Modeling L-band radar backscatter of Alaskan boreal forest. - Yong Wang 011; John L. Day; Frank W. Davis; John Melack (IEEE Trans. Geosci. Remote. Sens., 1993)

Simulated and observed backscatter at P-, L-, and C-bands from ponderosa pine stands. - Yong Wang 011; Frank W. Davis; John M. Melack (IEEE Trans. Geosci. Remote. Sens., 1993)

Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar. - Laura L. Hess; John Melack; Solange Filoso; Yong Wang 011 (IEEE Trans. Geosci. Remote. Sens., 1995)

Amazon floodplain water level changes measured with interferometric SIR-C radar. - Douglas E. Alsdorf; Laurence C. Smith; John Melack (IEEE Trans. Geosci. Remote. Sens., 2001)

Applications of quantitative analysis techniques to monitor water quality of Curuai Lake, Brazil. - J. C. Carvalho; Cláudio C. F. Barbosa; Evlyn M. L. M. Novo; J. E. Mantovani; John Melack; W. Pereira Filho (IGARSS, 2003)

Contribution of remote sensing to international conventions regarding wetlands: examples from the large-scale biosphere-atmosphere experiment in Amazonia. - Laura L. Hess; John M. Melack (IGARSS, 2003)

Use of MODIS Enhanced Vegetation Index to Detect Seasonal Patterns of Leaf Phenology in Central Amazon Várzea Forest. - Laura L. Hess; Piyachat Ratana; Alfredo R. Huete; Chris Potter; John Melack (IGARSS (4), 2009)

A multisensor, multitemporal approach for monitoring herbaceous vegetation growth in the Amazon floodplain. - Thiago Sanna Freire Silva; Maycira P. F. Costa; Evlyn M. L. M. Novo; John M. Melack (MultiTemp, 2013)

Wetlands. - John Melack (Encyclopedia of Remote Sensing, 2014)

A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network. - Louise C. Bruce; Marieke A. Frassl; George B. Arhonditsis; Gideon Gal; David P. Hamilton; Paul C. Hanson; Amy L. Hetherington; John M. Melack; Jordan S. Read; Karsten Rinke; Anna Rigosi; Dennis Trolle; et al. (Environ. Model. Softw., 2018)

Detecting Land Degradation in Eastern China Grasslands with Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) and GIMMS NDVI3g Data. - Caixia Liu 002; John Melack; Ye Tian 007; Huabing Huang; Jinxiong Jiang; Xiao Fu; Zhouai Zhang (Remote. Sens., 2019)

Landsat observations of chlorophyll-a variations in Lake Taihu from 1984 to 2019. - Zhigang Cao; Ronghua Ma; John M. Melack; Hongtao Duan 001; Miao Liu; Tiit Kutser; Kun Xue; Ming Shen; Tianci Qi; Huili Yuan (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Evaluating and Optimizing VIIRS Retrievals of Chlorophyll-a and Suspended Particulate Matter in Turbid Lakes Using a Machine Learning Approach. - Zhigang Cao; Ronghua Ma; Nima Pahlevan; Miao Liu; John M. Melack; Hongtao Duan 001; Kun Xue; Ming Shen (IEEE Trans. Geosci. Remote. Sens., 2022)

Hydrodynamic modeling of floodplains with inundated trees and floating plants. - Wencai Zhou; John M. Melack; Sally MacIntyre (Environ. Model. Softw., 2024)

Assessing Land Degradation and Restoration in Eastern China Grasslands from 1985 to 2018 Using Multitemporal Landsat Data. - Caixia Liu 002; Huabing Huang; John M. Melack; Ye Tian 007; Jinxiong Jiang; Xiao Fu; Zhiguo Cao; Shaohua Wang (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)