scholarly journals Considerations towards a Novel Approach for Integrating Angle-Count Sampling Data in Remote Sensing Based Forest Inventories

Forests ◽  
2017 ◽  
Vol 8 (7) ◽  
pp. 239 ◽  
Author(s):  
◽  
◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Forest Inventories ◽  
Novel Approach ◽  
Angle Count Sampling

Correcting the nondetection bias of angle count sampling

2013 ◽  
Vol 43 (4) ◽  
pp. 344-354 ◽  
Author(s):  
Tim Ritter ◽  
Arne Nothdurft ◽  
Joachim Saborowski
Keyword(s):  
Forest Inventory ◽  
Distance Sampling ◽  
Sampling Technique ◽  
Approximately Unbiased ◽  
Forest Inventories ◽  
Novel Approach ◽  
Inclusion Probabilities ◽  
Detection Probabilities ◽  
Efficient Sampling ◽  
Angle Count Sampling

The well-known angle count sampling (ACS) has proved to be an efficient sampling technique and has been applied in forest inventories for many decades. However, ACS assumes total visibility of objects; any violation of this assumption leads to a nondetection bias. We present a novel approach, in which the theory of distance sampling is adapted to traditional ACS to correct for the nondetection bias. Two new estimators were developed based on expanding design-based inclusion probabilities by model-based estimates of the detection probabilities. The new estimators were evaluated in a simulation study as well as in a real forest inventory. It is shown that the nondetection bias of the traditional estimator is up to −52.5%, whereas the new estimators are approximately unbiased.

Improving bioclimatic envelop modeling for Lichens through remote sensing based substratum correction: A study over Indian Himalaya

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
C. P. Singh ◽  
R. Bajpai ◽  
R. P. Singh ◽  
D. K. Upreti
Keyword(s):  
Remote Sensing ◽  
Predictive Accuracy ◽  
Geographic Area ◽  
Jammu And Kashmir ◽  
Indian Himalaya ◽  
Novel Approach ◽  
Digital Elevation ◽  
Average Probability ◽  
Niche Area ◽  
Elevation Model

In alpine Himalaya, the niche map of lichens and its characteristics is a gap area. A novel approach of improving the bioclimatic envelop through use of remote sensing inputs was employed. The 19 bioclimatic indices and digital elevation model were used for training niche models through occurrence records of 33 lichen species across Indian Himalaya. Substratum correction was carried out using LU/LC data. About 45% of the total geographic area studied is found to be very conducive (with niche probability > 70%) for the growth of lichens with predictive accuracy of 91% ascertained through cross-validation. Jammu and Kashmir is having highest niche area (36.02%); however, average probability niche score is highest in Uttarakhand (81.08). Area between 27o - 28o N latitude is having highest area however average probability score is highest in 30o - 31o N. Overall maximum niche area (35.50 %) is found in the regions dominated by alpine meadow, alpine grasslands and parts of cold deserts. The potential use lies in reporting yet to be explored lichens in the Indian Himalaya.

scholarly journals A novel approach to characterize the variability in mass-Dimension relationships: results from MC3E

2018 ◽  
Author(s):  
Joseph A. Finlon ◽  
Greg M. McFarquhar ◽  
Stephen W. Nesbitt ◽  
Robert M. Rauber ◽  
Hugh Morrison ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Numerical Models ◽  
Radar Data ◽  
Chi Square ◽  
University Of North Dakota ◽  
Microphysical Properties ◽  
Novel Approach ◽  
Mass Dimension ◽  
Lower Temperature ◽  
B Coefficients

Abstract. Mass-dimension (m-D) relationships determining bulk microphysical properties such as total water content (TWC) and radar reflectivity factor (Z) from particle size distributions are used in both numerical models and remote sensing retrievals. The a and b coefficients representing m = aDb relationships, however, can vary significantly depending on meteorological conditions, particle habits, definition of particle maximum dimension, the probes used to obtain the data, techniques used to process the cloud probe data, and other unknown reasons. Thus, considering a range of a,b coefficients may be more applicable for use in numerical models and remote sensing retrievals. Microphysical data collected by two-dimensional optical array probes (OAPs) installed on the University of North Dakota Citation aircraft during the Mid-latitude Continental Convective Clouds Experiment (MC3E) were used in conjunction with TWC data from a Nevzorov probe and ground-based S-band radar data to determine a and b using a technique that minimizes the chi-square difference between TWC and Z derived from the OAPs and that directly measured by a TWC probe and radar. All a and b within a specified tolerance were regarded as equally plausible solutions. Of the 16 near-constant temperature flight legs analyzed during the 25 April, 20 May, and 23 May 2011 events, the derived surfaces of solutions on the first two days where the aircraft sampled stratiform cloud had a larger range in a and b for lower temperature environments that corresponded to less variability in N(D), TWC, and Z for a flight leg. Because different regions of the storm were sampled on 23 May, differences in the variability of N(D), TWC, and Z influenced the distribution of chi-square values in (a,b) phase space and the specified tolerance in a way that yielded 6.7 times fewer plausible solutions compared to the flight legs on the other dates. These findings show the importance of representing the variability in a,b coefficients for numerical modeling and remote sensing studies rather than assuming fixed values, as well as the need to further explore how these surfaces depend on environmental conditions in ice and mixed phase clouds.

A novel approach to a Brillouin–LIDAR for remote sensing of the ocean temperature

2004 ◽  
Vol 79 (8) ◽  
pp. 955-961 ◽  
Author(s):  
A. Popescu ◽  
K. Schorstein ◽  
T. Walther
Keyword(s):  
Remote Sensing ◽  
Ocean Temperature ◽  
Novel Approach

Carbon Stores, Sinks, and Sources in Forests of Northwestern Russia: Can We Reconcile Forest Inventories with Remote Sensing Results?

2004 ◽  
Vol 67 (2-3) ◽  
pp. 257-272 ◽  
Author(s):  
Olga N. Krankina ◽  
Mark E. Harmon ◽  
Warren B. Cohen ◽  
Doug R. Oetter ◽  
Zyrina Olga ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Inventories ◽  
Carbon Stores ◽  
Northwestern Russia

Extinction profiles: A novel approach for the analysis of remote sensing data

2016 ◽  
Author(s):  
Pedram Ghamisi ◽  
Roberto Souza ◽  
Leticia Rittner ◽  
Jon A. Benediktsson ◽  
Roberto Lotufo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Novel Approach
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