We have entered the urban century and addressing a broad suite of sustainability challenges in urban areas is increasingly key for our chances to transform the entire planet towards sustainability. For example, cities are responsible for 70% of global greenhouse gas emissions and, at the same time, 90% of urban areas are situated on coastlines, making the majority of the world's population increasingly vulnerable to climate change. While urbanization accelerates, meeting the challenges will require unprecedented transformative solutions for sustainability with a careful consideration of resilience in their implementation. However, global and local policy processes often use vague or narrow definitions of the concepts of 'urban sustainability' and 'urban resilience', leading to deep confusion, particularly in instances when the two are used interchangeably. Confusion and vagueness slow down needed transformation processes, since resilience can be undesirable and many sustainability goals contrast, or even challenge efforts to improve resilience. Here, we propose a new framework that resolves current contradictions and tensions; a framework that we believe will significantly help urban policy and implementation processes in addressing new challenges and contributing to global sustainability in the urban century.

Mega- urban agglomerations in China play a vital role in both national economic development strategies and national new-type urbanization, and undertake important historical responsibility with the world economic center transfer to China. However, they suffer a series of increasingly serious eco- environmental problems in the process of development. Thus,studies on the interactive coupled effects between urbanization and eco-environment in megaurban agglomerations are the frontier areas and high priority tasks in the earth system science for the future ten years. This paper analyses the basic theory frame of the interactive coupled effects between urbanization and eco- environment in mega- urban agglomerations systematically. In theoretical aspect, based on the nonlinear relationship and coupling characteristics of the natural and human elements in mega- urban agglomerations system, we could estimate the interactive coercing intensity, nearcoupling and telecoupling mechanism ofthe inside and outside mega-urban agglomerations system after scientific identification of the key elements, and then form the basic interactive coupling theory. Moreover, we could build a spatio- temporal coupling dynamic model, which is integrated with multi- elements, multiscales,multi-scenarios, multi-modules and multi-agents. The model will be used to develop the intelligent decision support system for urban agglomeration sustainable development. In methodology aspect, the mega- urban agglomeration is regarded as an open complex giantsystem. We should establish the standardized shared database for exploring the interactive coupled effects between urbanization and eco- environment. Then using new technology for analyzing big data and the integration methods incorporating of multi- elements, multi- scales,multi- targets, multi- agents, multi- scenarios and multi- modules, we can build a methodology framework to analyze the complex interaction coupling between urbanization and ecoenvironment. The technical route is to analyze spatiotemporal evolution characteristics, identifythe key elements, interpret coupling relationship, reveal the mechanism of coercing effect, find the general rules, filtrate the control variables, solve the critical thresholds, conduct regulation experiments, simulate different scenarios, propose an optimized schemes, and achieve national goals. Furthermore, we could put forward the overall optimization scheme. In general, this research could provide theoretical guidance and method support for the transformation and sustainable development in mega-urban agglomerations.

特大城市群地区是国家经济发展的战略核心区和国家新型城镇化的主体区，担当着世界经济重心转移承载地的历史重任，但在发展过程中面临着日益严重的资源与生态环境的胁迫压力。开展特大城市群地区城镇化与生态环境交互耦合效应的研究，是未来10 年地球系统科学研究的前沿领域和高优先研究主题。本文系统解析了特大城市群地区城镇化与生态环境交互耦合效应的基本理论框架。首先从理论上分析了特大城市群系统各自然要素和人文要素交互作用的非线性耦合关系及耦合特征，科学辨识近远程主控要素作用下城市群系统内外部各要素相互作用的胁迫强度、近远程耦合机理与规律，总结特大城市群地区城镇化与生态环境交互耦合圈理论，进一步构建多要素—多尺度—多情景—多模块—多智能体集成的时空耦合动力学模型，研发特大城市群地区可持续发展优化智能调控决策支持系统；其次从方法上将特大城市群地区视为一个开放的复杂巨系统，在建立同一标准化共享数据库的基础上，采用多要素—多目标—多模型—多情景环境下的城镇化与生态环境交互耦合集成技术方法、大数据支持下的城镇化与生态环境交互耦合技术方法，构建多尺度—多技术—多智能体集成的城镇化与生态环境交互耦合技术框架，按照分析时空演变特征—寻求主控要素—辨识耦合关系—揭示胁迫机制—发现耦合规律—筛选调控变量—求解临界阈值—进行调控试验—完成情景模拟—提出优化方案—完成情景模拟—提出优化方案—实现国家目标这样一条技术路径，提出解决问题的整体优化方案。本文旨在为特大城市群地区由问题集中区转为可持续发展区提供理论指导和方法支撑。

