scholarly journals A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data

2018 ◽  
Vol 10 (10) ◽  
pp. 1623 ◽  
Author(s):  
Michael Wulder ◽  
Zhan Li ◽  
Elizabeth Campbell ◽  
Joanne White ◽  
Geordie Hobart ◽  
...  
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Regional Variability ◽  
National Assessment ◽  
Wetland Dynamics ◽  
Earth Observations ◽  
Land Condition ◽  
Earth Observation Satellite ◽  
Forested Ecosystems ◽  
Land Cover Maps

Wetlands are important globally for supplying clean water and unique habitat, and for storing vast amounts of carbon and nutrients. The geographic extent and state of wetlands vary over time and represent a dynamic land condition rather than a permanent land cover state. Herein, we combined a time series of land cover maps derived from Landsat data at 30-m resolution to inform on spatial and temporal changes to non-treed and treed wetland extents over Canada’s forested ecosystems (>650 million ha) from 1984 to 2016. Overall, for the period, 1984 to 2016, we found the extent of wetlands (non-treed and treed combined) in Canada’s forested ecosystems to be stable, with some regional variability, often resulting from offsetting decreases and increases within a given ecozone. Notwithstanding difficulties in using optical satellite data for mapping a land condition, by accumulating wetland evidence via earth observations consistently through multiple decades, our results capture the trends in wetland cover over a previously unmapped, national extent at a level of spatial detail and temporal reach suitable for further focused interpretations of wetlands and drivers and projections of wetland dynamics.

scholarly journals Detection of wetland dynamics with ENVISAT ASAR in support of methane modelling at high latitudes

2011 ◽  
Vol 8 (4) ◽  
pp. 8241-8268 ◽  
Author(s):  
A. Bartsch ◽  
A. M. Trofaier ◽  
G. Hayman ◽  
D. Sabel ◽  
S. Schlaffer ◽  
...  
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Climate Models ◽  
Open Water ◽  
Data Availability ◽  
Climate Modelling ◽  
Wetland Dynamics ◽  
Water Fraction ◽  
Envisat Asar ◽  
Statistical Measures

Abstract. Spatial information on inundation dynamics is expected to improve greenhouse gas estimates in climate models. Satellite data can provide land cover information from local to global scale. The detection capability for dynamics is however limited. Cloud cover and daylight independent methods are required for frequent updates. Suitable are therefore sensors which make use of microwaves. The purpose of the present study is to assess such data for determination of wetland dynamics from the viewpoint of use in climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR) operating in C-band due to, among microwave systems, comparably good spatial resolution and data availability. Continuity is also expected for such systems. Simple classification algorithms can be applied to detect open water in an automatised way allowing the processing of time series. Such approaches are robust when the water surface is smooth. C-band data from ENVISAT ASAR (Advanced SAR) operating in wide swath mode (150 m resolution) have been investigated for implementation of an automated detection procedure of open water fraction. More than 4000 samples (single acquisitions tiled into 0.5 degree grid cells) have been analysed for July/August 2007 and 2008. Modification of input parameters results in differences below 1 % open water fraction. The actual challenge is the frequent occurrence of waves due to wind and precipitation. This reduces the separability of the water class from other land cover. The possible update intervals for surface water extent are therefore decreased considerably. Statistical measures of the backscatter distribution can be applied in order to retrieve the for classification suitable data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution has been used for assessment. On average only 40 % of acquisitions allow a separation of the open water class. Satellite data are available every 2–3 days over the Western Siberian study region. With respect to the irregular acquisition intervals and varying length of unsuitable weather periods a minimum update interval of 10 days is suggested for the Northern Eurasian test case. Although SAR data availability is currently constraint future satellite missions which aim for operational services such as Sentinel-1 with its C-band SAR instrument may provide the basis for inundation monitoring in support of climate modelling.

A scale-up method for reference data for validation of global land cover maps using ALOS/AVNIR-2 satellite data

2015 ◽  
Author(s):  
Noriko Soyama ◽  
Kanako Muramatsu ◽  
Itsuko Ohashi ◽  
Motomasa Daigo ◽  
Fumio Ochiai ◽  
...  
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Reference Data ◽  
Scale Up ◽  
Global Land Cover ◽  
Global Land ◽  
Land Cover Maps

scholarly journals INTER-COMPARISON OF THE GLOBAL LAND COVER MAPS IN AFRICA SUPPLEMENTED BY SPATIAL ASSOCIATION OF ERRORS

2019 ◽  
Vol XLII-4/W14 ◽  
pp. 11-16
Author(s):  
G. Bratic ◽  
D. Oxoli ◽  
M. A. Brovelli
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Confusion Matrix ◽  
Spatial Association ◽  
Probability Of Error ◽  
Earth Observations ◽  
Area Of Interest ◽  
Global Land Cover ◽  
Land Cover Maps ◽  
Single Pixel

<p><strong>Abstract.</strong> Recent advances in Earth Observations supported development of high-resolution land cover (LC) maps on a large-scale. This is an important step forward, especially for developing countries, which experienced problems in the past due to absence of reliable LC information. Nevertheless, increasing number of LC products is imposing additional validation workload to confirm their quality. In this paper inter-comparison of two recent LC products (GlobeLand30 and S2 prototype LC 20m map of Africa) for country of Rwanda in Africa was done. It is a way to facilitate validation by identifying the areas with higher probability of error. Specific approach of comparison of single pixel of one map with multiple pixels of another map provided confusion matrix and sub-pixel agreement table. In this work, accuracy indexes based on the confusion matrix were computed as a measure of similarity between the two maps. Furthermore, Moran’s I index was computed for estimation of spatial association of the pixels in disagreement. Also, total disagreement, as well as disagreement of particularly confused classes was visualised to analyse their spatial distribution. The results are showing that similarity of the two maps is about 66%. Disagreements are spatially associated and the most evident in the eastern and north-western part of the area of interest. This coincides also with the distribution of the two most confused classes Wetland and Shrubland. The results delineate areas of inconsistency between the two maps, and therefore areas where careful accuracy analysis are needed.</p>

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