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The AGU’s Honors Program 2017 is Still Open For Nominations

AGU’s Honors Program is a diverse program for recognizing individuals who have made outstanding contributions to the advancement of the geophysical sciences, to the service of the community, and public outreach. The program aligns with AGU’s strategic goals in scientific leadership, talent pool development, science and society and organizational excellence.

Check this link to nominate.

Canopy Height Estimation by Characterizing Waveform LiDAR Geometry Based on Shape-Distance Metric

Title: Canopy Height Estimation by Characterizing Waveform LiDAR Geometry Based on Shape-Distance Metric

Authors: Eric Ariel L. Salas and Geoffrey M. Henebry

 Abstract: There have been few approaches developed for the estimation of height using waveform LiDAR data. Unlike any existing methods, we illustrate how the new Moment Distance (MD) framework can characterize the canopy height based on the geometry and return power of the LiDAR waveform without having to go through curve modeling processes. Our approach offers the possibilities of using the raw waveform data to capture vital information from the variety of complex waveform shapes in LiDAR. We assess the relationship of the MD metrics to the key waveform landmarks—such as locations of peaks, power of returns, canopy heights, and height metrics—using synthetic data and real Laser Vegetation Imaging Sensor (LVIS) data. In order to verify the utility of the new approach, we use field measurements obtained through the DESDynI (Deformation, Ecosystem Structure and Dynamics of Ice) campaign. Our results reveal that the MDI can capture temporal dynamics of canopy and segregate generations of stands based on curve shapes.

Citation: Eric Ariel L. Salas, Geoffrey M. Henebry. Canopy Height Estimation by Characterizing Waveform LiDAR Geometry Based on Shape-Distance Metric. AIMS Geosciences, 2016, 2(4): 366-390. doi: 10.3934/geosci.2016.4.366 

Download the free PDF copy here.

Species Distribution Model SDM Package Tool in R Software

I used the Species Distribution Model SDM Package Tool in R software all the time.

sdm is an object-oriented, reproducible and extensible R platform for species distribution modelling. The sdm package is designed to create a comprehensive modelling and simulation framework that: 

1) provides a standardised and unified structure for handling species distributions data and modelling techniques (e.g. a unified interface is used to fit different models offered by different packages);

2) is able to support markedly different modelling approaches;

3) enables scientists to modify the existing methods, extend the framework by developing new methods or procedures, and share them to be reproduced by the other scientists;

4) handles spatial as well as temporal data for single or multiple species;

5) employs high performance computing solutions to speed up modelling and simulations, and finally;

6) uses flexible and easy-to-use GUI interface. For more information, check the published paper by Naimi and Araujo (2016) in the journal of Ecography.

Download the package here.

MDI: Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs

Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs
by Eric Ariel L. Salas, Kenneth G. Boykin and Raul Valdez

Abstract: We tested the Moment Distance Index (MDI) in combination with texture features for the summer vegetation mapping in the eastern Pamir Mountains, Tajikistan using the 2014 Landsat OLI (Operational Land Imager) image. The five major classes identified were sparse vegetation, medium-dense vegetation, dense vegetation, barren land, and water bodies. By utilizing object features in a random forest (RF) classifier, the overall classification accuracy of the land cover maps were 92% using a set of variables including texture features and MDI, and 84% using a set of variables including texture but without MDI. A decrease of the Kappa statistics, from 0.89 to 0.79, was observed when MDI was removed from the set of predictor variables. McNemar’s test showed that the increase in the classification accuracy due to the addition of MDI was statistically significant (p < 0.05). The proposed method provides an effective way of discriminating sparse vegetation from barren land in an arid environment, such as the Pamir Mountains.

Keywords: object-based analysis; Pamir Mountains Tajikistan; Moment Distance; MDI; Marco Polo argali; multispectral application; image texture; arid environment

To cite the paper:
AMA Style
Salas EAL, Boykin KG, Valdez R. Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs. Remote Sensing. 2016; 8(1):78.

Chicago/Turabian Style
Salas, Eric A.L.; Boykin, Kenneth G.; Valdez, Raul. 2016. “Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs.” Remote Sens. 8, no. 1: 78.

Download the paper here (PDF).

Marco Polo Argali Habitat in the Eastern Pamir Mountains of Tajikistan

Download free GIS datasets for the Southeastern Pamir Mountains of Tajikistan

Title: Geographic Layers as Landscape Drivers for the Marco Polo Argali Habitat in the Southeastern Pamir Mountains of Tajikistan

Download free maps and GIS dataset here.
Download the paper here.

