CLIMsystems to Unveil New Marine Climate Adaptation Mapping Tool and CMIP5 data for ArcGIS at 2013 Esri UC

CLIMsystems Ltd is dedicated to providing state-of-the-art climate adaptation and change risk assessment tools and services to a wide range of clients. They will be launching the new SimCLIM for Arc GIS/Marine to accompany the SimCLIM for Arc GIS/Climate solution on July 8th, 2013, at the Esri User Conference in San Diego, CA.

Climate adaptation is increasingly recognised as a factor to be considered across sectors such as infrastructure, agriculture, water resources, marine, conservation, biodiversity and disaster risk management. CLIMsystems wishes to put the knowledge, capability and climate-proofing capacity in your hands for conducting climate change risk and adaptation assessments.

CLIMsystems is proud to announce the release of the two new data sets and a new toolbar for ArcGIS Desktop. To follow on the successful launch of the SimCLIM for ArcGIS/Climate add-in earlier this year CLIMsystem announces SimCLIM for ArcGIS/Marine add-in. After extensive testing and end user review the new marine climate adaptation add-in is available in July 2013.

The new add-in includes nine key ocean variables:

  • sea surface temperature
  • pH
  • primary production
  • total alkalinity
  • dissolved oxygen, nitrate, phosphate, iron and silicate.

Baselines and general circulation model data is all derived from the most recent CMIP5 global models. The new marine add-in also includes the capacity for ensemble application and the 2.6, 4.5, 6.0, and 8.5 representative concentration pathways (RCPs). The tool and datasets represent a revolution in the provision of climate change marine data for a range of end users. Climate change and adaptation is impacting on the management of marine resources. The tool SimCLIM for Arc GIS/Marine ready to handle this uncertainty is now within the grasp of Esri Arc GIS® users.

The current SimCLIM for ArcGIS/Climate add-in has also been upgraded to include ensemble capabilities for the Unites States. Bias corrected, statistically downscaled data derived from the latest CMIP5 models with four RCPs is now available for the continental USA and as individual US states. It includes the variables of precipitation and minimum, mean and maximum temperature. Users have described SimCLIM for Arc GIS/Climate as an “easy to use tool which supports rapid integration of prospective scenarios. The creation of scenarios becomes much less time consuming which optimizes research costs and enhances our current capacity to achieve. In our industry, the greatest benefit would be for the GIS analyst supporting ecological studies.”

CLIMsystems can be visited during the Esri UC 2013 in San Diego from July 8th to 11th at the Environment Showcase (Hall C) at booth V1424, in the Map Gallery Upper Level in the Sails Pavilion on Monday the 8th from 3:30 to 8:00 pm, in their presentation in the Demo Theater of the Environment Showcase (Hall C) on Tuesday 9 July at 11:15 am and at the Paper Session Climate Change – Analysis and Adaptation on the Upper Level in Room 23C on 9 July at 8:30 am.

CLIMsystems, established in 2003, has an impressive international footprint delivering innovative climate modelling tools backed by high quality data processing capabilities. The science underpinning the models is supported by a prestigious scientific advisory panel of preeminent climate change scholars. The extensive network of Associates located around the world and affiliated with a range of stakeholder groups further strengthens the commitment and capacity for CLIMsystems to deliver high quality products and services for climate adaptation and risk assessment.

For more information on CLIMsystems products and services visit: https://www.climsystems.com or info@climsystems.com SimCLIM for Arc GIS/Climate Free Trail version and data sets are available from http://www.climsystems.com/simclimarcgis/

[Source: CLIMsystems press release]

Mapping the Elevation Change of Lambert Glacier in East Antarctica using ICESat GLAS

Journal of MapsJournal of Maps, Volume 8, Issue 4, December 2012, pages 473-477

Dong Zhang, Bo Sun, Chang-Qing Ke, Xin Li, Xiang-Bin Cui & Jing-Xue Guo

“We initially derived elevation changes of Geoscience Laser Altimeter System level-2 altimetry data of Lambert Glacier overlapping footprints during each mission from 2003 to 2008. Then, surface elevation changes during every two adjacent missions were interpolated using inverse distance weighted, natural neighbor, triangulated irregular network with linear method, radial basis functions and ANUDEM in ArcGIS. The best results were obtained by ANUDEM, so these data were clipped to conform to the study area boundary defined by hydrology tools. Finally, elevation changes over 10 periods were mapped. In these maps, we chose the Antarctic digital elevation model as background and used a translucent layer to mask the area outside Lambert Glacier, and then displayed elevation changes using gradient colors. Results indicate that elevation changes of the entire Lambert Glacier are not evident, particularly in the upstream area. There are a few elevation changes in some downstream areas. Elevation of the grounding zone in the southernmost Amery Ice Shelf decreased more than 2 m in 2004–2005, 2006–2007, and during 2008.”

