Fine-scale monitoring of lake ice phenology by synthesizing remote sensed and climatologic features based on high-resolution satellite constellation and modeling.

Lake ice, as a crucial component of the cryosphere, serves as a sensitive indicator of climate change. Fine-scale monitoring of spatiotemporal patterns in lake ice phenology holds significant importance in scientific research and environmental management. However, the rapid and dynamic nature of the freeze-thaw process of lake ice poses challenges to existing methods, resulting in their limited application in small lakes. In this study, we propose a novel approach of investigating ice phenology of lakes in various sizes. We conducted a case study in Hoh Xil, known for its vulnerability to climate change and a wide distribution of small lakes, to analyze the ice phenology of 372 lakes (>1 km2) during 2017-2021. Firstly, ensemble machine-learning model was developed for lake ice identification from Landsat-8/9 and Sentinel-2 A/B imagery. The accuracy evaluation reveals the overall good performance for ice extraction results based on Landsat-8/9 (97.03 %) and Sentinel-2 A/B (96.89 %). Next, the XGBoost models were employed to reconstruct ice coverages on unobserved dates for the freezeup and breakup periods, respectively. Totally, 744 XGBoost models were constructed for the study lakes, and the majority of them perform well. Based on the reconstructed daily ice coverage, phenology parameters could be extracted for examining the spatiotemporal characteristics of ice cover and possible relationships with lake sizes and terrains. From early-October to early-November, the Hoh Xil lakes freeze from the northwest to the southeast, while the breakup period starts in late-March and lasts until late-June. Moreover, the results indicate relatively small variability in freezeup-end dates among lakes, but significant differences in breakup dates, showing a greater sensitivity to temperature variations. Furthermore, ice phenology in small lakes exhibit stronger consistency with subtle climatic fluctuations. The results highlight the significant role of ice phenology in small lakes, as they dominate the overall tendency of ice phenology in Hoh Xil.

Long-term and inter-monthly dynamics of aquatic vegetation and its relation with environmental factors in Taihu Lake, China.

This paper discussed the long-term and inter-monthly variation in the distribution area of aquatic macrophytes in Taihu Lake, as well as the relationship between these variations and environmental factors. The findings were of great significance to the protection and environmental remediation of lake ecosystems. This paper presented data from 92 periods during 1980 to 2017 on the distribution area of aquatic macrophytes (including submerged macrophytes and floating-leaved macrophytes, but excluding emergent macrophytes) in Taihu Lake. Data were acquired by remote-sensing and subsequent image interpretation. The analysis of the inter-monthly variation indicated that the area occupied by aquatic macrophytes first increased and then decreased from January to December. Specifically, the distribution area was very small from January to March, began to increase gradually from April to August, reached its maximum in September, and decreased gradually from October to December. The analysis of the long-term variation showed that the distribution and area of aquatic macrophytes experienced two stages during the years 1980 to 2017: 1) gradual increase, 2) sharp decrease. In the first stage (1980 to 2014), the area occupied by aquatic macrophytes increased by 9 times, the maximum distribution area was 206.27 km2 (in May), 307.92 km2 (in September) and 277.33 km2 (in October). In the second stage (2015 to 2017), the distribution area of aquatic macrophytes decreased sharply to 50 km2 or less. The distribution area of aquatic macrophytes during the months of January to December had a significant positive correlation with monthly average temperature, CODMn value, secchi disk depth(SDD), area of cyanobacteria and chlorophyll-a (Chl-a) concentration, a significant negative correlation with water quality indices such as dissolved oxygen (DO) value and NH3-N concentration, but no significant correlation with water quality indices such as pH values and total suspended matter (TSM) concentration. The distribution area of aquatic macrophytes from 1980 to 2017 had a significant positive correlation with annual average temperature, annual minimum water level, pH value, SDD, area of cyanobacteria and Chl-a concentration, but no significant correlation with water quality indices such as DO value, CODMn value, NH3-N concentration and TSM concentration. The sharp decrease in the distribution area of aquatic macrophytes in 2015 and subsequent years was primarily due to the mechanized salvage of aquatic plants.

