The Normalized Difference Vegetation Index (NDVI): Unforeseen Successes in Animal Ecology

This authors of this review article discuss the latest applications for the Normalized Difference Vegetation Index (NDVI) for ecological research. Since its development in 1981, researchers have greatly expanded the breadth of this technology's utility for studies of the natural world. NDVI has been established as a central tool for the assessment of historical and future biodiversity consequences resulting from changes in climate, vegetation cycling, and primary productivity of plants. This is made possible, even in areas with sparse vegetation, by NDVI's ability to utilize climate models that compile information from historical patterns of vegetation dynamics and from anticipated trends in changing climates to make predictions about the most likely effects on habitat biodiversity.

NDVI technology, however, does have some limitations for its ability to accurately explore the link between climatic variation and ecological processes. Since the collection of NVDI satellite data began in 1981, that is the most historical records it can draw from, which create the possibility that the models constructed by this technology will unreliably represent ecological factors that change on a slower time-scale. Another potential hurdle that researchers implementing NVDI technology must address is the accurate portrayal of human impact on ecosystems, because this is the primary threat to their persistence. Much of the limitations raised by the reviewers of this articles are said to be effectively mitigated if accurate ecosystem data from outside NDVI databases are used to supplement study efforts and refine the renderings of associated climate models. Emphasis on interdisciplinary study efforts between ecology, geophysics, and remote sensing is also mentioned as an additional means of promoting more accurate use of satellite data for ecological research applications.  

Pettorelli, N., Ryan, S., Mueller, T., Bunnefeld, N., Jędrzejewska, B., Lima, M., & Kausrud, K. (2011). The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology. Climate Research, 46(1), 15-27.

Neighbourhoods and health: a GIS approach to measuring community resource accessibility

This study, conducted by Jamie Pearce, Karen Witten, Phil Bartie, looked at how accessible different communities were to different health related resources. They examined different resources such as: shopping, education, recreation, food stores, and health facilities. They broke down a map of an area like Christchurch by neighborhoods and looked at how far it would take different people in different neighborhoods to get to places.



They continued to use maps like this to come up with a general census of how far people are from these community resources. They found when looking at New Zealand as a whole the travel time for people coming from 'low accessibility' neighborhoods 23.22 minutes while coming from 'high accessibility' to being only 2.83 minutes. Although this is a very large gap this study examined different neighborhoods all across New Zealand both urban and rural.




Pearce, J., Witten, K., & Bartie, P. (2006). Neighbourhoods and health: a GIS approach to measuring community resource accessibility. Journal of epidemiology and community health, 60(5), 389-395.

Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention

This article discusses the pandemic of a novel strain of H1N1 swine-origin influenza A virus that emerged in the United States and Mexico in the spring of 2009. The ability of real-time reports of influenza-like illness symptoms and rapid influenza diagnostic tests were examined to approximate the spatiotemporal distribution of PCR-confirmed S-OIV cases for the purposes of focusing local intervention efforts.

The results suggested that influenza-like illness symptoms and rapid influenza diagnostic  spatiotemporal analysis may be useful in understanding the nature of S-OIV outbreaks in space and time. An understanding of  real-time intervention and control can effectively inform when and where local intervention should be focused and minimize outbreak impacts.

Wilson, J. G., Ballou, J., Yan, C., Fisher-Hoch, S. P., Reininger, B., Gay, J., . . . Calvillo, F. (2010). Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention. Health & Place,16(6), 1230-1239. doi:10.1016/j.healthplace.2010.08.010

GIS and Policy

GIS, Public Service, and the Issue of Democratic Governance:

Akhlaque Haque

In this essay, Haque discusses the role GIS can play in examining social, economic, and political circumstances, specifically in regards to how policy is implemented.  Within this, Haque introduces technocracy, which refers to a government in which technically trained experts influence society by virtue of their specialized knowledge and position. Essentially, throughout this, Haque takes the position that well trained experts in GIS have the opportunity to positively impact policy, if given the chance. Moreover, he argues that GIS should be engrained within public service in order to ensure accurate representation of economic disparities, racial lines, and political differences in regards to how people ought to be represented and governed. I don’t particularly agree with the notion of a technocracy, I think there is place for educated elites, and while I desire my governing body to be educated, I do not think it needs to be entirely controlled by the opinions of technicians. However, I do appreciate that there ought to be a larger space devoted to ensuring the discourse of how different people are actually being governed, and seeing that tangibly on a map is invaluable.  

