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2020 | Buch

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Remote Sensing of Land Use and Land Cover in Mountain Region

A Comprehensive Study at the Central Tibetan Plateau

verfasst von: Duo Chu

Verlag: Springer Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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Über dieses Buch

This book presents the spatial and temporal dynamics of land use and land cover in the central Tibetan Plateau during the last two decades, based on various types of satellite data, long-term field investigation and GIS techniques. Further, it demonstrates how remote sensing can be used to map and characterize land use, land cover and their dynamic processes in mountainous regions, and to monitor and model relevant biophysical parameters.
The Tibetan Plateau, the highest and largest plateau on the Earth and well known as “the roof of the world,” is a huge mountainous area on the Eurasian continent and covers millions of square kilometers, with an average elevation of over 4000 m. After providing an overview of the background and an introduction to land use and land cover change, the book analyzes the current land use status, dynamic changes and spatial distribution patterns of different land-use types in the study area, using various types of remotely sensed data, digital elevation models and GIS spatial analysis methods to do so. In turn, it discusses the main driving forces, based on the main physical environment variables and socioeconomic data, and provides a future scenario analysis of land use change using a Markov chain model. Given its scope, it provides a valuable reference guide for researchers, scientists and graduate students working on environmental change in mountainous regions around the globe, and for practitioners working at government and non-government agencies.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

Land-use and land-cover change (LUCC) plays a pivotal role in global environmental change and significantly affects Earth-atmosphere interactions, ecosystem services, climate change, biogeochemical cycles, and biodiversity. Understanding their dynamic processes and impacts is crucial to better use and manage precious land resources and to realize sustainable development. Global mountain regions cover one fourth of the Earth’s land surface and are most vulnerable and sensitive to environmental change and global warming, which provide unique opportunities to monitor and study environmental change processes and consequences. Meanwhile, remote sensing provides spatially continuous observations on the Earth’s surface from space. The integration with geographic information systems (GIS) is an effective approach to characterize, map, and monitor land-use and land-cover change and dynamic processes. With the advancement in remote sensing, GIS, and computer technology, it is now possible to monitor, map, and assess land cover and land-cover changes at multiple spatial and temporal scales with more spatially and temporally explicit ways.

Duo Chu

Chapter 2. Study Area

Abstract

The study region is the Lhasa area, which is located at the middle and lower reaches of Lhasa River basin in central Tibetan Plateau (TP). Lhasa City, as the capital city and center of politics, economy, culture, transportation, and religion of Tibet Autonomous Region (TAR, hereafter also referred to as Tibet), is situated within the study area. The region has a long history of land resources development and utilization and the highest population density in TAR, which makes that the impact of human activities on regional environment is marked and extensive compared to other areas in the TP.

Duo Chu

Chapter 3. Land-Use Status

Abstract

A new land-use status classification system is developed based on the first land-use status survey of Tibet Autonomous Region (TAR) to be applicable for mapping land-use status in Tibet with different spatial scales of remote sensing data from aerial photograph to orbit satellite. It is a hierarchically based three-level classification system and contains 8 level I, 34 level II, and 12 level III. Land-use status map for the Lhasa area located at central Tibetan Plateau is made based on the color infrared aerial photographs and Landsat Thematic Mapper (TM) using proposed classification system. Results show that in the Lhasa area the grassland covers the largest area extent with 71.48% of total land area, followed by unused land (16.88%) and water body (5.25%). Other land-use types account for less than 4%. Among these, cultivated land is 70021.72 ha., covering 2.37% of total land area, and is distributed in all counties except Damshung County in the north.

