XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/5: METHODS FOR CHANGE DETECTION AND PROCESS MODELLING]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: SEASONAL DIFFERENCES IN SPATIAL SCALES OF CHLOROPHYLL-A CONCENTRATION IN LAKE TAIHU, CHINA Ying Bao, Qingjiu Tian, Shaojie Sun, Hongwei Wei, Jia Tian

Document type:: Multivolume work

Structure type:: Chapter

co- n. In "rnia, high- cord, ds: a Ag 6. A ffine ^e en sdex, ough soi I, 5- In a ) and g of In sing, Edge chine ction es of 1987 | and 5. In: sing, Edge ester, E In: | pP- International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia SEASONAL DIFFERENCES IN SPATIAL SCALES OF CHLOROPHYLL-A CONCENTRATION IN LAKE TAIHU, CHINA Ying Bao^, Qingjiu Tian * *, Shaojie Sun*, Hongwei Wei“, Jia Tian 8 8) ] ? International Institute for Earth System Science, Nanjing University, Nanjing 210093, China- qiheye100@163.com,tiangj@nju.edu.cn,sunshaojie87@126.com,piaoxue.6416931@163.com ^ School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China- tian-jia08@163.com Commission VII, WG VII/5 KEY WORDS: Chlorophyll-a concentration, Scale Heterogeneity, Scale Error, Different Seasons ABSTRACT: Spatial distribution of chlorophyll-a (chla) concentration in Lake Taihu is non-uniform and seasonal variability. Chla concentration retrieval algorithms were separately established using measured data and remote sensing images (HJ-1 CCD and MODIS data) in October 2010, March 2011, and September 2011. Then parameters of semi- variance were calculated on the scale of 30m, 250m and 500m for analyzing spatial heterogeneity in different seasons. Finally, based on the definitions of Lumped chla (chlaL) and Distributed chla (chlaD), seasonal model of chla concentration scale error was built. The results indicated that: spatial distribution of chla concentration in spring was more uniform. In summer and autumn, chla concentration in the north of the lake such as Meiliang Bay and Zhushan Bay was higher than that in the south of Lake Taihu. Chla concentration on different scales showed the similar structure in the same season, while it had different structure in different seasons. And inversion chla concentration from MODIS 500m had a greater scale error. The spatial scale error changed with seasons. It was higher in summer and autumn than that in spring. The maximum relative error can achieve 2396. 1. INTRODUCTION Chlorophyll-a (chla) plays a significant role in water ecosystem. It is a basic indicator of lake eutrophication (Zhou et al., 2009). The change of its spatial distribution and concentration can influence the lake ecosystem. In recent decades, water quality remote sensing has become an effective way to monitor it. However, spatial heterogeneity could cause scale effect in the retrieval of chla concentration from multi-resolution remote sensing images (Bao et al., 2011). It brings scale error (Chen et al, 2010). And the error affects the retrieval accuracy and varies with seasons. Therefore, studying seasonal differences in spatial scales of chla concentration is useful for improvement of the retrieval accuracy. Spatial scale effect and uncertainty based on remote sensing images had been studied domestic and abroad. Moran coefficient, Geary ration, coefficient of variation and variograms were the most commonly used methods for analyzing spatial heterogeneity (Zhang, 2008). Researches usually provided variogram function for studying spatial heterogeneity and spatial effect of water quality parameters. They found that spatial distribution of chla concentration exist structure (Xia et al., 2011; Liu et al., 2002). In addition, new methods such as hydrodynamic model, biological model were introduced to solve practical problem (Chen et al., 2010; Fragoso et al., 2008). Moreover, spatial scale uncertainty is also a hotspot in current studying (Zhang, 2008). Radiative transfer model, regressive model and fractal theory are popular methods for studying spatial errors and spatial scaling (Chen et al., 2006). But most methods for spatial uncertainties were based on vegetation. The work for water quality parameters has not been extensively researched. As there is no sensor for inland water * Correspond author: Qingjiu Tian, Professor in Nanjing University, China. Main research direction is Hyperspectral remote sensing quality remote sensing, land satellites and ocean colour satellite were used to estimate chla concentration (Zhou et al., 2009). Both of the data souses and spatial heterogeneity of chla concentration can affect the retrieval accuracy. In this paper, Lake Taihu in the east of China was selected as the study area. Based on the chla concentration retrieval algorithm and the results of spatial effects, a model of spatial scale error was established for MODIS 500m. Then the paper analyzed seasonal results which were calculated in different spatial scales. 2. STUDY AREA AND DATA PREPROCESS 2.4 Study Area Lake Taihu is one of the five largest freshwater lakes in China. The lake, situated in the southeast of the country (30°55'40"- 31?32'58"N, 30?55'40"-31?32'58"E), is a typical inland shallow lake with a water area of 2388km? (Tang et al., 2007; Zhang et al. 2011). Taihu Basin is located in Shanghai, Jiangsu and Zhejiang Province (see Figure 1.). It is one of the most developed regions in China. In recent years, water pollution of Lake Taihu is more and more serious because of the rapid development of the economy (Feng et al, 2007). And the pollution (especially eutrophication) has been attracted great attention. In the East and Eastern Lakeshore of the lake, water quality is clear and remains stable in good condition. No cyanobacterial bloom has been found so far in these areas (Ma et al., 2006). But the chla concentration content of blue-green algae in the other part of Lake Taihu is high and variable. The spatial

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