An Innovative Approach for Improving the Accuracy of Digital Elevation Models for Cultivated Land

Yuyang Ma,Mengyuan Xu,Linghua Meng,Yang Cui,Fanchang Kong,Baiwen Jiang,Yue Yin,Haixiang Guan,Huanjun Liu,MengPei Wang

doi:10.3390/rs12203401

Abstract

The redistribution of solar radiation, temperature, soil moisture and heat by topography affects the physical and chemical properties of the soil and the spatial distribution characteristics of crop growth. Analyses of the relationship between topography and these variables may help to improve the accuracy of digital elevation models (DEMs). The purpose of correcting Shuttle Radar Topography Mission (SRTM) data is to obtain high-precision DEM data in cultivated land. A typical black soil area was studied. A high-precision reference DEM was generated from an unmanned aerial vehicle (UAV) and extensive measured ground elevation data. The normalized differential vegetation index (NDVI), perpendicular drought index (PDI) extracted from SPOT-6 remote sensing images and potential solar radiation (PSR) extracted from SRTM. The interactions between topography and NDVI, PDI, and PSR were analyzed. The NDVI, PDI and PSR in June, July, August and September of 2016 and the SRTM were used as independent variables, and the UAV DEM was used as the dependent variable. Linear stepwise regression (LSR) and a back-propagation neural network (BPNN) were used to establish an elevation prediction model. The results indicated that (1) The correlation between topography and NDVI, PSR, PDI was significant at 0.01 level. The PDI and PSR improved the spatial resolution of SRTM data and reduce the vertical error. (2) The BPNN (R21 = 0.98, root mean square error, RMSE1 = 0.54) yielded a higher SRTM accuracy than did the studied linear model (RMSE1 = 1.00, R21 = 0.90). (3) A series of significant improvements in the SRTM were observed when assessed with the reference DEMs for two different areas, with RMSE reductions of 91% (from 14.95 m to 1.23 m) and 93% (from 15.6 m to 0.94 m). The proposed method improved the accuracy of existing DEMs and could provide support for accurate farmland management.

Highlights

The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is free and publicly available
The spectral response pattern of crops was similar to that in the peak growth period; the normalized differential vegetation index (NDVI) was relatively high. These results demonstrated that the NDVI was closely related to topography and affected by surface matter during the crop growth period
This study presented a new method for improving the accuracy of SRTM DEMs in cultivated land areas

Summary

Introduction

The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is free and publicly available. Improvements to the SRTM would greatly increase the value of the public data and improve the corresponding application reliability especially in typical black soil areas, in which the surface of the soil appears black and the topsoil in the region is covered with black or dark humus. The typical soil type in black soil regions is directly defined as black soil in the Genetic Soil Classification of China [1]. These soils are named phaeozems in the World Reference Base for Soil Resources (WRB). Selecting suitable methods to improve the accuracy of SRTM data in cultivated land areas is important and challenging

Methods

Results

Discussion

Conclusion