Creating a Lowland and Peatland Landscape Digital Terrain Model (DTM) from Interpolated Partial Coverage LiDAR Data for Central Kalimantan and East Sumatra, Indonesia

Ronald Vernimmen,Aljosja Hooijer,Martijn Visser,Angga T Yuherdha,James Ouellette,Rizka Akmalia,Dedi Mulyadi,Dirk Eilander,Natan Fitranatanegara,Warwick Hadley,Heri Andreas,Maarten Pronk

doi:10.3390/rs11101152

Ronald Vernimmen, Aljosja Hooijer + Show 10 more

Open Access

https://doi.org/10.3390/rs11101152

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Abstract

Coastal lowland areas support much of the world population on only a small part of its terrestrial surface. Yet these areas face rapidly increasing land surface subsidence and flooding, and are most vulnerable to future sea level rise. The accurate and up to date digital terrain models (DTMs) that are required to predict and manage such risks are absent in many of the areas affected, especially in regions where populations are least developed economically and may be least resilient to such changes. Airborne LiDAR is widely seen as the most accurate data type for elevation mapping but can be prohibitively expensive, as are detailed field surveys across a broad geographic scale. We present an economical method that utilizes airborne LiDAR data along parallel flight lines (‘strips’) covering between 10% and 35% of the land depending on terrain characteristics, and manual interpolation. We present results for lowland areas in Central Kalimantan and East Sumatra (Indonesia), for which no accurate DTM currently exists. The study areas are covered with forest, plantations and agricultural land, on mineral soils and peatlands. The method is shown to yield DTM differences within 0.5 m, relative to full coverage LiDAR data, for 87.7–96.4% of the land surface in a range of conditions in 15 validation areas, and within 1.0 m for 99.3% of the area overall. After testing, the method was then applied to the entire eastern coastal zone of Sumatra, yielding a DTM at 100 m spatial resolution covering 7.1 Mha of lowland area from 1.45 Mha of effective LiDAR coverage. The DTM shows that 36.3%, or 2.6 Mha, of this area is below 2 m +MSL and, therefore, at risk of flooding in the near future as sea level rise continues. This DTM product is available for use in flood risk mapping, peatland mapping and other applications.

Highlights

Coastal lowland areas including river deltas host much of the world’s population and economic activity on only a small proportion of its terrestrial area [1]
Elevation models derived from Shuttle Radar Topography Mission (SRTM) data are still often used [1,7,8,9,10], but these can have a vertical error of many meters, especially in vegetated areas
While the bias correction method applied by [11] on the SRTM data increased the fraction of land areas having a vertical accuracy with ± 2 m or better from 39–58% of the world, it remains unsuitable for most applications in lowlands

Summary

Introduction

Coastal lowland areas including river deltas host much of the world’s population and economic activity on only a small proportion of its terrestrial area [1]. They face rapidly increasing risks of flooding, as well as crop failure due to high water levels and saltwater intrusion in the channels, made worse by land surface subsidence and sea level rise [2,3,4,5,6]. Elevation models derived from Shuttle Radar Topography Mission (SRTM) data are still often used [1,7,8,9,10], but these can have a vertical error of many meters, especially in vegetated areas. LiDAR is a costly technique, limiting its economical use to large landscapes, e.g., the hundreds of millions of hectares of lowland, globally, that urgently require such data for accurate modelling

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