scholarly journals Evaluation of the Simard et al. 2011 Global Canopy Height Map in Boreal Forests

2020 ◽  
Vol 12 (7) ◽  
pp. 1114
Author(s):  
Wei Yang ◽  
Akihiko Kondoh
Keyword(s):  
Boreal Forests ◽  
Forest Canopy ◽  
Spatial Separation ◽  
Canopy Height ◽  
Tree Cover ◽  
Data Sets ◽  
Data Set ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Light detection and ranging (LiDAR) provides a state-of-the-art technique for measuring forest canopy height. Nevertheless, it may miss some forests due to its spatial separation of individual spots. A number of efforts have been made to overcome the limitation of global LiDAR datasets to generate wall-to-wall canopy height products, among which a global satellite product produced by Simard et al. (2011) (henceforth, the Simard-map) has been the most widely applied. However, the accuracy of the Simard-map is uncertain in boreal forests, which play important roles in the terrestrial carbon cycle and are encountering more extensive climate changes than the global average. In this letter, we evaluated the Simard-map in boreal forests through a literature review of field canopy height. Our comparison shows that the Simard-map yielded a significant correlation with the field canopy height (R2 = 0.68 and p < 0.001). However, remarkable biases were observed with the root mean square error (RMSE), regression slope, and intercept of 6.88 m, 0.448, and 10.429, respectively. Interestingly, we found that the evaluation results showed an identical trend with a validation of moderate-resolution imaging spectroradiometer (MODIS) tree-cover product (MOD44B) in boreal forests, which was used as a crucial input data set for generating the Simard-map. That is, both the Simard-map and MOD44B yielded an overestimation (underestimation) in the lower (upper) tails of the scatterplots between the field and satellite data sets. This indicates that the MOD44B product is the likely source of error for the estimation biases of the Simard-map. Finally, a field calibration was performed to improve the Simard-map in boreal forests by compensating for the estimation biases and discarding non-forest areas, which provided a more reliable canopy height product for future applications.

scholarly journals Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI

2016 ◽  
Vol 16 (1) ◽  
pp. 47-69 ◽  
Author(s):  
R. Alfaro-Contreras ◽  
J. Zhang ◽  
J. R. Campbell ◽  
J. S. Reid
Keyword(s):  
Interannual Variability ◽  
Orthogonal Polarization ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time ◽  
Aerosol Index

Abstract. Seven and a half years (June 2006 to November 2013) of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud layer products are compared with collocated Ozone Monitoring Instrument (OMI) aerosol index (AI) data and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products in order to investigate variability in estimates of biannual and monthly above-cloud aerosol (ACA) events globally. The active- (CALIOP) and passive-based (OMI-MODIS) techniques have their advantages and caveats for ACA detection, and thus both are used to derive a thorough and robust comparison of daytime cloudy-sky ACA distribution and climatology. For the first time, baseline above-cloud aerosol optical depth (ACAOD) and AI thresholds are derived and examined (AI  =  1.0, ACAOD  =  0.015) for each sensor. Both OMI-MODIS and CALIOP-based daytime spatial distributions of ACA events show similar patterns during both study periods (December–May) and (June–November). Divergence exists in some regions, however, such as Southeast Asia during June through November, where daytime cloudy-sky ACA frequencies of up to 10 % are found from CALIOP yet are non-existent from the OMI-based method. Conversely, annual cloudy-sky ACA frequencies of 20–30 % are reported over northern Africa from the OMI-based method yet are largely undetected by the CALIOP-based method. Using a collocated OMI-MODIS-CALIOP data set, our study suggests that the cloudy-sky ACA frequency differences between the OMI-MODIS- and CALIOP-based methods are mostly due to differences in cloud detection capability between MODIS and CALIOP as well as QA flags used. An increasing interannual variability of  ∼  0.3–0.4 % per year (since 2009) in global monthly cloudy-sky ACA daytime frequency of occurrence is found using the OMI-MODIS-based method. Yet, CALIOP-based global daytime ACA frequencies exhibit a near-zero interannual variability. Further analysis suggests that the OMI-derived interannual variability in cloudy-sky ACA frequency may be affected by OMI row anomalies in later years. A few regions are found to have increasing slopes in interannual variability in cloudy-sky ACA frequency, including the Middle East and India. Regions with slightly negative slopes of the interannual variability in cloudy-sky ACA frequencies are found over South America and China, while remaining regions in the study show nearly zero change in ACA frequencies over time. The interannual variability in ACA frequency is not, however, statistically significant on both global and regional scales, given the relatively limited sample sizes. A longer data record of ACA events is needed in order to establish significant trends of ACA frequency regionally and globally.

