Modeling Land-Cover Types Using Multiple Endmember Spectral Mixture Analysis in a Desert City

Spectral mixture analysis is probably the most commonly used approach among sub-pixel analysis techniques. This method models pixel spectra as a linear combination of spectral signatures from two or more ground components. However, spectral mixture analysis does not account for the absence of one of the surface features or spectral variation within pure materials since it utilizes an invariable set of surface features. Multiple endmember spectral mixture analysis (MESMA), which addresses these issues by allowing endmembers to vary on a per pixel basis, was employed in this study to model Landsat ETM+ reflectance in the Phoenix metropolitan area. Image endmember spectra of vegetation, soils, and impervious surfaces were collected with the use of a fine resolution Quickbird image and the pixel purity index. This study employed 204 (=3x17x4) total four-endmember models for the urban subset and 96 (=6x6x2x4) total five-endmember models for the non-urban subset to identify fractions of soil, impervious surface, vegetation, and shade. The Pearson correlation between the fraction outputs from MESMA and reference data from Quickbird 60 cm resolution data for soil, impervious, and vegetation were 0.8030, 0.8632, and 0.8496 respectively. Results from this study suggest that the MESMA approach is effective in mapping urban land covers in desert cities at sub- pixel level.

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown

Remotely-Sensed Derived Built-up Area as an Alternative Indicator in the Study of Thailand’s Regional Development

Nowadays measuring national and regional development primarily relies on demographic and socio-economic indicators. An indicator in physical dimension e.g., areas of human settlements and their economic uses of lands is usually ignored due to unavailability of data in countries like Thailand. Remotely-sensed derived built-up area was used, for the first time, as a physical indicator for studying Thailand’s regional development. Remote sensing - using the decision tree classifier with the combination indices of band ratios, NDVI, MNDWI, and NDBI - and GIS techniques were utilized to estimate the regional proportion of built-up area. The relationships between the percentage of the derived built-up area and the three development indicators - urbanization rate, Gross Regional Product, and Human Achievement Index - were analyzed. Resultantly, the estimate of the 2019 derived built-up area in Thailand was 2.46% with the average accuracy of 84.5%. Regional variation in development levels existed and relationships between the percentage of built-up area and the three development indicators for the regions were strong. However, there was no relationship after excluding the region having the effect of Bangkok. Therefore, remotely-sensed derived built-up area gives new information and is suggested for use for the analysis of Thailand’s regional development

Permanent disappearance and seasonal fluctuation of urban lake area in Wuhan, China monitored with long time series remotely sensed images from 1987 to 2016

Lakes are important to the healthy functioning of the urban ecosystem. The urban lakes in Wuhan, China, which is known as ‘city of hundreds of lakes’, are facing substantial threats mainly due to rapid urbanization. This paper focused on detecting the spatial and temporal change of urban lakes in Wuhan, using a long time series of Landsat and HJ-1A remotely sensed data from 1987 to 2016. The permanent disappearance and seasonal fluctuation of 28 main urban lakes were analysed, and their relationships with climatic change and human activities were discussed. The results show that most lakes in Wuhan had shrunk over the past 30 years resulting in a permanent change from water to land. The shrinkage was also most apparent in the central region of the city. Seasonal fluctuations of lake area were evident for most lakes but the relative important driving variable of lake area change varied between sub-periods of time for different lakes. The explanatory power of impervious surface to five-year permanent water change is 91.75%, suggesting that urbanization – as increasing impervious surface – had led to the shrinkage of urban lakes in Wuhan. In all, 128.28 km2 five-year permanent water disappeared from 1987 to 2016