Spatial and Temporal Analysis of Deforestation and Forest Degradation in Selangor: Implication to Carbon Stock Above Ground

4th Conference on Data Mining and Optimization (DMO)4th Conference on Data Mining and Optimization (DMO), 02-04 September 2012

Syed Abdullah and Sharifah Mastura

“This paper aims to develop an operational methodology for monitoring spatial and temporal changes due to deforestation in Selangor over a 22 year period. The driving forces determining the changes were also analysed. Overall, the results show that the causes of deforestation were the economic factors, namely agriculture intensification, and population dynamics, related to the process of urbanization. However, deforestation statistics shows only a total of 10 percent decrease; it is the degradation of the remaining forest that is the major concern. Knowledge on deforestation and its driving forces in Selangor is very important as it provides the basis for the calculation of the total amount of carbon stock above ground. It also gives insight into the appropriate intervention measures that can be taken to increase carbon stock, thus reducing the release of carbon dioxide emission to the atmosphere.”

The Influence of DEM Quality on Mapping Accuracy of Coniferous- and Deciduous-Dominated Forest Using TerraSAR‑X Images

Remote Sensing, 2012, 4(3), 661-681

Sonia M. Ortiz, Johannes Breidenbach, Ralf Knuth and Gerald Kändler

“Climate change is a factor that largely contributes to the increase of forest areas affected by natural damages. Therefore, the development of methodologies for forest monitoring and rapid assessment of affected areas is required. Space-borne synthetic aperture radar (SAR) imagery with high resolution is now available for large-scale forest mapping and forest monitoring applications. However, a correct interpretation of SAR images requires an adequate preprocessing of the data consisting of orthorectification and radiometric calibration. The resolution and quality of the digital elevation model (DEM) used as reference is crucial for this purpose. Therefore, the primary aim of this study was to analyze the influence of the DEM quality used in the preprocessing of the SAR data on the mapping accuracy of forest types.

Application of the classification model in Biberach.

Application of the classification model in Biberach. (a) Map of deciduous- and
coniferous-dominated forest based on combined leaf-on and leaf-off TerraSAR-X images (acquired in 2008 and 2009) preprocessed with the ALS DTM; (b) official forest stand map (established 2007); (c) ortho-photographs (acquired on 2007).

“In order to examine TerraSAR-X images to map forest dominated by deciduous and coniferous trees, High Resolution SpotLight images were acquired for two study sites in southern Germany. The SAR images were preprocessed with a Shuttle Radar Topography Mission (SRTM) DEM (resolution approximately 90 m), an airborne laser scanning (ALS) digital terrain model (DTM) (5 m resolution), and an ALS digital surface model (DSM) (5 m resolution). The orthorectification of the SAR images using high resolution ALS DEMs was found to be important for the reduction of errors in pixel location and to increase the classification accuracy of forest types. SAR images preprocessed with ALS DTMs resulted in the highest classification accuracies, with kappa coefficients of 0.49 and 0.41, respectively. SAR images preprocessed with ALS DTMs resulted in greater accuracy than those preprocessed with ALS DSMs in most cases. The classification accuracy of forest types using SAR images preprocessed with the SRTM DEM was fair, with kappa coefficients of 0.23 and 0.32, respectively.Analysis of the radar backscatter indicated that sample plots dominated by coniferous trees tended to have lower scattering coefficients than plots dominated by deciduous trees. Leaf-off images were only slightly better suited for the classification than leaf-on images. The combination of leaf-off and leaf-on improved the classification accuracy considerably since the backscatter changed between seasons, especially in deciduous-dominated forest.”

Read the paper [PDF]

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

Remote Sensing, 2012, 4(4), 810-829

Sandra Eckert

“Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. In order to develop improved forest stratum–specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson’s correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression.

Overview and zoom map of the study area.

Overview and zoom map of the study area.

“Pearson’s correlation coefficients revealed that (a) texture measures correlated more with biomass and carbon than spectral parameters, and (b) correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%). For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%). These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a) developing and applying forest stratum–specific models, and (b) including textural information in addition to spectral information.”

Clinton Climate Initiative Receives 2012 Special Achievement in GIS Award

Clinton FoundationLast month at the Esri International User Conference, Clinton Climate Initiative (CCI) received the 2012 Special Achievements in GIS Award. The award recognized CCI for using geographic information system (GIS) technology to help countries monitor their carbon levels.

CCI’s Forestry Program is developing forestry projects and carbon measurement systems that help governments and local communities receive compensation for preserving and re-growing forests. As global warming is caused by increased carbon dioxide in the atmosphere from burning fossil fuels – and deforestation accounts for about 15% of total carbon dioxide emissions in the world – scientists predict that if governments and communities don’t take action to reduce carbon dioxide emissions, our world will face increasingly drastic consequences ranging from stronger heat waves to more droughts and floods to increasing sea level. All of these affect agriculture, food security, viability of coastal cities, and water availability around the world.

