This page has only limited features, please log in for full access.
With the increase in global urbanization, satellite imagery and other types of geospatial data have been extensively used in urban landscape change research, which includes environmental modeling in order to assess the change impact on urban watersheds. For urban hydrological modeling, as a focus of this study, several related research questions are raised: (1) How sensitive are runoff simulation to land use and land cover change patterning? (2) How will input data quality impact the simulation outcome? (3) How effective is integrating and synthesizing various forms of geospatial data for runoff modeling? These issues were not fully or adequately addressed in previous related studies. With the aim of answering these questions as research objectives, we conducted a spatial land use and land cover (LULC) change analysis and an urban runoff simulation in the Blue River watershed in the Kansas City metropolitan area between 2003 and 2017. In this study, approaches were developed to incorporate the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model with remote sensing, geographic information systems (GIS), and radar rainfall data. The impact of data quality on the model simulation outcome was also analyzed. The results indicate that there are no significant differences between simulated runoff responses in the two study years (2003 and 2017) due to spatial and temporal heterogeneity of urbanization processes in the region. While the metropolitan area has been experiencing remarkable urban development in the past few decades, the gain in built-up land in the study watershed during the study period is insignificant. On the other hand, the gain in vegetated land caused by forestation activities is offset by a decrease in farmland and grassland. The results show that increasing spatial data resolution does not necessarily or noticeably improve the HEC-HMS model performance or outcomes. Under these conditions, using Next Generation Weather Radar (NEXRAD) rainfall data in the simulation provides a satisfactory fit in hydrographs’ shapes, peak discharge amounts and time after calibration efforts, while they may overestimate the amount of rainfall as compared with gauge data. This study shows that the developed approach of synthesizing satellite, GIS, and radar rainfall data in hydrological modeling is effective and useful for incorporating urban landscape and precipitation change data in dynamic flood risk assessment at a watershed level.
Amnah Elaji; Wei Ji. Urban Runoff Simulation: How Do Land Use/Cover Change Patterning and Geospatial Data Quality Impact Model Outcome? Water 2020, 12, 2715 .
AMA StyleAmnah Elaji, Wei Ji. Urban Runoff Simulation: How Do Land Use/Cover Change Patterning and Geospatial Data Quality Impact Model Outcome? Water. 2020; 12 (10):2715.
Chicago/Turabian StyleAmnah Elaji; Wei Ji. 2020. "Urban Runoff Simulation: How Do Land Use/Cover Change Patterning and Geospatial Data Quality Impact Model Outcome?" Water 12, no. 10: 2715.
Several studies have shown human impacts on urban wetlands. These impacts are mostly studied at broad scales, which may generalize and aggregate important information needed for landscape quantification or terrain analysis. This situation can weakly or inappropriately address the structure of wetland landscapes, thus affecting the assessment of the quantities and qualities of terrestrial wetland habitats. To address these issues for urban wetland dynamics, this study proposes the use of landscape and terrain indices to characterize the landscape structure of urban wetlands at a fine scale in order to assess its usefulness in contributing to wildlife sustainability. To achieve this goal, secondary terrain attribute data are integrated with an object-based satellite image classification at the wetland and watershed level. The result reveals a general swell in wetland coverage at the watershed level. Further analysis shows the size and shape complexities, and edge irregularities are increased significantly at the patch level but slightly at the watershed level. Terrain analysis further reveals a potential increase in wetness and decrease in stream power vulnerability for most of the major wetlands under study. These results suggest that terrain and landscape indices are effective in characterizing the structure of urban wetlands that supports socio-ecological sustainability.
Olusola O. Festus; Wei Ji; Opeyemi A. Zubair. Characterizing the Landscape Structure of Urban Wetlands Using Terrain and Landscape Indices. Land 2020, 9, 29 .
AMA StyleOlusola O. Festus, Wei Ji, Opeyemi A. Zubair. Characterizing the Landscape Structure of Urban Wetlands Using Terrain and Landscape Indices. Land. 2020; 9 (1):29.
Chicago/Turabian StyleOlusola O. Festus; Wei Ji; Opeyemi A. Zubair. 2020. "Characterizing the Landscape Structure of Urban Wetlands Using Terrain and Landscape Indices." Land 9, no. 1: 29.