In 2016, the World Health Organization declared that 'Health is one of the most effective markers of any city's successful sustainable development' (World Health Organisation, 2016). With estimates that around 6.7 billion people will live in cities by 2050, 21 century city planning decisions will play a critical role in achieving the United Nations (UN) Sustainable Development Goals (SDGs). They will determine the city structure and access to health-enhancing (or health-damaging) urban environments, and ultimately lifestyle choices that impact both individual and planetary health. Benchmarking, monitoring and evaluating city planning policies and interventions is therefore critical to optimise urban outcomes. In 2017, the UN adopted a global SDG indicator framework, calling for complementary national and regional indicators to be collected by member countries. UN Habitat has also developed an indicator action framework specifically for cities. This paper examined the extent to which the UN indicators will help cities evaluate their efforts to deliver sustainability and health outcomes. It identified inconsistencies between the two UN indicator frameworks. Many of the SDG indicators assess outcomes, rather than the comprehensive and integrated 'upstream' policies and interventions required to deliver outcomes on-the-ground. Conversely, the UN Habitat framework incorporates intervention indicators, but excludes health outcome indicators. A more comprehensive approach to benchmarking, monitoring and evaluating policies designed to achieve healthy and sustainable cities and assessing spatial inequities is proposed.Copyright © 2019 Elsevier B.V. All rights reserved.

The sustainable development of the city is the key to the realization of the global sustainable development goals. Urban sustainability evaluation is a measure to the sustainable development of cities, and basis of sustainable urban development. The current evaluation method is based on statistical data which is low spatial resolution, long period and high cost. In recent years, remote sensing data, network data and the multivariate data have been used for the evaluation for the sustainable development of cities, and there have been many related research cases, which provides a new idea and method to carry out the high resolution evaluation of urban sustainable development rapidly, accurately and cheaply. This article reviewed the remote sensing data and network data in the progress of the application in the evaluation to the sustainable development of cities, and discussed the advantages of remote sensing and network big data in the objectivity, accuracy, and timeliness of evaluation compared with traditional data. Based on the sustainable urban development indicators of the United Nations Sustainable Development Goals (SDG), a basic framework for the evaluation of sustainable development of cities with high temporal and spatial resolution of big data such as remote sensing data and network big data was proposed. The introduction of remote sensing and network big data will change the inherent paradigm of sustainability assessment, make high-resolution real-time evaluation possible, further innovate analytical techniques, improve data accuracy, and make clear the alternative relationship with traditional data being the focus and the only way to realize the replacement of traditional data by remote sensing and network big data.

城市可持续发展是关系全球可持续发展目标实现的重中之重,城市可持续性评价是度量城市可持续发展水平的标尺,是实现城市可持续发展的基础。当前的评价方法多以统计数据为基础,评价时空分辨率低、周期长、花费高。近年来,遥感数据、网络大数据等多元数据陆续被用于城市可持续性评价,相关研究案例大量涌现,这为快速、准确、廉价地开展高分辨率城市可持续性评价提供了新的思路与方法。回顾了遥感数据、网络大数据在城市可持续性评价中的应用进展,探讨了遥感和网络大数据相较于传统数据在评价客观性、准确性、时效性方面的优势。在此基础上,以联合国可持续发展目标(SDG)中城市可持续发展指标为导向,提出了基于遥感数据、网络大数据等地球大数据开展高时空分辨率城市可持续性评价的基本框架。遥感与网络大数据的引入将改变可持续性评价的固有范式,使高分辨率实时评价成为可能,进一步创新分析技术、提升数据精度、明确与传统数据的替代关系是遥感和网络大数据实现对传统数据替代的工作重点。

The United Nations (UN) 2030 Sustainable Development Agenda, signed in 2015 and backed-up with its seventeen Sustainable Development Goals (SDGs), mentions cities as key players for evolving actively towards more sustainability. This underpins that living in the cities of the urban age is increasingly becoming the focus of sustainability discussions, which is particularly reflected in SDG 11 “Making cities and human settlements inclusive, safe, resilient and sustainable”. As urban sustainability strategies are playing a key role for the development of cities, this article sheds light on four cities’ sustainability strategies. The case studies highlight shortcomings, in terms of integrated visions, clear targets, and indicators in existing urban (sustainability) strategies. The article discusses these issues in light of an analytical framework, and stresses challenges and opportunities that SDG implementation involves.

