Dongting Lake Dynamics ID-10697 Current Advances in Monitoring - - PowerPoint PPT Presentation
Dongting Lake Dynamics ID-10697 Current Advances in Monitoring Inundation and Land Use Dynamics of Dongting Lake Wetlands Juliane HUTH, YANG Bo, LI Jing, Claudia KUENZER ESA-Dragon-3-Symposium June 22-26, 2015, Interlaken, Switzerland
Current Advances in Monitoring Inundation and Land Use Dynamics of Dongting Lake Wetlands Juliane HUTH, YANG Bo, LI Jing, Claudia KUENZER
ESA-Dragon-3-Symposium June 22-26, 2015, Interlaken, Switzerland
Study Site – Dongting Lake, Hunan, China
Challenges at Dongting Lake
Economic Use of Wetland Areas Floods and Droughts Cash Crops Water Quality Urban Growth
Objectives of the Project ID 10697
"Assessing Wetland Dynamics and Land Resources of Dongting Lake, China"
Chinese and European satellite sensors
wetland degradation, derivation of land use change in direct surrounding
with preferably automated derivation of surface water, and further parameter to describe flood events and land cover change
Dongting Lake Flood Monitoring
WaMaPro – Principles and Techniques
Input data (DN) Medianfilter (3x3) Convert to binary images B1 (water) B2 (land) B3 Comparison (B3 && B2) || B1 B4 B5 Remove ‚islands’ and ‚lakes’ (island size, lake size) Watermask Image Dilation (sesize) Morphological Closing (fix value) Threshold Definition (water and land threshold)
Input: SAR amplitude DN values Filtering Threshold definition (confident water and confident land) Image processing in buffer zone
Morphological operations for edge smoothing with fixed value Removing of artefacts with user given size software tool implementation
GSTAIGER, V., GEBHARDT, S., HUTH, J., WEHRMANN; T. and C. KUENZER, 2012: Multi-sensoral derivation of inundated areas using TerraSAR-X and ENVISAT ASAR data. International Journal of Remote Sensing, Vol. 33, 22, 7291-7304, DOI:10.1080/01431161.2012.700421
WaMaPro – open-source based tool implementation WaMaPro – open-source based tool implementation
WaMaPro – open-source based tool – GUI
Accuracy Assessment
Watermask derived from TSX stripmap compared to digitization from high-resolution
Producers Accuray: 96,7 % Users Accuracy: 89,9 % Overall Accuracy: 91,3 %
MARTINIS, S., KUENZER, C., WENDLEDER, A., HUTH, J., TWELE, A., ROTH, A., DECH, S.: Comparing four different approaches for operational SAR- based water and flood detection. Submitted to International Journal of Remote Sensing. aquaculture
Sentinel-1A Data – available since Spring 2015
Sentinel-1A Watermask Processing Results
Sentinel-1A 2015-04-28 Watermask result from Sentinel-1A 2015-04-28 data set
Comparison of spatial resolution TSX 3m vs. Sentinel-1A 10m vs. ASAR 150m
TerraSAR-X stripmap mode 2012-04-16 Sentinel-1A 2015-04-28 Envisat ASAR-WSM 2010-05-17
Derivation of Inundation Frequency Products
Slide 13
KUENZER, C., GUO, H., LEINENKUGEL, L, HUTH, J., LI, X., and S. DECH, 2013: Flood mapping and flood dynamics of the Mekong Delta: An ENVISAT-ASAR-WSM based Time Series Analyses, Remote Sensing 5 (doi:10.3390/rs5020687), 687-715
TerraSAR-X Data Footprint
Inundation Frequency at East Dongting Lake derived from high resolution TerraSAR–X Data 2012/2013
2012 2013
Flood Extent for 2012 – from TSX – Detail Views
3 4 1 5 2
1 2 3 4 5
Sentinel-1A Data Footprint
Inundation Frequency for Dongting Lake derived from NEW Sentinel-1A Data – April and May 2015
ASAR-WSM Data Subset Footprint
Annual Flood Distribution at Dongting Lake derived from ASAR–WSM Data – 2010/2011
hydrological station – measured between 27 m up to 33 m in this period
Sentinel-1A- Watermask Processing for Flood Detection
Dongting Lakes Monitoring of Land Resources Quantification of Economically Important Vegetation Types within Wetlands of DTL
SPOT Data Footprint
Flowchart of data processing for SPOT image classification based on seasonal information
included as next step
Processing SPOT data using seasonal information
Classification of 2007 and 2010 SPOT data – including seasonal information
Validation Matrix 2007 – with absolute numbers of validation samples and User’s Accuracy (UA) and Producer’s Accuracy (PA) in [%]
CLASSIFIED
type 1
type 2
type 3 poplar tree cover reed fresh cut reed