Prairies or grasslands together with areas designated as agricultural lands are one of the largest types of land cover and land use that exist today. While prairies provide habitat to a wide variety of animals and organisms, and agricultural lands support human populations, these lands, especially those in the immediate vicinities of large urban areas, are giving way to urbanization at alarming rates. In particular, prairies are often viewed as wastelands because their benefit to the effective functioning of the urban ecosystem is often not fully understood. On the other hand, many agricultural lands are being converted for several urban uses because of the high economic returns from their sale. In this study, we classified SPOT (Satellite Pour l’Observation de la Terre) satellite data of the study area using the supervised maximum likelihood classification approach in order to investigate the loss of prairies and agricultural lands due to urban expansion in six sub-watersheds in the Kansas City metropolitan area of the States of Kansas and Missouri in the U.S. Based on the classified maps, we computed the magnitude and rate of urban expansion, and the proportion of loss in prairies and agricultural lands that was a result of urban expansion. Results from the 22-year study revealed that in all six sub-watersheds, agricultural lands and grassland were depleted at alarming rates with no sustainable effort to conserve them. These results provide baseline information that can support a data-driven and sustainable path for urban expansion in the examined sub-watersheds.
Opeyemi Zubair; Wei Ji; Olusola Festus. Urban Expansion and the Loss of Prairie and Agricultural Lands: A Satellite Remote-Sensing-Based Analysis at a Sub-Watershed Scale. Sustainability 2019, 11, 4673 .
AMA StyleOpeyemi Zubair, Wei Ji, Olusola Festus. Urban Expansion and the Loss of Prairie and Agricultural Lands: A Satellite Remote-Sensing-Based Analysis at a Sub-Watershed Scale. Sustainability. 2019; 11 (17):4673.
Chicago/Turabian StyleOpeyemi Zubair; Wei Ji; Olusola Festus. 2019. "Urban Expansion and the Loss of Prairie and Agricultural Lands: A Satellite Remote-Sensing-Based Analysis at a Sub-Watershed Scale." Sustainability 11, no. 17: 4673.
Preserving riparian vegetation is important for maintaining water quality and riparian functions. Streamside protection ordinances have been widely established in many rapidly urbanizing areas, however, there has been a lack of assessment of the effectiveness of such ordinances. A study was conducted to determine the effectiveness of riparian vegetation preservation with and without ordinance protection. SPOT imagery was used to classify landscape changes over time (1992 through 2012) across multiple jurisdictions and pre- and post-ordinance implementation periods. Results indicated the spatial and temporal patterns of vegetation change differed by administrative areas and ordinance boundaries. The rate of tree loss and gains in developed lands in ordinance-protected areas generally increased following implementation of ordinances but at a lower rate than in non-ordinance areas. These findings suggest spatial and temporal monitoring of riparian ordinance implementation across adjacent jurisdictions is important to ensure the full effects of the ordinance protection on stream systems. Such monitoring and assessments can be used by local decision makers to adapt existing ordinances or in the development of new ordinances.
Trina E. Weilert; Wei Ji; Opeyemi A. Zubair. Assessing the Impacts of Streamside Ordinance Protection on the Spatial and Temporal Variability in Urban Riparian Vegetation. ISPRS International Journal of Geo-Information 2018, 7, 282 .
AMA StyleTrina E. Weilert, Wei Ji, Opeyemi A. Zubair. Assessing the Impacts of Streamside Ordinance Protection on the Spatial and Temporal Variability in Urban Riparian Vegetation. ISPRS International Journal of Geo-Information. 2018; 7 (7):282.
Chicago/Turabian StyleTrina E. Weilert; Wei Ji; Opeyemi A. Zubair. 2018. "Assessing the Impacts of Streamside Ordinance Protection on the Spatial and Temporal Variability in Urban Riparian Vegetation." ISPRS International Journal of Geo-Information 7, no. 7: 282.
Urban wetlands play important roles in providing several ecosystem services that support the urban environment. As such, scientists have studied them to understand the urban processes that lead to their continued decline. However, little attention has been given to the drivers of land-use change that may affect this fragile ecosystem in the future. Understanding this could serve as a critical step towards urban wetland management and sustainability. In this study, we utilized an integrated approach that combined Similarity Weighted Instance-based Machine Learning and Markov chain, both embedded in the IDRISI Land Change Modeler to simulate change in the landscape of three watersheds in the Kansas City Metropolitan area. The purpose was to assess the possible future impacts of urban expansion-induced landscape change on wetlands within the study area, using a retrospective approach. To achieve this, classified SPOT satellite data covering the three watersheds were used to generate historical land cover maps of the study area between 1992 and 2010 to analyze changes to the landscape. In addition, the study identified several drivers of land change associated with the historical change process in the study area, and accounted for their role in the modeling process. On this basis, the study made the prediction of urban landscape transformation to the end date of 2014. The prediction result was verified with a more accurate map that was derived from independently classifying a 2014 SPOT image of the study area. Results from this study show that impervious surfaces, which were used as an index of urban expansion, may increase by approximately the same magnitude experienced historically, which may result in a small but significant loss of wetlands and other land cover classes within the study area.
