A Dynamic GIS as an Efficient Tool for Integrated Coastal Zone Management

isprsISPRS International Journal of Geo-Information 2014, 3(2), 391-407

By Françoise Gourmelon, Damien Le Guyader, and Guy Fontenelle

“This contribution addresses both the role of geographical information in participatory research of coastal zones, and its potential to bridge the gap between research and coastal zone management. Over a one year period, heterogeneous data (spatial, temporal, qualitative and quantitative) were obtained which included the process of interviews, storing in a spatio-temporal database.

Activity zones for supervised maritime activities in the Bay of Brest (A) and boats density

Activity zones for supervised maritime activities in the Bay of Brest.

“The GIS (Geographic Information System) produced temporal snapshots of daily human activity patterns allowing it to map, identify and quantify potential space-time conflicts between activities. It was furthermore used to facilitate the exchange of ideas and knowledge at various levels: by mapping, simulation, GIS analysis and data collection. Results indicated that both captured data and the participatory workshop added real value to management and therefore it was deemed well managed by stakeholders. To incorporate a dynamic GIS would enhance pro-active integrated management by opening the path for better discussions whilst permitting management simulated scenarios. ”

Scientists Use LiDAR, 3-D Modeling Software to Intricately Map Active Chinese Fault Zone

Chinese and American scientists collaborating in the study of an active seismic fault that produced one of China’s most deadly earthquakes say their deployment of an airborne LiDAR system, which uses pulses of laser light to calculate distances and chart terrain features, has helped them produce the most precise topographical measurements ever of the fault zone.

“Light detection and ranging (LiDAR) presents a new approach to build detailed topographic maps effectively,” they report. They add that these high-precision three-dimensional models can be used to illustrate not only land surface changes following past quakes, but also features of past ruptures that could point to the possibility of future temblors.

Experts at the State Key Laboratory of Earthquake Dynamics and at the National Earthquake Infrastructure Service in Beijing, working with a colleague at the United States Geological Survey (USGS) in Pasadena, California, mounted a Leica ALS-60 LiDAR system aboard a Chinese Yun Five aircraft and then began scanning the Haiyuan fault zone in a series of flights over the course of a week. The fault zone is similar to the San Andreas fault in California, which has similarly been scanned and studied as a comparison.

“During the past century,” they explain in a new study, “the Haiyuan fault zone produced two great earthquakes: the M 8.5 Haiyuan earthquake in 1920, along the eastern Haiyuan fault, and the M 8𔃆.3 Gulang earthquake in 1927.”

“The Haiyuan earthquake of 16 December 1920 is one of the largest intra- continental earthquakes ever documented in history,” they add, “and ruptured about a 237-kilometer-long ground surface, with a maximum left-lateral slip of 10.2 m, and claimed over 220,000 lives.”

In the new study, “Quantitative study of tectonic geomorphology along the Haiyuan fault based on airborne LiDAR,” lead scientist Jing Liu and her colleagues at the Earthquake Dynamics Lab, part of the China Earthquake Administration in Beijing, state their experiments with the LiDAR scanning system and related building of a high-resolution topographical model provide “an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards.”

Sections of the 3D digital model generated with the LiDAR data are “intensively analyzed to demonstrate tectonic geomorphic feature identification and displacement measurement,” they state. The LiDAR data are also used, for example, to calculate horizontal and vertical coseismic offsets in one section of the fault zone.

LiDAR data can be used to verify measurements made during fieldwork on offsets of tectonic landform features, state co-authors Tao Chen, Pei Zhen Zhang, Jing Liu, Chuan You Li, and Zhi Kun Ren, along with Ken Hudnut at the USGS, who visited the China Earthquake Administration to participate in this study. “The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain fault displacement measurements quantitatively,” they explain.

With LiDAR-generated digital models of the topography across fault zones, the “link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards,” says the team of scientists.

More precise measurements of the active fault zone made possible by the LiDAR system, and their depiction in sophisticated three-dimensional maps, are helping scientists not only in basic research, but also in terms of calculating the probability of a seismic shock recurring, say the co-authors of the new study, which was published online in the journal Chinese Science Bulletin by Science China Press and Springer-Verlag.

Airborne laser swath mapping helps scientists to virtually remove the vegetation covering from topographical models; this “bare earth” representation provides for more accurate identification of tectonic features and changes following a quake.