Agenda 2030 pursues a universal approach and identifies countries in the Global South and in the Global North that are in need of transformation toward sustainability. Therefore, countries of the Global North such as Germany have signed the commitment to implement the Sustainable Development Goals (SDGs). However, the SDGs need to be “translated” to the specific national context. Existing sustainability indicators and monitoring and reporting systems need to be adjusted as well. Our paper evaluates how three different initiatives translated SDG 11 (“Make cities and human settlements inclusive, safe, resilient, and sustainable”) to the German context, given the specific role of cities in contributing to sustainable development. These initiatives included the official ‘National Sustainable Development Strategy’ of the German Government, a scientific initiative led by the ‘German Institute for Urban Affairs’, and a project carried out by the ‘Open Knowledge Foundation’, a non-governmental organization (NGO). This article aims to analyze how global goals addressing urban developments are contextualized on a national level. Our findings demonstrate that only a few of the original targets and indicators for SDG 11 are used in the German context; thus, major adjustments have been made according to the main sustainability challenges identified for Germany. Furthermore, our results show that the current contextualization of SDG 11 and sustainable urban development in Germany are still ongoing, and more changes and commitments need to be made.

The campaign for the inclusion of a specifically urban goal within the United Nations’ Sustainable Development Goals (SDGs) was challenging. Numerous divergent interests were involved, while urban areas worldwide are also extremely heterogeneous. It was essential to minimize the number of targets and indicators while still capturing critical urban dimensions relevant to human development. It was also essential to test the targets and indicators. This paper reports the findings of a unique comparative pilot project involving co-production between researchers and local authority officials in five diverse secondary and intermediate cities: Bangalore (Bengaluru), India; Cape Town, South Africa; Gothenburg, Sweden; Greater Manchester, United Kingdom; and Kisumu, Kenya. Each city faced problems in providing all the data required, and each also proposed various changes to maximize the local relevance of particular targets and indicators. This reality check provided invaluable inputs to the process of finalizing the urban SDG prior to the formal announcement of the entire SDG set by the UN Secretary-General in late September 2015.

On 25 September, 2015, world leaders met at the United Nations in New York, where they adopted the Sustainable Development Goals. These 17 goals and 169 targets set out an agenda for sustainable development for all nations that embraces economic growth, social inclusion, and environmental protection. Now, the agenda moves from agreeing the goals to implementing and ultimately achieving them. Across the goals, 42 targets focus on means of implementation, and the final goal, Goal 17, is entirely devoted to means of implementation. However, these implementation targets are largely silent about interlinkages and interdependencies among goals. This leaves open the possibility of perverse outcomes and unrealised synergies. We demonstrate that there must be greater attention on interlinkages in three areas: across (e.g., finance, agriculture, energy, and transport), across societal (local authorities, government agencies, private sector, and civil society), and between and among low, medium and high income. Drawing on a global sustainability science and practice perspective, we provide seven recommendations to improve these interlinkages at both global and national levels, in relation to the UN's categories of means of implementation: finance, technology, capacity building, trade, policy coherence, partnerships, and, finally, data, monitoring and accountability.

Progress towards the UN Sustainable Development Goals (SDGs) is being evaluated through the use of indicators. Despite the importance of these indicators, the academic community has done little in terms of a critical reflection on their choice, relevance, framing and operationalization. This holds for many SDG domains, also for the urban sector domain of target 11. To partially address this void, we aim to critically review the UN methodology for the urban access indicator, SDG indicator 11.2. In discussing its conceptual framing against the background of paradigm shifts in transportation planning, we argue that this indicator has a number of shortcomings. The most important one is that it is supply oriented and measures access to transportation infrastructure, rather than accessibility to activity locations. As an alternative, we develop two accessibility indicators that show substantial variation in accessibility across geographical areas. We implement all indicators for the city of Bogotá in Colombia, using a geo-information based approach. Our results show that SDG indicator 11.2 fails to represent the transport reality well. Its supply oriented focus neglects transport demand, oversimplifies the transport system and hides existing inequalities. Moreover, it does not provide useful evidence for targeting new interventions. The proposed accessibility indicators provide a more diverse, complete and realistic picture of the performance of the transport system. These indicators also capture the large spatial and socio-economic inequalities and can help to target improvements in urban transportation.