Haque, A. (2001). GIS, Public Service, and the Issue of Democratic Governance. Public Administration Review, 61(3), 259-265. Retrieved from http://www.jstor.org/stable/977598

Effects of Urbanization on Mammal Species in the U.S.

Due to a rapidly growing population in the San Antonio and Austin areas, urbanization in central Texas has developed quickly over the past few years. Although current nature preserves live alongside these urbanized areas, it's important to research whether the development on the land will still have an impact on these mammals.

A study was conducted where researchers filmed with motion-activated cameras at 72 sites across 6 different regions throughout Austin and San Antonio. Ten different urbanizing factors were considered when concluding the influence of urbanization on medium-sized mammal species.

It was concluded that even though urbanization is ongoing and will develop over the years, natural preservations continue to provide a habitable area for many species. None of the 7 species studied showed a negative correlation with urbanization. This study highlights the importance of green spaces and natural havens to keep species thriving.

Haverland, M. B., & Veech, J. A. (2017). Examining the occurrence of mammal species in natural areas within a rapidly urbanizing region of Texas, USA. Landscape and Urban Planning, 157, 221-230.

Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods

Remote Sensing and GIS isn’t just for analyzing terrestrial environments.   A study by Vahtmae and Kutser (2013) use geospatial data and regression models to gain an understanding of the health of the Baltic sea.  The authors point out that, as one of the most polluted, the Baltic Sea’s ecological conditions need to be protected.  Due to the lack of information, insufficient data, and scientific resources, environmental planning has been limited and not very effective (Vahtmae, Kutser, 2013).

The health of a marine environment can often be evaluated by measuring benthic macrophyte habitats.  The authors indicate a reduction of the abundance of certain macroalgae, an indicator species in the Baltic Sea.  By using large-scale analysis of marine habitats, they will be able to gain a broader understanding of marine habitats and provide evidence with which to gain environmental change.

Since the Baltic Sea is a shallow marine environment with several terrestrial imputs, particulate matter, dissolved organic matter and phytoplankton blooms stay suspended large areas of the sea.  Image-based supervised classification techniques such as Maximum Likelihood, spectral Angle Mapper, can make it very difficult for certain types of remote sensing, not to mention time consuming and costly. 

This article describes several alternative approaches.  One such approach uses a modeled spectral library, in which remote sensing reflectances are compared to simulated reflectances. Though the known properties of the substrates and the optical properties of the water are necessary for this form of image classification and may negatively affect the accuracy.  The third approach, is a basic classification method such as Spectral Angle Mapper, or SAM which has no sensitivity to illumination or albedo effects.  With this method, one can change the accuracy and compare data with spectral library in the same instance. 

The study tested both image-based approach and spectral library approach.  Though the image-based method performed better than the spectral library method, they had to take into account that the turbidity of the water could change the results.   In evaluation of the data, the suitability of the two methods for shallow water habitat mapping show basically no difference between airborne hyperspectral and satellite multispectral data (Vahtmae, Kutser, 2013).

This is just one of many studies that show the use of GIS in monitoring the health of marine environments.  Due to more accurate means of evaluation, this could become key in maintaining a balanced ecosystem throughout our waters.

Vahtmäe, Ele, and Tiit Kutser. "Classifying the Baltic Sea shallow water habitats using image-based and spectral library methods." Remote Sensing 5, no. 5

(2013): 2451-2474.

FOOTBALL GAME ANALYSIS: A NEW APPLICATION AREA FOR CARTOGRAPHERS AND GI-SCIENTISTS?

With the rise in competition and battle for the top spots in competitive sports such as football, more data is needed. However, with the current state of data there is limited upward movement. This has caused an increase in a need for geo spatial data, that can be concluded by GIS work.

Using tracking data and event data, maps are able to be constructed to represent this data form the game. By first mapping the field itself, you can use spatial elements such as the players, ball, and referees to get spatial data. This blog analyzes that while it is in the beginning phases, the door is open for GIS to model a game more concretely than current practices in the future. The lacking knowledge is how this data can be connected to represent the game as a whole instead of "snapshots" of individual portions.