Estimating the biomass of unevenly distributed aquatic vegetation in a lake using the normalized water-adjusted vegetation index and scale transformation method.

Satellite remote sensing is advantageous for the mapping and monitoring of aquatic vegetation biomass at large spatial scales. We proposed a scale transformation (CT) method of converting the field sampling-site biomass from the quadrat to pixel scale and a new normalized water-adjusted vegetation index (NWAVI) based on remotely sensed imagery for the biomass estimation of aquatic vegetation (excluding emergent vegetation). We used a modeling approach based on the proposed CT method and NWAVI as well as statistical analyses including linear, quadratic, logarithmic, cubic, exponential, inverse and power regression to estimate the aquatic vegetation biomass, and we evaluated the performance of the biomass estimation. We mapped the spatial distribution and temporal change of the aquatic vegetation biomass using a geographic information system in a test lake in different months. The exponential regression models based on CT and the NWAVI had optimal adjusted R2, F and Sig. values in both May and August 2013. The scatter plots of the observed versus the predicted biomass showed that most of the validated field sites were near the 1:1 line. The RMSE, ARE and RE values were small. The spatial distribution and change of the aquatic vegetation biomass in the study area showed clear variability. Among the NWAVI-based and other vegetation index-based models, the CT and NWAVI-based models had the largest adjusted R2, F and the smallest ARE values in both tests. The proposed modeling scheme is effective for the biomass estimation of aquatic vegetation in lakes. It indicated that the proposed method can provide a most accurate spatial distribution map of aquatic vegetation biomass for lake ecological management. More accurate biomass maps of aquatic vegetation are essential for implementing conservation policy and for reducing uncertainties in our understanding of the lake carbon cycle.

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate statistical modeling techniques, demonstrated advantages for estimating the TP concentration in a large lake and had a strong potential for universal application for the TP concentration estimation in large lake waters worldwide.

Regionalizing aquatic ecosystems based on the river subbasin taxonomy concept and spatial clustering techniques.

Aquatic ecoregions were increasingly used as spatial units for aquatic ecosystem management at the watershed scale. In this paper, the principle of including land area, comprehensiveness and dominance, conjugation and hierarchy were selected as regionalizing principles. Elevation and drainage density were selected as the regionalizing indicators for the delineation of level I aquatic ecoregions, and percent of construction land area, percent of cultivated land area, soil type and slope for the level II. Under the support of GIS technology, the spatial distribution maps of the two indicators for level I and the four indicators for level II aquatic ecoregion delineation were generated from the raster data based on the 1,107 subwatersheds. River subbasin taxonomy concept, two-step spatial clustering analysis approach and manual-assisted method were used to regionalize aquatic ecosystems in the Taihu Lake watershed. Then the Taihu Lake watershed was divided into two level I aquatic ecoregions, including Ecoregion I1 and Ecoregion I2, and five level II aquatic subecoregions, including Subecoregion II11, Subecoregion II12, Subecoregion II21, Subecoregion II22 and Subecoregion II23. Moreover, the characteristics of the two level I aquatic ecoregions and five level II aquatic subecoregions in the Taihu Lake watershed were summarized, showing that there were significant differences in topography, socio-economic development, water quality and aquatic ecology, etc. The results of quantitative comparison of aquatic life also indicated that the dominant species of fish, benthic density, biomass, dominant species, Shannon-Wiener diversity index, Margalef species richness index, Pielou evenness index and ecological dominance showed great spatial variability between the two level I aquatic ecoregions and five level II aquatic subecoregions. It reflected the spatial heterogeneities and the uneven natures of aquatic ecosystems in the Taihu Lake watershed.

Spatial variation of surface soil available phosphorous and its relation with environmental factors in the Chaohu Lake watershed.

