Application Remote Sensing in Forest - Lecture Note - Lecture Material
Application Remote Sensing in Forest


Tropical forest diversityForests are a valuable resource providing food, shelter, wildlife habitat, fuel, and daily supplies such as medicinal ingredients and paper. Forests play an important role in balancing the Earth's CO2 supply and exchange, acting as a key link between the atmosphere, geosphere, and hydrosphere. Tropical rainforests, in particular, house an immense diversity of species, more capable of adapting to, and therefore surviving, changing environmental conditions than monoculture forests. This diversity also provides habitat for numerous animal species and is an important source of medicinal ingredients. The main issues concerning forest management are depletion due to natural causes (fires and infestations) or human activity (clear-cutting, burning, land conversion), and monitoring of health and growth for effective commercial exploitation and conservation.

Extraction of wood in tropical forestHumans generally consider the products of forests useful, rather than the forests themselves, and so extracting wood is a wide-spread and historical practice, virtually global in scale. Depletion of forest resources has long term effects on climate, soil conservation, biodiversity, and hydrological regimes, and thus is a vital concern of environmental monitoring activities. Commercial forestry is an important industry throughout the world. Forests are cropped and re-harvested, and the new areas continually sought for providing a new source of lumber. With increasing pressure to conserve native and virgin forest areas, and unsustainable forestry practices limiting the remaining areas of potential cutting, the companies involved in extracting wood supplies need to be more efficient, economical, and aware of sustainable forestry practices. Ensuring that there is a healthy regeneration of trees where forests are extracted will ensure a future for the commercial forestry firms, as well as adequate wood supplies to meet the demands of a growing population.

Clearing of forest in Costa RicaNon-commercial sources of forest depletion include removal for agriculture (pasture and crops), urban development, droughts, desert encroachment, loss of ground water, insect damage, fire and other natural phenomena (disease, typhoons). In some areas of the world, particularly in the tropics, (rain) forests, are covering what might be considered the most valuable commodity - viable agricultural land. Forests are burned or clear-cut to facilitate access to, and use of, the land. This practice often occurs when the perceived need for long term sustainability is overwhelmed by short-term sustenance goals. Not only are the depletion of species-rich forests a problem, affecting the local and regional hydrological regime, the smoke caused by the burning trees pollutes the atmosphere, adding more CO2, and furthering the greenhouse effect.

Of course, monitoring the health of forests is crucial for sustainability and conservation issues. Depletion of key species such as mangrove in environmentally sensitive coastline areas, removal of key support or shade trees from a potential crop tree, or disappearance of a large biota acting as a CO2 reservoir all affect humans and society in a negative way, and more effort is being made to monitor and enforce regulations and plans to protect these areas.

International and domestic forestry applications where remote sensing can be utilized include sustainable development, biodiversity, land title and tenure (cadastre), monitoring deforestation, reforestation monitoring and managing, commercial logging operations, shoreline and watershed protection, biophysical monitoring (wildlife habitat assessment), and other environmental concerns.

General forest cover information is valuable to developing countries with limited previous knowledge of their forestry resources. General cover type mapping, shoreline and watershed mapping and monitoring for protection, monitoring of cutting practices and regeneration, and forest fire/burn mapping are global needs which are currently being addressed by Canadian and foreign agencies and companies employing remote sensing technology as part of their information solutions in foreign markets.

