Spatial Econometric Models for Panel Data

2005 ◽  
Vol 1902 (1) ◽  
pp. 80-90 ◽  
Author(s):  
Christopher Frazier ◽  
Kara M. Kockelman
Keyword(s):  
Land Cover ◽  
Satellite Images ◽  
Agricultural Land ◽  
Population Data ◽  
Demographic Variables ◽  
Vehicle Ownership ◽  
Spatial Econometric ◽  
Spatial Econometric Models ◽  
Land Cover Data ◽  
Complicated Task

Cities are constantly evolving, complex systems, and modeling them, both theoretically and empirically, is a complicated task. However, understanding the manner in which developed regions change over time and space can be important for transportation researchers and planners. In this paper, methodologies for modeling developed areas are presented, and spatial and temporal effects of the data are incorporated into the methodologies. The work emphasizes spatial relationships between various geographic, land use, and demographic variables that characterize fine zones across regions. It derives and combines land cover data for the Austin, Texas, region from a panel of satellite images and U.S. Census of Population data. Models for population, vehicle ownership, and developed, residential, and agricultural land cover are estimated; the effects of space and time on the models are shown to be statistically significant. Simulations of population and land cover for the year 2020 help to illustrate the strengths and limitations of the models.

scholarly journals Regionalisation of asset values for risk analyses

2006 ◽  
Vol 6 (2) ◽  
pp. 167-178 ◽  
Author(s):  
A. H. Thieken ◽  
M. Müller ◽  
L. Kleist ◽  
I. Seifert ◽  
D. Borst ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Census Data ◽  
Population Data ◽  
Dasymetric Mapping ◽  
Unit Value ◽  
Land Cover Data ◽  
Mapping Techniques ◽  
Asset Data

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.

scholarly journals Land-Use/Land-Cover Change and Anthropogenic Causes Around Koupa Matapit Gallery Forest, West-Cameroon

2018 ◽  
Vol 10 (2) ◽  
pp. 56 ◽  
Author(s):  
Marie Caroline Solefack Momo ◽  
Andre Ledoux Njouonkou ◽  
Lucie Felicite Temgoua ◽  
Romuald Djouda Zangmene ◽  
Junior Baudoin Wouokoue Taffo ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Satellite Images ◽  
Agricultural Land ◽  
Local Population ◽  
Forest Products ◽  
Anthropogenic Factors ◽  
Significant Implication ◽  
Gallery Forest

This study assesses land cover change of the Koupa Matapit forest gallery, West Cameroon, in relation to anthropogenic factors. Ethnobotanical surveys were conducted to investigate the relationships between the local population and the gallery forest; the spatio-temporal dynamics of the landscapes around the gallery forest were studied from the diachronic analysis of three Landsat TM satellite images of 1984, Landsat ETM + 1999 and Landsat OLI_TIRS of 2016, supplemented by verification missions on field. The satellite images were processed using ArcGIS and Erdas Imagine software. According to surveys, it should be noted that agriculture and livestock are the main economic activities of the population of Koupa Matapit, agriculture and fuel wood collection for energy were the main anthropogenic activities responsible for deforestation and degradation of the forest gallery. The collection of non-timber forest products (NTFPs) would have a significant implication in land use and cover changes. The results indicate that the extension of savannah/agricultural land (from 6989 ha in 1984 to 7604 ha in 2016) and bare soil/built up area (from 71 ha in 1984 to 342 ha in 2016) would have led to the disappearance of much of the forest area (1465 ha in 1984 to 580 ha in 2016). The rapid population growth of Koupa Matapit would be responsible for these pressures. There is an urgent need to implement appropriate land use policy in this area.

Hal Shelton Revisited: Designing and Producing Natural-Color Maps with Satellite Land Cover Data

2004 ◽  
pp. 28-55 ◽  
Author(s):  
Tom Patterson ◽  
Nathaniel Vaughn Kelso
Keyword(s):  
Twentieth Century ◽  
Land Cover ◽  
Satellite Images ◽  
Physical Maps ◽  
Full Color ◽  
Natural Color ◽  
Land Cover Data ◽  
Adobe Photoshop ◽  
Data Yield

This paper examines natural-color maps by focusing on the painted map art of Hal Shelton, the person most closely associated with developing the genre during the mid twentieth century. Advocating greater use of natural-color maps by contemporary cartographers, we discuss the advantages of natural-color maps compared to physical maps made with hypsometric tints; why natural-color maps, although admired, have remained comparatively rare; and the inadequacies of using satellite images as substitutes for natural-color maps. Seeking digital solutions, the paper then introduces techniques for designing and producing natural-color maps that are economical and within the skill range of most cartographers. The techniques, which use Adobe Photoshop software and satellite land cover data, yield maps similar in appearance to those made by Shelton, but with improved digital accuracy. Full-color illustrations show examples of Shelton’s maps and those produced by digital techniques.

