Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Abstract

Monitoring woody cover by remote sensing is considered a key methodology towards sustainable management of trees in dryland forests. However, while modern very high resolution satellite (VHRS) sensors allow woodland mapping at the individual tree level, the historical perspective is often hindered by lack of appropriate image data. In this first study employing the newly accessible historical HEXAGON KH-9 stereo-panoramic camera images for environmental research, we propose their use for mapping trees in open-canopy conditions. The 2–4 feet resolution panchromatic HEXAGON satellite photographs were taken 1971–1986 within the American reconnaissance programs that are better known to the scientific community for their lower-resolution CORONA images. Our aim is to evaluate the potential of combining historical CORONA and HEXAGON with recent WorldView VHRS imagery for retrospective woodland change mapping on the tree level. We mapped all trees on 30 1-ha test sites in open-canopy argan woodlands in Morocco in the field and from the VHRS imagery for estimating changes of tree density and size between 1967/1972 and 2018. Prior to image interpretation, we used simulations based on unmanned aerial system (UAS) imagery for exemplarily examining the role of illumination, viewing geometry and image resolution on the appearance of trees and their shadows in the historical panchromatic images. We show that understanding these parameters is imperative for correct detection and size-estimation of tree crowns. Our results confirm that tree maps derived solely from VHRS image analysis generally underestimate the number of small trees and trees in clumped-canopy groups. Nevertheless, HEXAGON images compare remarkably well with WorldView images and have much higher tree-mapping potential than CORONA. By classifying the trees in three sizes, we were able to measure tree-cover changes on an ordinal scale. Although we found no clear trend of forest degradation or recovery, our argan forest sites show varying patterns of change, which are further analysed in Part B of our study. We conclude that the HEXAGON stereo-panoramic camera images, of which 670,000 worldwide will soon be available, open exciting opportunities for retrospective monitoring of trees in open-canopy conditions and other woody vegetation patterns back into the 1980s and 1970s.

Monitoring dryland trees with remote sensing. Part B: Combining tree cover and plant architecture data to assess degradation and recovery of Argania spinosa woodlands of South Morocco

“…In Part A of our study (Marzolff et al, 2022) we found that HEXAGON imagery has a remarkably similar potential for identifying individual trees compared to the WorldView images, although both have limited ability for mapping small trees and trees in clumped-canopy groups. By using the combination of tree locations known a priori from field mapping with a retrospective mapping approach opting for stability in case of doubt, we could ensure very high accuracy for tree-density and tree-cover measures in 2018 and a conservative tendency towards underestimation rather than overestimation of change.…”

“…As a representative example for the tree-cover change maps 1972-2018, Figure 4 shows the test site MAO1n, where the overall tree density and cover change is quite similar to the average of all 30 test sites (compare with change map Figure 7 in Marzolff et al, 2022). The tree density at MAO1n remained unchanged at 55 trees ha −1 , and 33 (or 60%) of the 1972 trees remained in the same size class (yellow circles).…”

“…Part A of our study on tree-cover mapping by way of panchromatic (black and white) satellite images showed that results can be prone to errors, because depending on the image Frontiers in Environmental Science frontiersin.org viewing geometry and illumination angle, tree shadows cannot be separated visually from the tree crown. With the most unfavourable conditions in the case of our study, shadows can make up over 40% of the mapped tree, which may lead to severe miscalculations and misinterpretations of forest cover if disregarded (Marzolff et al, 2022). To avoid potential errors associated with inaccurate tree-crown delineations, we did not map tree canopy cover on a continuous scale, but opted for measuring tree-cover changes on an ordinal scale.…”

“…To avoid potential errors associated with inaccurate tree-crown delineations, we did not map tree canopy cover on a continuous scale, but opted for measuring tree-cover changes on an ordinal scale. In the following, we will use the term "tree-crown size" for the ordinal crown sizes small, medium and large, and the term "tree-cover change" for the resulting ordinal change classes, which integrate increased or decreased crown size, loss or establishment of trees (see 2.4 as well as Marzolff et al, 2022). Vegetation cover in general may change (positively or negatively) or stay unchanged (Ries, 2005;Sloan et al, 2019).…”

“…By using the combination of tree locations known a priori from field mapping with a retrospective mapping approach opting for stability in case of doubt, we could ensure very high accuracy for tree-density and tree-cover measures in 2018 and a conservative tendency towards underestimation rather than overestimation of change. More details on the tree-mapping procedure, especially concerning the complex effects of resolution, viewing and illumination angles in the historical HEXAGON imagery, may be found in Part A of our study (Marzolff et al, 2022).…”