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works

Brunt Ice Shelf (West Brunt) - Copernicus Sentinel2 2022-09-28

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