Opeyemi A. Zubair; Wei Ji; Trina E. Weilert. Modeling the Impact of Urban Landscape Change on Urban Wetlands Using Similarity Weighted Instance-Based Machine Learning and Markov Model. Sustainability 2017, 9, 2223 .
AMA StyleOpeyemi A. Zubair, Wei Ji, Trina E. Weilert. Modeling the Impact of Urban Landscape Change on Urban Wetlands Using Similarity Weighted Instance-Based Machine Learning and Markov Model. Sustainability. 2017; 9 (12):2223.
Chicago/Turabian StyleOpeyemi A. Zubair; Wei Ji; Trina E. Weilert. 2017. "Modeling the Impact of Urban Landscape Change on Urban Wetlands Using Similarity Weighted Instance-Based Machine Learning and Markov Model." Sustainability 9, no. 12: 2223.
This study proposes the concept of urban wet-landscapes (loosely-defined wetlands) as against dry-landscapes (mainly impervious surfaces). The study is to examine whether the dynamics of urban wet-landscapes is a sensitive indicator of the coupled effects of the two major driving forces of urban landscape change – human built-up impact and climate (precipitation) variation. Using a series of satellite images, the study was conducted in the Kansas City metropolitan area of the United States. A rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. The spatial analyses of wetland changes were implemented at the scales of metropolitan, watershed, and sub-watershed as well as based on the size of surface water bodies in order to reveal urban wetland change trends in relation to the driving forces. The study identified that wet-landscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while smaller wetlands decreased mainly due to human development activities. These findings suggest that wet-landscapes, as against the dry-landscapes, can be a more effective indicator of the coupled effects of human impact and climate change.
Wei Ji. REMOTELY-SENSED URBAN WET-LANDSCAPES: AN INDICATOR OF COUPLED EFFECTS OF HUMAN IMPACT AND CLIMATE CHANGE. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2016, XLI-B8, 915 -918.
AMA StyleWei Ji. REMOTELY-SENSED URBAN WET-LANDSCAPES: AN INDICATOR OF COUPLED EFFECTS OF HUMAN IMPACT AND CLIMATE CHANGE. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2016; XLI-B8 ():915-918.
Chicago/Turabian StyleWei Ji. 2016. "REMOTELY-SENSED URBAN WET-LANDSCAPES: AN INDICATOR OF COUPLED EFFECTS OF HUMAN IMPACT AND CLIMATE CHANGE." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8, no. : 915-918.
This study aimed to detect and understand remotely sensed urban wetland dynamics as a sensitive indicator of the combined effects of human disturbances and climate impacts in the course of global change. To address this objective, the study developed technical approaches to detect and interpret wetland changes across spatial scales in complex urban landscapes. Using a series of Satellite Pour l’Observation de la Terre (SPOT) images covering 1992–2010, the study was conducted in the Kansas City metropolitan area of the USA, which has experienced significant urban sprawl in recent decades. As a fine-tuning of the traditional supervised image classification, a knowledge-based classification algorithm was developed to identify fine-scale, hidden wetlands that cannot be appropriately detected based on their spectral differentiability. The analyses of wetland change were implemented at the metropolitan, watershed, and sub-watershed scales as well as being based on the size of surface water bodies in order to reveal real pictures of urban wetland change trends in relation to major driving factors. The results of the study indicated that the knowledge-based classification approach improved the detection capability and accuracy of urban wetlands by fine-tuning the traditional classification results. The cross-scale analysis of detected land covers revealed that wetland dynamics varied in trend and magnitude from metropolitan, watersheds, to sub-watershed scales. The study found that increased precipitation swelled wetlands, which inflated the findings of remotely sensed wetland cover and related trend interpretation. During an 18 year study period, human development activities in the study area resulted in a large increase in impervious surfaces, which was mainly at the expense of farmland/grassland areas and some small wetlands in all urban watersheds. In contrast, increased precipitation in the region swelled large wetlands in particular. This mixed picture of urban wetland dynamics, associated with the analysis of underlying driving factors, provides a new baseline for relevant urban planning, management, and research in a global change perspective.
