Land use planning and wildfire risk mitigation: an analysis of wildfire-burned subdivisions using high-resolution remote sensing imagery and GIS data

This paper evaluates risk factors that influence the probability that a house will burn from wildfire. A logistic regression is used to analyse data processed from pre-fire and post-fire IKONOS images and other geo-referenced data. The dependent variable is the probability that a given house will burn. A total of 12 independent variables are evaluated: vegetation density; area of defensible space; adjacency of a parcel to public lands; proximity of a house to fire station; road width; road type; parcel size; subdivision morphology; assessed value; elevation; slope and aspect. Model results generally support dominant land use planning and design strategies for wildfire risk reduction including vegetation treatments, site selection with respect to topography, and improving access to fire stations.     

The role of remote sensing in hydrological modelling of the Okavango Delta, Botswana

A coupled surface water-groundwater model of the Okavango Delta has been built based on the United States Geological Survey software MODFLOW 2000 including the SFR2 package for stream-flow routing. It will provide a new tool for evaluating water management and climate change scenarios. The delta's size and limited accessibility make direct, on the ground data acquisition difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both model input parameters and calibration. Topography, aquifer thickness, channel positions, evapotranspiration and precipitation data are all based on remote sensing. Simulated flooding patterns are compared to patterns derived from visible to thermal NOAA-AVHRR data and microwave radar ENVISAT-ASAR data.     

Remote sensing and GIS for wetland inventory, mapping and change analysis

A multiple purpose wetland inventory is being developed and promoted through partnerships and specific analyses at different scales in response to past uncertainties and gaps in inventory coverage. A partnership approach is being promoted through the Ramsar Convention on Wetlands to enable a global inventory database to be compiled from individual projects and analyses using remote sensing and GIS. Individual projects that are currently part of this global effort are described. They include an analysis of the Ramsar sites' database to map the distribution of Ramsar sites across global ecoregions and to identify regions and wetland types that are under-represented in the database. Given the extent of wetland degradation globally, largely due to agricultural activities, specific attention is directed towards the usefulness of Earth Observation in providing information that can be used to more effectively manage wetlands. As an example, a further project using satellite data and GIS to quantify the condition of wetlands along the western coastline of Sri Lanka is described and trends in land use due to changes in agriculture, sedimentation and settlement patterns are outlined. At a regional scale, a project to map and assess, using remote sensing, individual wetlands used for agriculture in eight countries in southern Africa is also described. Land cover and the extent of inundation at each site is being determined from a multi-temporal data set of images as a base for further assessment of land use change. Integrated fully within these analyses is the development of local capacity to plan and undertake such analyses and in particular to relate the outcomes to wetland management and to compile data on the distribution, extent and condition of wetlands globally.     

Land use change and carbon exchange in the tropics: III. Structure,basic equations,and sensitivity analysis of the model

The rationale, assumptions, structure and basic mathematical functions of the model used to produce the simulation results reported in the first two articles of this series are described in detail. Sensitivity analysis indicates that the most important parameters in the model, and, presumably, in the carbon exchange between tropical forests and the atmosphere, are: (a) the conversion rate of forests to permanent pasture and agriculture, (b) the changes that are occurring and have occurred in the shifting cultivation system, and (c) the fate of cleared vegetation. Although it is not possible to validate the model against direct measurements of carbon exchange, the model has been proven robust when subject to a series of explicit analyses and comparisons with other assessments.     

A socioeconomic and natural vulnerability index for oil spills in an Amazonian harbor: A case study using GIS and remote sensing

The coastal zone of the Brazilian state of Maranhão is an area characterized by a large variety of human activities and services, in particular in the Itaqui-Bacanga port complex (IBC). The IBC is an area prone to oil spills resulting from the processes of transportation, storage, and tank cleaning. The present study aimed to map the different physical environments adjacent to this complex and the socioeconomic profile of the local population that would be most vulnerable to this type of disaster. Vulnerability studies are essential as one of the first step in the development of an integrated coastal zone management. The variables analyzed in this study included geomorphological units, and the income, education, and dependence on fishing of the local population. The estimate of the vulnerability index was based on the relationships between these variables, which were used to generate a vulnerability map using GIS and the interpretation of high-resolution remote sensing, showing the areas of highest priority for intervention in the case of oil spills. The analysis of the natural and socioeconomic environments indicated that the areas of highest vulnerability correspond to the mangroves and the Vila Nova and Alto da Esperança neighborhoods, respectively. These neighborhoods have a direct relationship with fishing, and low levels of both income and education. By contrast, the lowest vulnerability was attributed to the coastal plateau and the central Anjo da Guarda neighborhood, which is occupied by residents with relatively high income and education, who do not depend on fishing.     