To cite the paper:
Salas, E.A.L.; Valdez, R.; Boykin, K.G. Geographic Layers as Landscape Drivers for the Marco Polo Argali Habitat in the Southeastern Pamir Mountains of Tajikistan. ISPRS Int. J. Geo-Inf. 2015, 4, 2094-2108.
Keywords: Tajikistan Pamirs; remote sensing; Landsat; vegetation; pasture; GIS analysis; Free GIS maps; bighorn sheep; Free sheep GIS dataset

Landsat 9 Satellite To Launch in 2023 To Continue Land Imaging Legacy

NASA and the U.S. Geological Survey (USGS) have started work on Landsat 9, planned to launch in 2023, which will extend the Earth-observing program’s record of land images to half a century.

The Landsat program has provided accurate measurements of Earth’s land cover since 1972. With data from Landsat satellites, ecologists have tracked deforestation in South America, water managers have monitored irrigation of farmland in the American West, and researchers have watched the growth of cities worldwide. With the help of the program’s open archive, firefighters have assessed the severity of wildfires and scientists have mapped the retreat of mountain glaciers.

The President’s fiscal year 2016 budget calls for initiation of a Landsat 9 spacecraft as an upgraded rebuild of Landsat 8, as well as development of a low-cost thermal infrared (TIR) free-flying satellite for launch in 2019 to reduce the risk of a data gap in this important measurement. The TIR free flyer will ensure data continuity by flying in formation with Landsat 8. The budget also calls for the exploration of technology and systems innovations to provide more cost effective and advanced capabilities in future land-imaging missions beyond Landsat 9, such as finding ways to miniaturize instruments to be launched on smaller, less expensive satellites.

“Moving out on Landsat 9 is a high priority for NASA and USGS as part of a sustainable land imaging program that will serve the nation into the future as the current Landsat program has done for decades,” said John Grunsfeld, associate administrator for science at NASA Headquarters, Washington. “Continuing the critical observations made by the Landsat satellites is important now and their value will only grow in the future, given the long term environmental changes we are seeing on planet Earth.”

Because an important part of the land imaging program is to provide consistent long-term observations, this mission will largely replicate its predecessor Landsat 8. The mission will carry two instruments, one that captures views of the planet in visible, near infrared and shortwave-infrared light, and another that measures the thermal infrared radiation, or heat, of Earth’s surfaces. These instruments have sensors with moderate resolution and the ability to detect more variation in intensity than the first seven satellites in the Landsat program.

The Landsat 9 mission is a partnership between NASA and the USGS. NASA will build, launch, perform the initial check-out and commissioning of the satellite; USGS will operate Landsat 9 and process, archive, and freely distribute the mission’s data.

"Landsat is a remarkably successful partnership," said Sarah Ryker, USGS deputy associate director for climate and land use change, Reston, Virginia. "Last year the White House found that GPS, weather satellites, and Landsat are the three most critical types of Earth-orbiting assets for civil applications, because they're used by many economic sectors and fields of research. Having Landsat 9 in progress, and a long-term commitment to sustainable land imaging, is great for natural resource science and for data-driven industries such as precision agriculture and insurance."

NASA’s Goddard Space Flight Center in Greenbelt, Maryland, will lead development of the Landsat 9 flight segment. Goddard will also build the Thermal Infrared Sensor (TIRS), which will be similar to the TIRS that the center built for Landsat 8. The new improved TIRS will have a five-year design lifetime, compared to the three-year design lifetime of the sensor on Landsat 8.

"This is good news for Goddard, and it’s great news for the Landsat community to get the next mission going," said Del Jenstrom, the Landsat 9 project manager at NASA Goddard. "It will provide data consistent with, or better than, Landsat 8."

With decades of observations, scientists can tease out subtle changes in ecosystems, the effects of climate change on permafrost, changes in farming technologies, and many other activities that alter the landscape.

“With a launch in 2023, Landsat 9 would propel the program past 50 years of collecting global land cover data,” said Jeffrey Masek, Landsat 9 Project Scientist at Goddard. "That’s the hallmark of Landsat: the longer the satellites view the Earth, the more phenomena you can observe and understand. We see changing areas of irrigated agriculture worldwide, systemic conversion of forest to pasture – activities where either human pressures or natural environmental pressures are causing the shifts in land use over decades.”

"We have recognized for the first time that we’re not just going to do one more, then stop, but that Landsat is actually a long-term monitoring activity, like the weather satellites, that should go on in perpetuity," Masek said.

NASA uses the vantage point of space to increase our understanding of our home planet, improve lives, and safeguard our future. NASA develops new ways to observe and study Earth's interconnected natural systems with long-term data records. The agency freely shares this unique knowledge and works with institutions around the world to gain new insights into how our planet is changing.

For more information on the Landsat program, visit: http://landsat.gsfc.nasa.gov


Featured Video

The Penn State Public Broadcasting launched the Geospatial Revolution Project, an integrated public media and outreach initiative about the impact of digital mapping. Watch two of the four high-definition video episodes that have already been released. You can visit the project via: geospatialrevolution.psu.edu.

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