An easily implemented method to estimate impervious surface area on a large scale from MODIS time-series and improved DMSP-OLS nighttime light data

It is important for researchers and policy-makers to frequently update the amount and spatial distribution of impervious surface area (ISA) on earth, because the level of imperviousness not only indicates urbanization, but is also a key indicator of ecological conditions. In this study, we developed an easily implemented method for estimating the ISA percentage (ISA%) from vegetation index data obtained from a moderate resolution imaging spectroradiometer (MODIS) and nighttime light data obtained from the Defense Meteorological Satellite Program’s Operational Line-scan System (DMSP-OLS). The proposed method consists of four major steps. First, a non-vegetation fraction map was generated from 16-day composited time-series MODIS normalized difference vegetation index data using the temporal mixture analysis method. Second, the enhanced-vegetation-index-adjusted nighttime light index (EANTLI) was used to overcome the saturation problem and blooming effects in the original DMSP-OLS data. Third, the relationship between ISA% and EANTLI was derived based on a statistical analysis of the non-vegetation fraction image and the EANTLI image to obtain a preliminary ISA% map. Finally, the final ISA% map was obtained by selecting smaller values from the preliminary ISA% map and non-vegetation fraction map for each pixel. The validation results showed that the developed method has promising accuracy for estimating the ISA% in our study area (mainly consisting of four Southeast Asian countries: Thailand, Laos, Cambodia, and Vietnam), with a root mean square error value of 0.111, a systematic error value of 0.061, and a determination coefficient of 0.87. Another important finding is that there are two relationships between ISA% and improved nighttime light (i.e., EANTLI): the natural logarithmic function is suitable for ISA% values between 0% and 50%, and the quadratic polynomial function should be used for ISA% values larger than 50%. The developed method has high potential for application to the generation of global ISA% maps with frequent updates due to its easy implementation and the ready availability of input data

A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan

The impervious surface area (ISA) has emerged not only as an indicator of the degree of urbanization, but also as a major indicator of environmental quality for drainage basin management. However, since almost all of the methods for estimating ISA have been developed for urban environments, it is questionable whether these methods can be successfully applied to drainage basins, such as those found in Japan, which usually have more complicated vegetation components (e.g. paddy field, plowed field and dense forest). This paper presents a pre-screened and normalized multiple endmember spectral mixture analysis (PNMESMA) method, which includes a new endmember selection strategy and an integration of the normalized spectral mixture analysis (NSMA) and multiple endmember spectral mixture analysis (MESMA), for estimating the ISA fraction in Lake Kasumigaura Basin, Japan. This new proposed method is superior to the previous methods in that the estimation error of the proposed method is much smaller than the previous SMA- or NSMA-based methods for drainage basin environments. The overall root mean square error was reduced to 5.2%, and no obvious underestimation or overestimation occurred for high or low ISA areas. Through the assessment of environmental quality in Lake Kasumigaura Basin using the ISA fraction, the results showed that the basin has been in the impacted category since 1987, and that in the two decades since, the environmental quality has continued to decline. If this decline continues, then Lake Kasumigaura Basin will fall into the degraded category by 2017

Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan

As a proxy measure of the human ecological footprint, impervious surface area (ISA) has recently become a key concept in the field of urban remote sensing, with a focus on estimation of the ISA at a city-scale by using Landsat-style satellite images. However, ISA estimation is also in demand in disciplines such as the environmental assessment and policy making at a national scale. This paper proposes a new method for estimating the ISA fraction in Japan based on a temporal mixture analysis (TMA) technique. The required inputs for the proposed method are rearranged MODIS NDVI time-series datasets at the temporal stable zone (i.e., the first to the sixth largest NDVI values in a year). Three ISA distribution maps obtained from Landsat-5 TM data were used as reference maps to evaluate the performance of the proposed method. The results showed that the proposed TMA-based method achieved a large reduction in the effects of endmember variability compared with the previous methods (e.g., SMA and NSMA), and thus the new method has promising accuracy for estimating ISA in Japan. The overall root mean square error (RMSE) of the proposed method was 8.7%, with a coefficient of determination of 0.86, and there was no obvious underestimation or overestimation for the whole ISA range

Will hypolimnetic waters become anoxic in all deep tropical lakes?