Forestry applications of remote sensing include the following:

1) reconnaissance mapping:
Objectives to be met by national forest/environment agencies include forest cover updating, depletion monitoring, and measuring biophysical properties of forest stands.
  • forest cover type discrimination
  • agroforestry mapping
2) Commercial forestry:
Of importance to commercial forestry companies and to resource management agencies are inventory and mapping applications: collecting harvest information, updating of inventory information for timber supply, broad forest type, vegetation density, and biomass measurements.
  • clear cut mapping / regeneration assessment
  • burn delineation
  • infrastructure mapping / operations support
  • forest inventory
  • biomass estimation
  • species inventory
3) Environmental monitoring
Conservation authorities are concerned with monitoring the quantity, health, and diversity of the Earth's forests.
  • deforestation (rainforest, mangrove colonies)
  • species inventory
  • watershed protection (riparian strips)
  • coastal protection (mangrove forests)
  • forest health and vigour

Canadian requirements for forestry application information differ considerably from international needs, due in part to contrasts in tree size, species diversity (monoculture vs. species rich forest), and agroforestry practices. The level of accuracy and resolution of data required to address respective forestry issues differs accordingly. Canadian agencies have extensive a priori knowledge of their forestry resources and present inventory and mapping needs are often capably addressed by available data sources.

For Canadian applications requirements, high accuracy (for accurate information content), multispectral information, fine resolution, and data continuity are the most important. There are requirements for large volumes of data, and reliable observations for seasonal coverage. There is a need to balance spatial resolution with the required accuracy and costs of the data. Resolution capabilities of 10 m to 30 m are deemed adequate for forest cover mapping, identifying and monitoring clearcuts, burn and fire mapping, collecting forest harvest information, and identifying general forest damage. Spatial coverage of 100 - 10000 km2 is appropriate for district to provincial scale forest cover and clear cut mapping, whereas 1-100 km2 coverage is the most appropriate for site specific vegetation density and volume studies.

Tropical forest managers will be most concerned with having a reliable data source, capable of imaging during critical time periods, and therefore unhindered by atmospheric conditions.

Did you know?

The forest around Mt. St. Helens after the eruption

Natural disasters can also wipe out huge areas of forest. Burns can destroy several thousand of hectares, landslides can displace trees down a slope, and excessive flooding can damage trees. Volcanoes however, have the greatest potential for destroying forests in the shortest amount of time. In 1980, Mt. St. Helens in northwestern United States violently erupted. The volcanic blast, reaching 320 km/hour, levelled over 600km2 of forest.


Clear Cut Mapping & Deforestation

severe depletion of forest

Deforestation is a global problem, with many implications. In industrialized Europe, pollution (acid rain, soot and chemicals from factory smoke plumes) has damaged a large percentage of forested land. In the former Czechoslovakia, one half of the forests are destroyed or damaged from pollutants. Similar effects are felt in Germany, Poland, and even the Scandinavian countries. In tropical countries, valuable rainforest is being destroyed in an effort to clear potentially valuable agricultural and pasture land. This has resulted in huge losses of tropical rainforest throughout Latin America (Central America, southern Mexico, Haiti), South America (Brazil), Africa and Asia. In both Haiti and Madagascar in particular, the results have been devastating. The loss of forests increases soil erosion, river siltation, and deposition, affecting navigation, fisheries, wildlife habitat, and drinking water supplies, as well as farming productivity and self-sufficiency.

Sensitive estuarine environments are protected by mangrove forest, which is cut or lost to urban growth, aquaculture, or damaged by pollutants or siltation. Monitoring the health of this forest is a step towards protecting the coastlines from erosion and degradation, and nearby inland areas from flooding.

The loss of forests also affects the genetic diversity of species on Earth, which controls our intrinsic ability to adapt to changing conditions and environment. Rainforests account for approximately one half of the plant and animal species on Earth, and destroying large sections will only serve to reduce the gene and species pool.

The rate and extent of deforestation, as well as monitoring regeneration, are the key parameters measured by remote sensing methods.

Why remote sensing?
Remote sensing brings together a multitude of tools to better analyze the scope and scale of the deforestation problem. Multitemporal data provides for change detection analyses. Images of earlier years are compared to recent scenes, to tangibly measure the differences in the sizes and extents of the clearcuts or loss of forest. Data from a variety of sources are used to provide complementary information. Radar, merged with optical data, can be used to efficiently monitor the status of existing clearcuts or emergence of new ones, and even assess regeneration condition. In countries where cutting is controlled and regulated, remote sensing serves as a monitoring tool to ensure companies are following cut guidelines and specifications.