scholarly journals Analysis of Forest Deforestation and its Driving Factors in Myanmar from 1988 to 2017

2019 ◽  
Vol 11 (11) ◽  
pp. 3047 ◽  
Author(s):  
Rongfeng Yang ◽  
Yi Luo ◽  
Kun Yang ◽  
Liang Hong ◽  
Xiaolu Zhou
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Agricultural Land ◽  
Temporal Evolution ◽  
Driving Factors ◽  
Deforestation Rate ◽  
Land Cover Data ◽  
Spatio Temporal ◽  
Landsat Satellite

Myanmar, abundant in natural resources, is one of the countries with high forest cover in Southeast Asia. Along with its rapid socio-economic development, however, the construction of large-scale infrastructure, expansion of agricultural land, and an increasing demand for timber products have posed serious threats to the forests and significantly affected regional sustainable development. However, the geographical environment in Myanmar is complex, resulting in the lack of long-term sequence of land cover data products. Based on 30 years’ Landsat satellite remote sensing imagery data and the land cover data extracted by a mixed classification method, this paper examined the spatial and temporal evolution characteristics of forest cover in Myanmar and investigated driving factors of the spatio-temporal evolution. Results show that the forest cover has decreased by 110,621 km2 in the past 30 years with the annual deforestation rate of 0.87%. Cropland expansion is the main reason for the deforestation throughout the study period. The study can provide basic information of the forest cover data to the Myanmar government for ecological environment protection. At the same time, it can provide important support to the “Belt and Road” initiative to invest in the region’s economy.

scholarly journals Land Cover Changes in Ghana over the Past 24 Years

2021 ◽  
Vol 13 (9) ◽  
pp. 4951
Author(s):  
Peter A. Y. Ampim ◽  
Michael Ogbe ◽  
Eric Obeng ◽  
Edwin K. Akley ◽  
Dilys S. MacCarthy
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
European Space Agency ◽  
Original Data ◽  
Bare Area ◽  
The Past ◽  
Space Agency ◽  
Land Cover Data ◽  
Emerging Issues ◽  
Wide Scale

Changes in land cover (LC) can lead to environmental challenges, but few studies have investigated LC changes at a country wide scale in Ghana. Tracking LC changes at such a scale overtime is relevant for devising solutions to emerging issues. This study examined LC changes in Ghana for the past almost two and half decades covering 1995–2019 to highlight significant changes and opportunities for sustainable development. The study used land cover data for six selected years (1995, 2000, 2005, 2010, 2015, and 2019) obtained from the European Space Agency. The data was analyzed using R, ArcGIS Pro and Microsoft Excel 365 ProPlus. The original data was reclassified into eight LC categories, namely: agriculture, bare area, built-up, forest, grassland, other vegetation, waterbody, and wetland. On average, the results revealed 0.7%, 131.7%, 23.3%, 46.9%, and 11.2% increases for agriculture, built-up, forest, waterbody, and wetland, respectively, across the nation. However, losses were observed for bare area (92.8%), grassland (51.1%), and other vegetation (41%) LCs overall. Notably, agricultural land use increased up to 2015 and decreased subsequently but this did not affect production of the major staple foods. These findings reveal the importance of LC monitoring and the need for strategic efforts to address the causes of undesirable change.

scholarly journals Impact of Land Use Land Cover Change on Coastal Tourism in Kundapura, Karnataka, Using Multi-temporal Remotely Sensed Data and GIS Techniques

2018 ◽  
Vol 13 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Shekar Naik ◽  
H Gangadhara Bhat ◽  
T N Sreedhara
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Agricultural Land ◽  
Coastal Development ◽  
Land Use Land Cover ◽  
Coastal Tourism ◽  
Remotely Sensed Data ◽  
Erdas Imagine ◽  
Multi Temporal

The present study is an attempt to examine the Land Use Land Cover changes in parts of Kundapura Taluk in Karnataka for the period 2006 and 2016 and its impact on coastal tourism. IRS satellite images of 2006 and 2016 have been used and processed using ERDAS Imagine and ArcGIS. The result indicated tremendous changes, particularly in mixed urban and agricultural land and proved that RS/GIS has advantages over conventional techniques. The result obtained, based on the multi-dated satellite data study, will assist in decision making and help to take appropriate measures to monitor and regulate coastal development in order to achieve sustainable and integrated coastal development.

scholarly journals Land Use and Land Cover Detection by Different Classification Systems using Remotely Sensed Data of Kuala Tiga, Tanah Merah Kelantan, Malaysia