Land use and management in the People's Republic of China

Widespread disregard for essential principles of sound environmental management and protection during the three decades of Communist rule prior to 1980 have exacerbated traditional shortages of good arable land and productive forest cover in the People's Republic of China. The government's policies have also drastically reduced valuable freshwater surfaces, caused extensive grassland deterioration and soil erosion, and brought about many local and regional climatic changes. However, new policies put into effect recently are attempting to reverse these trends with a sound ecosystemic approach to land management.     

Land use change in California,USA: Nonpoint source water quality impacts

California’s population increased 25% between 1980 and 1990, resulting in rapid and extensive urbanization. Of a total 123,000 ha urbanized in 42 of the state’s 58 counties between 1984 and 1990, an estimated 13% occurred on irrigated prime farmland, and 48% on wildlands or fallow marginal farmlands. Sixty-six percent of all new irrigated farmland put into production between 1984 and 1990 was of lesser quality than the prime farmland taken out of production by urbanization. Factors dictating the agricultural development of marginal farmlands include the availability and price of water and land, agricultural commodity prices, and technical innovations such as drip irrigation systems that impact the feasibility and costs of production. The increasing amount of marginal farmland being put into production could have significant water quality consequences because marginal lands are generally steeper, have more erodible soils, poorer drainage, and require more fertilizer than prime farmlands. Although no data exist to test our hypothesis, and numerous variables preclude definitive predictions, the evidence suggests that new irrigated marginal lands can increase nonpoint source (NPS) pollution for a given size area by an order of magnitude in some cases.     

Georelational Analysis of Soil Type, Soil Salt Content, Landform, and Land Use in the Yellow River Delta, China

The Yellow River Delta, one of China’s three major river deltas, is becoming a major region for the development of agriculture and fisheries. Protecting the delicate ecology of newly formed aquatic systems as well as the evolution of soils, natural vegetation, and fauna on older upland environments in the delta is a priority in planning for the wise use of the delta’s resources for future agricultural development. In this article, we use a Geographic Information System (GIS) to analyze relationships between land-use/land-cover characteristics in the Dongying municipality, one of the most intensely developed areas of the delta, and spatial variations in soil salinity and landforms. This analysis reveals that soil salt content decreases from regionally high values in isolated depressions to relatively moderate values in embanked former back swamps, with the lowest values occurring in abandoned river courses. Comparing the present land use on this soil salinity–landform pattern shows that it is basically at odds with general concepts of land suitability for agricultural utilization of saline soils. Crop-based agriculture in the region is probably overdeveloped, whereas more appropriate agricultural development, like cattle and forest production, is underrepresented. Future development should focus on converting farmland in embanked former back swamps and abandoned river courses into grasslands and forests. Crop-based agriculture (up to 151,000 ha) could be planned at the low-salinity terrace uplands and flood plains. The article provides guidelines for decision-makers regarding agricultural land use and wetland protection in the Yellow River Delta.     

Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed

Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method--the RIparian Classification Algorithm (RICAL)--to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies for the handling of non-point source pollution, bird habitat monitoring, and grazing and live stock management in the future.     

Detection and mapping of water pollution variation in the Nile Delta using multivariate clustering and GIS techniques

The limited water resources of Egypt lead to widespread water-stress. Consequently, the use of marginal water sources, such as agricultural drainage waters, provides one of the national feasible solutions to the problem. However, the marginal quality of the drainage waters may restrict their use.The objective of this research is to develop a tool for planning and managing the reuse of agricultural drainage water for irrigation in the Nile Delta. This is achieved by classifying the pollution levels of drainage water into several categories using a statistical clustering approach that may ensure simple but accurate information about the pollution levels and water characteristics at any point within the drainage system.The derived clusters are then visualized by using a Geographical Information System (GIS) to draw thematic maps based on the entire Nile Delta, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Nile Delta regions. The clustering process also provides an effective overview of those spots in the Nile Delta where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment and redesign of the Egyptian national water quality monitoring network.     

