scholarly journals AN ASSESSMENT OF CITIZEN CONTRIBUTED GROUND REFERENCE DATA FOR LAND COVER MAP ACCURACY ASSESSMENT

2015 ◽  
Vol II-3/W5 ◽  
pp. 219-225 ◽  
Author(s):  
G. M. Foody
Keyword(s):  
Best Practices ◽  
Land Cover ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Good Practice ◽  
Thematic Mapping ◽  
Gold Standard Reference ◽  
Land Cover Map ◽  
Map Accuracy Assessment ◽  
Map Accuracy

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.

scholarly journals ASSESSING THE ACCURACY OF LAND USE LAND COVER (LULC) MAPS USING CLASS PROPORTIONS IN THE REFERENCE DATA

2020 ◽  
Vol V-3-2020 ◽  
pp. 669-674 ◽  
Author(s):  
C. C. Fonte ◽  
L. See ◽  
J. C. Laso-Bayas ◽  
M. Lesiv ◽  
S. Fritz
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Reference Database ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Data Set ◽  
Mixed Pixels ◽  
Land Cover Map

Abstract. Traditionally the accuracy assessment of a hard raster-based land use land cover (LULC) map uses a reference data set that contains one LULC class per pixel, which is the class that has the largest area in each pixel. However, when mixed pixels exist in the reference data, this is a simplification of reality that has implications for both the accuracy assessment and subsequent applications of LULC maps, such as area estimation. This paper demonstrates how the use of class proportions in the reference data set can be used easily within regular accuracy assessment procedures and how the use of class proportions can affect the final accuracy assessment. Using the CORINE land cover map (CLC) and the more detailed Urban Atlas (UA), two accuracy assessments of the raster version of CLC were undertaken using UA as the reference and considering for each pixel: (i) the class proportions retained from the UA; and (ii) the class with the majority area. The results show that for the study area and the classes considered here, all accuracy indices decrease when the class proportions are considered in the reference database, achieving a maximum difference of 16% between the two approaches. This demonstrates that if the UA is considered as representing reality, then the true accuracy of CLC is lower than the value obtained when using the reference data set that assigns only one class to each pixel. Arguments for and against using class proportions in reference data sets are then provided and discussed.

scholarly journals Evaluating the Effectiveness of Unmanned Aerial Systems (UAS) for Collecting Thematic Map Accuracy Assessment Reference Data in New England Forests

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 24 ◽  
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
New England ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Unmanned Aerial Systems ◽  
Complex Environments ◽  
Thematic Map ◽  
Object Based ◽  
Aerial Systems ◽  
Map Accuracy Assessment ◽  
Map Accuracy

Thematic mapping provides today’s analysts with an essential geospatial science tool for conveying spatial information. The advancement of remote sensing and computer science technologies has provided classification methods for mapping at both pixel-based and object-based analysis, for increasingly complex environments. These thematic maps then serve as vital resources for a variety of research and management needs. However, to properly use the resulting thematic map as a decision-making support tool, an assessment of map accuracy must be performed. The methods for assessing thematic accuracy have coalesced into a site-specific multivariate analysis of error, measuring uncertainty in relation to an established reality known as reference data. Ensuring statistical validity, access and time constraints, and immense costs limit the collection of reference data in many projects. Therefore, this research proposes evaluating the feasibility of adopting the low-cost, flexible, high-resolution sensor-capable Unmanned Aerial Systems (UAS, UAV, or Drone) platform for collecting reference data to use in thematic map accuracy assessments for complex environments. This pilot study analyzed 377.57 ha of New England forests, over six University of New Hampshire woodland properties, to compare the similarity between UAS-derived orthomosaic samples and ground-based continuous forest inventory (CFI) plot classifications of deciduous, mixed, and coniferous forest cover types. Using an eBee Plus fixed-wing UAS, 9173 images were acquired and used to create six comprehensive orthomosaics. Agreement between our UAS orthomosaics and ground-based sampling forest compositions reached 71.43% for pixel-based classification and 85.71% for object-based classification reference data methods. Despite several documented sources of uncertainty or error, this research demonstrated that UAS are capable of highly efficient and effective thematic map accuracy assessment reference data collection. As UAS hardware, software, and implementation policies continue to evolve, the potential to meet the challenges of accurate and timely reference data collection will only increase.

Conventional and fuzzy accuracy assessment of the New York Gap Analysis Project land cover map

2002 ◽  
Vol 81 (2-3) ◽  
pp. 443-455 ◽  
Author(s):  
M Laba ◽  
S.K Gregory ◽  
J Braden ◽  
D Ogurcak ◽  
E Hill ◽  
...  
Keyword(s):  
New York ◽  
Land Cover ◽  
Gap Analysis ◽  
Accuracy Assessment ◽  
Land Cover Map

Design and Analysis for Thematic Map Accuracy Assessment

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

scholarly journals Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment

2019 ◽  
Vol 11 (20) ◽  
pp. 2420 ◽  
Author(s):  
Brian Alan Johnson ◽  
Shahab Eddin Jozdani
Keyword(s):  
Land Cover ◽  
Thermal Environment ◽  
Accuracy Assessment ◽  
Remote Sensing Data ◽  
Physical Characteristics ◽  
Anthropogenic Heat ◽  
Climate Zone ◽  
Local Climate ◽  
Local Climate Zone ◽  
Map Accuracy

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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