Yeqiao Wang

Remote Sensing of Mangrove Change Along the Tanzania Coast

This article contributes to the understanding of the changes in distribution and total area of mangrove forests along the mainland Tanzania coast over the past decade. Mangroves are recognized as critical coastal habitat requiring protection and special attention. The Tanzania coastline forms a suitable habitat for establishment of mangrove forests. Mangrove forests are distributed from Tanga in the north to Mtwara in the south covering approximately 109,593 hectares from 1988-1990 and about 108,138 hectares in 2000. The largest continuous mangrove stands are found in the districts of Rufiji, Kilwa, Tanga-Muheza, and Mtwara. Comparison of data between these two time periods shows that the geographic coverage of mangroves has no dramatic change in the past decade. The Tanzania Mangrove Management Project and other closely related programs and efforts pertaining to mangrove conservation contribute to direct restoration and natural regeneration of mangroves. This study documents the changes of mangroves and demonstrates that remote sensing and GIS offer important data and tools in the advancement of coastal resource management and ecosystem monitoring. Application of geographic information technologies is critical for improved coastal resources management and decision making for sustainable development in Tanzania.

Extraction of Impervious Surface Areas from High Spatial Resolution Imagery by Multiple Agent Segmentation and Classification

In recent years impervious surface areas (ISA) have emerged as a key paradigm to explain and predict ecosystem health in relationship to watershed development. The ISA data are essential for environmental monitoring and management in coastal State of Rhode Island. However, there is lack of information on high spatial resolution ISA. In this study, we developed an algorithm of multiple agent segmentation and classification (MASC) that includes submodels of segmentation, shadow-effect, MANOVA-based classification, and postclassification. The segmentation sub-model replaced the spectral difference with heterogeneity change for regions merging. Shape information was introduced to enhance the performance of ISA extraction. The shadow-effect sub-model used a split-and-merge process to separate shadows and the objects that cause the shadows. The MANOVA-based classification sub-model took into account the relationship between spectral bands and the variability in the training objects and the objects to be classified. Existing GIS data were used in the classification and post-classification process. The MASC successfully extracted ISA from high spatial resolution airborne true-color digital orthophoto and space-borne QuickBird-2 imagery in the testing areas, and then was extended for extraction of high spatial resolution ISA in the State of Rhode Island.

Estimating Soil Moisture Conditions of the Greater Changbai Mountains by Land Surface Temperature and NDVI

Soil moisture is an important indicator of the land surface environment. The combination of land surface temperature (LST) and normalized difference vegetation index (NDVI) could enhance the ability of extracting information on soil moisture conditions. In this study, we employed multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) data products of LST, NDVI, and land cover types to obtain the information about soil moisture for the greater Changbai Mountains. We selected nine time periods in 2007 for inversion of the soil moisture conditions and focused the analysis on four critical time periods. According to the spatial pattern of the LST and NDVI, we established the ¿wet-edge¿ and ¿dry-edge¿ equations and determined the relative parameters. We obtained the temperature-vegetation dryness index (TVDI) using the wet-edge and dry-edge relationships to reveal temporal changes of the land surface soil moisture conditions of the study area. We also analyzed the relationship between different land cover types in five TVDI classes. This paper demonstrates that TVDI is an effective indicator to detect soil moisture status in the greater Changbai Mountains region.

A SPLIT Model for Extraction of Subpixel Impervious Surface Information

This paper introduces a Subpixel Proportional Land cover Information Transformation (SPLIT) model to extract proportions of impervious surfaces in urban and suburban areas. High spatial resolution airborne Digital Multispectral Videography (DMSV) data provided subpixel information for Landsat TM data. The SPLIT model employed a Modularized Artificial Neural Network (MANN) to integrate multi-sensor remote sensing data and to extract proportions of impervious surfaces and other types of land cover within TM pixels. Through a control unit, the MANN was able to decompose a complex task into multiple subtasks by using a group of sub-networks. The SPLIT model identified spectral relations between TM pixel values and the corresponding DMSV subpixel patterns. The established relationship allows extrapolation of the SPLIT model to the areas beyond DMSV data coverage. We applied five intervals, i.e., 81 percent, to map the subpixel proportions of land cover types. We extrapolated the SPLIT model from training sites that have both TM and DMSV coverage into the entire DuPage County with TM data as the input. The extrapolation received 82.9 percent overall accuracy for the extracted proportions of urban impervious surface.

Involving Geospatial Information in the Analysis of Land-Cover Change Along the Tanzania Coast

Abstract This article provides the first comprehensive scientific data on land-use and land-cover change in the coastal zone of Tanzania over the 1990 and 2000 time periods. The research was part of an African region initiative to demonstrate the practical application of geographic information for sustainable development. Remotely sensed images from close to 1990 Landsat Thematic Mapper (TM) sensor and 2000 Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor and geographic information system (GIS) technologies are applied to discern changes in land cover and land use along the mainland Tanzania coast. Change detection results show that urban land area has increased dramatically. Mangrove forest area declined modestly, but field verification shows severe deterioration of their conditions near urban areas. While the area of dense woodland decreased, the area of open woodland and the area of woodland interspersed with agriculture increased. This study demonstrates how geospatial information science and technologies provide critical information and tools for coastal resource managers who work at the crossroads of resource use, land-cover change, poverty alleviation, and environmental management.