Kotzbek, G., & Kainz, W. (2014). Football Game Analysis: A New Application Area for Cartographers and GI-Scientists. In Proceedings (Vol. 1, pp. 299-306).

Drug Pricing in the US

An increasingly popular topic in our national news is the pricing of pharmaceutical drugs in North America. Our drug prices increase annually and are drastically higher in almost all categories than most, if not all other developed countries. Access to healthcare and price varies depending on your location in the United States but chronic eye disease does not vary from place to place. According to new Medicare data, the way doctors treat chronic eye disease does differ from location to location and those changes have major effects on personal and US budgets.

The map above shows the use of Lucentis a drug used to treat eye disease differs from area to area. The brightest reds show places where the vast majority of the money spent in treating the disease is spent on Lucentis; the deepest blues, shows places where most of the money spent treating the disease is spent on its cheaper alternatives.Such variety in treatment calls into question whether doctors are treating patients based on the best available evidence, or other considerations.

Rich, Steven. "These maps tell you everything that’s wrong with our drug pricing system." The Washington Post. WP Company, 11 Apr. 2014. Web. 27 Feb. 2017.

Mapping Micro-Urban Heat Islands using LANDSAT TM and a GIS

In this article, the author discusses how LANDSAT TM satellite data and GIS software were used to map micro-urban heat islands in a portion of Dallas, Texas. Unsupervised classifications were performed on a LANDSAT sub-scene to extract tree cover information which was merged with TM data to make a map showing the location of micro-urban heat islands and wooded areas. Heat islands are generally described as urban areas that produce higher than background surface temperatures associated with rural surroundings.  Major factors leading to the formation of heat islands include; the effects of street canyon geometry on radiation, the effects of thermal properties on heat storage release, and waste heat from residential and other buildings.

The study area within Dallas is named White Rock Lake. It contains both older and newer residential neighborhoods, major highways, shopping centers, a warehouse district, wooded areas, and a large lake, providing variable land cover with contrasting thermal regimes. The methodology for mapping out the area involves LANDSAT TM processing and classification, thermal map generation, and GIS merging and final map production.

In the figure above, the hot spots in the White Rock Lake area exist as heat island patterns with the warmest temperatures in the center and coolest temperatures around the edges.

After examining the maps, it was noted that hot spots throughout this urban area were radiative in nature. The hottest areas were where land use was associated with impervious cover such as a large warehouse district, asphalt parking lots and roads, and a large number of apartment complexes. Also, new neighborhoods were significantly warmer than older neighborhoods. The coolest areas were those with heavy tree cover, including the forested park just north of the lake.

LINK TO THE ARTICLE: http://www.sciencedirect.com/science/article/pii/0098300495000335

Aniello Cathy, Morgan Ken,  Busbey Arthur, and Newland Leo (1994). Mapping Micro-Urban Heat Islands Using LANDSAT TM And A GIS. Computers & Geoscience. Vol. 21, No.8. 

The effects of deforestation and climate variability on the streamflow of the Araguaia River, Brazil

From the 1970's to the 1990's the Araguaia River in Brazil had a huge increase in water discharge. This large increase was believed to correspond with the deforestation seen in the area.

In Brazil the Araguaia watershed has seen massive amounts of deforestation. The amount of deforestation in the twenty year study period was estimated to be as high as 55%. This amount of deforestation leads to dramatic hydrological changes in the area, such as increased runoff .

The conditions created by the deforestation has lead to a nearly 25% increase in water discharge from the river. This increase is even more astounding when compared to a increase of only 2.5% precipitation. Computer simulations of the changes over the years point to 2/3's of the increase come directly from Deforestation.

Effects of increased runoff.

• Larger river outputs 
• Increased erosion of sediment 
• Increased pollutants in the water 
• Increased vulnerability of flash flooding   

As a result of this the Brazilian Government has increased protection over deforestation. Proper management of the area along with protecting the area from deforestation will lead to a decline in the increase of runoff, and could even lead to a overall reduction of discharge.

 Coe, M. T., Latrubesse, E. M., Ferreira, M. E., & Amsler, M. L. (2011). The effects of deforestation and climate variability on the streamflow of the Araguaia River, Brazil. Biogeochemistry, 105(1-3), 119-131.