The rising concern about sustainable development led most states worldwide to adopt the 2030 Agenda for Sustainable Development to achieve 17 new goals before the end of 2030. Due to the prominent role of urbanization, the Sustainable Development Goal (SDG) #11 was introduced to make cities and human settlements more resilient, sustainable, safe and inclusive. The frameworks built so far to assess sustainable urban development primarily focus on sustainability, disregarding inclusiveness, safety and resilience. Under the joint consideration of these four facets, this research devised a new tool to evaluate communities and cities by selecting 61 indicators from an extensive literature review, which were weighted subsequently to ensure the balance among the four sustainability dimensions, namely society, economy, environment and governance. Data extracted from international organizations and the targets of the SDGs were used to score the indicators of the system. Mexico City, as one of the most overcrowded cities in the planet, was selected as a case study to apply the proposed tool. The research determined that the minimum thresholds set for the safety, sustainability and inclusiveness domains were not reached. In contrast, the city performed over the resilience limit. Consequently, RESSICOM was revealed as a helpful framework to identify shortcomings in cities related to the achievement of SDG #11. (C) 2018 Elsevier Ltd.

The 17 Sustainable Development Goals (SDGs) defined by the Transform our World:2030 Agenda for Sustainable Develepment represents a new coherent way of embracing economic prosperity, social inclusion, and environmental protection as an "indivisible whole". In order to ensure the implementation of this global agenda, the United Nations had proposed a systematic follow-up and review through indicators-based tracking and reporting of the progress with statistical and geospatial information towards SDGs at national, regional and global levels. This has posed many technical and coordination challenges, such as selection of appropriate indicators for a given nation or sub-nation regions, availability and acquisition of reliable data sets, spatio-temporal analysis with a geographical perspective, interaction between SDGs and cross-sector coordination. Although the international society has devoted great attention to this hot topic, most of them remain on the conceptual design and preliminary testing. There are very few good practices for a comprehensive measurement and assessment of progress towards SDGs with integration of statistical and geospatial information at nation or sub-national level. This paper presents the methodology and results of a pioneer project which measured the progress towards SDGs at a county level in China by combining integration of statistical and geospatial information. The major conclusions are ① the comprehensive progress towards SDGs in an entire administrative region can best be measured and assessed by integrating geospatial and statistical information; ② the Deqing county has made significant economic and social advances while maintaining a good ecological environment over the past few years. The results were released at the first United Nations World Geospatial Information Congress as a good practice and a live example to stimulate discussions and further actions on better supporting SDGs with geospatial information.

目前世界各国正积极落实联合国《2030年可持续发展议程》及其17项可持续发展目标（Sustainable Development Goals，英文缩写为SDGs），重要举措之一是利用统计和地理信息进行SDGs进展评估监测。就总体而言，国内外这方面研究尚处于概念设计、方法探讨和单指标、小范围试点阶段。究其原因，主要是涉及因素众多、技术过程复杂，既面临全球指标体系的科学理解、海量时空数据的融合处理、顾及地理视角的指标计算、基于事实的SDGs分析评估等诸多技术难题，还要实现跨学科的综合分析、多机构的沟通协调等。针对这一国际前沿课题，笔者研究提出了统计和地理信息相结合的综合评估方法，完成了浙江省德清县践行2030议程情况的定量综合评估。既为总结当地践行SDGs经验、发现存在问题、制定改进方案提供了重要科学依据，也为国内外其他区域开展SDGs定量评估监测提供了可借鉴的方法与范例。

One of the most important advancements in recent social science research (including applied social sciences and public policy) has been the application of computational methods in studying the complex human or social systems. Geographic Information Systems (GIS) has played an important role in this movement because of its capability of integrating and analyzing various datasets, particularly spatial data. Social sciences with a spatial focus can be grouped as "spatially-integrated social sciences". Drawing from research projects supported by various federal grant agencies in the U.S., this paper uses examples to demonstrate the value of GIS in social sciences including economics (urban economics), history and linguistics, sociology (criminology) and public health.

The study brings forward the basic conception of spatial information system for Chinese terrestrial ecosystem.Based on reviews of recent spatialization technology research of meteorology and climate information at home and abroad,we appraised virtue of methods in existence and discussed the model of spatial distribution of meteorology and climate information.Meanwhile,we summarized our preliminary achievement and set forth prospective applications.The developments of ecological,resources and environmental sciences imperiously call for spatia-lization technology research and data product exploitation of Chinese terrestrial eco-information.However,establishing a favorable spatial database of terrestrial eco-information which provides fine spatial-temporal resolution fitting in with diverse disciplines requirements demands long-ter-m study and disciplinary cooperation;simultaneously,it needs a lot of social funds devotion.

