Modeling Directional Brightness Temperature (DBT) over crop canopy with effects of intra-row heterogeneity

Yongming Du, Biao Cao*, Hua Li, Zunjian Bian, Boxiong Qin, Qing Xiao, Qinhuo Liu, Yijian Zeng, Zhongbo Su

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
58 Downloads (Pure)


In order to improve the simulation accuracy of directional brightness temperature (DBT) and the retrieval accuracy of component temperature, a model considering intra-row heterogeneity to simulate the DBT angular distribution over crop canopy is proposed. At individual scale, the probability of leaf appearance is inversely proportional to the distance from central stem. On the basis of this assumption, we formulated leaf area volume density (LAVD) spatial distribution at three hierarchical scales: individual scale, row scale, and scene scale. The equations for directional gap probability and bi-directional gap probability were modified to adapt the heterogeneity of row structure. Afterwards, a straightforward radiative transfer model was built based on the gap probabilities. A set of simulated data was generated by the thermal radiosity-graphics combined model (TRGM) as the benchmark to evaluate both forward simulation and inversion ability of the new model; we compared the new DBT model against an existing model assuming row as homogeneous box. With the growth of crops, the canopy structure of row crops will gradually change from row structure to continuous canopy. The new DBT model agreed with the TRGM model much better than the homogeneous row model at the middle stage of the crop growth season. The new model and the homogeneous row model achieve similar accuracy at early stage and end stage. At the middle growth stage, the new model can improve the accuracy of soil temperature retrieval. We recommend the new DBT model as an option to improve the DBT simulation and component temperature retrieval for row-planted crop canopy. In particular, the more accurate component temperatures during the middle growth stage are fundamentally important in characterizing crop water status, evapotranspiration, and soil moisture, which are subsequently critical for predicting crop productivity.
Original languageEnglish
Article number2667
Pages (from-to)1-20
Number of pages20
JournalRemote sensing
Issue number17
Early online date19 Aug 2020
Publication statusPublished - 1 Sept 2020




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