Terrestrial and Submerged Aquatic Vegetation Mapping in Fire Island National Seashore Using High Spatial Resolution Remote Sensing Data

The vegetation communities and spatial patterns on the Fire Island National Seashore are dynamic as the result of interactions with driving forces such as sand deposition, storm-driven over wash, salt spray, surface water, as well as with human disturbances. We used high spatial resolution QuickBird-2 satellite remote sensing data to map both terrestrial and submerged aquatic vegetation communities of the National Seashore. We adopted a stratified classification and unsupervised classification approach for mapping terrestrial vegetation types. Our classification scheme included detailed terrestrial vegetation types identified by previous vegetation mapping efforts of the National Park Service and three generalized categories of high-density seagrass, low-density seagrass coverages, and unvegetated bottom to map the submerged aquatic vegetation habitats. We used underwater videography, GPS-guided field reference photography, and bathymetric data to support remote sensing image classification and information extraction. This study achieved approximately 82% and 75% overall classification accuracy for the terrestrial and submnerged aquatic vegetations, respectively, and provided an updated vegetation inventory and change analysis for the Northeast Coastal and Barrier Network of the National Park Service.

An Assessment of Impervious Surface Areas in Rhode Island

Abstract Impervious surface area (ISA) has emerged as a key indicator to explain and predict ecosystem health in relationship to watershed development. In this study, we extracted the information of ISA for the state of Rhode Island using 1-m spatial resolution true-color digital orthophotography data. We employed an object-oriented algorithm of multiple-agent segmentation and classification (MASC) that we developed for ISA information extraction. The result indicates that, as of 2004, 10% of the state land has been covered by ISA. The major population centers and historical cities, such as Providence, Woonsocket, and Newport, have ISA over 30%. The heavily settled suburban communities have ISA between 10 and 30%. Only 17 out of 39 towns in the state have less than 10% ISA. The average ISA for the coastal towns is 14%. Because most stream-quality indicators are predicted to decline when watershed ISA exceeds 10%, the results from this study serve as an alarming indicator for managing the states watershed and coastal ecosystems. The tested MASC model could be extended to coastal Massachusetts and Connecticut to provide a more comprehensive indication of the impacts of human-induced land-cover change on southern New Englands coast.

The Variation of Land Surface Phenology From 1982 to 2006 Along the Appalachian Trail

The gradients of the Appalachian Trail (A.T.) in elevations and latitudes provide a megatransect to study environmental variations in the eastern United States. This paper reveals patterns and trends of land surface phenology (LSP) in association with climatic variables within a corridor area along the A.T. We employed time-series data from Global Inventory Modeling and Mapping Studies and the Surface Observation and Gridding System between 1982 and 2006 to extract spatial and temporal variation patterns of LSP metrics and the correlations with meteorological parameters. The derived trends in LSP metrics indicate that the extended length of season mainly resulted from delayed end of season (EOS) across the study area. More significant change occurred in the northern segment than in the southern segment, which reflects latitudinal effects. We analyzed the relationship between LSP and longitude, latitude, elevation, local climatic variables, and large-scale climate oscillations. Delayed start of season in 1989 and advanced EOS in 1988 were observed responding to the La Niña episode during 1988-1989. This paper provides information about the effects of climate and topography on LSP along the Appalachian Mountain ridges.

MODIS-derived land surface moisture conditions for monitoring blacklegged tick habitat in southern New England

Temperature and humidity have been identified as significant determinants of suitable blacklegged tick (Ixodes scapularis) habitat. The temperature–vegetation dryness index (TVDI) uses remotely sensed observations of both temperature and vegetation cover to characterize moisture status on the ground. The TVDI has previously been applied to large studies of conservation, drought monitoring, and disease forecasting. In this study, we applied the TDVI model in an effort to characterize land surface conditions influencing tick habitat and human health risk in the southern New England region of the USA. Findings derived from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and normalized difference vegetation index (NDVI) data products in TDVI modelling and site-specific validations suggested that remotely sensed surface moisture conditions is one environmental parameter that could be useful in large-scale tick habitat monitoring.

Variation and trends of landscape dynamics, land surface phenology and net primary production of the Appalachian Mountains

Abstract. The gradients of elevations and latitudes in the Appalachian Mountains provide a unique regional perspective on landscape variations in the eastern United States and southeastern Canada. We reveal patterns and trends of landscape dynamics, land surface phenology, and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies and Advanced Very High Resolution Radiometer Global Production Efficiency Model datasets. We analyze the spatial and temporal patterns of the normalized difference vegetation index (NDVI), length of growing season (LOS), and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions. We compare the results in different spatial contexts, including North America and the Appalachian Trail corridor area. To reveal latitudinal variations, we analyze data and compare the results between the 30°-to-40°N and the 40°-to-50°N latitudes. The result reveal significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was a − 0.0018 ( R 2 = 0.55 , P < 0.0001 ) NDVI unit decrease per year during 25 years from 1982 to 2006. The LOS was prolonged by 0.3     days   per   year − 1 during the 25-year percent. The NPP increased by 2.68     g   Cm − 2   yr − 2 from 1981 to 2000.