High resolution data provide a detailed view of forest depletion, while radar can provide a view that may otherwise be obscured by clouds. All remote sensing devices, however, provide a view of often remote and inaccessible areas, where illegal cutting or damage could continue unnoticed for long periods of time if aerial surveillance wasn't possible.

Data requirements
Global monitoring initiatives, such as rain forest depletion studies, depend on large area coverage and data continuity, so it is important to use a sensor that will have successive generations launched and operational. Clear cut mapping and monitoring also require regional scale images and moderate or high resolution data depending on whether cuts are to be simply detected or delineated. As for many multi-temporal applications, a higher resolution image can be used to define the baseline, and coarser resolution images can be used to monitor changes to that baseline.

Canada vs. International
Optical sensors are still preferred for clear cut mapping and monitoring in Canada because forest vegetation, cuts, and regenerating vegetation have distinguishable spectral signatures, and optical sensors can collect sufficient cloud-free data.

SAR image

photo comparaison

Comparison of photo (bottom)andSAR image (top)
of forest cuts along road.

Radar is more useful for applications in the humid tropics because its all weather imaging capability is valuable for monitoring all types of depletion, including clear cuts, in areas prone to cloudy conditions. Cuts can be defined on radar images because clear cuts produce less backscatter than the forest canopy, and forest edges are enhanced by shadow and bright backscatter. However, regenerating cuts are typically difficult to detect, as advanced regeneration and mature forest canopy are not separable. Mangrove forests generally occur in tropical coastal areas, which are prone to cloudy conditions, therefore a reliable monitoring tool is required to successively measure the rate of forest depletion. Radar has been proven to differentiate mangrove from other land covers, and some bands have long wavelengths capable of penetrating cloud and rain. The only limitation is in differentiating different mangrove species.

Case study (example)
Landsat Thematic Mapper overview of Whitecourt, ABIn Alberta, much of the province's forestland has been sold to offshore investors who are interested in selling pulp and paper products. Around the area of Whitecourt, clear cutting of conifer forest has been occurring for decades. In recent years however, the increasing demand for wood products has accelerated the cutting of the forests, resulting in a dissected and checkered landscape. Besides cutting for wood supply, forest depletion is also occurring due to cuts for seismic lines for oil and gas exploration and extraction. Both optical and radar sensors have been used to monitor the clear cuts and regeneration.

Optical scene of forest clear cutting Radar scene of forest clear cutting

Optical and Radar scenes of forest clear cutting.


Species Identification & Typing

Forest cover typing and species identification are critical to both forest conservation managers and forestry companies interested in their supply inventory. Forest cover typing can consist of reconnaissance mapping over a large area, while species inventories are highly detailed measurements of stand contents and characteristics (tree type, height, density).

Why remote sensing?
Remote sensing provides a means of quickly identifying and delineating various forest types, a task that would be difficult and time consuming using traditional ground surveys. Data is available at various scales and resolutions to satisfy local or regional demands Large scale species identification can be performed with multispectral, hyperspectral, or airphoto data, while small scale cover type delineation can be performed by radar or multispectral data interpretation. Both imagery and the extracted information can be incorporated into a GIS to further analyze or present with ancillary data, such as slopes, ownership boundaries, or roads.

Hyperspectral imagery can provide a very high spatial resolution while capturing extremely fine radiometric resolution data. This type of detailed spectral information can be used to generate signatures of vegetation species and certain stresses (e.g. infestations) on trees. Hyperspectral data offers a unique view of the forest cover, available only through remote sensing technology.

Data requirements
Requirements depend on the scale of study to be conducted. For regional reconnaissance mapping, moderate area coverage, with a sensor sensitive to differences in forest cover (canopy texture, leaf density, spectral reflection) is needed. Multitemporal datasets also contribute phenology information that may aid in interpretation by incorporating the seasonal changes of different species.

