Satellite remote sensing for forestry planning—A review

Abstract

Satellite remote sensing for forestry planning-a review. This review attempts, from a critical perspective, to put 25 years of satellite remote sensing research into the context of forestry planning. It is limited to temperate and boreal regions and to remote sensing in the visible and near infra-red spectra. It is structured as follows: firstly, the forestry planning problem is defined and information requirements are identified; secondly, the attempts to use satellite remote sensing as an information source for forestry planning are reviewed, divided into the topics inventory and monitoring; and, finally, the methods for extracting forest information from satellite images are re-examined, and their inherent limitations and methodological weaknesses are discussed.It is concluded that satellite images seldom contain enough information to support the decision process in applied forestry. Although regional level applications may be useful, few successful and reliable applications for local forest inventory, planning or damage monitoring have evolved. Stratification for multi-stage sampling and monitoring of clear-cuts are areas in which satellite images have been shown to be feasible. However, it is doubtful whether the costs involved can be justified for such uses alone. A further conclusion is that many studies have adopted simplistic views of the information needs in the forestry planning process. These studies do not relate the analysis to management decisions, but instead assume that plain and approximate mapping of the forest has a great value. Present developments in the discipline involve complex modelling of reflectance, taking into consideration internal shading, topography and other features, yet without dramatic improvements compared with earlier studies. Furthermore, satellite remote sensing and digital image analysis are no longer technologically spectacular, facts which may affect future research in the discipline. It is, perhaps, time to draw the conclusion that current satellite sensors are not in general suitable for forestry planning, since (a) they contain little relevant information, and (b) for forest management planning purposes there are often more efficient ways of collecting the information required.

Foundation of CS-DC e-Laboratory: Open Systems Exploration for Ecosystems Leveraging

“…In the level of ecosystems, remote sensing technologies are extensively applied to the measurement in large-scale agriculture and assessment of ecological state. The application has a wide range such as international assessment of climate change [11], estimation of river inundation [12], weed control [13], prediction of drought [14], resource management [15], agroecosystem modeling [16], forestry planning [17] [18], estimation of crop biomass [19], and so on. The research trend is focused mainly on 2 areas, conventional agriculture systems and global observation of ecosystems: Sensing of agricultural ecosystems aims to gain specific information necessary for the prediction and control.…”

The contribution of remote sensing to the assessment of drought effects in forest ecosystems

“…Numerous studies on air pollution effects and pests and diseases impacts on forest condition are reported in the literature since 1980 [2,7,44,50,64,65,73,80,87,88,91,96,97,107], among others) and show that "severe" damage (affecting a "sufficient" number of trees) can be easily detected, while scattered tree decline is difficult to see with the limited resolution of space remotely sensed data [6,24], and without ground assessment. Finally, the feasibility of depicting forest decline is closely depending on the topography of the study area, on the structure of forest stands, on the date and frequency of data acquisition and on the spatial resolution of the remotely sensed data.…”

Application of knowledge for automated land cover change monitoring

“…Mapping of land cover features would be improved if other data was applied (e.g. Holmgren and Thuresson 1998). Due to LCS88 classification detail, this trend is reflected in work that has considered how LCS88 may be updated (Birnie 1996, Horgan et al 1997, Wright and Morrice 1997.…”