The study presented in this paper attempts to evaluate the spatial pattern of soil available phosphorus, as well as the relation between soil available phosphorus and environment factors including elevation, slope, precipitation, percentage of cultivated land, percentage of forest land, percentage of construction land and NDVI using statistical methods and GIS spatial analysis techniques. The results showed that the Spline Tension method performed the best in the prediction of soil available phosphorus in the Chaohu Lake watershed. The spatial variation of surface soil available phosphorus was high in Chaohu Lake watershed and the upstream regions around Chaohu Lake, including the west of Chaohu lake (e.g., southwest of Feixi county, east of Shucheng county and north of Lujiang county) and to the north of Chaohu Lake (e.g., south of Hefei city, south of Feidong county, southwest of Juchao district), had the highest soil available phosphorus content. The mean and standard deviation of soil available phosphorus content gradually decreased as the elevation or slope increased. The cultivated land comprised 60.11% of the watershed and of that land 65.63% belonged to the medium to very high SAP level classes, and it played a major role in SAP availability within the watershed and a potential source of phosphorus to Chaohu Lake resulting in eutrophication. Among the land use types, paddy fields have some of the highest maximum values and variation of coefficients. Subwatershed scale soil available phosphorus was significantly affected by elevation, slope, precipitation, percentage of cultivated land and percentage of forest land and was decided by not only these environmental factors but also some other factors such as artificial phosphorus fertilizer application.

LULC Classification and Topographic Correction of Landsat-7 ETM+ Imagery in the Yangjia River Watershed: the Influence of DEM Resolution.

DEM-based topographic corrections on Landsat-7 ETM+ imagery from rugged terrain, as an effective processing techniques to improve the accuracy of Land Use/Land Cover (LULC) classification as well as land surface parameter retrievals with remotely sensed data, has been frequently reported in the literature. However, few studies have investigated the exact effects of DEM with different resolutions on the correction of imagery. Taking the topographic corrections on the Landsat-7 ETM+ images acquired from the rugged terrain of the Yangjiahe river basin (P.R. China) as an example, the present work systematically investigates such issues by means of two commonly used topographic correction algorithms with the support of different spatial resolution DEMs. After the pre-processing procedures, i.e. atmospheric correction and geo-registration, were applied to the ETM+ images, two topographic correction algorithms, namely SCS correction and Minnaert correction, were applied to assess the effects of different spatial resolution DEMs obtained from two sources in the removal of topographic effects and LULC classifications. The results suggested that the topographic effects were tremendously reduced with these two algorithms under the support of different spatial resolution DEMs, and the performance of the topographic correction with the 1:50,000-topographic-map DEM was similar to that achieved using SRTM DEM. Moreover, when the same topographic correction algorithm was applied the accuracy of LULC classification after topographic correction based on 1:50,000-topographic-map DEM was similar as that based on SRTM DEM, which implies that the 90 m SRTM DEM can be used as an alternative for the topographic correction of ETM+ imagery when high resolution DEM is unavailable.

[3 + 2] Cycloaddition reactions in the synthesis of triazolo[4,5-b]pyridin-5-ones and pyrrolo[3,4-b]pyridin-2-ones.

The reaction of 5-benzenesulfonyl-3,4-dihydro-1 H-pyridin-2-one derivatives with azides or isocyanides provided two new classes of compounds, triazolo[4,5-b]pyridin-5-ones 3 or pyrrolo[3,4-b]pyridin-2-ones 4, respectively, in good yields and regioselectivity. A representative set of 20 compound 3 and 12 compound 4 was prepared.

[3+2] cycloaddition reactions in the solid-phase synthesis of 1,2,3-triazoles.

[Structure: see text] An efficient and regioselective procedure for the synthesis of 1,2,3-triazoles via a [3+2] cycloaddition of polymer-bound vinyl sulfone and sodium azide is described. Microwave irradiation provided significant rate enhancement in all steps of the three-step protocol. A representative set of 23 compounds was prepared.