Socioeconomic statistical data is usually aggregated in units of administrative regions. The socioeconomic statistical data can reflect the heterogeneity between statistical units, but it cannot reflect the heterogeneity within a statistical unit. The socioeconomic statistical data cannot meet the needs of socioeconomic departments concerned in arbitrary regions. The spatial disaggregation of socioeconomic statistical data is an effective way to solve this problem. This study summarizes the existing methods of spatial disaggregation of socioeconomic statistical data, the auxiliary data used in methods for obtaining spatial disaggregation of socioeconomic statistical data, and the main socioeconomic grid data products. This study also predicts future development trends of the spatial disaggregation of socioeconomic statistical data in three aspects: the constraints and improvement directions of methods, the exploration of new auxiliary data and the comprehensive utilization of multi-source auxiliary data, the development of high temporal and spatial resolution and high-precision grid data products. The research results can provide references for the selection and improvement of spatial disaggregation methods of socioeconomic statistical data, the selection and comprehensive utilization of auxiliary data, and the selection and improvement of socioeconomic grid data products.

社会经济统计数据通常是以各级行政区为单位的汇总数据,它虽然能反映统计单元之间的差异但却不能反映统计单元内部的异质性,在实际应用中,无法满足统计任意区域内的社会经济数据的需求,而社会经济统计数据空间化则是有效解决该问题的一条重要途径。本文对现有社会经济统计数据的空间化方法、社会经济统计数据空间化过程所依赖的辅助数据、现有主要的社会经济空间化数据产品进行了归纳总结,并从空间化方法的制约因素和改进方向、新型辅助数据的探索和多源辅助数据的综合利用、高时空分辨率和高精度数据产品研发3个方面展望了社会经济统计数据空间化的未来发展趋势。研究结果可为社会经济统计数据空间化方法的选择与改进、辅助数据的选择与综合利用、社会经济空间化数据产品的选择与改进提供参考。

Climate research, monitoring, prediction, and related services rely on accurate observations of the atmosphere, land, and ocean, adequately sampled globally and over sufficiently long time periods. The Global Climate Observing System, set up under the auspices of United Nations organizations and the International Council for Science to help ensure the availability of systematic observations of climate, developed the concept of essential climate variables (ECVs). ECV data records are intended to provide reliable, traceable, observation-based evidence for a range of applications, including monitoring, mitigating, adapting to, and attributing climate changes, as well as the empirical basis required to understand past, current, and possible future climate variability. The ECV concept has been broadly adopted worldwide as the guiding basis for observing climate, including by the United Nations Framework Convention on Climate Change (UNFCCC), WMO, and space agencies operating Earth observation satellites.

The successes and failures of the UN Millennium Development Goals and the establishment of a new set of Sustainable Development Goals provide many opportunities for geographic engagement and critical attention. Development goals, in their focus at the national level and on measurable indicators, redirect investment and frame views of the world. They are often difficult to measure and implement and sometimes contradictory. In reviewing the history, progress, and critiques of the UN goals, this article asks what a geographic perspective shares and adds to the debates about development, its measurement, and impact.

All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive, safe, resilient and sustainable”. In order to monitor progress regarding SDG 11, there is a need for proper indicators, representing different aspects of city conditions, obviously including the Land Cover (LC) changes and the urban climate with its most distinct feature, the Urban Heat Island (UHI). One of the aspects of UHI is the Surface Urban Heat Island (SUHI), which has been investigated through airborne and satellite remote sensing over many years. The purpose of this work is to show the present potential of Google Earth Engine (GEE) to process the huge and continuously increasing free satellite Earth Observation (EO) Big Data for long-term and wide spatio-temporal monitoring of SUHI and its connection with LC changes. A large-scale spatio-temporal procedure was implemented under GEE, also benefiting from the already established Climate Engine (CE) tool to extract the Land Surface Temperature (LST) from Landsat imagery and the simple indicator Detrended Rate Matrix was introduced to globally represent the net effect of LC changes on SUHI. The implemented procedure was successfully applied to six metropolitan areas in the U.S., and a general increasing of SUHI due to urban growth was clearly highlighted. As a matter of fact, GEE indeed allowed us to process more than 6000 Landsat images acquired over the period 1992–2011, performing a long-term and wide spatio-temporal study on SUHI vs. LC change monitoring. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations (calibration problems related to LST determination from Landsat imagery were evidenced), pave the way for a possible global service on SUHI monitoring, able to supply valuable indications to address an increasingly sustainable urban planning of our cities.

