White Rock Lake and Micro Urban Heat Islands

Cathy Aniello, Ken Morgan, Arthur Busbey, and Leo Newland used LANDSAT TM and GIS to map micro-urban heat islands in Dallas, Tx. Specifically, the researchers looked at the White Rock Lake area which has diverse land cover including impervious cover, bare soil, grass, trees, and apartment buildings. Micro urban heat islands are different than heat islands. Heat islands are areas generalized as having higher temperatures than the surrounding rural areas. Micro urban heat islands (MUHI) are hot-spots within the city urban heat island. These researchers believed that increased tree cover would offset the effects of these MUHIs. They looked at satellite temperature readings from LANDSAT TM and found that areas with trees were not only cooler, but had a radiative cooling effect that extended well beyond the tree canopy. They found that the MUHIs also had a radiative heat effect. Interestingly, older apartments and housing areas were significantly cooler than newer ones due to their increased tree cover. The hottest areas in White Rock Lake were land uses associated with impervious cover such as a warehouse district, asphalt parking lots and roads, and the new apartment complexes on the West side of the lake. Big areas of bare soil and grass around the lake were also hot spots. The coolest areas were those with the most tree cover such as the heavily forested area to the North of the lake and the older apartments and residential areas and White Rock Lake. This data reinforces the idea that increased tree cover leads to cooling of surrounding areas and could be used to combat the heat island effect. The MUHIs are an average of 5 to 11 degrees Celsius warmer than their surroundings. Increasing tree cover in urban areas would not only help reduce temperatures but would also help sequester more carbon emissions and other pollutants (which are abundant in urban settings), help prevent runoff and soil erosion, as well as create visually pleasing green spaces.  

Aniello, C., Morgan, K., Busbey, A., & Newland, L. (1995). Mapping micro-urban heat islands using Landsat TM and a GIS. Computers & Geosciences,21(8), 965-969.

Measuring Insolation and Soil Temperature in the Rocky Mountains

Insolation, incoming solar radiation, is essential for life on Earth and is integral to physical, chemical, and biological processes in our world. Insolation has direct effects on water and energy balances and therefore indirectly affects evapotranspiration, photosynthesis, wind conditions, snow melt, as well as air and soil temperature. In this study the main focus was soil temperature. Pinde Fu and Paul M. Rich used digital elevation models (DEMs) and insolation models that accounted for a variety of variables including elevation, atmospheric conditions, and varied topography to create an insolation model for an area near the Rocky Mountain Biological Laboratory in Colorado. 

Digital Elevation Model for the study area

Most interpolation methods to this point are for use on broad scales such as country or continent, but a finer method for smaller areas is not as common. Variables such as elevation, surface orientation (slope), and vegetable cover end up creating a gradient of insolation that changes with the topography. Most methods of interpolating insolation require tremendous data input and computation which in turn require expensive and sophisticated software. Other methods tend to be inaccurate and don’t account for all the aforementioned variables. The goal of this study was to create high resolution temperature maps for the study area using a few measurements from high resolution insolation models. They used Solar Analyst to derive average solar conditions/insolation for the study area. They combined physical soil temperature data samples with their temperature model to calculate temperature gradients based on elevation, topography, and vegetation cover. The result was an accurate and high resolution temperature map of their study area. The temperature and insolation data have applications in both agriculture and forestry. Looking at and understanding the levels and distribution of inoslation over different topographies could be used to determine the best areas to plant crops or which areas of forest are at risk for fires.

 Finished soil temperature map

Fu, P., & Rich, P. M. (2002). A geometric solar radiation model with applications in agriculture and forestry. Computers and electronics in agriculture, 37(1), 25-35.

L’île d’Yeu, Un Espace Convoité : Développement et Aménagement

Comme pour mon dernier article, nous faisons un bond de près de 20 ans en arrière pour lever le voile sur cette étude. Il est question cette fois d’une charmante petite île sur la côte atlantique française, l’île d’Yeu. Cette île, comme la grande partie de la côte atlantique française, bénéficie d’une économie liée à la pêche depuis des années. Les changements apportés à cette île durant la dernière quarantaine d’années ont été très important et c’est pour cela que Patrick Pottier et Marc Robin ont trouvé intéressant de cartographier ces changements à l’aide du SIG.

Ils leur alors fallu prendre en compte un grand nombre de composantes pour construire un modèle simple d’organisation spatiale, d’organisation du territoire. Les deux composantes principales sont séparées en deux sphères interne et externe, où la sphère interne n’est autre que le paysage urbain, agricole et la végétation urbaine, alors que la sphère externe représente le milieu physique, la topographie, l'altitude et le contrôle anthropique. Ces informations ont été récoltées au travers des années afin de créer une carte représentative de l’année 1951 et une de l’année 1990.

Au final, une simple délimitation par polygone est utilisée pour cartographier les zones occupées par l’urbain et l’agricole.

Evolution de l'espace urbain

Evolution de l'agriculture

Deux cartes qui ne sont pas forcément compliquées à réaliser. Ce qui est plus complexe par contre, c’est toute la problématique que montre ces cartes. En effet, lorsque l’on analyse ces cartes, la perte de l’espace agricole au bénéfice de l’espace urbain. En effet, nous pouvons voir par rapport aux années une consommation de l’espace urbain sur l’espace agricole. Tout cela a commencé en 1951 avec l’explosion urbaine de l’île jusqu’en 1995 où 30% du territoire est occupé. C’est d’ailleurs avec ces statistiques que l’on comprend les raisons des changements sur l’île d’Yeu. Effectivement, c’est île a su tirer profit de sa situation favorable au tourisme alors que 51% de ses habitations sont des habitations secondaires.

En conclusion, le système d’information géographique aide à démontrer que l’île a bénéficié d’une économie touristique à la place de se concentrer sur les ressources naturelles. Cela explique l’expansion urbaine aussi importante en défaveur des espaces agricoles.

Reference: « L’île d’Yeu, Un Espace Convoité : Développement et Aménagement », Patrick Pottier et Marc Robin, Mappemonde, 1997.