Assessing catchment-wide mining-related impacts on sediment movement in the Swift Creek catchment, Northern Territory, Australia, using GIS and landform-evolution modelling techniques

The Swift Creek catchment, the first catchment to be affected should any impact occur as a result of mining of the Jabiluka uranium ore deposit, is located partly within the World Heritage Kakadu National Park (KNP), and partly within the Jabiluka Mineral Lease (JML) that has been excised from KNP. Preliminary linking of a landform evolution model with a Geographic Information System (GIS) has been completed and tested on a catchment-wide basis for long-term total catchment management. This project represents the first attempt to apply the model on a catchment-wide basis in the region. Linking the model with a GIS enhances the modelling process, as the GIS assists in the derivation, storage, manipulation, processing and visualisation of geo-referenced data on a catchment-wide scale. This preliminary assessment of landform evolution in the Swift Creek catchment demonstrates the complex process associated with the parameterisation of the SIBERIA model, and illustrates the benefits of integrating GIS with landform evolution modelling techniques. Additional research is required to develop a more integrated GIS and landform evolution modelling approach to assessing the possible impacts of mining on catchment sedimentary and hydrological processes.     

珠江三角洲水土资源开发利用问题与对策

本文全面分析了珠江三角洲水土资源开发利用的现状，阐明了水土资源开发利用中出现的环境问题及原因。因此，提出了该地区水土资源进一步合理开发利用的对策。     

First principles of the MameLuke multi-actor modelling framework for land use change, illustrated with a Philippine case study

This paper presents the first principles of the MameLuke framework, an agent-based modelling framework for studying environmental issues and land use and cover change (LUCC). The MameLuke framework enhances the understanding of the relationship between societal processes and LUCC by modelling individual and group decisions and human-environment interactions. The framework allows for the transformation of real-life stories into computerised models following a predetermined sequence. By doing so, the framework allows for a truly integrative approach, because it is not bound to any particular scientific discourse. Even better, the framework enables its users to combine scientific discourses regarding human decisions and behaviour on multiple scales and levels. The agents (actors and locations) in the framework are heterogeneous. This heterogeneity of agent behaviour is established by dividing the agents into categories. If an agent is a member of an agent category or combination of categories, it has access to a defined set of implementable actions. The actions are constructed out of potential option paths (POPs) and potential option nodes (PONs). The whole of POPs represent a theoretical construct of agent behaviour and decisions that the framework user wishes to explore. The POP defines a sequence of PONs. The PON is a transaction interface between an initialising agent and a recipient agent where they exchange material and immaterial capital. This paper explains the basic architecture of the MameLuke framework and shows its applicability with a model of a Philippine case study. This case study concerns the dynamics of migration and deforestation. It is part of a larger study on land use change in the San Mariano watershed area at the forest fringe of the Sierra Madre mountains in the Philippines.     

Land use change and carbon exchange in the tropics: I. Detailed estimates for Costa Rica,Panama, Peru,and Bolivia

Our group, composed of modelers working in conjunction with tropical ecologists, 3 has produced a simulation model that quantifies the net carbon exchange between tropical vegetation and the atmosphere due to land use change. The model calculates this net exchange by combining estimates of land use change with several estimates of the carbon stored in tropical vegetation and general assumptions about the fate of cleared vegetation. In this report, we use estimates of land use and carbon storage organized into sixlife zone (sensu Holdridge) categories to calculate the exchange between the atmosphere and the vegetation of four tropical countries. Our analyses of these countries indicate that this life zone approach has several advantages because (a) the carbon content of vegetation varies significantly among life zones, (b) much of the land use change occurs in life zones of only moderate carbon storage, and (c) the fate of cleared vegetation varies among life zones. Our analyses also emphasize the importance of distinguishing between temporary and permanent land use change, as the recovery of vegetation on abandoned areas decreases the net release of carbon due to clearing. We include sensitivity analysis of those factors that we found to be important but are difficult to quantify at present.     