A LiDAR airborne scanning system of the Earth’s terrain was deployed over the section of the southwestern Chinese province of Sichuan that was the epicenter of a Mw7.9 earthquake that struck in May of 2008; LiDAR data were used to map the scale of landslides and ultimately to develop rescue schemes.

In the new study, the Chinese and American scientists say that digital models created using LiDAR data from the Haiyuan fault zone “have a much higher resolution than existing topographic data and most aerial photographs, allowing us to map the locations of fault traces more accurately than ever.”

The high level of precision of the digital models constructed with information from the LiDAR laser scans of the topography in this fault zone will encourage future “site-specific fault activity studies,” state the scientists.

“In the future,” they predict, “we can expect that more and more concepts or models of fault activity would benefit from this unprecedented survey technique.”

Along the Haiyuan fault zone in the western Chinese province of Gansu, LiDAR scans and related digital models have already been used to identify 600 channels and other linear geomorphic features slated for more comprehensive analysis.

“The next step is to measure the displacements along the whole Haiyuan fault and analyze the principle of the slip distribution,” states the team of scientists, “which would help people better understand the fundamental link between fault activity and large earthquakes and assess potential risk for future earthquake hazards.”

In places where slip during past earthquakes was less pronounced, it is possible that future earthquakes could have greater slip in order to accommodate and equalize motions along the fault system. Alternatively, slip may be large repeatedly in some places and small elsewhere. Such variations in slip may help to assess future hazards, so observations of this kind are very important to answer unresolved questions that are central to research on hazards of earthquake fault zones around the world.

[Source: Science China Press]

GEOFIM: A WebGIS Application for Integrated Geophysical Modelling in Active Volcanic Regions

Computers & GeosciencesComputers & Geosciences, Accepted 02 May 2014

By Gilda Currenti, Rosalba Napoli, Antonino Sicali, Filippo Greco, and Ciro Del Negro

“We present GEOFIM (GEOphysical Forward/Inverse Modeling), a WebGIS application for integrated interpretation of multiparametric geophysical observations. It has been developed to jointly interpret scalar and vector magnetic data, gravity data, as well as geodetic data, from GPS, tiltmeter, strainmeter and InSAR observations, recorded in active volcanic areas. GEOFIM gathers a library of analytical solutions, which provides an estimate of the geophysical signals due to perturbations in the thermal and stress state of the volcano. The integrated geophysical modeling can be performed by a simple trial and errors forward modeling or by an inversion procedure based on NSGA-II algorithm. The software capability was tested on the multiparametric data set recorded during the 2008-2009 Etna flank eruption onset. The results encourage to exploit this approach to develop a near-real-time warning system for a quantitative model-based assessment of geophysical observations in areas where different parameters are routinely monitored.”

Spatio-temporal Analysis of Abundances of Three Malaria Vector Species in Southern Benin using Zero-truncated Models

pnvParasites & Vectors 2014, 7:103 , Published Online 12 March 2014

By Nicolas Moiroux, Armel Djènontin, Abdul S Bio-Bangana, Fabrice Chandre, Vincent Corbel, and Hélène Guis


A better understanding of the ecology and spatial-temporal distribution of malaria vectors is essential to design more effective and sustainable strategies for malaria control and elimination. In a previous study, we analyzed presence-absence data of An. funestus, An. coluzzii, and An. gambiae s.s. in an area of southern Benin with high coverage of vector control measures. Here, we further extend the work by analysing the positive values of the dataset to assess the determinants of the abundance of these three vectors and to produce predictive maps of vector abundance.


Positive counts of the three vectors were assessed using negative-binomial zero-truncated (NBZT) mixed-effect models according to vector control measures and environmental covariates derived from field and remote sensing data. After 8-fold cross-validation of the models, predictive maps of abundance of the sympatric An. funestus, An. coluzzii, and An. gambiae s.s. were produced.


Cross-validation of the NBZT models showed a satisfactory predictive accuracy. Almost all changes in abundance between two surveys in the same village were well predicted by the models but abundances for An. gambiae s.s. were slightly underestimated. During the dry season, predictive maps showed that abundance greater than 1 bite per person per night were observed only for An. funestus and An. coluzzii. During the rainy season, we observed both increase and decrease in abundance of An. funestus, which are dependent on the ecological setting. Abundances of both An. coluzzii and An. gambiae s.s. increased during the rainy season but not in the same areas.