scholarly journals Snow Albedo Seasonality and Trend from MODIS Sensor and Ground Data at Johnsons Glacier, Livingston Island, Maritime Antarctica

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3569
Author(s):  
Calleja ◽  
Corbea-Pérez ◽  
Fernández ◽  
Recondo ◽  
Peón ◽  
...  
Keyword(s):  
Moving Average ◽  
Data Sets ◽  
Snow Albedo ◽  
Livingston Island ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sky Conditions ◽  
Cloud Mask

The aim of this work is to investigate whether snow albedo seasonality and trend under all sky conditions at Johnsons Glacier (Livingston Island, Antarctica) can be tracked using the Moderate Resolution Imaging Spectroradiometer (MODIS) snow albedo daily product MOD10A1. The time span is from December 2006 to February 2015. As the MOD10A1 snow albedo product has never been used in Antarctica before, we also assess the performance for the MOD10A1 cloud mask. The motivation for this work is the need for a description of snow albedo under all sky conditions (including overcast days) using satellite data with mid-spatial resolution. In-situ albedo was filtered with a 5-day windowed moving average, while the MOD10A1 data were filtered using a maximum filter. Both in-situ and MOD10A1 data follow an exponential decay during the melting season, with a maximum decay of 0.049/0.094 day−1 (in-situ/MOD10A1) for the 2006–2007 season and a minimum of 0.016/0.016 day−1 for the 2009–2010 season. The duration of the decay varies from 85 days (2007–2008) to 167 days (2013–2014). Regarding the albedo trend, both data sets exhibit a slight increase of albedo, which may be explained by an increase of snowfall along with a decrease of snowmelt in the study area. Annual albedo increases of 0.2% and 0.7% are obtained for in-situ and MOD10A1 data, respectively, which amount to respective increases of 2% and 6% in the period 2006–2015. We conclude that MOD10A1 can be used to characterize snow albedo seasonality and trend on Livingston Island when filtered with a maximum filter.

scholarly journals Retrieval of canopy height using moderate-resolution imaging spectroradiometer (MODIS) data

2011 ◽  
Vol 115 (6) ◽  
pp. 1595-1601 ◽  
Author(s):  
Zhuosen Wang ◽  
Crystal B. Schaaf ◽  
Philip Lewis ◽  
Yuri Knyazikhin ◽  
Mitchell A. Schull ◽  
...  
Keyword(s):  
Canopy Height ◽  
Modis Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

scholarly journals Analysis of the Spatial Differences in Canopy Height Models from UAV LiDAR and Photogrammetry

2020 ◽  
Vol 12 (18) ◽  
pp. 2884
Author(s):  
Qingwang Liu ◽  
Liyong Fu ◽  
Qiao Chen ◽  
Guangxing Wang ◽  
Peng Luo ◽  
...  
Keyword(s):  
Point Cloud ◽  
Forest Canopy ◽  
Point Clouds ◽  
Canopy Height ◽  
Central China ◽  
Data Sets ◽  
Interpolation Algorithm ◽  
Data Set ◽  
Spatial Differences ◽  
Mean Square Errors

