Lin Li
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Remote sensing of inland water quality
Outbreaks of cyanobacteria in inland water bodies, especially water sources, can pose a serious threat to public health. Studies have shown that public exposure or ingestion of cyanobacterial cells and toxins can cause a series of harmful health consequences, such as skin irritation, allergic reactions, mucous membrane blistering, muscle and joint pain, gastroenteritis, lung consolidation, liver and kidney damage, and various neurological effects. Furthermore, the outbreak of cyanobacteria can cause factory shutdowns and tremendous economic losses. Therefore, the scientific value and socio-economic significance of inland water quality remote sensing monitoring and early warning research are beyond doubt. Chlorophyll-a and phycocyanin are important indicators for monitoring and early warning of outbreaks of cyanobacteria in inland water bodies with remote sensing because both pigments exhibit diagnostic absorption spectral features in the visible spectral region.
Over the last 15 years, Dr. Lin Li's research group has been making efforts to improve remote sensing approaches to monitoring inland water quality. Particularly, the effort was put in deriving the absorption and scattering coefficients of optically active substances (OACs) in water from remote sensing reflectance spectra and decomposing the total absorption of OACs to achieve the separation of the absorption coefficients of algal pigments from other constituents such as soluble organic matter and suspended sediment. An accurate retrieval of pigment absorption coefficients makes it possible to reliably map chlorophyll-a and phycocyanin and assess inland water quality. This would provide water management authorities and managers with an effective remote sensing tool for dealing with the outbreak of cyanobacteria in inland water bodies.
Dr. Li's work to improve remote sensing and monitoring of inland water quality is another excellent example of how IUPUI's faculty members are TRANSLATING their RESEARCH INTO PRACTICE.
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Item BAND SELECTION METHOD APPLIED TO M3 (MOON MINERALOGY MAPPER)(Office of the Vice Chancellor for Research, 2012-04-13) Cavanagh, Patrick D.; Li, LinRemote sensing optical sensors, such as those on board satellites and planetary probes, are able to detect and measure solar radiation at both im-proved spectral and spatial resolution. In particular, a hyperspectral dataset often consists of tens to hundreds of specified wavelength bands and con-tains a vast amount of spectral information for potential processing. One drawback of such a large spectral dataset is information redundancy result-ing from high correlation between narrow spectral bands. Reducing the data dimensionality is critical in practical hyperspectral remote sensing applica-tions. Price’s method is a band selection approach that uses a small subset of bands to accurately reconstruct the full hyperspectral dataset. The method seeks to represent the dataset by a weighted sum of basis functions. An it-erative process is used to successively approximate the full dataset. The process ends when the last basis function no longer provides a significant contribution to the reconstruction of the dataset, i.e. the basis function is dominated by noise. The research presented examines the feasibility of Price’s method for ex-tracting an optimal band subset from recently acquired lunar hyperspectral images recorded by the Moon Mineralogy Mapper (M3) instrument on board the Chandrayaan-1 spacecraft. The Apollo 17 landing site was used for test-ing of the band selection method. Preliminary results indicate that the band selection method is able to successfully reconstruct the original hyperspectral dataset with minimal error. In a recent test case, 15 bands were used to reconstruct the original 74 bands of reflectance data. This represents an accurate reconstruction using only 20% of the original dataset. The results from this study can help to configure spectral channels of fu-ture optical instruments for lunar exploration. The channels can be chosen based on the knowledge of which wavelength bands represent the greatest relevant information for characterizing geology of a particular location.Item The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.