REGIONAL CHARACTERISTICS OF ENVIRONMENTAL CAPACITY FOR HEAVY METALS IN SIEROZEM ZONE AND ITS RELATION TO PHYSICALGEOGRAPHIC PROCESSES

Soil environmental capacity is defined as the maximumpermitted load of the pollutant in a cettain soil environmental unitwithin a certain temporal period. With that load, the criteria canbe maintained, production and quality of crops can be gqaranteed.Regional soil capacity is the function of physical geographiccharacteristics. In determining capacity of sierozem, key stepsinclude: (1) establishing the criteria on comprehensive basis, (2)calculating the permitted input with the application of the capacitymodel. Dynamic capacity of Cd, Cu, As and Pb for sierozem isreported and compared with that of phaiozem and red 1oam.According to the results, it is obvious that regional differentiationin capacity is distinct and the distribution pattern of permittedload is closely related to the spacial variation of physicalgeographic processes.

Promoting Geography for Sustainability

The discipline of geography encompasses both natural and social sciences and has the natural advantage of enabling the study of sustainability from a transdisciplinary perspective.There are great opportunities for geographers to participate in sustainability research.However,while geographers have set sustainability goals,they have rarely clarified the details for reaching those goals.Current knowledge on the relationship between humans and the environment and the methodologies for studying this relationship are inadequate to solve the transdisciplinary questions in sustainability science.Five research areas:geographical processes;ecosystem services and human wellbeing;human-environmental systems;sustainable development;and geo-data and modelling for sustainability are proposed as those needed to help geography achieve sustainability.The key objective of promoting geography for sustainability is to reveal the mechanisms of human-environmental system dynamics.This depends on understanding the processes in the natural and social systems and their mutual feedback as well as clarifying the relationships between the structures,functional characteristics and interactions in the human-environmental systems at multiple scales.The advancement of geography and its methodologies and technologies will provide a more profound understanding of the future.Geographers have the responsibility of promoting the discipline as the key pathway for carrying natural and social sciences towards sustainability.

Processes and events in the centre:a dynamic data model for representing spatial change

Traditional geographic information system models for map representation use superposition of layers to model physical reality,neglecting the integrity of the environment and limiting the ability to express interactions between features in complex phenomenon.This results in limitations regarding dynamic simulation and geographic causality reasoning.In this paper,we extend the framework of the geographic scene by formalizing the relationship between geographic processes and events to construct a dynamic data model:the process-event-centred dynamic data model.The key element of this data model is relationships between processes,events,and states of the natural or man-made phenomenon of interest.The identified relationships can be translated into a network of hierarchical,developmental,and causal graphs and realized in the Neo4j graph database.The implementation in the graph database supports spatio-temporal reasoning in geographic scenes and achieves an organizational framework for simulating spatio-temporal dynamics and complex calculations.The example of a 2019 mega-typhoon process is used to demonstrate the introduced process-event-centred model and its implementation in the graph database.A series of queries to the graph database show the capabilities of the data model for spatial reasoning and dynamic modeling.

Processes and events in the center: a taxi trajectory-based approach to detecting traffic congestion and analyzing its causes

A novel approach is introduced for the detection of the location and direction of traffic congestion using GPS data from taxis.This approach uses a dynamic model that conceptualizes events,processes,and states.The states are the locations of the taxis,the processes are the motion of taxis,and the events are congestion.The model is implemented as a graph database,which represents the relationships between states,events,processes,and things(such as points of interest and road grid).Algorithms for constructing and updating the relationships and taxi behaviors dynamic retrieval method in Neo4j are presented and are used to demonstrate the capabilities in dynamic expression and reasoning.An implementation of Shanghai in 2015finally demonstrated the ability of congestion direction detection and the cause searching of traffic congestion.