Forest canopy height is one of the most important spatial characteristics for forest resource inventories and forest ecosystem modeling. Light detection and ranging (LiDAR) can be used to accurately detect canopy surface and terrain information from the backscattering signals of laser pulses, while photogrammetry tends to accurately depict the canopy surface envelope. The spatial differences between the canopy surfaces estimated by LiDAR and photogrammetry have not been investigated in depth. Thus, this study aims to assess LiDAR and photogrammetry point clouds and analyze the spatial differences in canopy heights. The study site is located in the Jigongshan National Nature Reserve of Henan Province, Central China. Six data sets, including one LiDAR data set and five photogrammetry data sets captured from an unmanned aerial vehicle (UAV), were used to estimate the forest canopy heights. Three spatial distribution descriptors, namely, the effective cell ratio (ECR), point cloud homogeneity (PCH) and point cloud redundancy (PCR), were developed to assess the LiDAR and photogrammetry point clouds in the grid. The ordinary neighbor (ON) and constrained neighbor (CN) interpolation algorithms were used to fill void cells in digital surface models (DSMs) and canopy height models (CHMs). The CN algorithm could be used to distinguish small and large holes in the CHMs. The optimal spatial resolution was analyzed according to the ECR changes of DSMs or CHMs resulting from the CN algorithms. Large negative and positive variations were observed between the LiDAR and photogrammetry canopy heights. The stratified mean difference in canopy heights increased gradually from negative to positive when the canopy heights were greater than 3 m, which means that photogrammetry tends to overestimate low canopy heights and underestimate high canopy heights. The CN interpolation algorithm achieved smaller relative root mean square errors than the ON interpolation algorithm. This article provides an operational method for the spatial assessment of point clouds and suggests that the variations between LiDAR and photogrammetry CHMs should be considered when modeling forest parameters.

scholarly journals Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests

2021 ◽  
Vol 18 (2) ◽  
pp. 621-635
Author(s):  
Jan Pisek ◽  
Angela Erb ◽  
Lauri Korhonen ◽  
Tobias Biermann ◽  
Arnaud Carrara ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Distribution Function ◽  
Boreal Forests ◽  
Bidirectional Reflectance Distribution Function ◽  
Bidirectional Reflectance ◽  
Modis Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution

Abstract. Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing.

scholarly journals The Collection 6 MODIS aerosol products over land and ocean

2013 ◽  
Vol 6 (11) ◽  
pp. 2989-3034 ◽  
Author(s):  
R. C. Levy ◽  
S. Mattoo ◽  
L. A. Munchak ◽  
L. A. Remer ◽  
A. M. Sayer ◽  
...  
Keyword(s):  
Arid Land ◽  
Data Set ◽  
Deep Blue ◽  
New Information ◽  
Spatial Coverage ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces ◽  
Cloud Mask

Abstract. The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.

Intercomparison of Surface broadband Albedo products from MODIS, CGLS over Northeast Asia

2020 ◽  
Author(s):  
Noh-Hun Seong ◽  
Sungwon Choi ◽  
Donghyun Jin ◽  
Daeseong Jung ◽  
Kyung-soo Han
Keyword(s):  
Northeast Asia ◽  
Radiation Budget ◽  
Data Sets ◽  
Land Type ◽  
Comparison Results ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Types

&lt;p&gt;Surface broadband albedo&amp;#160;is one of the climate variables that understand Earth&amp;#8217;s radiation budget. Currently, the polar-orbit satellite-derived surface broadband albedo products are retrieved by several organizations. As there are many kinds, it is necessary to identify the characteristics of each products. In this study, we were to compare representative products for long-term that the albedo products based on polar-obit satellite such as moderate resolution imaging spectroradiometer (MODIS) and the Copernicus Global Land Service (CGLS). We studied the Northeast Asia region where the land type remains unchanged from 2000 to 2018. The overall trend of the two products was similar. However, differences occurred depending on the land types and season. The relatively high value of MODIS albedo was calculated in winter because it was sensitive to the snow. In other seasons, the CGLS albedo was higher than the MODIS albedo. The MODIS albedo was calculated higher than CGLS albedo for all land types except forest. The comparison results showed that caution should be given before operational use of the albedo data sets in these regions.&lt;/p&gt;

scholarly journals Validation of MODIS 3 km Land Aerosol Optical Depth from NASA's EOS Terra and Aqua Missions