Cities are recognised as key enablers for the world’s sustainable future. Urban sprawl and inefficient use of land are important issues significantly impacting the provision and use of open green spaces. The United Nations Sustainable Development Goal (SDG) indicator 11.7.1 aims at globally monitoring the amount of land that is dedicated by cities for public space. In Europe, the indicator “Share of urban population without green urban areas in their neighbourhood” is supposed to correspond to the SDG11.7.1 but is currently on-hold due to methodological issues and lack of data. Moreover, to efficiently assess public space conditions, timely and spatially disaggregated information is essential but not yet widely adopted by urban practitioners. Hereafter, we use a combination of satellite and crowdsourced Earth Observations (EO) to model physical accessibility to urban green spaces in four European cities. Findings suggest that it is technically feasible to derive information on the share of urban population without green urban areas in their neighbourhood. Results demonstrate that the proposed methodology represents a consistent, valid, reliable, low-cost, timely and continuous source of information for sustainable urban development. Open and free EO data can be a good complement to enhance official and traditional statistics on urban areas facilitating EU reporting against the SDG indicator for better comparison between EU countries.

Beautiful China Initiative (BCI) aims at sustainable development with blue sky and green land, lucid waters and lush mountains, prosperous society and rich people, and harmony between humans and nature. The BCI is a Chinese practice to implement the SDGs 2030 of the United Nations, and an important method to promote the harmonious development between humans and nature and to win the gold and silver mountains by maintaining clear waters and green mountains. Geography, an applied cross-discipline serving the country's socio-economic development, has comprehensive and regional characteristics. Geographers shoulder the historical mission of building a beautiful China, and are duty-bound to take the lead in becoming pioneers and practitioners of the BCI. The theory of pericoupling and telecoupling between humans and nature is the theoretical foundation of the BCI. The interdisciplinary and comprehensive integration of geography is the practical means for the BCI. The complex system simulation and optimization of geography provide a scientific tool for coupling ways between humans and nature of the BCI. The main coupling ways for geography to promote the BCI include: carry out major scientific and technological projects and coupling demonstrations; perform dynamic assessment and monitoring of the coupled human and natural systems for the BCI; draw up the strategic coupling roadmap and the action plan of the 14th Five-Year Plan (2021-2025) for the BCI; build a concept of beautiful land to comply with the objectives of the National Territorial Space Plan of China; develop a comprehensive regionalization of coupled human and natural systems in accordance with local conditions, and build a group of beautiful urban agglomerations and national parks; undertake pilot projects for the construction of Beautiful China and summarize the regional coupling models for the BCI. These coupling paths will ensure that the whole country and each of its provincial-level region are getting closer to the target according to the schedule and roadmap for building a beautiful China, and diverse regions will achieve the overall goals in the competition.

美丽中国是一个天蓝地绿、山清水秀、强大富裕、人地和谐的可持续发展强国。建设美丽中国是落实联合国2030年可持续发展目标的中国实践和国家样板,是推进人与自然和谐发展、守住“绿水青山”赢得“金山银山”的重要手段。地理学作为服务国家经济社会发展的交叉应用学科,其综合性和区域性特点决定了地理学家肩负着建设美丽中国、筑造美好家园的历史使命,责无旁贷地率先成为美丽中国建设的先行者和实践者,地理学倡导的人地系统耦合论是美丽中国建设的理论基石,地理学的学科交叉与综合集成是美丽中国建设与调控人地关系的实践手段,地理学的复杂系统模拟和优化方法为美丽中国建设的人地系统耦合路径选择提供了科学工具,综合地理区划是因地制宜地建设美丽中国的分区基础。地理学推进美丽中国建设的人地系统耦合路径包括:开展美丽中国建设的重大科技攻关和人地耦合试验示范;进行美丽中国建设的动态评估与人地耦合监测;编制美丽中国建设的人地系统耦合路线图与“十四五”规划行动方案;树立美丽国土观,在《全国国土空间规划纲要》中充分体现美丽中国建设目标;因地制宜地做好美丽中国建设的人地系统耦合区划,建设好美丽城市群和美丽公园群;先行开展美丽中国建设样板试点,总结美丽中国建设的人地系统耦合模式。通过这些耦合路径确保全国及各省市区按照美丽中国建设的时间表和路线图逐步接近目标值,在“比美健美”的竞建行动中实现美丽中国建设的总目标。