Supporting decision makers through rapid assessments of remote sensing data: the case of Tefé National Forest, Brazil

Author(s):  
Ana Carolina Moreira Pessôa ◽  
Liana O. Anderson ◽  
Rafael Suertegaray Rossato ◽  
Victor Marchezini ◽  
Bruna Maria Pechini Bento ◽  
...  

<p>Providing scientific subsidies for public policies is a compromise that is beyond the boundaries created by the academic universe, requiring scientists to respond to the challenges posed by increasingly complex societies, both socially and environmentally. Considering this, the objective of this work was to build a pilot project for rapid assessment of Tefé National Forest (TNF) land use zoning and evaluate its relevance as a tool to support actions and influence discussions in protected area management councils.</p><p>The assessment considered remote sensing data on deforestation and fire from 2005 to 2015. Deforestation maps (PRODES-INPE) and active fire (MODIS) information were overlapped with TNF land use zoning. Although National Forest, in general, has its land use rules provided by law, each protected area defines on its Management Plan their own land use zoning, with specific rules.</p><p>The study showed that in 2015, 97% of TNF was covered by forest, and although no deforestation was recorded in the same year, the number of active fires was 1.8 times higher than the average from 2005 to 2014. This demonstrates the vulnerability of this area to the extreme drought which affected the region this year. The Population Zone, where 44% of the TNF population lives, recorded the highest rates of deforestation and fire. The Preservation Zone, on the other hand, showed to be fulfilling its function, presenting no active fires and only one deforestation event during the whole analyzed period.</p><p>These results were presented at the 20th TNF Council Meeting, in 2017. The TNF manager pointed out the great importance of spatial and temporal diagnoses, which can exert in prioritize actions to tackle specific problems in most threatened zones. Community leaders participating in the meeting contributed to the completion of the results with in situ day-to-day reports, offering hypotheses for some phenomena observed on the assessment, such as the deforestation observed in 2010. After that, it became clear that actions directly focused on the Population Zone, and mainly related to the use of fire in years of extreme drought, can improve the conservation outcome for this protected area. Integrated socio-environmental diagnosis, such as this pilot project, can be an important tool, allowing a broader version of the monitoring strategies.</p>

2015 ◽  
Vol 19 (1) ◽  
pp. 507-532 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.


Author(s):  
Hua Ding ◽  
Ru Ren Li ◽  
Li Shuang Sun ◽  
Xin Wang ◽  
Yu Mei Liu

2021 ◽  
Vol 3 ◽  
pp. 180-185
Author(s):  
Y. M. Kenzhegaliyev ◽  
◽  
◽  

The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.


Author(s):  
K Choudhary ◽  
M S Boori ◽  
A Kupriyanov

The main objective of this study was to detect groundwater availability for agriculture in the Orenburg, Russia. Remote sensing data (RS) and geographic information system (GIS) were used to locate potential zones for groundwater in Orenburg. Diverse maps such as a base map, geomorphological, geological structural, lithology, drainage, slope, land use/cover and groundwater potential zone were prepared using the satellite remote sensing data, ground truth data, and secondary data. ArcGIS software was utilized to manipulate these data sets. The groundwater availability of the study was classified into different classes such as very high, high, moderate, low and very low based on its hydro-geomorphological conditions. The land use/cover map was prepared using a digital classification technique with the limited ground truth for mapping irrigated areas in the Orenburg, Russia.


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