Our models helped characterize the ecological preferences of three major African malaria vectors. This works highlighted the importance to study independently the binomial and the zero-truncated count processes when evaluating vector control strategies. The study of the bio-ecology of malaria vector species in time and space is critical for the implementation of timely and efficient vector control strategies.”

Spatial Distribution and Conservation of Speckled Hind and Warsaw Grouper in the Atlantic Ocean off the Southeastern U.S.

PLOS ONE, 19 November 2013

By Nicholas A. Farmer and Mandy Karnauskas

“There is broad interest in the development of efficient marine protected areas (MPAs) to reduce bycatch and end overfishing of speckled hind (Epinephelus drummondhayi) and warsaw grouper (Hyporthodus nigritus) in the Atlantic Ocean off the southeastern U.S. We assimilated decades of data from many fishery-dependent, fishery-independent, and anecdotal sources to describe the spatial distribution of these data limited stocks. A spatial classification model was developed to categorize depth-grids based on the distribution of speckled hind and warsaw grouper point observations and identified benthic habitats. Logistic regression analysis was used to develop a quantitative model to predict the spatial distribution of speckled hind and warsaw grouper as a function of depth, latitude, and habitat.

Point and spawning observations.

Point and spawning observations.

“Models, controlling for sampling gear effects, were selected based on AIC and 10-fold cross validation. The best-fitting model for warsaw grouper included latitude and depth to explain 10.8% of the variability in probability of detection, with a false prediction rate of 28–33%. The best-fitting model for speckled hind, per cross-validation, included latitude and depth to explain 36.8% of the variability in probability of detection, with a false prediction rate of 25–27%. The best-fitting speckled hind model, per AIC, also included habitat, but had false prediction rates up to 36%. Speckled hind and warsaw grouper habitats followed a shelf-edge hardbottom ridge from North Carolina to southeast Florida, with speckled hind more common to the north and warsaw grouper more common to the south. The proportion of habitat classifications and model-estimated stock contained within established and proposed MPAs was computed. Existing MPAs covered 10% of probable shelf-edge habitats for speckled hind and warsaw grouper, protecting 3–8% of speckled hind and 8% of warsaw grouper stocks. Proposed MPAs could add 24% more probable shelf-edge habitat, and protect an additional 14–29% of speckled hind and 20% of warsaw grouper stocks.”

Big Data Visual Analytics for Exploratory Earth System Simulation Analysis

Computers & Geosciences, 61 (2013) pp.71–82

Chad A.Steed, Daniel M. Ricciuto, Galen Shipman, Brian Smith, Peter E.Thornton,
Dali Wang, Xiaoying Shi, and Dean N. Williams


  • EDEN is freely available and was developed in close collaboration with climate scientists.
  • EDEN employs interactive visualizations and statistical analytics for understanding of earth system simulations and climate change.
  • Bridges the growing gap between viable visualization techniques and real-world climate analysis.
  • Exploratory analysis of real-world CLM data sets using interactive parallel coordinates and other coordinated views augmented by statistical analytics.
  • Visualizations permit visually forming multi-faceted selections using information scent to guide the scientist to the most promising relationships.
“Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called “big data” analysis challenges. However, conventional climate analysis techniques are inadequate in dealing with the complexities of today’s data. In this paper, we describe and demonstrate a visual analytics system, called the Exploratory Data analysis ENvironment (EDEN), with specific application to the analysis of complex earth system simulation data sets.
An early version of EDEN is used to visually analyze a 1000 simulation CLM4 point ensemble data set with 81 parameters and 7 output variables on ORNL's EVEREST power wall facility which offers 11,520×3072 (35 million) pixels.

An early version of EDEN is used to visually analyze a 1000 simulation CLM4 point ensemble data set with 81 parameters and 7 output variables on ORNL’s EVEREST power wall facility which offers 11,520×3072 (35 million) pixels.

“EDEN represents the type of interactive visual analysis tools that are necessary to transform data into insight, thereby improving critical comprehension of earth system processes. In addition to providing an overview of EDEN, we describe real-world studies using both point ensembles and global Community Land Model Version 4 (CLM4) simulations.”

