Spectral Characteristic Analysis of Burned Area Based on MODIS Data

2019 ◽  
pp. 391-404
Author(s):  
Rui Ba ◽  
Weiguo Song ◽  
Siuming Lo ◽  
Zixi Xie
Keyword(s):  
Spectral Characteristic ◽  
Burned Area ◽  
Characteristic Analysis ◽  
Modis Data

scholarly journals A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data

2020 ◽  
Vol 236 ◽  
pp. 111493 ◽  
Author(s):  
Joshua Lizundia-Loiola ◽  
Gonzalo Otón ◽  
Rubén Ramo ◽  
Emilio Chuvieco
Keyword(s):  
Burned Area ◽  
Modis Data ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Clustering Approach ◽  
Spatio Temporal

scholarly journals Global Analysis of Burned Area Persistence Time with MODIS Data

2018 ◽  
Vol 10 (5) ◽  
pp. 750 ◽  
Author(s):  
Andrea Melchiorre ◽  
Luigi Boschetti
Keyword(s):  
Global Analysis ◽  
Burned Area ◽  
Modis Data ◽  
Persistence Time

Spectral Characteristic Analysis and Remote Sensing Classification of Coastal Aquaculture Areas Based on GF-1 Data

2019 ◽  
Vol 90 (sp1) ◽  
pp. 49 ◽  
Author(s):  
Hongchun Zhu ◽  
Kaiqiang Li ◽  
Lin Wang ◽  
Jialan Chu ◽  
Ning Gao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Characteristic ◽  
Characteristic Analysis ◽  
Remote Sensing Classification ◽  
Coastal Aquaculture

Burnt Area Index (BAIM) for burned area discrimination at regional scale using MODIS data

2006 ◽  
Vol 234 ◽  
pp. S221 ◽  
Author(s):  
M. Pilar Martín ◽  
Israel Gómez ◽  
Emilio Chuvieco
Keyword(s):  
Regional Scale ◽  
Burned Area ◽  
Burnt Area ◽  
Area Index ◽  
Modis Data

scholarly journals A Comparison of Burned Area Time Series in the Alaskan Boreal Forests from Different Remote Sensing Products

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 363 ◽  
Author(s):  
Moreno-Ruiz ◽  
García-Lázaro ◽  
Arbelo
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Time Series ◽  
Spatial Resolution ◽  
Reference Data ◽  
Global Climate ◽  
Fire Service ◽  
Burned Area ◽  
Spatial And Temporal Patterns ◽  
Modis Data

Alaska’s boreal region stores large amounts of carbon both in its woodlands and in the grounds that sustain them. Any alteration to the fire system that has naturally regulated the region’s ecology for centuries poses a concern regarding global climate change. Satellite-based remote sensors are key to analyzing those spatial and temporal patterns of fire occurrence. This paper compiles four burned area (BA) time series based on remote sensing imagery for the Alaska region between 1982–2015: Burned Areas Boundaries Dataset-Monitoring Trends in Burn Severity (BABD-MTBS) derived from Landsat sensors, Fire Climate Change Initiative (Fire_CCI) (2001–2015) and Moderate-Resolution Imaging Spectroradiometer (MODIS) Direct Broadcast Monthly Burned Area Product (MCD64A1) (2000–2015) with MODIS data, and Burned Area-Long-Term Data Record (BA-LTDR) using Advanced Very High Resolution Radiometer LTDR (AVHRR-LTDR) dataset. All products were analyzed and compared against one another, and their accuracy was assessed through reference data obtained by the Alaskan Fire Service (AFS). The BABD-MTBS product, with the highest spatial resolution (30 m), shows the best overall estimation of BA (81%), however, for the years before 2000 (pre-MODIS era), the BA sensed by this product was only 44.3%, against the 55.5% obtained by the BA-LTDR product with a lower spatial resolution (5 km). In contrast, for the MODIS era (after 2000), BABD-MTBS virtually matches the reference data (98.5%), while the other three time series showed similar results of around 60%. Based on the theoretical limits of their corresponding Pareto boundaries, the lower resolution BA products could be improved, although those based on MODIS data are currently limited by the algorithm’s reliance on the active fire MODIS product, with a 1 km nominal spatial resolution. The large inter-annual variation found in the commission and omission errors in this study suggests that for a fair assessment of the accuracy of any BA product, all available reference data for space and time should be considered and should not be carried out by selective sampling.

Spectral characteristic analysis of lung cancer serum

2001 ◽  
Author(s):  
Xiao Zhou Li ◽  
Huiqiang Jin ◽  
Huasheng Liu ◽  
Jianhua Ding ◽  
Junxiu Lin
Keyword(s):  
Lung Cancer ◽  
Spectral Characteristic ◽  
Characteristic Analysis

Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data

2007 ◽  
Vol 109 (4) ◽  
pp. 429-442 ◽  
Author(s):  
T. Loboda ◽  
K.J. O'Neal ◽  
I. Csiszar
Keyword(s):  
Burned Area ◽  
Modis Data ◽  
Burned Area Mapping
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