Hongsheng Zhang

Bio: Hongsheng Zhang is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Impervious surface & Synthetic aperture radar. The author has an hindex of 19, co-authored 66 publications receiving 1019 citations. Previous affiliations of Hongsheng Zhang include South China Normal University & The Chinese University of Hong Kong.

GA-SVM Algorithm for Improving Land-Cover Classification Using SAR and Optical Remote Sensing Data

Abstract: Multisource remote sensing data have been widely used to improve land-cover classifications. The combination of synthetic aperture radar (SAR) and optical imagery can detect different land-cover types, and the use of genetic algorithms (GAs) and support vector machines (SVMs) can lead to improved classifications. Moreover, SVM kernel parameters and feature selection affect the classification accuracy. Thus, a GA was implemented for feature selection and parameter optimization. In this letter, a GA-SVM algorithm was proposed as a method of classifying multifrequency RADARSAT-2 (RS2) SAR images and Thaichote (THEOS) multispectral images. The results of the GA-SVM algorithm were compared with those of the grid search algorithm, a traditional method of parameter searching. The results showed that the GA-SVM algorithm outperformed the grid search approach and provided higher classification accuracy using fewer input features. The images obtained by fusing RS2 data and THEOS data provided high classification accuracy at over 95%. The results showed improved classification accuracy and demonstrated the advantages of using the GA-SVM algorithm, which provided the best accuracy using fewer features.

Textural–Spectral Feature-Based Species Classification of Mangroves in Mai Po Nature Reserve from Worldview-3 Imagery

Abstract: 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.

Optical absorption and fluorescence properties of chromophoric dissolved organic matter in natural waters

Abstract: Complete optical absorption and fluorescence spectra were collected for a diverse suite of 0.2-μm-filtered marine, riverine, and estuarine waters, as well as for colored dissolved organic matter (CDOM) isolated from several of these waters by solid-phase C 18 extraction. Absorption and fluorescence parameters for these samples are reported. For surface waters, variations in the fluorescence quantum yields obtained with 355- and 337-nm excitation fell within a narrow window (< 2.5-fold variation about the mean values), demonstrating that fluorescence measurements can be used to determine absorption coefficients of CDOM in the ultraviolet region with reasonably good accuracy. Methods for predicting absorption coefficients and line shapes from the fluorescence data are introduced and tested. The absorption and fluorescence spectra of CDOM extracted from some seawaters differed significantly from those of the original waters, demonstrating that material isolated by hydrophobic adsorption is not necessarily representative of the suite of colored organic matter present in aquatic systems. These results clearly illustrate that great care must be taken when extracted material is used to infer the optical properties of natural waters

Biodiversity increases the resistance of ecosystem productivity to climate extremes

Abstract: It remains unclear whether biodiversity buffers ecosystems against climate extremes, which are becoming increasingly frequent worldwide. Early results suggested that the ecosystem productivity of diverse grassland plant communities was more resistant, changing less during drought, and more resilient, recovering more quickly after drought, than that of depauperate communities. However, subsequent experimental tests produced mixed results. Here we use data from 46 experiments that manipulated grassland plant diversity to test whether biodiversity provides resistance during and resilience after climate events. We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16–32 species was more resistant, changing by only approximately 25%. By a year after each climate event, ecosystem productivity had often fully recovered, or overshot, normal levels of productivity in both high- and low-diversity communities, leading to no detectable dependence of ecosystem resilience on biodiversity. Our results suggest that biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events. Anthropogenic environmental changes that drive biodiversity loss thus seem likely to decrease ecosystem stability, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity to climate events.

A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

Abstract: The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification) was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.