Author:
Bo Li, Graeme G. Wilkinson & Souheil Khaddaj

Abstract.

Generalization is perhaps the most intellectually challenging task for cartographers. It has proved to be very difficult to automate. In this paper, a cell-based model is applied to GIS generalization, which represents a new methodology within the GIS context. Cellular Automata (CA) has found a place in many interesting real world applications, including the modeling and simulation of numerous systems, across many disciplines. CA has a number of unique advantages in geographical and environmental modeling. Thus, it has attracted growing attention in urban simulation because of its potential in spatial modeling. Geographical phenomena have extremely complex characteristics as a result of interactions among different components in a study area. CA provides a promising new approach to simulate and understand spatial phenomena. In this study, which is based on CA techniques, an extended neighborhood algorithm is used in the cell-based model to automatically generalize raster thematic maps derived from classified satellite images. An example of generalizing a land use map of Lisbon Bay in Portugal is given, which gives satisfactory results.

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http://www.geocomputation.org/2001/papers/li.pdf

Author:

1. CLAUDIA MARIA DE ALMEIDA
2. ANTONIO MIGUEL VIEIRA MONTEIRO
3. GILBERTO CAMARA
4. BRITALDO SILVEIRA
5. SOARES-FILHO
6. GUSTAVO COUTINHO CERQUEIRA
7. CASSIO LOPES PENNACHIN
8. MICHAEL BATTY

Abstract:

This paper is concerned with building up methodological guidelines for modelling urban land-use change through Geographical Information Systems, remote sensing imagery and Bayesian probabilistic methods. A medium-sized town in the west of Sa˜o Paulo State, Bauru, was adopted as a case study. Its urban structure was converted into a 100m6100m resolution grid and transition probabilities were calculated for each grid cell by means of the ‘weights of evidence’ statistical method and upon the basis of the information related to the technical infrastructure and socio-economic aspects of the town. The probabilities obtained from there fed a cellular automaton simulation model—DINAMICA—developed by the Centre for Remote Sensing of the Federal University of Minas Gerais (CSR-UFMG), based on stochastic transition algorithms. Different simulation outputs for the case study town in the period 1979–1988 were generated, and statistical validation tests were then conducted for the best results, employing a multiple resolution fitting procedure.  This modelling experiment revealed the plausibility of adopting Bayesian empirical methods based on the available knowledge of technical infrastructure and socio-economic status to simulate urban land-use change. It indicates their possible further applicability for generating forecasts of growth trends both for Brazilian cities and cities world-wide.

Publisher:

International Journal of Remote Sensing
Vol. 26, No. 4, 20 February 2005, 759–774

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Author : Kazuo Oki, Yoshifumi Yasuoka, and K. Tokumura

Content:

• Chlorophyll-a Estimation Model,
• Spectral Reflectance at Lake,
• Measurement of Spectral Reflectance,
• Remove the Effect of Specular Reflection,
• Specular Reflection Model,

Abstract A remote sensing method to estimate distribution of rich chlorophyll concentration in takes or inland seas in proposed. First, the basic relationship the chlorophyll concentration and the spectral reflectance of water was investigated. As a result, chlorophyll estimation model was derived using the ratio of spectral reflectance at two different wavelengths of 675 nm (red range) and 700 nm (near-infrared range). It was found that the spectral signature of near infrared range is investigate the behaviour of the proposed model was used in rich chlorophyll water types. Furthermore, the amount of specular reflection from the water surface was assessed based on the spectral signature data measured above and below the water surface. The percentage of specular reflection was evaluated at least 20% of the total radiance at the surface within the range of 400nm. Finally a method to remove the effect of specular reflection at the water surface was investigated for the proposed model. The model for specular reflection was proposed to eliminate its effect and to improve chlorophyll estimation accuracy.