2018 ◽  
Author(s):  
Pawan Gupta ◽  
Lorraine A. Remer ◽  
Robert C. Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Aerosol Retrieval ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sensor Degradation ◽  
Over Time

Abstract. The two MODerate Resolution Imaging Spectroradiometer (MODIS) sensors, aboard Earth Observing Satellites (EOS) Terra and Aqua, have been making aerosol observations for more than 15 years. From these observations, the MODIS dark target (DT) aerosol retrieval algorithm provides aerosol optical depth (AOD) products, globally over both land and ocean. In addition to the standard resolution product (10 × 10 km2), the MODIS collection 6 (C006) data release included a higher resolution (3 × 3 km2). Other than accommodations for the two different resolutions, the 10 km, and 3 km DT algorithms are basically the same. In this study, we perform global validation of the higher resolution AOD over global land by comparing against AERONET measurements. The MODIS-AERONET collocated data sets consist of 161,410 high-confidence AOD pairs from 2000 to 2015 for MODIS Terra and 2003 to 2015 for MODIS-Aqua. We find that 62.5 % and 68.4 % of AODs retrieved from MODIS-Terra and MODIS-Aqua, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2*AOD), with a high correlation (R = 0.87). The scatter is not random but exhibits a mean positive bias of ~ 0.06 for Terra and ~ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e. true AOD) but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with MODIS-Terra showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

scholarly journals Estimating Forest Canopy Height Using MODIS BRDF Data Emphasizing Typical-Angle Reflectances

2019 ◽  
Vol 11 (19) ◽  
pp. 2239 ◽  
Author(s):  
Lei Cui ◽  
Ziti Jiao ◽  
Yadong Dong ◽  
Mei Sun ◽  
Xiaoning Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Canopy ◽  
Forest Biomass ◽  
Canopy Height ◽  
Validation Data ◽  
Climate Change Research ◽  
Auxiliary Data ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Imaging Sensor

Forest-canopy height is an important parameter for the estimation of forest biomass and terrestrial carbon flux and climate-change research at regional and global scales. Currently, various methods combining Light Detection and Ranging (LiDAR) data with various auxiliary data, particularly satellite remotely sensed reflectances, have been widely used to produce spatially continuous canopy-height products. However, current methods in use for remote sensing reflectances mainly focus on the nadir view direction, while anisotropic reflectances, which are theoretically more sensitive to the forest canopy height in the multiangle remote sensing field, have rarely been explored. Here, we attempted to examine the potential of using modeled multiangle reflectances at three typical viewing angles (i.e., from the hotspot, darkspot, and nadir directions) to estimate forest-canopy height as auxiliary data sources. First, the sensitivities of the typical angular reflectances as a function of forest canopy height were fully examined using the Extended Fourier Amplitude Sensitivity Test (EFAST) method based on the 4-scale Bidirectional Reflectance Distribution Function (BRDF) model simulations. This indicated that reflectances in the off-nadir viewing directions are generally sensitive to canopy-height variations. Then, the canopy heights were extracted from airborne Laser Vegetation Imaging Sensor (LVIS) data, which were further divided into training and validation data. Moderate Resolution Imaging Spectroradiometer (MODIS) multiangle reflectances at typical viewing angles were calculated from the MODIS BRDF parameter product (MCD43A1, version 6) as partial training-input data, based on a hotspot-adjusted, kernel-driven linear BRDF model. Subsequently, the Random Forest (RF) machine learning model was trained to acquire the relationship between the extracted canopy heights and the corresponding MODIS typical viewing reflectances. The trained model was further applied to estimate the canopy height metrics in the study areas of Howland Forest, Harvard Forest, and Bartlett Forest. Finally, the estimated canopy heights were independently validated by canopy heights extracted from the LVIS data. The results indicate that the canopy heights modeled through this method exhibit generally high accordance with the LVIS-derived canopy heights (R = 0.65−0.67; RMSE = 3.63−5.78). The results suggest that the MODIS multiangle reflectance data at typical observation angles contain important information regarding forest canopy height and can, therefore, be used to estimate forest canopy height for various ecological applications.

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