evergreen trees wet-land veget. artif. surface mud-flat water Total PA R agricultural area type 1 62 13 1 7 5 88 70,45 E agricultural area type 2 7 74 1 1 1 84 88,1 F agricultural area type 3 4 227 9 22 262 86,64 E poplar tree cover 17 457 4 478 95,61 R reed- fresh cut 25 242 6 273 88,64 E reed-
23 302 325 92,92 N evergreen trees 4 1 1 20 1 127 3 157 80,89 C wetland vegetation 3 31 34 91,18 E artif. surface 3 3 1 94 101 93,07 mudflat 1 4 177 9 191 92,67 water 99 15 24 313 451 69,4 Total 79 95 371 492 280 330 128 42 104 201 322 UA 78,48 77,89 61,19 92,89 86,43 91,52 99,22 73,81 90,38 88,06 97,21
86,2%
Validation Matrix 2010 – with absolute numbers of validation samples and User’s Accuracy (UA) and Producer’s Accuracy (PA) in [%]
CLASSIFIED
type 1
type 2
type 3 poplar tree cover reed fresh cut reed
evergreen trees wet-land veget. artif. surface mud-flat water Total PA R agricultural area type 1 46 17 6 7 76 60,53 E agricultural area type 2 5 80 2 87 91,95 F agricultural area type 3 5 257 6 2 1 8 279 92,11 E poplar tree cover 1 272 6 66 345 78,84 R reed- fresh cut 1 203 3 207 98,07 E reed-
30 166 196 84,69 N evergreen trees 1 22 10 75 108 69,44 C wetland vegetation 7 23 4 2 36 63,89 E artif. surface 2 2 2 8 8 77 6 1 106 72,64 mudflat 3 9 1 211 8 232 90,95 water 23 1 46 348 418 83,25 Total 62 104 268 332 251 170 141 40 96 267 359 UA 74,19 76,92 95,9 81,93 80,88 97,65 53,19 57,5 80,21 79,03 96,94
84,1%
Classification of HJ-1A data of 2013-01-01
Classification more difficult compared to SPOT etc., since no atmospheric correction can be applied for HJ-1 with standard procedures like ATCOR, therefore seasonal combinations cannot be applied single dataset classification
Validation Matrix 2013 – with absolute numbers of validation samples and User’s Accuracy (UA) and Producer’s Accuracy (PA) in [%]
CLASSIFIED
type 1
type 2
type 3 poplar tree cover reed fresh cut reed
evergreen trees wet-land veget. artif. surface mud-flat water Total PA R agricultural area type 1 318 1 319 99,69 E agricultural area type 2 7 173 11 34 13 1 9 248 69,76 F agricultural area type 3 6 171 6 2 185 92,43 E poplar tree cover 43 245 10 67 34 399 61,4 R reed- fresh cut 8 20 110 14 152 72,37 E reed-
11 438 449 97,55 N evergreen trees 3 9 110 122 90,16 C wetland vegetation 20 10 1 27 58 46,55 E artif. surface 3 4 2 3 102 114 89,47 mudflat 217 217 100 water 1 358 359 99,72 Total 402 215 182 281 158 444 191 62 112 217 358 UA 79,1 80,47 93,96 87,19 69,62 98,65 57,59 43,55 91,07 100 100
86,5%
Changes of economically important vegetation types - poplar and reed - at South DTL (2007-2010-2013)
Development of land use within inner dyke subset
from remote sensing analyses from statistical data year poplar tree area [km²] reed area [km²] afforestation area [km²] for Yuanjiang district 2007 104.81 203.98
2007-2009
2010 125.25 176.68 development 2007-2010 +19.51%
125.2 km² (2007-2010) 2013 163.60 242.26 development 2010-2013 +24.05% +35.85%
Changes of poplar plantation (2007-2010)
Quantitative change analyses for poplar plantation (2007-2010)
Related to harvest of poplar trees Related to afforestation
Conclusion and Future work
Conclusion
vegetation types reed and poplar trees – remote sensing based monitoring revealed expansion of about 20% every 3 years. Future Work in ID10697
www.DLR.de • Chart 36
New Chinese Satellite Data – HJ-1A/B of 2014
HJ-1A 2014-01-22 HJ-1B 2014-02-20 HJ-1B 2014-01-24
most current HJ-1 dataset from Dongting Lake 2014-01-24
Thank you for your attention! Presenter: juliane.huth@dlr.de
Assessing Flood-, Wetland and Landuse Dynamics of Dongting Lake (DTL) ID 10697
Main Results
I. The maximum water area of DTL (without any dike broken) is 2713.855 km2 II. Analyses on the variations of water area in DTL based on SPOT-VGT data. III. Mutual effects between morphological characteristics and variations of flow- sediment process in DTL. IV. Estimation of wetlands methane emission in DTL based on remote sensing. V. Temporal and spatial analysis of COD concentration in East DTL wetland. VI. Comprehensive evaluation of ecosystem health of East DTL wetland.
wetland.
wetland. IX. Agricultural drought monitoring in DTL watershed by using of MODIS data.
characteristics of DTL Basin
1825-1915 After 1915 Now
Main Results (Ⅰ) The maximum water area of DTL without any dike broken is 2713.855 km2 (2001).