2017 ◽  
Vol 5 (3) ◽  
pp. 145-151
Author(s):  
Wani Sofia Udin ◽  
Zuhaira Nadhila Zahuri
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Classification System ◽  
Supervised Classification ◽  
Satellite Images ◽  
Agricultural Land ◽  
Unsupervised Classification ◽  
Land Cover Classification ◽  
Classification Systems

Land use and land cover classification system has been used widely in many applications such as for baseline mapping for Geographic Information System (GIS) input and also target identification for identification of roads, clearings and also land and water interface. The research was conducted in Kuala Tiga, Tanah Merah, Kelantan and the study area covering about 25 km2. The main purpose of this research is to access the possibilities of using remote sensing for the detection of regional land-use change by developing a land cover classification system. Another goal is to compare the accuracy of supervised and unsupervised classification systems by using remote sensing. In this research, both supervised and unsupervised classifications were tested on satellite images of Landsat 7 and 8 in the years 2001 and 2016. As for supervised classification, the satellite images are combined and classified. Information and data from the field and land cover classification are utilized to identify training areas that represent land cover classes. Then, for unsupervised classification, the satellite images are combined and classified by means of unsupervised classification by using an Iterative Self- Organizing Data Analysis Techniques (ISODATA) algorithm. Information and data from the field and land cover classification are utilized to assign the resulting spectral classes to the land cover classes. This research was then comparing the accuracy of two classification systems at dividing the landscape into five classes; built-up land, agricultural land, bare soil, forest land, water bodies. Overall accuracies for unsupervised classification are 36.34 % for 2016 and 51.76% for 2001 while for supervised classification, accuracy assessments are 95.59 % for 2016 and 96.29 % for 2001.

scholarly journals Pressions Anthropiques Et Dynamique D’occupation Des Terres Dans Le Terroir De Ziguéna, Zone Cotonnière Du Mali

2016 ◽  
Vol 12 (5) ◽  
pp. 90
Author(s):  
Abdou Ballo ◽  
Souleymane Sidi Traoré ◽  
Baba Coulibaly ◽  
Cheick Hamalla Diakité ◽  
Moriké Diawara ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Population Data ◽  
Natural Vegetation ◽  
Rate Of Change ◽  
Visual Interpretation ◽  
Anthropogenic Pressures ◽  
Landsat Images ◽  
Comparison Of The Results

In Ziguéna terroir, the combined effects of drought and anthropogenic actions led to the widespread degradation of vegetation cover and of land. This work aimed at characterizing the dynamics of land use and land cover in relation to anthropogenic pressures in Ziguéna terroir. The methodology consisted in identifying and characterizing land use and land cover classes. Landsat images for the years 1986 and 2013 and population data for the years 1987, 1998 and 2009 were used. Visual interpretation of the images and post-classification comparison of the results were used to generate land use and land cover classes and calculate their rate of change. The results reveal that the natural vegetation has lost 55% of its original coverage (1514.3 ha) between 1987 and 2013. During the same period, the agricultural area increased by 47% (1608 ha). The projection of land use and land cover classes predicted an increase of agricultural land of about 34.60% by year 2030 compared to its coverage of year 2013 (+1191.03 ha) at the expense of natural vegetation which will lose about 40.63% of its coverage (-1121.70 ha). The dynamics of agricultural land is strongly linked to population growth rates with a correlation coefficient r equal to 0.99. This confirms a strong anthropogenic influence on land use and land cover dynamics. The results show the usefulness of remote sensing for mapping land use and land cover. Nevertheless it would be interesting to take into account the socioeconomic aspects for proper understanding of the dynamics.

scholarly journals Temporal Changes of Land Cover in Relation to Chosen Environmental Variables in Different Types of Landscape

2010 ◽  
Vol 14 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Maria Zachwatowicz ◽  
Tomasz Giętkowski
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Land Cover Changes ◽  
Lake District ◽  
Land Cover Data ◽  
Starting Point ◽  
Different Types ◽  
Topographical Maps ◽  
Modelling And Forecasting

Abstract Good understanding of relations between historical land cover changes and accompanying environmental components should be a starting point for landscape modelling and forecasting its future patterns. Analysis presented here focuses on the relationships between chosen environmental conditions and agricultural land cover changes in the period of over 150 years. The study area consisted of fragments of Nidziańska Basin and South Pomeranian Lake District macroregions. The land cover data was derived from a number of archival and contemporary topographical maps. Long-term changes of land cover were then related to underlying landscape elements (geological deposits and morphometric landforms). With the help of canonical analysis major correlations were identified and described.

Sign in / Sign up

Export Citation Format

Share Document