Reply published on 23 June 2016,
see
Remote Sens. 2016, 8(7), 534.
Comment of
Remote Sens. 2014, 6(5), 3923-3943.
Comment on Gebhardt et al. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923–3943
1
Centro de Investigaciones en Geografía Ambiental, Universidad Nacional Autónoma de México, Campus Morelia, Antigua Carretera a Pátzcuaro 8701, Col. Ex-Hacienda de San José de La Huerta, C.P. 58190 Morelia, Mexico
2
Instituto de Geografía, Universidad Nacional Autónoma de México, Circuito de la Investigación Científica, Ciudad Universitaria, Del. Coyoacán, C.P. 04510 México D.F., Mexico
3
Universidad de Guanajuato, Sede Belén, Av. Juárez 77, Zona Centro, C.P. 4500 Guanajuato, Mexico
4
El Colegio de la Frontera Sur, Unidad San Cristóbal, Carretera Panamericana y Periférico Sur s/n Barrio María Auxiliadora, C.P. 29290 San Cristóbal de Las Casas, Chiapas, Mexico
*
Author to whom correspondence should be addressed.
Academic Editors: Partha Sarathi Roy, Heiko Balzter and Prasad S. Thenkabail
Remote Sens. 2016, 8(7), 533; https://doi.org/10.3390/rs8070533
Received: 27 May 2015 / Revised: 12 May 2016 / Accepted: 24 May 2016 / Published: 23 June 2016
Gebhardt et al. (2014) presented the Monitoring Activity Data for the Mexican REDD+ program (MAD-MEX), an automatic nation-wide land cover monitoring system for the Mexican REDD+ MRV. Though MAD-MEX represents a valuable first effort toward establishing a national reference emissions level for the implementation of REDD+ in Mexico, in this paper, we argue that this land cover system has important limitations that may prevent it from becoming operational for REDD+ MRV. Specifically, we show that (1) the accuracy assessment of MAD-MEX land cover maps is optimistically biased; (2) the ability of MAD-MEX to monitor land cover change, including deforestation and forest degradation; is poor and (3) the use of an entirely automatic classification approach, such as that followed by MAD-MEX, is highly problematic in the case of a large and heterogeneous country like Mexico. We discuss these limitations and call into question the ability of a land cover monitoring system, such as MAD-MEX, both to elaborate a national reference emissions level and to monitor future forest cover change, as part of a REDD+ MRV system. We provide some insights with the aim of improving the development of nation-wide land cover monitoring systems in Mexico and elsewhere.
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Keywords:
land cover mapping; accuracy assessment; Landsat; image classification; Monitoring, Reporting and Verification (MRV); Reduced Emissions from Deforestation and Degradation plus (REDD+)
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MDPI and ACS Style
Mas, J.-F.; Couturier, S.; Paneque-Gálvez, J.; Skutsch, M.; Pérez-Vega, A.; Castillo-Santiago, M.A.; Bocco, G. Comment on Gebhardt et al. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923–3943. Remote Sens. 2016, 8, 533.
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