In monitoring, planning and maintaining the dynamics of forests on a sustainable basis, the use of satellite imagery is of primary importance. Many web applications have already been developed to assist general and specialist forest monitoring using high (for example, Landsat) and very high spatial resolution images.

With the help of satellite images and remote sensing technologies, it is possible to identify forest cover characteristics such as the degree of disturbance to the the forest ecosystem (assessment of "health"), the completeness of forest stands (density of plantations, the degree of closeness of the stand), the prevailing age of the forest stand, the prevailing types of forest stand (for temperate forests the height of individual trees, the height of the tree layers, the diameter of the crowns of individual trees, the boundaries of the forest), forest fires in the near real-time range, territories with burned forests for a year of observation, felling of different ages.

Vegetation cover disturbance

Vegetation indices are widely used for both revealing the ecological characteristics of the earth's surface and the use of the NDVI index is the widest character. NDVI (Normalized Difference Vegetation Index) is one of the most commonly used indices for solving problems using quantitative estimates of vegetation cover. The use of the NDVI index from the satellite image of the study area facilitates assessment of the type and state (degree of disturbance) of vegetation cover, including the forest cover for the date of survey. The comparison of NDVI index maps for different years allows us to assess the dynamics of the evolving state of the vegetation cover at different periods.

Coverage type - the NDVI index value

NDVI Coverage type
0.8-1.0 Very powerful, dense vegetation (for example - a tropical or healthy deciduous forest)
0.67 - 0.80 Thick vegetation (forest)
0.4 - 0.5 Scant and sparse tree and shrub vegetation
0.2 - 0.4 Shrubs and pastures
0.09 - 0.2 Open soil
-0.1 - 0.1 Rocks, sand, snow
-0.42 … -0.33 Water
-0.55 … -0.50 Anthropogenic pavements (concrete, asphalt)
0 Clouds

The NDVI index maps cover the territory of the State of Rondônia, Brazil, of which tropical forest logging has taken place for approx.17 years via Landsat 5 (TM) 1990-04-06 and Landsat 8 2017-10-09. Comparing the obtained values ​​of the NDVI index, and also based on the understanding that the higher the NDVI index, the denser and healthier the forest cover, it is possible to analyze the state of the vegetation cover for the two specified years and visually assess the process of change over 17 years.

  • NDVI satellite image of São Miguel do Guaporé, State of Rondônia, Brazil
    São Miguel do Guaporé - State of Rondônia, Brazil 11.13863°S 63.59436°W
  • NDVI satellite image of São Miguel do Guaporé, State of Rondônia, Brazil in year
    São Miguel do Guaporé - State of Rondônia, Brazil 11.13863°S 63.59436°W
Foresty scene comparison forest cover comparison

Supervised Classification

With the old land-use maps and the Supervised Classification method, it is possible to identify early areas that are authentically occupied by arable land and to study in more detail (as areas of great interest in assessing the effectiveness of the reforestation method) the dynamics of reforestation for the following years, as well as the current state of the ecosystem.

Identification and monitoring of forest fires and burnt out areas

The MODIS images obtained from Terra and Aqua satellites are the main resources for determining fires and burnt territories. Due to the small time interval between receiving images for the same territory (only 1-2 days), MODIS data can provide analysis of the situation in near real-time.

MODIS detects two types of fire activity: active burning sites, areas burning at the time of shooting (active fires, hotspots), and already burned areas (burned areas). Active hotbeds are obtained from MODIS-MOD14 products. Fires are detected based on their strong emission of middle infrared range radiation. However, the approach to detecting hotbeds has a number of limitations and cannot be used to estimate the spatial coverage of fire-affected areas, because at the time of active burning, the satellite is often absent from the point necessary for detection or the view is obscured by cloud-cover. Burned territories are determined by MODIS- MCD45 is the algorithm used to detect burnt areas, and is based on the analysis of time series of daily data on the reflectivity of the surface.

Forest pathology identification

Satellite images can detect damaged forest areas in large areas and diagnose the type of damage: top fires, shrinking of trees, swamping, cutting, overgrowing, etc. This enables specialists to react quickly and take measures to eliminate the causes of damage. Remote sensing technologies could be used to monitor the situation and determine whether the damaged forest area is recovering. The ability to analyze the state of the forest cover for 40 years makes it possible to study the effectiveness of the methodologies used to eliminate damage.

Determination of tree height and crown diameter

For tropical forests, the presence of a high tier (30-45 m) is a sign of a healthy forest ecosystem (indicating that the ecosystem is unbroken or, for a restored forest, that its quality is close to the that of an intact ecosystem). Therefore, such a technique would help determine the degree of disturbance of the tropical forest cover, and, for practical purposes, identify areas of high quality that should be prioritised for conservation; identify problem regions and the subsequent development of measures to eliminate damage; and evaluate the effectiveness of reforestation methods.

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