Designing spatially cohesive reserves with backup coverage (SCoRe-BC) – Python
Data for the case study(zipped): weareGrassland
- weareGrass_Area.txt: information on each patch, including ID, location and area
- weareGrass_weight.txt: information of biodiversity for each patch
- weareGrass_Dist.txt: distance between each patch, using vertices
Python code to generate LP file: CaseStudyCplex
Python code to solve by genetic algorithm CaseStudyGeneticAlgorithm
Python code to solve by genetic algorithm (given of reserves) CaseStudyGeneticAlgorithmGivenCluster
Space-Time Kernel Density Estimation (STKDE) – Python
Link to Python Code [PDF]
Link to Python Code [PDF]
STKDE, Python, Voxler
References:
Delmelle, E., Dony, C., Casas, I., Jia, M., & Tang, W. (2014). Visualizing the impact of space-time uncertainties on dengue fever patterns. International Journal of Geographical Information Science, 28(5), 1107-1127.
Delmelle, E., Dony, C., Casas, I., Jia, M., & Tang, W. (2014). Visualizing the impact of space-time uncertainties on dengue fever patterns. International Journal of Geographical Information Science, 28(5), 1107-1127.
Delmelle, E., Jia, M., Dony, C., Casas, I., & Tang, W. (2015). Space-time visualization of dengue fever outbreaks. in: Kanaroglou P., Delmelle E. and A. Paez (Eds): Spatial analysis in health geography. Ashgate.