Duo Chu

Chapter 4. Spatial Distribution of Land-Use Types

Abstract

Land use is one of the most important ways that humans use land resources to meet their material, social, and cultural needs, and its spatial distribution pattern largely features topographic dependence in mountain regions. Study on spatial distribution of different land-use types in the Lhasa area at central Tibetan Plateau shows that the altitude difference between the highest and the lowest points is 3612 m with an average elevation of 4616 meters above sea level (masl), and most of land ranges from 3550 to 5500 masl with 92.27% of total land area. As a mountainous region, in the study area the flat land without slope gradient is limited in area and covers 23.70% of total land area. Most of cultivated land is in elevation range from 3550 to 4000 masl with covering 74.32% of total cultivated land, while forest distribution is spatially much broader and natural shrub is dominant cover type. Over 50% of settlement and built-up land is in elevation range from 3650 to 3750 masl. Grassland is the largest land-use type with 93.78% lying in elevation range from 4000 to 6000 masl, while lake covers the largest area in water body and is composed of eastern part of Namtso Lake within Lhasa area.

Duo Chu

Chapter 5. Land-Use Change

Abstract

Based on the result of the first land resources survey in Tibet Autonomous Region (TAR) carried out in the late 1980s, land-use map of Lhasa area in 1990 is produced using aerial photographs obtained in April, May, and October 1991 for the main agricultural area in the river valleys and Landsat TM images acquired in the late 1980s and 1991 for the rest of the area. Using these remotely sensed data, land-use status of Lhasa area in 1991, 1992, 1993, 1995, 1999, and 2000 is mapped through updating annual changes of cultivated land, artificial forest and grass planting, grassland restoration, built-up area expansion, and so on. Land-use map for the Lhasa area in 2007 is made using ALOS AVNIR-2 composite images acquired on October 24 and December 26, 2007, through updating changes of main land-use types. Of which, based on the land-use status in 1990, 1995, 2000, and 2007, the spatial and temporal land-use change and dynamics in the Lhasa area located at central Tibetan Plateau from 1990 to 2007 are analyzed using GIS spatial analysis techniques in this chapter.

Duo Chu

Chapter 6. Land-Use Change Scenario

Abstract

Land-use change models are tools to support the analysis of the causes and consequences of land-use dynamics. Scenario analysis with land-use models can support land-use planning and policy. In this study, Markov chain model, which describes land-use and land-cover change from one period to another and uses this as the basis to predict future changes, is applied to project land-use changes in the future for Lhasa area located at the central Tibetan Plateau over a 20-year period from 2000 to 2020 based on the land-use change dynamics and transition probability matrix from 1990 to 2000, and comparison analysis between areas from land-use planning and Markov model projection is made. Results indicated that Markov chain model is found to be useful tool for describing and predicting land-use change process in the study area, and the general trends of future land-use change in the study area are effectively captured, which shows that cultivated land, grassland, water body, and unused land-use types would decrease, whereas forest, horticultural, and built-up land would continue to increase. Studying land-use changes in the past few years and predicting these changes in the future years to come may play a significant role in planning and optimal use of natural resources and harnessing the non-normative changes in the future.

Duo Chu

Chapter 7. Land-Cover Change

Abstract

In this chapter, land-cover change based on the Normalized Difference Vegetation Index (NDVI) derived from the NOAA AVHRR Global Vegetation Index (GVI) for the Lhasa area at the central Tibetan Plateau from 1985 to 1999 is presented, and its sensitivity to climate conditions is discussed, followed by analysis on vegetation phenologies and dynamics using the discrete Fourier transform (DFT). The time series of NDVI demonstrate a positive trend from 1985 to 1999, which means that general vegetation biomass on land surface presents increasing, and this trend is strongly associated with increased rainfall and temperature from the mid-1980s to 1990s. The correlation analysis shows that the NDVI is more sensitive to precipitation (r = 0.75, P < 0.01) than temperature (r = 0.63, P < 0.01) in this semiarid climate zone. The study also indicated that DFT is a very useful tool to understand vegetation phenologies and dynamic change through decomposition of temporal data to frequency domain.

