Accuracy assessment on the crop area estimating method based on RS sampling at national scale: a case study of China's rice area estimation assessment

2008 ◽  
Author(s):  
Yonglan Qian ◽  
Bangjie Yang ◽  
Xianfeng Jiao ◽  
Zhiyuan Pei ◽  
Xuan Li
Keyword(s):  
Accuracy Assessment ◽  
National Scale ◽  
Area Estimation ◽  
Rice Area ◽  
Crop Area

Industrial destabilisation: The case of Rajajinagar, Bangalore

Urban Studies ◽  
2021 ◽  
pp. 004209802110440
Author(s):  
Shriya Anand ◽  
Aditi Dey
Keyword(s):  
Industrial Restructuring ◽  
National Scale ◽  
Local Economies ◽  
Industrial Transformation ◽  
Engineering Economy ◽  
Neighbourhood Scale ◽  
The City ◽  
Indian Cities ◽  
Suitable Case

There has been a recent interest in expanding the focus of deindustrialisation studies to the cities of the Global South. Bangalore, with its long legacy of state sponsored industrialisation, as well as a substantial shift in its economy following economic liberalisation in 1991, presents itself as a suitable case to examine the impacts of industrial transformation. We study the decline of the engineering economy in one of Bangalore’s earliest planned industrial suburbs, Rajajinagar, to understand how industrial restructuring at the city and national scale has affected and reconfigured local economies. Using this case study, we make two main theoretical contributions: one, we bring out shifts at a neighbourhood scale that go beyond the existing literature on neoliberal transformations in Bangalore as well as other Indian cities. Two, the case also allows us to assess the limitations of deindustrialisation as a framework to analyse these changes, and we suggest a modified framework, that of ‘industrial destabilisation’.

scholarly journals National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo

2013 ◽  
Vol 8 (4) ◽  
pp. 044039 ◽  
Author(s):  
A Tyukavina ◽  
S V Stehman ◽  
P V Potapov ◽  
S A Turubanova ◽  
A Baccini ◽  
...  
Keyword(s):  
Democratic Republic ◽  
National Scale ◽  
Carbon Loss ◽  
Scale Estimation ◽  
Aboveground Carbon ◽  
Republic Of The Congo

Accuracy assessment of a mobile terrestrial laser scanner for tree crops

2017 ◽  
Vol 8 (2) ◽  
pp. 178-182 ◽  
Author(s):  
F. H. S. Karp ◽  
A. F. Colaço ◽  
R. G. Trevisan ◽  
J. P. Molin
Keyword(s):  
Data Acquisition ◽  
Spatial Data ◽  
Accuracy Assessment ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Tree Crops ◽  
Area Estimation ◽  
Gnss Receiver ◽  
Truncated Cone ◽  
Set Up

LiDAR technology is one option to collect spatial data about canopy geometry in many crops. However, the method of data acquisition includes many errors related to the LiDAR sensor, the GNSS receiver and the data acquisition set up. Therefore, the objective of this study was to evaluate the errors involved in the data acquisition from a mobile terrestrial laser scanner (MTLS). Regular shaped objects were scanned with a developed MTLS in two different tests: i) with the system mounted on a vehicle and ii) with the system mounted on a platform running over a rail. The errors of area estimation varied between 0.001 and 0.071 m2 for the circle, square and triangle objects. The errors on volume estimations were between 0.0003 and 0.0017 m3, for cylinders and truncated cone.

scholarly journals Coupling Uncertainties with Accuracy Assessment in Object-based Slum Detections, Case Study: Jakarta, Indonesia

2017 ◽  
Author(s):  
Jati Pratomo ◽  
Monika Kuffer ◽  
Javier Martinez ◽  
Divyani Kohli
Keyword(s):  
Land Tenure ◽  
Classification Accuracy ◽  
Accuracy Assessment ◽  
False Negative ◽  
National Policy ◽  
True Positive ◽  
True Negative ◽  
Object Based ◽  
The Impact

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

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