Dynamic estimation model of vegetation fractional coverage and drivers

This research reveals major changes of VFC and drivers in 2000 to 2010 in Guangdong province, China. Using MODIS NDVI, VFC directly calculated. Spatial patterns of VFC changes classified into four levels such as low (90%) in 2000, 2005 and 2010 separately. Time series of VFC showed the fitting curve is a straight line of value 0.783 (78.3%). Results showed that level >90% has highest mean of change annually, with values between 3.89% to 21.44% and level <50% has the lowest mean among all levels. The values of level 50-70% are between 7.79% and 19% and values of level 70-90% are between 68.38% and 77.25%. Trend analysis of VFC showed that in the northern mountainous regions, the economy is undeveloped and there is less human disturbance, leads to having higher VFC. In the southern coastal parts, human disturbance such as industrialization and urbanization can be seen, leads to having low VFC. Plus, using DMSP/OLS, CNLI computed. The driving factors of VFC dynamics considered human activities and climatic factors and finally Pearson correlation coefficient confirmed the relationship between VFC, climatic factors and CNLI. Result showed that VFC is positively correlated with sunshine hour, but VFC is not related to CNLI indicates that at provincial scale over research period of about 10 years, Even though urbanization and industrialization had a defined impact on the change of VFC in some cases

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics

Multitemporal Imagery Based Analysis of Urban Land in St. Tammany Parish in Conjunction with Socioeconomic Data

The role of urbanization in the history of civilization is a profound and intricate part of human geography. By utilizing socioeconomic data and then integrating it with more technological innovations, such as remote sensing, the spread of sprawl and the urban corridor can better be mapped and quantified by researchers. Many different types of socioeconomic data were implemented in addition to the remotely sensed data. In this paper, six Landsat 5 TM images were used to create land cover classification maps of the developed or built-up land in St. Tammany Parish from 1984 to 2008. It was found that, in addition to St. Tammany expanding in population, the urban areas are becoming denser using a method called the remote method. This method is an advanced function of density that allows researchers to estimate consumption of the developed land

Remotely sensed mid-channel bar dynamics in downstream of the Three Gorges Dam, China

The downstream reach of the Three Gorges Dam (TGD) along the Yangtze River (1560 km) hosts numerous mid-channel bars (MCBs). MCBs dynamics are crucial to the river’s hydrological processes and local ecological function. However, a systematic understanding of such dynamics and their linkage to TGD remains largely unknown. Using Landsat-image-extracted MCBs and several spatial-temporal analysis methods, this study presents a comprehensive understanding of MCB dynamics in terms of number, area, and shape, over downstream of TGD during the period 1985−2018. On average, a total of 140 MCBs were detected and grouped into four types representing small ( 2 km2), middle (2 km2 − 7 km2), large (7 km2 − 33 km2) and extra-large size (>33 km2) MCBs, respectively. MCBs number decreased after TGD closure but most of these happened in the lower reach. The area of total MCBs experienced an increasing trend (2.77 km2/yr, p-value 0.01) over the last three decades. The extra-large MCBs gained the largest area increasing rate than the other sizes of MCBs. Small MCBs tended to become relatively round, whereas the others became elongate in shape after TGD operation. Impacts of TGD operation generally diminished in the longitudinal direction from TGD to Hankou and from TGD to Jiujiang for shape and area dynamics, respectively. The quantified longitudinal and temporal dynamics of MCBs across the entire Yangtze River downstream of TGD provides a crucial monitoring basis for continuous investigation of the changing mechanisms affecting the morphology of the Yangtze River system

Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion

With increasing population growth, the Harare Metropolitan Province has experienced accelerated land use and land cover (LULC) changes, influencing the city’s growth. This study aims to assess spatiotemporal urban LULC changes, the axis, and patterns of growth as well as drivers influencing urban growth over the past three decades in the Harare Metropolitan Province. The analysis was based on remotely sensed Landsat Thematic Mapper and Operational Land Imager data from 1984–2018, GIS application, and binary logistic regression. Supervised image classification using support vector machines was performed on Landsat 5 TM and Landsat 8 OLI data combined with the soil adjusted vegetation index, enhanced built-up and bareness index and modified difference water index. Statistical modelling was performed using binary logistic regression to identify the influence of the slope and the distance proximity characters as independent variables on urban growth. The overall mapping accuracy for all time periods was over 85%. Built-up areas extended from 279.5 km2 (1984) to 445 km2 (2018) with high-density residential areas growing dramatically from 51.2 km2 (1984) to 218.4 km2 (2018). The results suggest that urban growth was influenced mainly by the presence and density of road networks