Localized areal disaggregation for linking agricultural census data to remotely sensed land cover data

2000 ◽  
pp. 217-230
2006 ◽  
Vol 6 (2) ◽  
pp. 167-178 ◽  
Author(s):  
A. H. Thieken ◽  
M. Müller ◽  
L. Kleist ◽  
I. Seifert ◽  
D. Borst ◽  
...  

Abstract. In risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population density and a unit value of residential assets for whole Germany. A dasymetric mapping approach, which uses land cover data (CORINE Land Cover) as ancillary variable, was adapted and applied to regionalize aggregated census data that are provided for all communities in Germany. The results were validated by two approaches. First, it was ascertained whether population data disaggregated at the community level can be used to estimate population in postcodes. Secondly, disaggregated population and asset data were used for a loss evaluation of two flood events that occurred in 1999 and 2002, respectively. It must be concluded that the algorithm tends to underestimate the population in urban areas and to overestimate population in other land cover classes. Nevertheless, flood loss evaluations demonstrate that the approach is capable of providing realistic estimates of the number of exposed people and assets. Thus, the maps are sufficient for applications in large-scale risk assessments such as the estimation of population and assets exposed to natural and man-made hazards.


2016 ◽  
Vol 111 (12) ◽  
pp. 750-756 ◽  
Author(s):  
Antoine Adde ◽  
Isabelle Dusfour ◽  
Emmanuel Roux ◽  
Romain Girod ◽  
Sébastien Briolant

2017 ◽  
Vol 9 (1) ◽  
pp. 191-199 ◽  
Author(s):  
Martin Wegmann ◽  
Benjamin F. Leutner ◽  
Markus Metz ◽  
Markus Neteler ◽  
Stefan Dech ◽  
...  

2008 ◽  
Vol 353 (3-4) ◽  
pp. 322-334 ◽  
Author(s):  
Carsten Montzka ◽  
Morton Canty ◽  
Ralf Kunkel ◽  
Gunter Menz ◽  
Harry Vereecken ◽  
...  

Author(s):  
P. D. Wu ◽  
Y. Yin ◽  
C. M. Li

Abstract. Merging is an important operation for the generalization of land-cover data. However, current research often entails merging on a global perspective, which is not conducive to capturing the spatial characteristics of geographic objects with significant spatial structures, i.e., structured geographic objects. As such, this paper proposes an area merging method that can maintain the boundary characteristics of the structured geographic objects. First, we identify the structured geographic objects based on the description parameters of the spatial structure. Second, a Miter-type buffer transformation is introduced to extract the boundary of each structured geographic object, and area elements inside the boundary are processed with corresponding merging operations. Finally, the boundary of the structured geographic objects and the merging result of the area elements are inserted back into the aggregated result of the original land-cover data using the NOT operation. The proposed approach is experimentally validated using geographical condition census data for a city in southern China. The experimental validation indicates that the proposed approach not only reasonably identify the typical characteristics of structured geographic objects but also effectively maintains the boundary characteristics of these objects.


Author(s):  
P. D. Wu ◽  
Y. Yin ◽  
C. M. Li ◽  
X. L. Liu

Abstract. Aggregation is an important operation for the generalization of land-cover data. However, current research often entails aggregation on a global perspective, which is not conducive to capturing the spatial characteristics of geographic objects with significant spatial structures, i.e., structured geographic objects. Hence this paper proposes an area aggregation method that can maintain the boundary characteristics of the structured geographic objects. First, we identify the structured geographic objects based on the description parameters of the spatial structure. Second, a Miter-type buffer transformation is introduced to extract the boundary of each structured geographic object, and area elements inside the boundary are processed with corresponding aggregation operations. Finally, the boundary of the structured geographic objects and the aggregation result of the area elements are inserted back into the aggregated result of the original land-cover data using the NOT operation. The proposed approach is experimentally validated using geographical condition census data for a city in southern China. The experimental result indicates that the proposed approach not only reasonably identify the typical characteristics of structured geographic objects but also effectively maintains the boundary characteristics of these objects.


2013 ◽  
Vol 4 (3) ◽  
pp. 19-38
Author(s):  
Janice F. Dyer ◽  
Luke Marzen ◽  
Diane Hite

Landownership is an important form of wealth, especially in a natural-resource dependent region such as the Black Belt of Alabama. We examine the connection between property ownership, land cover, and the well-being of communities in Macon County, Alabama. This study is an exploratory application of geographic information systems to integrate information from property tax assessment records, land cover data, and a well-being index based on census data. Research questions regarding the relationships between socioeconomic well-being, land tenure, and land cover were tested on rural parcels 50 acres or larger (N=1418). Test results reveal statistically significant relationships between socioeconomic conditions and absentee ownership (both out-of-state and out-of-county) and land cover type (in particular, evergreen forestland). Analyses of research findings offer insight to the cultural-ecological connections within the Black Belt and prompts exploration of the notion of space as political.


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