(PLOS, 2016) Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.; Department of Earth Sciences, School of ScienceSoil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.Item Sunlight induced chlorophyll fluorescence in the near-infrared spectral region in natural waters: Interpretation of the narrow reflectance peak around 761 nm(AGU, 2016-07) Lu, Yingcheng; Li, Linhai; Hu, Chuanmin; Li, Lin; Zhang, Minwei; Sun, Shaojie; Lv, Chunguang; Department of Earth Sciences, School of ScienceSunlight induced chlorophyll a fluorescence (SICF) can be used as a probe to estimate chlorophyll a concentrations (Chl) and infer phytoplankton physiology. SICF at ∼685 nm has been widely applied to studies of natural waters. SICF around 740 nm has been demonstrated to cause a narrow reflectance peak at ∼761 nm in the reflectance spectra of terrestrial vegetation. This narrow peak has also been observed in the reflectance spectra of natural waters, but its mechanism and applications have not yet been investigated and it has often been treated as measurement artifacts. In this study, we aimed to interpret this reflectance peak at ∼761 nm and discuss its potential applications for remote monitoring of natural waters. A derivative analysis of the spectral reflectance suggests that the 761 nm peak is due to SICF. It was also found that the fluorescence line height (FLH) at 761 nm significantly and linearly correlates with Chl. FLH(761 nm) showed a tighter relationship with Chl than the relationship between FLH(∼685 nm) and Chl mainly due to weaker perturbations by nonalgal materials around 761 nm. While it is not conclusive, a combination of FLH(761 nm) and FLH(∼685 nm) might have some potentials to discriminate cyanobacteria from other phytoplankton due to their different fluorescence responses at the two wavelengths. It was further found that reflectance spectra with a 5 nm spectral resolution are adequate to capture the spectral SICF feature at ∼761 nm. These preliminary results suggest that FLH(761 nm) need to be explored more for future applications in optically complex coastal and inland waters.Item Salt Content Distribution and Paleoclimatic Significance of the Lop Nur “Ear” Feature: Results from Analysis of EO-1 Hyperion Imagery(MDPI, 2017-08) Zhang, Tingting; Shao, Yun; Gong, Huaze; Li, Lin; Wang, Longfei; Department of Earth Sciences, School of ScienceLop Nur, a playa lake located on the eastern margin of Tarim Basin in northwestern China, is famous for the “Ear” feature of its salt crust, which appears in remote-sensing images. In this study, partial least squares (PLS) regression was used to estimated Lop Nur playa salt-crust properties, including total salt, Ca2+, Mg2+, Na+, Si2+, and Fe2+ using laboratory hyperspectral data. PLS results for laboratory-measured spectra were compared with those for resampled laboratory spectra with the same spectral resolution as Hyperion using the coefficient of determination (R2) and the ratio of standard deviation of sample chemical concentration to root mean squared error (RPD). Based on R2 and RPD, the results suggest that PLS can predict Ca2+ using Hyperion reflectance spectra. The Ca2+ distribution was compared to the “Ear area” shown in a Landsat Thematic Mapper (TM) 5 image. The mean value of reflectance from visible bands for a 14 km transversal profile to the “Ear area” rings was extracted with the TM 5 image. The reflectance was used to build a correlation with Ca2+ content estimated with PLS using Hyperion. Results show that the correlation between Ca2+ content and reflectance is in accordance with the evolution of the salt lake. Ca2+ content variation was consistent with salt deposition. Some areas show a negative correlation between Ca2+ content and reflectance, indicating that there could have been a small-scale temporary runoff event under an arid environmental background. Further work is needed to determine whether these areas of small-scale runoff are due to natural (climate events) or human factors (upstream channel changes)Item Slope algorithm to map algal blooms in inland waters for Landsat 8/ Operational Land Imager images(SPIE, 2016-12) Ogashawara, Igor; Li, Lin; Moreno-Madriñán, Max Jacobo; Department of Environmental Health Science, School of Public HealthMonitoring algal blooms using traditional methods is expensive and labor intensive. The use of satellite technology can attenuate such limitations. A common problem associated with the application of such technology is the need to eliminate the effects of atmosphere, which can be, at least, a time-consuming task. Thus, a remote sensed algal bloom monitoring system needs a simple algorithm which is nonsensitive to atmospheric correction and that could be applied to small aquatic systems. A slope algorithm (SAred−NIR) was developed to detect and map the extension of algal blooms using the Landsat 8/Operational Land Imager. SAred−NIR was shown to have advantages over other commonly used indices to monitor algal blooms, such as normalized difference vegetation index (NDVI), normalized difference water index, and floating algae index. SAred−NIR was shown to be less sensitive to different atmospheric corrections, less sensitive to thin clouds, and less susceptible to confusion when classifying water and moderate bloom