In order to reduce emissions, governments and economies must use less fossil fuels and increase use of energy efficient technologies and renewable technologies. CCI’s Forestry Program focuses on helping developing countries reverse deforestation and plant new trees. If countries are able to show that they can monitor and verify that they are reducing their carbon dioxide emissions, countries become eligible for funding to manage their forest programs and other low-carbon economic activities.

CCI was recognized with the 2012 Special Achievement in GIS Award for helping the country of Guyana become eligible for $70 million in forest-based payments from the government of Norway. Guyana is now using this funding to facilitate specific elements of a Low Carbon Development Plan envisioned and put in place by former Guyana President Bharrat Jagdeo. This project is part of CCI’s Forestry Program and has been supported by the Rockefeller Foundation and the governments of Norway and Australia.

CCI uses GIS technology as a centerpiece of forest carbon measurement, reporting, and verification (MRV) systems for developing countries. GIS is one of three legs of the platform–Data, Models, and GIS–that allows countries to determine how much carbon they have, how it is changing, and how the drivers of deforestation and forest degradation can be monitored and adjusted as required.

With GIS systems in place for forestry, developing countries can be eligible for direct payments through international agreements based on the effectiveness of their MRV systems. Once in place, the GIS systems can be used more broadly by the countries for other resource development, land surveys, and determination of land tenure.

Read more about CCI’s forestry projects.

[Source: Clinton Foundation press release]

University of Pittsburgh Geologists Map Prehistoric Climate Changes in Canada’s Yukon Territory

Pitt study one of many across the nation focused on understanding Arctic region’s climate changes

Researchers at the University of Pittsburgh have joined an international group of scientists to study past climate changes in the Arctic. Comprising geologists from Pitt’s Department of Geology and Planetary Science, the team has analyzed sedimentary and geochemical records of water-level changes in Rantin Lake, located in the boreal forest of Canada’s southeastern Yukon Territory. The results were published online in the April issue of Journal of Paleolimnologyas one of 18 articles dedicated to reconstructing Arctic lake sediments climate and environmental changes during the Holocene (about 12,000 years before present day).

“During the last 10,000 years, there have been certain times in which rapid climate change events occurred,” said David Pompeani, lead author and a Pitt PhD geology student. “By analyzing Rantin Lake, we’ve contributed a piece of the puzzle toward mapping the timing and magnitude of these prehistoric events throughout the Arctic.”

Rantin Lake is part of a watershed containing a series of small lakes hydrologically connected through groundwater flow. The regional climate is subarctic and characterized by warm, wet summers and dry, cold winters. The lake is located at 60 degrees north in the Canadian Arctic, only 30 degrees away from the North Pole, where climate change is expected to be amplified.

In July 2006, the Pitt team—including Mark Abbott, associate professor of geology and planetary science, and Byron Steinman, a former PhD geology student (now a postdoctoral researcher at Penn State University)—collected two sediment cores from the lake for analysis. The sediment cores were split and analyzed for paleoclimate proxy indicators, including geochemical composition, sedimentary structure, and macrofossil content (that which is visible without a microscope). The amount of water in a lake is directly related to its depth. Therefore, a loss in water during droughts is recorded by drop in lake levels, whereas wet periods are characterized by deep waters.

Using these proxy indicators, the researchers were able to make inferences about past variations in the balance between precipitation and evaporation in the southern Yukon. A comparison of the lake-level proxies with a previously developed fossil pollen record from the same lake found that rapid vegetation changes over the Holocene also occurred during shifts in the precipitation/evaporation balance, suggesting hydrologic conditions played an integral role in the evolution of the Yukon’s ecosystem. The development of unique shallow-water sediment at the deep-water core site indicated that lake levels dropped significantly during a “megadrought” in the early Holocene.

“About 8,400 years ago, the lake almost dried out,” said Pompeani. “We documented the timing of this drought and studied its transition to conditions more typical of what we observed in the late Holocene.”

Pitt’s study, says Pompeani, contributes to the long-term perspective on natural climate variability that is needed to understand historically unprecedented changes now occurring in the Arctic. Rapid changes in the Arctic climate system that occurred in the relatively recent past can be compared with climate models to improve the understanding of the processes responsible for such nonlinear changes.

Funding for this project was provided by the National Science Foundation.

The Holocene climate project focuses on climate records from the last 8,000 years, including two focus regions: eastern Beringia and the northwest Atlantic. For more information on the Holocene climate project, visit www.arcus.org/synthesis8k/index.php.

[Source: University of Pittsburgh press release]