For detailed species identification associated with forest stand analysis, very high resolution, multispectral data is required. Being able to view the images in stereo helps in the delineation and assessment of density, tree height, and species. In general, monitoring biophysical properties of forests requires multispectral information and finely calibrated data.

Canada vs. International
Current sources of data used operationally for forest cover typing and species identification applications within Canada are aerial photography, orthophotography, Landsat TM, and SPOT data. Landsat data are the most appropriate for executing reconnaissance level forest surveys, while aerial photography and digital orthophoto are the preferred data source for extracting stand and local inventory information. Airphotos are the most appropriate operational data source for stand level measurements including species typing. SAR sensors such as RADARSAT are useful where persistent cloud cover limits the usefulness of optical sensors.

SAR image used to interpret forest cover

In humid tropical areas, forest resource assessments and measurements are difficult to obtain because of cloudy conditions hindering conventional remote sensing efforts, and difficult terrain impeding ground surveys. In this situation, reliability of data acquisition is more crucial than resolution or frequency of imaging. An active sensor may be the only feasible source of data, and its reliability will facilitate regular monitoring. Radar will serve this purpose, and an airborne sensor is sufficient for high resolution requirements such as cover typing. This type of data can be used for a baseline map , while coarser resolution data can provide updates to any changes in the baseline.

Forest cover map derived from SAR data

Case study (example)

Inventory Branch, Ministry of Forests, Province of British Columbia, Canada
This is an example of the operational requirements and procedure for a provincial department involved in a number of forestry applications using remote sensing technology.

The Inventory Branch is responsible for maintaining a database of Crown Land information concerning historical, stand, and sustainable forest management information which is used for determining timber volumes and annual allowable cuts. The inventory itself is performed every ten years with 1:15,000 scale aerial photography, and updated with satellite imagery every two years.

The Inventory branch requires geocoded, terrain corrected data. For most studies, the branch currently buys precision geocoded data, and for large scale mapping projects, they will cut costs by obtaining systematic versus precision geocoded data. Further processing is done in-house on workstations. Some location data are now being provided by the private sector, conducting field traverses with GPS (global positioning system) data.

Present planimetric accuracy requirements are 20 m, but will be more demanding in the near future. Airphotos and orthophotos meet requirements and are good for interpretation but are limited by expense. Data continuity is important, as monitoring will be an ongoing operation. TM data for updating maps is reasonable in cost and information content for interim monitoring.

Much of the updating in the Ministry of Forests is done with TM data, either brought digitally into a MicroStation workstation to perform heads-up digitizing, or in transparency form with the image overlain onto existing maps using a projection device. The Ministry of Forests is presently investigating the potential of a number of data sources with various levels of processing applied, and integration possibilities to assess accuracy versus cost relationships.

The Ministry of Forests in B.C. employs an expert system SHERI (System of Hierarchical Expert Systems for Resource Inventories) to provide a link between remotely sensed data, GIS and growth and yield modelling. The end to end information flow is complete with the generation of final products including forest cover maps incorporating planimetric and administrative boundary information.

Case study (example)

Hyperspectral image

Stem count from hyperspectral imagery

Hyperspectral image and recent stem count from hyperspectral imagery

Forest companies use hyperspectral imagery to obtain stem counts , stand attributes, and for mapping of land cover in the forest region of interest. These images depict a false colour hyperspectral image of a Douglas fir forest on Vancouver Island at a resolution of 60 cm. The imagery was acquired in the fall of 1995 by the CASI (Compact Airborne Imaging Spectrometer). Attributes obtained from the imagery (a subset is shown) include:

Carte de la couverture du sol à partir d'images hyperspectrales

  • Stand Area (hectares) 9.0
  • Total number of trees 520
  • Tree density (stems/ha) 58
  • Crown closure (%) 12.46
  • Average tree crown area (sq m) 21.47

The corresponding land cover map contains the following classes:

  • Dark green: conifers
  • Green: lower branches
  • Light purple: gravel
  • Yellow: deciduous
  • Orange: dry ground cover
  • Red: wet ground cover
  • Blue (light): water
  • Blue (dark): deep or clear water

All imagery courtesy of MacMillan Bloedel and ITRES Research Limited.

