Sustainable Urbanization in the China‐Indochinese Peninsula Economic Corridor

Countries in the China‐Indochinese Peninsula are home to rich human and natural resource endowments and have the potential to be one of the world\u27s fastest growing areas. Sustainable urbanization in the China‐Indochinese Peninsula Economic Corridor is important for the regional economic development and prosperity. Taking the advantages of the remote sensing and Geographic Information System (GIS) technologies, this chapter is first presents a general overview of urbanization procession in this region and monitors the spatiotemporal dynamics of the urban environment; the second objective is to present the multiple driving force factor analysis for urban development in countries of the China‐Indochinese Peninsula Economic Corridor using statistical models. The results indicated that the China‐Indochinese Peninsula Economic Corridor has experienced a rapid urbanization process during the past 15 years both in terms of urban areas and urban population (UP). In addition to socioeconomic factors, there is also a noticeable correlation between foreign direct investment (FDI) and international trade and urban development in the China‐Indochinese Peninsula Economic Corridor. Active participation in international trade and attracting foreign investment are helpful for the regional urbanization. As a neighboring country, China\u27s economic and trade activity also has a significant impact on the urbanization in countries of the China‐Indochinese Peninsula Economic Corridor. Furthermore, as the launch of the Silk Road Economic Belt and the 21st Century Maritime Silk Road and the Asian Infrastructure Investment Bank (AIIB), the China‐Indochinese Peninsula Economic Corridor will witness a more rapid urbanization progress in the next decade. This study has its characteristics in focusing on the region of the Indochinese Peninsula in which the most rapid urbanization is occurring, presenting the state‐of‐the‐art techniques for monitoring urban expansion and probing into the driving factors of the urban expansion in the China‐Indochinese Peninsula Economic Corridor by multiple principles and multiple‐level data. It is expected to benefit policymakers in urban development and also provide a basis for further studies of sustainable urbanization in the China‐Indochinese Peninsula Economic Corridor

Monitoring the Coastal Environment Using Remote Sensing and GIS Techniques

The coastal zone has been of importance for economic development and ecological restoration due to their rich natural resources and vulnerable ecosystems. Remote sensing techniques have proven to be powerful tools for the monitoring of the Earth’s surface and atmosphere on a global, regional, and even local scale, by providing important coverage, mapping and classification of land cover features such as vegetation, soil, water and forests. This chapter introduced the methods for monitoring the coastal environment using remote sensing and GIS techniques. Case studies of port expansion monitoring in typical coastal regions, together with the coastal environment changes analysis were also presented

Simulating Spatiotemporal Dynamics of Sichuan Grassland Net Primary Productivity Using the CASA Model and In Situ Observations

Net primary productivity (NPP) is an important indicator for grassland resource management and sustainable development. In this paper, the NPP of Sichuan grasslands was estimated by the Carnegie-Ames-Stanford Approach (CASA) model. The results were validated with in situ data. The overall precision reached 70%; alpine meadow had the highest precision at greater than 75%, among the three types of grasslands validated. The spatial and temporal variations of Sichuan grasslands were analyzed. The absorbed photosynthetic active radiation (APAR), light use efficiency (ε), and NPP of Sichuan grasslands peaked in August, which was a vigorous growth period during 2011. High values of APAR existed in the southwest regions in altitudes from 2000 m to 4000 m. Light use efficiency (ε) varied in the different types of grasslands. The Sichuan grassland NPP was mainly distributed in the region of 3000–5000 m altitude. The NPP of alpine meadow accounted for 50% of the total NPP of Sichuan grasslands