Wei Ji; Xiaofan Xu; Dzingirai Murambadoro. Understanding urban wetland dynamics: cross-scale detection and analysis of remote sensing. International Journal of Remote Sensing 2015, 36, 1763 -1788.
AMA StyleWei Ji, Xiaofan Xu, Dzingirai Murambadoro. Understanding urban wetland dynamics: cross-scale detection and analysis of remote sensing. International Journal of Remote Sensing. 2015; 36 (7):1763-1788.
Chicago/Turabian StyleWei Ji; Xiaofan Xu; Dzingirai Murambadoro. 2015. "Understanding urban wetland dynamics: cross-scale detection and analysis of remote sensing." International Journal of Remote Sensing 36, no. 7: 1763-1788.
Hydrologic variation affects many functions of wetlands. Rapidly and accurately measuring hydrologic dynamics in a wetland watershed has become a fundamental need for estimating functional changes of wetlands. The satellite altimeters have become good data sources that can complement the measurements of gauge stations. As a case project applied in the Poyang Lake watershed, this study has developed a technical approach that integrates the altimeter measurements with the in situ water level data. The derived water surface heights with Envisat RA-2 data are compared with the daily observations of in situ water levels. The average absolute observation difference between the “altimeter station” and its nearest gauge station is 0.307 m, which is comparable to the average differences among the gauge stations. The results suggest that the derived water surface heights from the altimeter data have a good accuracy, which can be used along with the in situ observations as supplements to fill the ungauged area in Poyang Lake wetlands.
Xiaobin Cai; Wei Ji. Wetland hydrologic application of satellite altimetry – A case study in the Poyang Lake watershed. Progress in Natural Science 2009, 19, 1781 -1787.
AMA StyleXiaobin Cai, Wei Ji. Wetland hydrologic application of satellite altimetry – A case study in the Poyang Lake watershed. Progress in Natural Science. 2009; 19 (12):1781-1787.
Chicago/Turabian StyleXiaobin Cai; Wei Ji. 2009. "Wetland hydrologic application of satellite altimetry – A case study in the Poyang Lake watershed." Progress in Natural Science 19, no. 12: 1781-1787.
Conserving genetic diversity requires an assessment of the distribution of genetic variants in relation to patterns of land use and environmental variation at a regional scale. This assessment requires a novel approach to integrating and analyzing the genetic and environmental data across spatial scales. To explore the integration of genetic data with other geospatial data sets, we developed a GIS-based approach for examining patterns of genetic diversity for several species of salamanders in southern Appalachians. The genetic data, from allozyme surveys in the genetics literature, were integrated into a GIS database along with related attributes including population identifications and spatial locations. Using existing geospatial data, we classified sample locations as being either protected from anthropogenic disturbance (e.g., National Parks, Wilderness Areas) or as unprotected (e.g., private lands, multiple-use lands in National Forests). We used multidimensional scaling of allelic frequencies and contributions of populations to interpopulation differences in allelic richness to determine which populations had genetic characteristics most different from other populations in the sample. Measures of genetic differentiation were integrated into the GIS database to facilitate spatial analysis and visualization of the indices in relation to land use. This approach was useful for both identification of populations with components of genetic variation that were not well represented at protected sites and for identifying areas of species distributions where more genetic sampling would be necessary to make informed management decisions. Our approach could be readily adapted for use by managers and geneticists working with other species and types of genetic markers.
Wei (Wayne) Ji; Paul Leberg. A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians. Environmental Management 2002, 29, 531 -544.
AMA StyleWei (Wayne) Ji, Paul Leberg. A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians. Environmental Management. 2002; 29 (4):531-544.
Chicago/Turabian StyleWei (Wayne) Ji; Paul Leberg. 2002. "A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians." Environmental Management 29, no. 4: 531-544.
Wei Ji; Clinton Jeske. Spatial modeling of the geographic distribution of wildlife populations: a case study in the lower Mississippi River region. Ecological Modelling 2000, 132, 95 -104.
AMA StyleWei Ji, Clinton Jeske. Spatial modeling of the geographic distribution of wildlife populations: a case study in the lower Mississippi River region. Ecological Modelling. 2000; 132 (1-2):95-104.
Chicago/Turabian StyleWei Ji; Clinton Jeske. 2000. "Spatial modeling of the geographic distribution of wildlife populations: a case study in the lower Mississippi River region." Ecological Modelling 132, no. 1-2: 95-104.