Growing stock estimation through stratified sampling on satellite remote sensing data

1990 ◽  
Vol 18 (1-2) ◽  
pp. 29-42 ◽  
Author(s):  
Inderjit Singh ◽  
P. S. Roy
2009 ◽  
Author(s):  
Bingfeng Yang ◽  
Qiao Wang ◽  
Changzuo Wang ◽  
Huawei Wan ◽  
Yipeng Yang ◽  
...  

2021 ◽  
Vol 13 (21) ◽  
pp. 4483
Author(s):  
W. Gareth Rees ◽  
Jack Tomaney ◽  
Olga Tutubalina ◽  
Vasily Zharko ◽  
Sergey Bartalev

Growing stock volume (GSV) is a fundamental parameter of forests, closely related to the above-ground biomass and hence to carbon storage. Estimation of GSV at regional to global scales depends on the use of satellite remote sensing data, although accuracies are generally lower over the sparse boreal forest. This is especially true of boreal forest in Russia, for which knowledge of GSV is currently poor despite its global importance. Here we develop a new empirical method in which the primary remote sensing data source is a single summer Sentinel-2 MSI image, augmented by land-cover classification based on the same MSI image trained using MODIS-derived data. In our work the method is calibrated and validated using an extensive set of field measurements from two contrasting regions of the Russian arctic. Results show that GSV can be estimated with an RMS uncertainty of approximately 35–55%, comparable to other spaceborne estimates of low-GSV forest areas, with 70% spatial correspondence between our GSV maps and existing products derived from MODIS data. Our empirical approach requires somewhat laborious data collection when used for upscaling from field data, but could also be used to downscale global data.


Eos ◽  
2017 ◽  
Author(s):  
Zhong Liu ◽  
James Acker

Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.


2020 ◽  
Author(s):  
Ilham Ali ◽  
Jay Famiglietti ◽  
Jonathan McLelland

Water stress in both surface and groundwater supplies is an increasing environmental and sustainable management issue. According to the UN Environment Program, at current depletion rates almost half of the world's population will suffer severe water stress by 2030. This is further exacerbated by climate change effects which are altering the hydrologic cycle. Understanding climate change implications is critical to planning for water management scenarios as situations such as rising sea levels, increasing severity of storms, prolonged drought in many regions, ocean acidification, and flooding due to snowmelt and heavy precipitation continue. Today, major efforts towards equitable water management and governance are needed. This study adopts the broad, holistic lenses of sustainable development and water diplomacy, acknowledging both the complex and transboundary nature of water issues, to assess the benefits of a “science to policy” approach in water governance. Such negotiations and frameworks are predicated on the availability of timely and uniform data to bolster water management plans, which can be provided by earth-observing satellite missions. In recent decades, significant advances in satellite remote sensing technology have provided unprecedented data of the Earth’s water systems, including information on changes in groundwater storage, mass loss of snow caps, evaporation of surface water reservoirs, and variations in precipitation patterns. In this study, specific remote sensing missions are surveyed (i.e. NASA LANDSAT, GRACE, SMAP, CYGNSS, and SWOT) to understand the breadth of data available for water uses and the implications of these advances for water management. Results indicate historical precedent where remote sensing data and technologies have been successfully integrated to achieve more sustainable water management policy and law, such as in the passage of the California Sustainable Groundwater Management Act of 2014. In addition, many opportunities exist in current transboundary and interstate water conflicts (for example, the Nile Basin and the Tri-State Water Wars between Alabama, Georgia, and Florida) to integrate satellite-remote-sensed water data as a means of “joint-fact finding” and basis for further negotiations. The authors argue that expansion of access to satellite remote sensing data of water for the general public, stakeholders, and policy makers would have a significant impact on the development of science-oriented water governance measures and increase awareness of water issues by significant amounts. Barriers to entry exist in accessing many satellite datasets because of prerequisite knowledge and expertise in the domain. More user-friendly platforms need to be developed in order to maximize the utility of present satellite data. Furthermore, sustainable co-operations should be formed to employ satellite remote sensing data on a regional scale to preempt problems in water supply, quantity, and quality.


Sign in / Sign up

Export Citation Format

Share Document