Great strides have been made in Geographic Information Systems (GIS) research over the past half-century. However, this progress has created both opportunities and challenges. From a geographic perspective, certain challenges remain, including the modelling of geographic-featured environments with GIS data model, the enhancement of GIS’s analysis functions for comprehensive geographic analysis and achieving human-oriented geographic information presentation. Several basic theoretical and technical ideas that follow the workflow and processes of geographic information induction, geographic scenario modelling, geographic process analysis and geographic environment representation are proposed to fill the gaps between GIS and geography. We also call for designing methods for big geographic data-oriented analysis, making best use of videos and developing virtual geographic scenario-based GIS for further evolution.

The identification of species within an ecosystem plays a key role in formulating an inventory for use in the development of conservation management plans. The classification of mangrove species typically involves intensive field surveys, whereas remote sensing techniques represent a cost-efficient means of mapping and monitoring mangrove forests at large scales. However, the coarse spectral resolution of remote sensing technology has up until recently restricted the ability to identify individual species. The more recent development of very high-resolution spatial optical remote sensing sensors and techniques has thus provided new opportunities for the accurate mapping of species within mangrove forests over large areas. When dealing with the complex problems associated with discriminating among species, classifier performance could be enhanced through the adoption of more intrinsic features; such as textural and differential spectral features. This study explored the effectiveness of textural and differential spectral features in mapping mangrove inter-species obtained from WorldView-3 high-spatial-resolution imagery for mangrove species in Hong Kong. Due to the different arrangement of leaves, the branch density, and the average height and size of plants, we found that the differential spectral features could aid in reducing inner-species variability and increasing intra-species separation. Using a combination of textural and differential spectral features thus represents a promising tool for discriminating among mangrove species. Experimental results suggest that combining these features can greatly improve mapping accuracy, thereby providing more reliable mapping results.

Urbanization has become one of the most important human activities modifying the Earth’s land surfaces; and its impacts on tropical and subtropical cities (e.g., in South/Southeast Asia) are not fully understood. Colombo; the capital of Sri Lanka; has been urbanized for about 2000 years; due to its strategic position on the east–west sea trade routes. This study aims to investigate the characteristics of urban expansion and its impacts on land surface temperature in Colombo from 1988 to 2016; using a time-series of Landsat images. Urban land cover changes (ULCC) were derived from time-series satellite images with the assistance of machine learning methods. Urban density was selected as a measure of urbanization; derived from both the multi-buffer ring method and a gravity model; which were comparatively adopted to evaluate the impacts of ULCC on the changes in land surface temperature (LST) over the study period. The experimental results indicate that: (1) the urban land cover classification during the study period was conducted with satisfactory accuracy; with more than 80% for the overall accuracy and over 0.73 for the Kappa coefficient; (2) the Colombo Metropolitan Area exhibits a diffusion pattern of urban growth; especially along the west coastal line; from both the multi-buffer ring approach and the gravity model; (3) urban density was identified as having a positive relationship with LST through time; (4) there was a noticeable increase in the mean LST; of 5.24 °C for water surfaces; 5.92 °C for vegetation; 8.62 °C for bare land; and 8.94 °C for urban areas. The results provide a scientific reference for policy makers and urban planners working towards a healthy and sustainable Colombo Metropolitan Area.

Permafrost thaw subsidence, a key indicator of permafrost degradation, remains poorly quantified or understood. It is particularly challenging to detect and measure surface subsidence due to the loss of subsurface ice over a large area because it usually develops gradually, over several years or decades. Here we utilize the persistent scatterer interferometric synthetic aperture radar (PSI) approach to remotely measure gradual surface subsidence on Eboling Mountain in the northeastern region of the Qinghai‐Tibet Plateau, where thermal erosion gullies are well developed. Most of the previous multitemporal interferometric synthetic aperture radar studies on permafrost used the small baseline subset method. By contrast, the PSI approach benefits from the full spatial resolution and is less affected by temporal or geometric decorrelation. In the PSI analysis, we incorporate a piecewise elevation change model that includes periodic subsidence/uplift because of its seasonally varying components as well as its linear subsidence trends. Applying this permafrost‐designated PSI algorithm to 17‐L band ALOS‐1 PALSAR images taken between 2006 and 2011, we find that both the thermal erosion gullies and the surrounding regions (within about 300 m) subside gradually. The subsidence trends range from 0.3 to 3 cm/yr. This suggests that permafrost areas near the gullies are more vulnerable to gradual thawing and degradation. This study demonstrates the potential of using PSI to study permafrost thaw processes and of assessing its impacts over vast areas on the Qinghai‐Tibet Plateau and in the Arctic.

Due to the convenient transportation and construction, cities are prone to be situated in areas with flat terrain and unstable sediments, resulting in the concurrence of ground subsidence and urbanization. Here the interaction between geology, anthropogenic processes and ground subsidence geo-hazards were investigated in the Greater Pearl River Delta region of China. Geological evidences and 2006–2010 persistent scatterer data indicate that anthropogenic activities are dominant, although the distribution of river system and Quaternary sediments are also highly related to significant displacements (primarily at a rate of −15 to 15 mm a⁻¹). The surface displacements derived by synthetic aperture radar interferometry suggest that the urbanization rhythm has to be routinely monitored. Considering analogous urbanization modes, particularly in developing countries, ground subsidence monitoring together with the analysis of its driving force are critical for geo-hazards early-warning, city planning as well as sustainable urbanization.