Spatial Assessment of Attitudes Toward Tigers in Nepal

AMBIOAMBIO: A Journal of the Human Environment, Published Online 09 July 2013

Neil H. Carter, Shawn J. Riley, Ashton Shortridge, Binoj K. Shrestha, and Jianguo Liu

“In many regions around the world, wildlife impacts on people (e.g., crop raiding, attacks on people) engender negative attitudes toward wildlife. Negative attitudes predict behaviors that undermine wildlife management and conservation efforts (e.g., by exacerbating retaliatory killing of wildlife). Our study (1) evaluated attitudes of local people toward the globally endangered tiger (Panthera tigris) in Nepal’s Chitwan National Park; and (2) modeled and mapped spatial clusters of attitudes toward tigers. Factors characterizing a person’s position in society (i.e., socioeconomic and cultural factors) influenced attitudes toward tigers more than past experiences with tigers (e.g., livestock attacks).

Maps showing percentage of respondents per ward that (a) had <8 years of education, (b) were from lower caste Hindu and Terai Tibeto-Burmese ethnic groups, (c) were female, and (d) reported that a tiger had threatened/attacked a family member in the past. Percentage categories were defined by equal intervals.

Maps showing percentage of respondents per ward that (a) had

“A spatial cluster of negative attitudes toward tigers was associated with concentrations of people with less formal education, people from marginalized ethnic groups, and tiger attacks on people. Our study provides insights and descriptions of techniques to improve attitudes toward wildlife in Chitwan and many regions around the world with similar conservation challenges.”

Understanding Spatial Filtering for Analysis of Land Use-transport Data

Journal of Transport GeographyJournal of Transport Geography, Volume 31, July 2013, Pages 123–131

Yiyi Wang, Kara M. Kockelman, Xiaokun (Cara) Wang


  • We explore use of spatial filtering (SF) for regression model estimation.
  • We compare SF models and SAR-type models, and a distance decay parameter.
  • Data sets contain appraised values for private properties across Texas’ Travis County.
  • SF methods allow focus on the marginal effects of policy variables and other covariates.

“This paper summarizes the literature on spatial filtering (SF) for analysis of spatial data. Given the scarcity of its application in transportation and its fledgling nature, preliminary case studies were conducted using continuous and discrete response data sets, for land values and land use, in comparison with results from spatial autoregressive (SAR) models with distance decay parameters estimated using Bayesian techniques. For both the continuous land value and binary land use cases, the SF approach demonstrates great potential as a worthy competitor to more conventional SAR-based models. In addition to offering high fit statistics, somewhat shorter computing times, and more straightforward computations, the SF approach makes explicit the patterns of spatial dependency in the land value and land use data. By controlling for these spatial relationships, the SF approach yields more reliable marginal effects of policy variables of interest. Model results confirm the important role of transportation access (as quantified using distances to a region’s central business district, and various roadway types).”

Living near High-voltage Power Lines: GIS-based Modeling of the Risk in Nigeria’s Benin Region

Applied GIS, 2013; 9(1), 1-20

Felix Ndidi Nkeki

“This paper demonstrates the capabilities of Geographic Information System (GIS) methods for identifying populations which are both exposed to Electromagnetic Fields (EMFs) and at risk of electrocution because they live within the zone of potential risk around power lines in the Benin region GIS buffering, overlay and address geo-coding were used to generate a database consisting of both spatial and non-spatial information from which it was possible to holistically visualize the areal extent of population at risk. Potential risk areas were classified into zones of double risk and single risk, and of the approximately 20 per cent of the built-up area that was shown to be exposed to electromagnetic radiation, double-risk zones accounted for 51 per cent of this and single-risk zones 49 per cent. Also, the majority of exposed zones were found to be in high-density, residential areas located in the periphery of the region. It is evident that our GIS-assisted database will enhance future epidemiologic research and serve as a framework for effective decision making.”

The Steady-state Mosaic of Disturbance and Succession across an Old-growth Central Amazon Forest Landscape

PNAS-4.coverPNAS, 28 January 2013

Jeffrey Q. Chambers, Robinson I. Negron-Juarez, Daniel Magnabosco Marra, Alan Di Vittorio, Joerg Tews, Dar Roberts, Gabriel H. P. M. Ribeiro, Susan E. Trumbore, and Niro Higuchi

“Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomass⋅ha−1⋅y−1 were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1–16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.”