Modeling Landscape changes using Logit Models
Li-Ta Hsu
Associate Professor, Department of Environmental Design
Hua Fan University
1 Huafan Rd., Shr-Ding, Taipei, 223
Tel: (886)-2-2663-2102 #4563 Fax: (886)-2-2663-2102 #4570
E-mail: lita@mail.ht.net.tw
TAIWAN
Chi-Chuan Cheng
Deputy Director
Yu-Ching Lai
Post Doctoral Researcher
Taiwan Forestry Research Institute
53 Nan Hai Rd., Taipei, 100
Tel: (886)-2-2303-9978 #1208 Fax: (886)-2-2375-4216
E-mail: cccheng@serv.tfri.gov.tw
TAIWAN
Key Words
Landscape changes, Logit models
Abstract
Detecting and monitoring landscape changes is an important issue of landscape ecology and ecosystem management. This study used two sets of aerial photographs taken in 1988 and 1996 to derive land cover maps of the Liukuei ecosystem management area. The two maps were compared to identify transitions among land cover types. GIS and logit models were used to examine the historic changes of the landscape, and to predict probabilities of landscape changes. Three kinds of explanatory variables, namely, environmental factors, spatial factors, and patch attributes, were examined. Environmental factors include elevations, slopes and aspects of the randomly selected places. Spatial factors include distances to roads, to streams, and to natural forests. Patch attributes include the sizes, perimeters, and shape indices of the patches where the samples were located. Maximum likelihood methods were used to estimate the parameters of binary and multinomial logit models. Results show that the most influential factors of landscape changes were elevations, slopes and distances to natural forests, whereas none of the patch attributes examined in the model were significant. In general, conifer and hardwood plantations located at lower elevations and near natural forests were more likely to become natural forests. Bare lands were more likely to occur on high elevation places near roads and with steep slopes. On the other hand, low elevation bare lands near natural forests and away from roads were more likely to be reclaimed by natural forests. These results can be used to project the probabilities of landscape changes spatially, and would be useful for guiding the management practices of the Liukuei ecosystem management area in the future.
1. Introduction
Landscape ecology studies the structure, function, and spatial pattern of landscapes (Forman and Godron 1986). In landscape ecology, landscape indices are often used to describe and analyze the landscape structure of a landscape. For examples, O'Neill et al. (1988), Li (1990), Turner (1990), Turner and Gardner (1991) used various landscape indices to quantify landscape structures. In analyzing landscape changes, regression models and Markov models are often used to analyze the distributional changes of a landscape at different points in time. For instances, Alig (1986) used regression models to analyze the acreage changes of a forest landscape, Burnham (1973), Lindsay and Dunn (1979), and Muller and Middleton (1994) applied Markov models to study landscape changes. Another kind of landscape models is the spatial models. Spatial models of landscape changes focus on the spatial characteristics of landscape changes such as factors contributing to landscape changes, or variations in probabilities of landscape changes at different locations (Baker 1989). Distributional models such as Markov models and regression models can be modified into spatial, for example, Turner (1987) applied Markov probabilities to simulate spatial landscape changes using pixels. However, he suggested that because Markov models are non-spatial in nature, the probability in each pixed should be adjusted according to the conditions of its neighboring pixels. Another commonly used probabilistic spatial models are the probit or logit models. The principles of probit or logit models are similar to those of regression models. They can be used to analyze factors contributing to landscape changes, and use the results to predict probabilities of landscape changes at different spatial locations. Dale et al. (1993) used multinomial logit models to analyze the spatial pattern of deforestation in Brazil. In studies of land use changes, McMillen (1989)and Hsu (1996) further integrated logit models with economic theories, and used them to explore the spatial pattern of land use change. In Taiwan, there are also several literatures about monitoring landscape patterns, for example, Lin (1996) used Markov models and ridge regression models to model vegetation changes in Tainan, and Hsu and Cheng (2000) applied Markov models of predict long-term trends of landscape change in an ecosystem management area. However, until now, none of the literature has used probit or logit models in analyzing spatial landscape changes.
This study is a part of a long-term monitoring program carried out in Liukuei ecosystem management area. In this study, digital photogrammetry was used to generate land cover maps of the Liukuei ecosystem management area in 1988 and 1996. Logit models were used to examine the relationships between landscape changes and environmental factors. The results can provide useful information for the planning, monitoring of the landscape in the future.
2. Material and Methods
The study area, 'Liukuei ecosystem management area', is a part of the Liukuei experimental forest of the Taiwan Forestry Research Institute. Located at Maolin Township, Kaohsiung County, the study area encompasses seven forest compartments, and covers about 2500 ha. Elevation in the area ranges from 300m to 1800m, and the topography is up-sloped from southwest to northeast. The Shanping post and several nurseries are also located inside the area and are connected by service roads stretching throughout the area. Natural forests dominate 78% of the landscape, and man-made stands occupy the remaining 22%. Most of the man-made stands are coniferous plantations. On the other hand, natural forests consist of various broadleaf tree species, and some are mixed with conifers. Parts of the natural and man-made forests have recently undergone timber harvesting and reforestation. Therefore, some cut areas exist. In addition, there are some nonforested areas such as grasslands or bare lands resulted from landslides.
Aerial photographs taken in 1988 and 1996 were used to generate land cover maps of the study area. Positive films of the photographs were scanned into digital images. With several ground truth measurements, the images were subsequently rectified as orthogonal images with accurate positioning. Image pairs were then displayed as stereographs on computer screens, where features on the landscape were delineated and digitized. As a result, two sets of land cover map files were created in vector format (Fig.1).