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Author:
ZUBAIR, AYODEJI OPEYEMI

ABSTRACT
This project examines the use of GIS and Remote Sensing in mapping Land Use Land Cover in Ilorin between 1972 and 2001 so as to detect the changes that has taken place in this status between these periods. Subsequently, an attempt was made at projecting the observed land use land cover in the next 14 years. In achieving this, Land Consumption Rate and Land Absorption Coefficient were introduced to aid in the quantitative assessment of the change. The result of the work shows a rapid growth in built-up land between 1972 and 1986 while the periods between 1986 and 2001 witnessed a reduction in this class. It was also observed that change by 2015 may likely follow the trend in 1986/2001. Suggestions were therefore made at the end of the work on ways to use the information as contained therein optimally.

A PROJECT SUBMITTED TO THE DEPARTMENT OF GEOGRAPHY,
UNIVERSITY OF IBADAN IN PARTIAL FULFILMENT FOR THE
AWARD OF MASTER OF SCIENCE (MSc) DEGREE IN
GEOGRAPHICAL INFORMATION SYSTEMS
OCTOBER, 2006

Free Donwload Link to Article: http://www.gisdevelopment.net/thesis/OpeyemiZubair_ThesisPDF.pdf

By : Chaichoke Vaiphasa

Content :

• Remote sensing for mangrove studies
• Hyperspectral remote sensing for mangrove discrimination
• Burdens of hyperspectral data
• Dimensionality problems
• Noise levels
• mangrove-environment relationships
• Hyperspectral Data for Mangrove Discrimination
• Acquisition of hyperspectral data
• Spectral Smoothing
• Smoothing techniques (Moving average, Savitzky-Golay)
• Hyperspectral data collection
• Experimental use of smoothing filters (Statistical comparisons , Spectral separability analysis)
• Ecological Data Integration (Ecological data collection, Mangrove sampling)
• Input data for the post-classifier (Soil pH interpolation, Plant-environment relationships, The classified image)
• The post-classifier
• Hyperspectral data for mangrove discrimination
• Utilizing mangrove-environment relationships

Abstract :

Mangroves, important components of the world’s coastal ecosystems, are threatened by the expansion of human settlements, the boom in commercial aquaculture, the impact of tidal waves and storm surges, etc.  Such threats are leading to the increasing demand for detailed mangrove maps for the purpose of measuring the extent of the decline of mangrove ecosystems. Detailed mangrove maps at the community or species level are, however, not easy to produce, mainly because mangrove forests are very difficult to access. Without doubt, remote sensing is a serious alternative to traditional field-based methods for mangrove mapping, as it allows information to be gathered from the forbidding environment of mangrove forests, which otherwise, logistically and practically speaking, would be extremely difficult to survey. Remote sensing applications for mangrove mapping at the fundamental level are already well established but, surprisingly, a number of advanced remote sensing applications have remained unexplored for the purpose of mangrove mapping at a finer level. Consequently, the aim of this thesis is to unveil the potential of some of the unexplored remote sensing techniques for mangrove studies.  Specifically, this thesis focuses on improving class separability between mangrove species or community types. It is based on two important ingredients:
(i) the use of narrow-band hyperspectral data, and
(ii) the integration of ecological knowledge of mangroveenvironment relationships into the mapping process.
Overall, the results of this study reveal the potential of both ingredients. They show that delicate spectral details of hyperspectral data and the spatial relationships between mangroves and their surrounding environment help to improve mangrove class separability at the species level. Despite the optimism generated by the overall results, it was found that appropriate data treatments and analysis techniques such as spectral band selection and noise reduction were still required to harness essential information from both hyperspectral and ecological data. Thus, some aspects of these data treatments and analysis techniques are also presented in this thesis. Finally, it is hoped that the methodology presented in this thesis will prove useful and will be followed for producing mangrove maps at a finer level.

ISBN: 90-8504-353-0
ITC Dissertation Number: 129
International Institute for Geo-information Science & Earth Observation,
Enschede, The Netherlands
© 2006 Chaichoke Vaiphasa

Free Download Link: http://library.wur.nl/wda/dissertations/dis3897.pdf (1.55 MB)