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Land use is changing at accelerated rates in Taiwan, and illegal land use change practices (ILP) are regularly observed within conservation areas. For this reason, we map high-potential areas of ILP within the Soil and water conservation zone (SWCZ) as an aid for effective land management and conducted an exploratory analysis of explanatory variables to evaluate their variability within ILP hot spots. We used variables relevant to hot spots to develop a logistic regression model and identified seven statistically significant variables. We re-applied the logistic regression approach to produce spatially explicit predictions of ILP. High probability areas are distributed along the coastal regions, covering 26% of the SWCZ, and their major drivers are related to accessibility and topography. The results from this research provide relevant information on the major drivers of ILP and high-potential areas, which can support officials in monitoring efforts for better planning and governance within the SWCZ. [ABSTRACT FROM AUTHOR]

Forests in Honduras are endangered as a result of the relentless occurrence of wildfires during the dry season, and their frequency and area burned have been gradually increasing, a pattern attributable to the numerous ignition sources. For this reason, there is a substantial need to identify the major drivers of wildfires and map the regions where they are most likely to occur. In this study, we integrated the wildfire occurrences throughout the 2010–2015 period with a series of variables using the random forest algorithm. We included variables related to human activities such as the continuous distances to infrastructure and settlements. Other variables included are satellite observations that reflect the seasonal vegetation change, climatic conditions over the country, and topographical variables. The analysis of the explanatory variables revealed that the dry fuel conditions and low precipitation combined with the proximity to non-paved and paved roads were the major drivers of wildfires in the region. The estimated area with high and very high wildfire susceptibility was 15% of the country, located mainly in the central and eastern regions. The proposed national-scale wildfire susceptibility map can lead to enhanced preventive measures to minimize risk and the impacts caused by wildfires. [ABSTRACT FROM AUTHOR]

Abstract: Landslide mapping is important for emergency management and landslide risk assessment. In this study, we propose a new mapping method, which combines the spectral signal contained in a satellite image and the geoenvironmental information included in a landslide susceptibility map. The image analysis captures areas with spectral signatures of event landslides in the image, while the landslide susceptibility map filters sub-areas, which do not have landslide prone conditions. The method assigns to every pixel of the satellite image a combined probability of landslide presence. We mapped typhoon-triggered landslides in southern Taiwan using the method. To compare with a landslide inventory prepared from orthophotos, we converted the probability map to a binary map of landslides and landslide free areas. Map comparison resulted in an overall accuracy of 0.93, an area percentage of overlapped landslides of 0.84, a modified success rate of 0.89, and a kappa statistic of 0.73. The method is fast, flexible, and relatively easy to use, and the probability map the method produces is useful by itself. We expect that the method can facilitate the rapid production of event landslide inventory maps, which in turn can assist emergency management. [Copyright &y& Elsevier]

Landslide mapping is essential for effective watershed management. In Taiwan, a typhoon or earthquake event can trigger hundreds, even thousands, of shallow landslides in mountainous watersheds. Thus, improving the efficiency of landslide mapping by means of remote sensing techniques is an important issue. This study proposes a new method that uses concurrent aerial laser scanning (ALS) data and color ortho-imagery as input data: the topographic indices of slope, surface roughness, and object height model can be derived from the ALS data and the Green-Red Vegetation Index from the ortho-images. The method first uses these topographic and spectral indices in a global, semi-automatic algorithm to separate landslide from non-landslide pixels. It then offers a region growing tool and a 3D Eraser/Painter to edit detected landslides locally. These global and local operations are designed with a user interface, which is intuitive and user-friendly. Results from four test sites in a mountainous watershed prove that the method is easy, accurate, and suitable for landslide mapping in Taiwan. [ABSTRACT FROM AUTHOR]

Digital elevation models (DEMs) vary in resolution and accuracy by the production method. DEMs with different resolutions and accuracies can generate varied topographic and hydrological features, which can in turn affect predictions by soil erosion models, such as the WEPP (Water Erosion Prediction Project) model. This study investigates the effects of DEMs on deriving topographic and hydrological attributes, and on predicting watershed erosion using WEPP v2006.5. Six DEMs at three resolutions from three sources were prepared for two small forested watersheds located in northern Idaho, USA. These DEMs were used to calculate topographic and hydrological parameters that served as inputs to WEPP. The model results of sediment yields and runoffs were compared with field observations. For both watersheds, DEMs with different resolutions and sources generated varied watershed shapes and structures, which in turn led to different extracted hill slope and channel lengths and gradients, and produced substantially different erosion predictions by WEPP. [ABSTRACT FROM AUTHOR]