Main Results (Ⅱ) Analyses on the variations of water area in DTL based on SPOT- VGT data.
SPOT-VGT on each July (1998-2010) R2=0.558, F=102.872
Where x is the surface accumulated rainfall in drainage basin in April 1, y is corresponding to the time of water area is predicted
Main Results (Ⅳ) Estimation of wetlands methane emission in DTL based on remote sensing.
There are two study areas in Dongting Lake with a total of 17 sampling points. Junshan (Upper) area with 6 reed sampling points, and Cihukou (Lower) area with 6 paddy sampling points, 2 sedge sampling points, 2 beach sampling points, and 1 water sampling points .
Junshan (Upper) Cihukou (Lower)
Paddy Beach Water Sedge (a)Monitoring Time
A few specific period have been selected for 24 hours
continuous monitoring between November 2010 and October 2011.
(b)Monitoring Frequency
Routine monitoring, 3 times per month;24 hours of continuous monitoring, 1 time per 3 months.
(c)Sampling Time
The sampling time of routine monitoring between 9:00 and 16:00, taking one sample in every 10 minutes from the sampling box.
Data acquisition, pre-processing and temporal analysis of methane concentration
Data acquisition, pre-processing and temporal analysis of methane concentration
calibration Atmospheric Correction Geometric Correction Mosaic Mask Classification Modify Title Legend Scale North Arrow Modify Convertion(BSQ→BIL) HJ Result
ENVI ArcGIS
Mosaic Registration Mask Classification
The estimation model construction of methane emission based on type and size of wetlands Where i represents one kind of wetlands, n is the number of types of wetlands, T is the time of period(h), Fi is the average methane emission fluxes of this kind i of wetlands in the period of T(mg/m2/h), Si is the size of this kind i of wetlands(m2), Emission is the methane emissions of all kinds of wetlands in the period of T(mg).
Type Nov 2010 Apr 2011 May 2011 July 2011 Mean Total Water 97.12 219.88 195.70 12364.02 3219.18 12876.72 Reed Land 72.05 145.63 156.82 66.38 110.22 440.88 Paddy Field 499.18 17607.22 60621.41 48822.88 31887.68 127550.70 Sedge Land 2.07 135.13 45.26 23.61 51.52 206.07 Beach Land 133.65 308.26 240.44 406.82 272.29 1089.17 Total 804.06 18416.11 61259.64 61683.72 35540.88 142163.54
The estimation and analysis of methane emission in the study area
Unit: t
The estimation model construction of methane emission based on type and size of wetlands The estimation value of methane emission based on the model
2011-05-17 2011-07-20
Main Results (Ⅵ) Comprehensive evaluation for ecosystem health of East DTL wetland
Wetland Ecosystem Health State (WEHS) can be calculated by Comprehensive Evaluation Model:
WEHS = P × S × E × F
=
n i i i
1
X is the value of comprehensive evaluation, Wi is the weights of the ith evaluation indicator, Pi is the value of the ith evaluation indicator,
Result map of Comprehensive Evaluation of Ecosystem Health
Main Results (Ⅶ) Relationship between water Level and ecosystem health state of East DTL wetland
Structure Elasticity NDVI Water Level Water Level Water Level Water Level Water/area ratio
From 1993-2002, the area of forested land, reed land, and carex covered area increased, among them the reed land increased fastest, with an annual growth of 28.93km2. During 2002-2006, forested land increased rapidly, with an annual growth of 29.66km2, while the carex area decreased, and reeds remained unchanged. The distribution of centroids of forest, reed and carex in the East DTL wetland layer by layer are close to the lake center, and centroids of these three vegetation types ceaselessly shifted to the lake center from 1993 to 2006, among which, changes of forest and reed were more remarkable.
Reed Forest Carex Lake Center
Issues and Recommendations Issues
Flood and drought occur frequently around the DTL watershed. The variation of flow-sediment process has great effects on the morphological characteristics of DTL which need to be researched in depth. Sewage and residue discharged by paper mills are polluting DTL. DTL Wetland facing a series of ecological problems. e.g. ecological deterioration, biodiversity reduction, ecological adjustment function decreasing.
Recommendations
More optimal methods Prominent features of real-time, quantitative and dynamic More systematic and comprehensive indices High resolution and new data sources (e.g. Radar and Hyperspectral data ) Improve the precision and quality of models