To elucidate trends of hypolimnetic oxygen concentrations, vertical distributions of dissolved oxygen were measured in eight deep tropical bodies of water (one natural lake with two basins, five natural lakes, and one reservoir) in Indonesia. A comparison of those concentrations with previously reported data revealed that shoaling of hypolimnetic oxygen-deficient (around a few decimeters to a few meter per year) water had occurred in all of the lakes. Calculated areal hypolimnetic oxygen depletion rates were 0.046–5.9 g m−2 y−1. The oligomictic or meromictic characteristics of the bodies of water suppressed circulation and mixing in the hypolimnions and thus resulted in continuous shoaling of the uppermost oxygen-deficient layers. In some lakes, millions of fish sometimes died suddenly, probably owing to upward movement of oxygen-deficient water to near the surface during periods of strong winds. In the future, the rate of shoaling will be accelerated by human impacts in the basins and by climate warming, the influence of which has already been manifested by rising water temperatures in these lakes. Appropriate monitoring and discussions of future restoration challenges are urgently needed to prevent the hypolimnions of the lakes from becoming completely anoxic

Factors explaining the yearly changes in minimum bottom dissolved oxygen concentrations in Lake Biwa, a warm monomictic lake

Vertical profiles of dissolved oxygen (DO) and water temperature (WT) measured bi-monthly for 36 years (1980–2015) near the deepest part of a warm monomictic lake were analyzed with special reference to yearly minimum DO at bottom (DOmin). DOmin changed yearly (3.0 ± 1.2 mg l−1) and significant differences in DOmin were not observed between Period I (1980–1993; cooler and worse in water quality) and Period II (1994–2015; warmer and better in water quality). This unclear trend in DOmin was probably due to the offsetting influences between warming induced by global warming and oligotrophication attempted by local governments etc. for the study period. DOmin was positively correlated with disturbance time (timing of last cold water intrusion observed from Mar to Aug), which could be related to the start of DO depletion at bottom. Thus, the linear model using this parameter could predict yearly DOmin fairly well for the entire study period (r2 = 0.60). In addition, DOmin and time of disturbance were correlated negatively with water density at bottom in Jan and positively with water density equilibrated to air temperature (AT) in Mar. Higher lake water density after full depth mixing advances the disturbance time. In contrast, lower AT in Mar and/or higher density of influent water after Mar delays the time likely due to the larger amount of snowfall in the watershed. Further, DOmin was positively correlated with maximum wind velocity in Sep which probably induced the recovery of DO. Multiple-regression models to predict DOmin using these meteorological and water quality parameters were developed (r2 ≥ 0.38, worse performances than the model using disturbance time) to forecast future trends of DOmin through global warming and/or climate change. Significant influences of water or sediment oxygen demands on DOmin were not detected. We also discuss the applicability of the proposed models

Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters

One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP) -based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N \u3e 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (Rrs), (b) retrieval of particulate backscattering (bbp) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from bbp via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m3], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e.,from 10 to \u3e100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in Rrs leads to \u3c20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

Estimating the concentration of total suspended solids in inland and coastal waters from Sentinel-2 MSI: A semi-analytical approach

Inland and coastal waters provide key ecosystem services and are closely linked to human well-being. In this study, we propose a semi-analytical method, which can be applied to Sentinel-2 MultiSpectral Instrument (MSI) images to retrieve high spatial-resolution total suspended solids (TSS) concentration in a broad spectrum of aquatic ecosystems ranging from clear to extremely turbid waters. The presented approach has four main steps. First, the remote sensing reflectance (Rrs) at a band lacking in MSI (620 nm) is estimated through an empirical relationship from Rrs at 665 nm. Second, waters are classified into four types (clear, moderately turbid, highly turbid, and extremely turbid). Third, semi-analytical algorithms are used to estimate the particulate backscattering coefficient (bbp) at a reference band depending on the water types. Last, TSS is estimated from bbp at the reference band. Validation and comparison of the proposed method with three existing methods are performed using a simulated dataset (N = 1000), an in situ dataset collected from global inland and coastal waters (N = 1265) and satellite matchups (N = 40). Results indicate that the proposed method can improve TSS estimation and provide accurate retrievals of TSS from all three datasets, with a median absolute percentage error (MAPE) of 14.88 %, 31.50 % and 41.69 % respectively. We also present comparisons of TSS mapping between the Sentinel-3 Ocean and Land Colour Instrument (OLCI) and MSI in Lake Kasumigaura, Japan and the Tagus Estuary, Portugal. Results clearly demonstrate the advantages of using MSI for TSS monitoring in small water bodies such as rivers, river mouths and other nearshore waters. MSI can provide more detailed and realistic TSS estimates than OLCI in these water bodies. The proposed TSS estimation method was applied to MSI images to produce TSS time-series in Lake Kasumigaura, which showed good agreements with in situ and OLCI-derived TSS time-series

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in‐water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions