scholarly journals Valuing map validation: The need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services

2015 ◽  
Vol 111 ◽  
pp. 23-28 ◽  
Author(s):  
G.M. Foody
Author(s):  
G. M. Foody

It is now widely accepted that an accuracy assessment should be part of a thematic mapping programme. Authoritative good or best practices for accuracy assessment have been defined but are often impractical to implement. Key reasons for this situation are linked to the ground reference data used in the accuracy assessment. Typically, it is a challenge to acquire a large sample of high quality reference cases in accordance to desired sampling designs specified as conforming to good practice and the data collected are normally to some degree imperfect limiting their value to an accuracy assessment which implicitly assumes the use of a gold standard reference. Citizen sensors have great potential to aid aspects of accuracy assessment. In particular, they may be able to act as a source of ground reference data that may, for example, reduce sample size problems but concerns with data quality remain. The relative strengths and limitations of citizen contributed data for accuracy assessment are reviewed in the context of the authoritative good practices defined for studies of land cover by remote sensing. The article will highlight some of the ways that citizen contributed data have been used in accuracy assessment as well as some of the problems that require further attention, and indicate some of the potential ways forward in the future.


2021 ◽  
Vol 13 (15) ◽  
pp. 2950
Author(s):  
Yoshie Ishii ◽  
Koki Iwao ◽  
Tsuguki Kinoshita

The Degree Confluence Project (DCP) is a volunteer-based validation dataset that comprises useful information for global land cover map validation. However, there is a problem with using DCP points as validation data for the accuracy assessment of land cover maps. While resolutions of typical global land cover maps are several hundred meters to several kilometers, DCP points can only guarantee an area of several tens of meters that can be confirmed by ground photographs. So, the objective of this study is to create a land cover map validation dataset with added spatial uniformity information using satellite images and DCP points. For this, we devised a new method to semiautomatically guarantee the spatial uniformity of DCP validation data points at any resolution. This method can judge the validation data with guaranteed uniformity with a user’s accuracy of 0.954. Furthermore, we conducted the accuracy assessment for the existing global land cover maps by the DCP validation data with guaranteed spatial uniformity and found that the trends differed by class and region.


2002 ◽  
Vol 81 (2-3) ◽  
pp. 443-455 ◽  
Author(s):  
M Laba ◽  
S.K Gregory ◽  
J Braden ◽  
D Ogurcak ◽  
E Hill ◽  
...  

1998 ◽  
Vol 64 (3) ◽  
pp. 331-344 ◽  
Author(s):  
Stephen V. Stehman ◽  
Raymond L. Czaplewski

2019 ◽  
Vol 11 (20) ◽  
pp. 2420 ◽  
Author(s):  
Brian Alan Johnson ◽  
Shahab Eddin Jozdani

Local climate zone (LCZ) maps are increasingly being used to help understand and model the urban microclimate, but traditional land use/land cover map (LULC) accuracy assessment approaches do not convey the accuracy at which LCZ maps depict the local thermal environment. 17 types of LCZs exist, each having unique physical characteristics that affect the local microclimate. Many studies have focused on generating LCZ maps using remote sensing data, but nearly all have used traditional LULC map accuracy metrics, which penalize all map classification errors equally, to evaluate the accuracy of these maps. Here, we proposed a new accuracy assessment approach that better explains the accuracy of the physical properties (i.e., surface structure, land cover, and anthropogenic heat emissions) depicted in an LCZ map, which allows for a better understanding of the accuracy at which the map portrays the local thermal environment.


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