With its phenomenal development in recent decades, urbanization in China has been covered in a large number of studies. These studies have focused on large cities, with smaller and lesser known cities largely overlooked. This study analyzed the spatiotemporal changes of land use in Quanzhou, a historical city in Fujian Province, using GIS and remote sensing tools. Based on the land use change indices and spatial metrics, our results showed that built-up (urban) land in Quanzhou increased more than twofold in 1995–2010, at the expense of cultivated land, woodland, and grassland. During the same period, urban land patches increased in both number and size, while becoming more irregular and complex in shape. Most urban land expansion took place in the coastal areas, including the city districts and development and industrial zones. Although urbanization in Quanzhou has been remarkable since 1995, its average rate of urban land expansion has fallen behind Shenzhen and Dongguan in the Pearl River Delta. Geographic location and population growth are two important factors for the difference. Quanzhou is located in a less developed region of China, and its population growth has been slow due to its heavy reliance on labor-intensive, low-technology industries, which do not offer sufficient rural—urban wage differential to attract large inflows of migrant workers. Urbanization in China follows different paths in different cities and regions, as shown in this study by comparing Quanzhou with cities in the Pearl River Delta. [ABSTRACT FROM AUTHOR]

Abstract: We propose a semi-automatic approach to detect, map and classify rainfall-induced shallow landslides. The approach combines the classification of a post-event multispectral satellite image with information on the morphometric signature of landslides in a Bayesian framework. We apply the approach in two steps. First, we detect and map the rainfall-induced landslides separating the stable ground from the failed areas. Next, we classify internally the landslides separating the source from the run out areas. We obtain the prior probability from the Mahalanobis discriminant function used to classify the satellite image, and the likelihood from the frequency distribution of terrain slope and cross section convexity in the pre-existing shallow landslides. We tested the approach in southern Taiwan, in a catchment where Typhoon Morakot caused abundant landslides in August 2009. Using the semi-automatic approach, we obtained a detailed event landslide inventory map that we compared to an inventory obtained through the visual interpretation of post-event ortho-photographs taken a few days after the landslide triggering rainfall event. Quantitative comparison in a Geographical Information System revealed a degree of matching between the two event inventories exceeding 90%. The approach is general and flexible, and can be used with different satellite imagery and topographic data. Best suited in landscapes where shallow landslides leave distinct radiometric and topographic signatures, the approach is expected to facilitate the production of event landslide inventory maps with positive consequences for geomorphological investigations, landslide hazard and risk modeling, and for post event recovery efforts. [Copyright &y& Elsevier]

Abstract: Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Despite their importance, we estimate that landslide maps cover less than 1% of the slopes in the landmasses, and systematic information on the type, abundance, and distribution of landslides is lacking. Preparing landslide maps is important to document the extent of landslide phenomena in a region, to investigate the distribution, types, pattern, recurrence and statistics of slope failures, to determine landslide susceptibility, hazard, vulnerability and risk, and to study the evolution of landscapes dominated by mass-wasting processes. Conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography, aided by field surveys. These methods are time consuming and resource intensive. New and emerging techniques based on satellite, airborne, and terrestrial remote sensing technologies, promise to facilitate the production of landslide maps, reducing the time and resources required for their compilation and systematic update. In this work, we first outline the principles for landslide mapping, and we review the conventional methods for the preparation of landslide maps, including geomorphological, event, seasonal, and multi-temporal inventories. Next, we examine recent and new technologies for landslide mapping, considering (i) the exploitation of very-high resolution digital elevation models to analyze surface morphology, (ii) the visual interpretation and semi-automatic analysis of different types of satellite images, including panchromatic, multispectral, and synthetic aperture radar images, and (iii) tools that facilitate landslide field mapping. Next, we discuss the advantages and the limitations of the new remote sensing data and technology for the production of geomorphological, event, seasonal, and multi-temporal inventory maps. We conclude by arguing that the new tools will help to improve the quality of landslide maps, with positive effects on all derivative products and analyses, including erosion studies and landscape modeling, susceptibility and hazard assessments, and risk evaluations. [Copyright &y& Elsevier]