conditions. Based on ground truth data from Eagle Creek Reservoir, Indiana, SAred−NIR showed an accuracy of 88.46% while NDVI only showed a 46.15% accuracy. Finally, based on qualitative and quantitative results, SAred−NIR can be used as a tool to improve the governance of small size water resources.Item Monitoring the Invasion of Spartina alterniflora Using Multi-source High-resolution Imagery in the Zhangjiang Estuary, China(MDPI, 2017-06) Liu, Mingyue; Li, Huiying; Li, Lin; Man, Weidong; Jia, Mingming; Wang, Zongming; Lu, Chunyan; Earth Science, School of ScienceSpartina alterniflora (S. alterniflora) is one of the most harmful invasive plants in China. Google Earth (GE), as a free software, hosts high-resolution imagery for many areas of the world. To explore the use of GE imagery for monitoring S. alterniflora invasion and developing an understanding of the invasion process of S. alterniflora in the Zhangjiang Estuary, the object-oriented method and visual interpretation were applied to GE, SPOT-5, and Gaofen-1 (GF-1) images. In addition, landscape metrics of S. alterniflora patches adjacent to mangrove forests were calculated and mangrove gaps were recorded by checking whether S. alterniflora exists. The results showed that from 2003–2015, the areal extent of S. alterniflora in the Zhangjiang Estuary increased from 57.94 ha to 116.11 ha, which was mainly converted from mudflats and moved seaward significantly. Analyses of the S. alterniflora expansion patterns in the six subzones indicated that the expansion trends varied with different environmental circumstances and human activities. Land reclamation, mangrove replantation, and mudflat aquaculture caused significant losses of S. alterniflora. The number of invaded gaps increased and S. alterniflora patches adjacent to mangrove forests became much larger and more aggregated during 2003–2015 (the class area increased from 12.13 ha to 49.76 ha and the aggregation index increased from 91.15 to 94.65). We thus concluded that S. alterniflora invasion in the Zhangjiang Estuary had seriously increased and that measures should be taken considering the characteristics shown in different subzones. This study provides an example of applying GE imagery to monitor invasive plants and illustrates that this approach can aid in the development of governmental policies employed to control S. alterniflora invasion. View Full-TextItem The impact of fog on soil moisture dynamics in the Namib Desert(Elsevier, 2018-03) Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary; Earth Science, School of ScienceSoil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014–Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015–Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.Item Impacts of Climate Change on Tibetan Lakes: Patterns and Processes(MDPI, 2018-02-26) Mao, Dehua; Wang, Zongming; Yang, Hong; Li, Huiying; Thompson, Julian R.; Li, Lin; Song, Kaishan; Chen, Bin; Gao, Hongkai; Wu, Jianguo; Earth Sciences, School of ScienceHigh-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures.Item Partially-observed models for classifying minerals on Mars(IEEE, 2013) Dundar, Murat; Li, Lin; Rajwa, Bartek; Earth Sciences, School of ScienceThe identification of phyllosilicates by NASA's CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) strongly suggests the presence of water-related geological processes. A variety of water-bearing phyllosilicate minerals have already been identified by several research groups utilizing spectral enrichment techniques and matching phyllosilicate-rich regions on the Martian surface to known spectra of minerals found on earth. However, fully automated analysis of the CRISM data remains a challenge for two main reasons. First, there is significant variability in the spectral signature of the same mineral obtained from different regions on the Martian surface. Second, the list of mineral confirmed to date constituting the set of training classes is not exhaustive. Thus, when classifying new regions, using a classifier trained with selected minerals and chemicals, one must consider the potential presence of unknown materials not represented in the training library. We made an initial attempt to study these problems in the context of our recent work on partially-observed classification models and present results that show the utility of such models in identifying spectra of unknown minerals while simultaneously recognizing spectra of known minerals.Item Impacts of Climate Change on Tibetan Lakes: Patterns and Processes(MDPI, 2018-02-26) Mao, Dehua; Wang, Zongming; Yang, Hong; Li, Huiying; Thompson, Julian; Li, Lin; Song, Kaishan; Chen, Bin; Gao, Hongkai; Wu, Jianguo; Earth Sciences, School of ScienceHigh-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures.
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