Did you know?

Forest interpretation from SAR data

Forest interpretation from SAR data

Interpreting forest cover type with radar data is very similar to interpreting multispectral images. The same interpretation elements are used (tone, texture, shape, pattern, size, association), but texture plays a dominant role in the discrimination of different forest types. Viewing the images in stereo helps to differentiate relative tree heights, as well as define rivers that have specific vegetation along their banks.


Burn Mapping

Fire is part of the natural reproductive cycle of many forests revitalizing growth by opening seeds and releasing nutrients from the soil. However, fires can also spread quickly and threaten settlements and wildlife, eliminate timber supplies, and temporarily damage conservation areas. Information is needed to help control the extent of fire, and to assess how well the forest is recovering following a burn.

Why remote sensing?
Remote sensing can be used to detect and monitor forest fires and the regrowth following a fire. As a surveillance tool, routine sensing facilitates observing remote and inaccessible areas, alerting monitoring agencies to the presence and extent of a fire. NOAA AVHRR thermal data and GOES meteorological data can be used to delineate active fires and remaining "hot-spots" when optical sensors are hindered by smoke, haze, and /or darkness. Comparing burned areas to active fire areas provides information as to the rate and direction of movement of the fire. Remote sensing data can also facilitate route planning for both access to, and escape from, a fire, and supports logistics planning for fire fighting and identifying areas not successfully recovering following a burn.

Years following a fire, updates on the health and regenerative status of an area can be obtained by a single image, and multitemporal scenes can illustrate the progression of vegetation from pioneer species back to a full forest cover.

Data requirements
While thermal data is best for detecting and mapping ongoing fires, multispectral (optical and near-infrared) data are preferred for observing stages of growth and phenology in a previous burn area. The relative ages and area extent of burned areas can be defined and delineated, and health of the successive vegetation assessed and monitored. Moderate spatial coverage, high to moderate resolution, and a low turnaround time are required for burn mapping. On the other hand, fire detection and monitoring requires a large spatial coverage, moderate resolution and a very quick turnaround to facilitate response.

Canadian vs. International
Requirements for burn mapping are the same, except where cloud cover precludes the used of optical images. In this case, radar can be used to monitor previous burn areas, and is effective from the second year following a burn, onwards.

Case study (example) Northwest Territory Burn

Burned and burning forest near Norman Wells, NWT

Burned and burning forest near Norman Wells, NWT

In the western Northwest Territories along the Mackenzie River, boreal forest covers much of the landscape. Natives rely on the forests for hunting and trapping grounds, and the sensitive northern soil and permafrost are protected from erosion by the forest cover. In the early 1990's a huge fire devastated the region immediately east of the Mackenzie and threatened the town of Fort Norman, a native town south of Norman Wells.

The extent of the burned area, and the areas still burning, can be identified on this NOAA scene, as dark regions (A). The lake in the upper right is Great Bear Lake, and the lake to the lower right is Great Slave Lake. The distance represented by the yellow line is approximately 580 km. The course of the Mackenzie River can be seen to the left of these lakes. Fort Norman (B) is located at the junction of the Mackenzie River and Great Bear River, leading out of Great Bear Lake. At that location, the fire is on both sides of the river. Norman Wells (C) is known as an oil producing area, and storage silos, oil rigs, homes, and the only commercial airport in that part of the country were threatened. Fires in this region are difficult to access because of the lack of roads into the region. Winter roads provide only seasonal access to vehicles in this part of Canada. The small population base also makes it difficult to control, let alone fight, a fire of this magnitude.

Haze and smoke reflect a large amount of energy at shorter wavelengths and appear as blue on this image.