Analysis of water synergy benefits of coal de-capacity in China

The closure/withdrawal of mines, as one of the important measures to implement the State Council’s “Opinions on supporting the coal industries to resolve excess production capacity and achieve destructive development”, and is of great significance to the optimization of the regional energy structure, reduction of carbon emissions and environmental protection. In order to assess the synergistic benefits of water resources generated in the process of coal de-capacity and reveal the spatial and temporal evolution characteristics of closure/withdrawal mines, the number and capacity of closure/withdrawal mines during 2016—2022 were investigated with coal de-capacity as the policy background. Based on the analysis of the spatial and temporal distribution characteristics of the closure/withdrawal mines, the water resources synergy benefits brought about by coal de-capacity was quantified by combining the water resources-related mine water, water consumption and wastewater discharges coefficients in the coal mining and washing stages. The results show that a total of 4027 mines were closure/withdrawal from coal-related provinces in China during 2016—2022, with a de-capacity of 875 million t. The number of mines closure/withdrawal is concentrated in the upper reaches of the Yangtze River, and the areas with high density of coal de-capacity are concentrated in the "Ji" bays of the Yellow River. Meanwhile, the total of wasted water resources reduced by coal de-capacity is about 3 billion t, higher than the volume of China’s fourth largest freshwater Honghu lake, generating socio-economic benefits of about 46.165 billion yuan. The areas with positive benefits of water synergy are mainly located in the water shortage areas such as Southwest China, North China and the Yellow River basin. This research quantifies the synergistic benefits of water resources for coal de-capacity and discusses the future direction of mine water resources utilization, with a view to providing scientific basis and data support for sustainable development and “double carbon” target for coal de-capacity

Evaluating the Marginal Land Resources Suitable for Developing Bioenergy in Asia

Bioenergy from energy plants is an alternative fuel that is expected to play an increasing role in fulfilling future world energy demands. Because cultivated land resources are fairly limited, bioenergy development may rely on the exploitation of marginal land. This study focused on the assessment of marginal land resources and biofuel potential in Asia. A multiple factor analysis method was used to identify marginal land for bioenergy development in Asia using multiple datasets including remote sensing-derived land cover, meteorological data, soil data, and characteristics of energy plants and Geographic Information System (GIS) techniques. A combined planting zonation strategy was proposed, which targeted three species of energy plants, including Pistacia chinensis (P. chinensis), Jatropha curcas L. (JCL), and Cassava. The marginal land with potential for planting these types of energy plants was identified for each 1 km2 pixel across Asia. The results indicated that the areas with marginal land suitable for Cassava, P. chinensis, and JCL were established to be 1.12 million, 2.41 million, and 0.237 million km2, respectively. Shrub land, sparse forest, and grassland are the major classifications of exploitable land. The spatial distribution of the analysis and suggestions for regional planning of bioenergy are also discussed

Monitoring the Invasion of Spartina alterniflora

Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population

Evaluation of Hyperspectral Indices for Chlorophyll-a Concentration Estimation in Tangxun Lake (Wuhan, China)

Chlorophyll-a (Chl-a) concentration is a major indicator of water quality which is harmful to human health. A growing number of studies have focused on the derivation of Chl-a concentration information from hyperspectral sensor data and the identification of best indices for Chl-a monitoring. The objective of this study is to assess the potential of hyperspectral indices to detect Chl-a concentrations in Tangxun Lake, which is the second largest lake in Wuhan, Central China. Hyperspectral reflectance and Chl-a concentration were measured at ten sample sites in Tangxun Lake. Three types of hyperspectral methods, including single-band reflectance, first derivative of reflectance, and reflectance ratio, were extracted from the spectral profiles of all bands of the hyperspectral sensor. The most appropriate bands for algorithms mentioned above were selected based on the correlation analysis. Evaluation results indicated that two methods, the first derivative of reflectance and reflectance ratio, were highly correlated (R2 > 0.8) with the measured Chl-a concentrations. Thus, the spatial and temporal variations of Chl-a concentration could be conveniently monitored with these hyperspectral methods

Advances in Multi-Sensor Data Fusion: Algorithms and Applications

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of “algorithm fusion” methods; (3) Establishment of an automatic quality assessment scheme

Optimization of Production–Living–Ecological Space in National Key Poverty-Stricken City of Southwest China

Trade-offs and conflicts among different sectors of production, living, and ecology have become important issues in regional sustainable development planning due to both the versatility and limitation of land resources, especially in poverty-stricken mountainous areas. This study builds an optimization model to assist policymakers in simulating land demand and allocation in the future. The model takes socioeconomic and demographic development into consideration and couples local planning policy with land use data from the perspective of system integration. The model was employed for a case study of Zhaotong city to optimize production–living–ecological (PLE) space. The results show that the model provides a feasible method to explore the sustainable development pattern of territorial space, especially in distressed regions