Land use change and carbon exchange in the tropics: II. Estimates for the entire region

Determining the effect of tropical land use on the carbon dioxide (CO₂) content of the atmosphere requires: (a) estimates of the rates of land use change, (b) estimates of the difference between the carbon stored in forests and that stored in pastures and cultivated fields, and (c) a consideration of the fate of carbon stored in the cleared vegetation. The first article of this series analyzed land use in four tropical countries and estimated the carbon released to the atmosphere as a consequence of changes in land use. This article estimates the carbon released from the entire tropical region based on the two published studies of land use change for the tropics as a whole that distinguish between temporary and permanent land use: Seiler and Crutzen (1980) and Lanly (1982). We combine these estimates with two estimates of the difference in carbon storage between forests and fields derived from Whittaker and Likens (1975) and Brown and Lugo (1982), and the two scenarios of the fate of cleared vegetation, developed in the previous article, to produce several complete sets of data describing the necessary parameters to calculate carbon exchange. These data sets, entered into our model, produce a range of estimates of the annual release of carbon from tropical vegetation in 1980 of from 0.6 to 1.8 BMT/year, with the more likely range being 0.9–1.2 BMT/year. Our preliminary analysis suggests that the release from tropical soils due to land use change adds about an additional 0.3 BMT C/year, so that the total release is probably between 1.2 and 1.5 BMT C/year. Peng and others (1983) reported that new models of the oceanic carbon cycle can accommodate at least 1.2 BMT C/year in 1980 from forests and soils. Our results indicate that, given the uncertainties in the size of both the biotic release and oceanic uptake, the global carbon budget may be balanced if there is no significant release from nontropical ecosystems due to land use change and all mature ecosystems are in collective equilibrium with the atmosphere.     

Land use change and population growth in the Morobe Province of Papua New Guinea between 1975 and 2000

The relation between human population growth and land use change is much debated. Here we present a case study from Papua New Guinea where the population has increased from 2.3 million in 1975 to 5.2 million in 2000. Since 85% of the population relies on subsistence agriculture, population growth affects agricultural land use. We assessed land use change in the Morobe province (33,933 km2) using topographic maps of 1975 and Landsat TM images of 1990 and 2000. Between 1975 and 2000, agricultural land use increased by 58% and population grew by 99%. Most new agricultural land was taken from primary forest and the forest area decreased from 9.8 ha person(-1) in 1975 to 4.4 ha person(-1) in 2000. Total population change and total land use change were strongly correlated. Most of the agricultural land use change occurred on Inceptisols in areas with high rainfall (>2500 mm year(-1)) on moderate to very steep slopes (10-56%). Agricultural land use changes in logged-over areas were in the vicinity of populated places (villages), and in close proximity to road access. There was considerable variation between the districts but districts with higher population growth also had larger increases in agricultural areas. It is concluded that in the absence of improved farming systems the current trend of increased agriculture with rapid population growth is likely to continue.     

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.     

The Spatio-Temporal Dynamic Pattern of Rural Residential Land in China in the 1990s Using Landsat TM Images and GIS

Through interpreting Landsat TM images, this study analyzes the spatial distribution of rural settlements in China in 2000. It calculates rural residential land percentage for every 1-km² cell. The entire country is divided into 33 regions to investigate the spatio-temporal dynamic patterns of rural residential land during the 1990s. According to the remote sensing survey, the rural residential land increased by 7.88 × 10⁵ ha in the 1990s. The increment of rural residential land was 0.55 million ha in 1990–1995 and 0.23 million ha in 1995–2000. In 1990–1995, rural residential land increased dramatically in the eastern regions such as the Yangtze River Delta, Pearl River Delta, and North China Plain, accounting for 80.80% of the national growth; the expansion in the western regions was much more moderate. In 1995–2000, the expansion of rural residential land in eastern regions slowed, accounting for only 58.54% of the increase at the national level, whereas the expansion in the western regions accelerated. Rapid rural residential development resulted from increasing home construction and the limited control on rural land. The great regional disparity reflected the regional economic development and land-use policy change. Our finding shows that nearly 60% of the rural residential area came from cropland.     

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou,in the Yangtze River Delta of China

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.