Duo Chu

Chapter 8. Ecoregion Classification

Abstract

After a brief introduction, in this chapter, the spatial interpolation methods and regression models for main climate variables for the Lhasa area at the central Tibetan Plateau are developed. Subsequently, based on the comprehensive analysis on regional environmental characteristics and climatic conditions in the study area, seven key variables from topography and climate are selected as main indicators affecting ecological region, and then ecoregion classification is implemented based on these indicators using principal component analysis (PCA) and artificial neural networks (ANN) techniques, and main results are presented. The chapter ends with conclusion and discussion.

Duo Chu

Chapter 9. Land-Cover Classification

Abstract

Land-cover classification is an important application area of satellite remote sensing. However, deriving thematic map from satellite imagery through classification approaches is not a straightforward task, especially from high-resolution satellite imagery. In this study, Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral composite image is successfully used to land-cover classification for the Lhasa area located at central Tibetan Plateau (TP) using maximum likelihood classifier. Accuracy assessment for final results is also made using quantitative approaches. Study shows that there is a good agreement between classification results and reference data for defined land-cover classes in central TP. The overall classification accuracy is 87.68%. Reference and ancillary data are increasingly available and are very useful for refining accuracy of classification results during postclassification process. The integration of digital elevation model (DEM) into land-cover classification is particularly important in mountain region since land-cover distribution in mountain region is spatially topography-dependent. Study also suggests that with increase of spatial resolution, how to effectively use the spatial information inherent in satellite remote sensing images to extract thematic maps for various applications remains a challenge and is an important task to be fulfilled in the future.

Duo Chu

Chapter 10. Fractional Vegetation Cover

Abstract

Fractional vegetation cover (FVC) is an important parameter in the study of ecosystem balance, soil erosion, and climate change and is often used to evaluate and monitor vegetation degradation and desertification. Remote sensing provides the only feasible way to estimate FVC at regional and global scales. In the present study, an empirical model of FVC estimation is developed for central Tibetan Plateau (TP) based on the relationships between vegetation indices from Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) and corresponding field measurements derived from digital camera, which is followed by in-depth analysis on the spatial distribution of vegetation coverage using proposed method. Study shows that a linear relationship exists between vegetation coverage from the field observation and MODIS NDVI with coefficient of determination of R ² = 0.90, which is slightly better than MODIS SAVI performance with R ² = 0.89 and is an optimal regression model for FVC estimation. Vegetation coverage ranges 20–90% in the most part of central TP, presenting moderate to high as a whole, and generally decreases from east to west with strong regional differences due to discrepancies in land-cover types, plant species, topography and water resources availability, and so on.

Duo Chu

Chapter 11. Aboveground Biomass of Grassland

Abstract

Biomass is an important component of grassland ecosystems and plays a critical role in the sustainable use of grassland resources and the global carbon cycle. Satellite remote sensing provides an important approach for estimating aboveground biomass (AGB) at large spatial scales while biomass harvesting offers reliable and site-specific biomass magnitude and is only way to give indispensable ground truth for satellite remote sensing. In this study, estimate models for grassland AGB for the Lhasa area located at the central Tibetan Plateau (TP) are developed based on the relationships between the field measurements and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (NDVI, EVI), and the models are validated against independent field measurements. The result shows that exponential relationships exist between AGB and MODIS vegetation indices. MODIS NDVI is more effective to estimate grassland AGB in the study area with R ² = 0.63 than EVI with R ² = 0.50 and is an optimal regression model for AGB estimation. For green AGB estimation, the performance of NDVI (R ² = 0.69) is also better than EVI (R ² = 0.59). In the study area, AGB spatially presents decreases from east to west, with great regional differences due to inhomogeneous grassland types and impact of various environmental and climatic factors. AGB is above 100 g/m² in some eastern regions whereas it is lower than 20 g/m² in the west.

Duo Chu

Titel: Remote Sensing of Land Use and Land Cover in Mountain Region
verfasst von: Duo Chu
Verlag: Springer Singapore
Electronic ISBN: 978-981-13-7580-4
Print ISBN: 978-981-13-7579-8
DOI: https://doi.org/10.1007/978-981-13-7580-4